JP2009229204A - Location specifying system, computer program and location specifying method - Google Patents

Abstract

Provided are a position specifying device, a computer program, and a position specifying method capable of specifying the position of a pedestrian even when the pedestrian is indoors such as in an underground shopping center or a building.
A walking behavior determination unit 173 determines a walking behavior of a pedestrian based on data obtained by a distance sensor 132, an orientation sensor 133, an altitude sensor 134, and the like of a positioning unit 13. The position estimation unit 171 calculates the estimated position of the pedestrian on the map, and the error calculation unit 172 calculates the error range of the estimated position estimated by the position estimation unit 171. The position specifying unit 175 determines whether or not there is a feature point related to the walking behavior determined by the walking behavior determination unit 173 within the error range of the estimated position. Specify as the position of.
[Selection] Figure 1

Description

  The present invention relates to a position specifying technique, and in particular, to a position specifying apparatus that can accurately specify the position of a pedestrian when carried by a pedestrian, a computer program and a position specifying method for realizing the position specifying apparatus. .

  Examples of position detection methods widely used in navigation for detecting the position of a moving body such as a vehicle include self-contained navigation, satellite navigation, map matching, and hybrid navigation. Self-contained navigation uses a distance sensor, an azimuth sensor, an angular velocity sensor, etc., for example, based on the azimuth angle of the vehicle traveling with respect to an orthogonal coordinate system based on the longitude-latitude coordinate system and the traveling distance per unit time. Although it is calculated, consistency with the road is not taken into consideration, and there is a problem that errors in the vehicle position accumulate as the travel distance increases.

  Satellite navigation uses GPS (Global Positioning System), and the detected position includes an error of about 10 to 20 m. Since GPS is used, an in-vehicle sensor such as a distance sensor, an azimuth sensor, or an angular velocity sensor is unnecessary. However, on roads under elevated roads, roads between buildings, mountain roads, roadside trees, etc., radio waves cannot be received from a predetermined number of GPS satellites, and the detection accuracy is greatly degraded. is there. In addition, there is also a problem that the traveling road is wrong in a narrow street with a narrow road interval.

  In addition, the map matching method detects the position of the vehicle in consideration of the consistency (matching) between the travel locus by the self-contained navigation and the road map (see Patent Document 1). That is, the most probable road is selected from a plurality of road candidates considered to be traveling while comparing the trajectory obtained by the self-contained navigation with the road map data. Then, when the number of candidate roads is limited to one, the traveling locus of the vehicle obtained by the self-contained navigation is matched with the road. However, if the limited road is wrong, there is a problem that position detection after that becomes impossible.

  Hybrid navigation is a combination of satellite navigation and map matching, and it rationally estimates the position of the vehicle and identifies the road on which it is traveling, taking into account the errors between autonomous navigation and satellite navigation. (See Patent Document 2). In hybrid navigation, for example, the position of a vehicle is detected using a map matching method in normal times. When the vehicle position cannot be detected by the map matching method, the vehicle position and direction are detected by satellite navigation to estimate the vehicle position, and the vehicle position is detected in consideration of consistency with the road map data. To do. With hybrid navigation, except for special cases, there is almost no possibility of mistaken roads on which vehicles are traveling, and the positional accuracy in the direction of the road is within an error range of about 10 m on average. In the target navigation, the accuracy level is almost no problem in practical use.

On the other hand, in the pedestrian position detection method, position detection is performed using a portable device such as a mobile phone or a simple navigation device carried by the pedestrian. In such portable devices, for example, a method of detecting the current position of a pedestrian by radio waves from GPS satellites or communication with a base station has been put into practical use.
JP-A-63-148115 JP-A-2-275310

  However, when detecting the position by receiving radio waves from GPS satellites, the position error is about 10 to 20 m when the reception state of the GPS satellites is good, but the roads in the valleys of buildings such as buildings in the city center or under the overpass In such cases, it may be impossible to detect the position, or the position error may be about several hundred meters due to the influence of multipath or the like, and an accurate position may not be obtained. In particular, in the case of pedestrians, unlike mobile objects such as vehicles, there is a tendency to walk near buildings along the buildings, so the reception level of radio waves from GPS satellites decreases.

  Also, unlike the case of vehicles, pedestrians frequently enter indoors as well as outdoors. When pedestrians enter buildings, they can receive almost all radio waves from GPS satellites. In such a case, if the communication with the base station is impossible, the position cannot be detected at all. Even if communication with the base station is possible, the accuracy of position detection is greatly reduced.

  In particular, not only when pedestrians enter the indoor area, but also when traveling on a subway or other means of transportation (for example, a train), not only the communication with the base station is interrupted, The radio wave from the GPS satellite cannot be received, and the position cannot be detected only by positioning by normal self-contained navigation. For this reason, there is a problem in that position detection cannot be performed while the vehicle is moving on a transportation means, and for example, route guidance to a destination cannot be performed. In addition, once position detection has become impossible, when a pedestrian goes out to the ground where radio waves from GPS satellites can be received, it is necessary to search again for GPS satellites that can be received from that point. It took a long time to do so, and there was a problem that it was inconvenient for pedestrians.

  The present invention has been made in view of such circumstances, and a position specifying device that can specify the position of a pedestrian even when the pedestrian is indoors, such as in an underground shopping center or a building, It is an object to provide a computer program and a position specifying method for realizing a position specifying device.

  The position specifying device according to the first aspect of the present invention comprises positioning means for measuring its own position. In the position specifying device portable by a pedestrian, the walking behavior determining means for determining the walking behavior of the pedestrian, and the walking behavior Storage means for storing map information including position information of associated feature points, estimation means for estimating its own position on a map based on positioning data obtained by positioning by the positioning means, and the estimation means An error range calculation means for calculating an error range indicating an estimation error range of the estimated position estimated in step (2), and a feature relating to the walking behavior determined by the walking behavior determination means within the error range calculated by the error range calculation means When there is a point, it is characterized by comprising position specifying means for specifying the characteristic point as its own position.

  According to a second aspect of the present invention, in the first aspect of the invention, the position specifying device further includes an altitude information acquiring unit that acquires information about the altitude, and the position specifying unit is based on the altitude information acquired by the altitude information acquiring unit. It is characterized by being configured to specify the position of.

  The position specifying device according to a third aspect of the present invention is the position determination device according to the second aspect, wherein the position specifying means determines that the walking behavior is stop walking by the walking behavior determining means when the altitude information acquiring means acquires a change in altitude. At this point, a feature point within the error range calculated by the error range calculation means is specified as its own position.

  The position specifying device according to a fourth aspect of the present invention comprises, in the second aspect of the present invention, an altitude change determining unit that determines whether or not the altitude change is stable when the altitude change is acquired by the altitude information acquiring unit. The specifying unit associates the feature point within the error range calculated by the error range calculating unit with the altitude acquired by the altitude information acquiring unit when the altitude change determining unit determines that the altitude change is stable. It is characterized in that it is configured to specify its own position.

  According to a fifth aspect of the present invention, in the fourth aspect of the invention, when the position specifying unit determines that the walking behavior is the start of walking by the walking behavior determining unit, the error range calculated by the error range calculating unit. It is characterized in that it is configured to associate its own feature point with the altitude acquired by the altitude information acquisition means so as to specify its own position.

  According to a sixth aspect of the present invention, in the fourth aspect of the invention, in the fourth aspect, when the position specifying unit determines that the walking behavior is a change in walking speed by the walking behavior determining unit, the change in the walking speed is stable. When it is determined that the feature point within the error range calculated by the error range calculation unit and the altitude acquired by the altitude information acquisition unit are associated with each other, the own position is specified. Features.

  According to a seventh aspect of the present invention, in the fourth aspect of the invention, when the position specifying means determines that the walking behavior is a change in walking strength by the walking behavior determining means, the walking strength of the walking is determined. When it is determined that the fluctuation is stable, a feature point within the error range calculated by the error range calculation unit is associated with the altitude acquired by the altitude information acquisition unit, and the position of the device is specified. It is characterized by being.

  According to an eighth aspect of the present invention, in any one of the first through seventh aspects, the position specifying device includes a reliability calculating unit that calculates the reliability of the positioning data, and the position specifying unit includes the reliability calculating unit. When the reliability calculated in step (b) is lower than a predetermined threshold and the feature point within the error range calculated by the error range calculation means is an indoor feature point, the feature point is identified as its own position. It is characterized by being.

  In any one of the first to eighth inventions, when there are a plurality of feature points within the error range, the position specifying device according to a ninth aspect of the invention specifies one or more feature points among the feature points. It is characterized by comprising selection means for selecting as the position.

  According to a tenth aspect of the present invention, in any one of the first to ninth aspects, the storage means includes a staircase, an escalator, an elevator, a ticket vending machine, a ticket gate, a ferris wheel, a vending machine, and a boarding place. The position information of at least one feature point is stored.

  A computer program according to an eleventh aspect of the invention is a computer program for causing a computer to specify its own position based on positioning data. The computer program includes a walking behavior determining means for determining a walking behavior of a pedestrian, and positioning data. Estimating means for estimating its own position on the map, error range calculating means for calculating an error range indicating an estimation error range of the estimated position, and features associated with walking behavior within the calculated error range When there is a point, it is characterized by functioning as a position specifying means for specifying the characteristic point as its own position.

  A position specifying method according to a twelfth aspect of the present invention is the position specifying method for determining the position of the pedestrian by positioning and storing map information including position information of feature points associated with the walking behavior. Based on the positioning data obtained by positioning, estimate its own position on the map, calculate an error range indicating the estimated error range of the estimated position, and determine within the calculated error range If there is a feature point related to the walking behavior, the feature point is specified as its own position.

  In the first invention, the eleventh invention, and the twelfth invention, the position specifying device stores map information including position information of feature points associated with a walking behavior of a pedestrian in advance. The characteristic points are, for example, landing places such as stairs, elevators, escalators, ticket vending machines, ticket gates, and transportation means. The walking behavior indicates, for example, walking characteristics of a pedestrian and includes traveling characteristics when riding a bicycle. For example, start of walking, walking speed (including walking pitch), fluctuation in walking speed, walking strength (for example, level intensity indicated by acceleration by the step sensor), fluctuation in walking strength, unit time For example, the number of winning steps (in the case of a bicycle, the number of pedaling), the change in the number of steps, the walking direction, and the walking stop. The walking behavior can be acquired by a distance sensor such as an acceleration sensor or a step number sensor, and an orientation sensor such as an angular velocity sensor, an angular acceleration sensor, or a geomagnetic sensor. For example, when the pedestrian walks the stairs, the walking speed or the strength of the walking changes, so that the walking behavior can be associated with the stairs. Further, the map information may include not only road information but also a passage through which a pedestrian in an underground shopping center or a building can walk, and route information of transportation. The map information may be stored in advance, or may be acquired and stored by communication from the outside such as a nearby road device according to the position of the pedestrian.

  The position specifying device estimates its own position on the map based on the positioning data obtained by positioning, and calculates an error range (estimated range) indicating an estimated error range of the estimated position. For positioning of its own position, for example, positioning data such as GPS, base station communication, distance sensor, direction sensor can be used. Further, positioning can be performed by communication with an optical beacon, a radio beacon or the like. The error range varies depending on the accuracy of the positioning data, and can be used, for example, based on the standard deviation of the positioning position error (for example, an integer multiple of the standard deviation). The position identifying device determines the walking behavior of the pedestrian and determines whether there is a feature point related to the determined walking behavior within the calculated error range. The characteristic point is specified as the position of the pedestrian by correcting the point. For example, if there is a stairs within the pedestrian error range when there is a change in the walking speed or walking strength of the pedestrian, the estimated position is corrected (updated) to the position of the pedestrian. Can be specified. Thereby, a pedestrian's position can be pinpointed accurately regardless of the outdoors or indoors.

  In the second invention, the position specifying device acquires information related to altitude and specifies its own position based on the acquired information related to altitude. The information about the altitude is information such as the altitude itself, altitude fluctuation (more specifically, the start state of the altitude change, the state during the altitude change, the state where the altitude change is stable), and the like. Information related to altitude can be detected by an altitude sensor such as a barometric pressure sensor, for example. If there is a change in the walking speed or strength of the pedestrian, and there is a stairs within the error range of the estimated position of the pedestrian when a change in altitude is detected, the pedestrian walks the stairs Therefore, it is possible to determine the position of the pedestrian with higher accuracy by correcting (updating) the estimated position to the position of the stairs. Thereby, the position of a pedestrian can be specified with higher accuracy regardless of whether it is outdoors or indoors.

  In the third invention, when the altitude change is acquired, the position specifying device specifies a feature point within the calculated error range as its own position when it is determined that the walking behavior is stop walking. . For example, when a pedestrian gets on an escalator or an elevator, the pedestrian stops walking and the altitude changes by moving to an upper floor or a lower floor with the escalator or elevator. Therefore, if there is a feature point such as an escalator or elevator within the error range of the estimated position, there is a high possibility that the pedestrian is on the escalator or elevator. The position can be specified.

  In the fourth invention, the position specifying device determines whether or not the altitude change is stable when the altitude change is acquired. When the position identifying device determines that the altitude change is stable, it associates the feature point within the error range of the estimated position with the acquired altitude (for example, the altitude itself after the altitude change is stabilized) Identify the location. For example, altitude changes when a pedestrian moves to an upper floor or a lower floor by an escalator or an elevator. If you get off the escalator or elevator at the required floor, the altitude change will be stable, so the pedestrian is likely to be near the escalator or elevator on the floor corresponding to the stabilized altitude, and the position of the pedestrian The point can be corrected. Thereby, it is possible to accurately identify the floor where the pedestrian is in the vicinity of the escalator or elevator in the building.

  In the fifth invention, the position specifying device specifies its own position by associating the acquired altitude with the feature point within the error range of the estimated position when it is determined that the walking behavior is the start of walking. To do. For example, when a pedestrian moves to an upper or lower floor with an escalator or elevator, the pedestrian's walking behavior starts from walking stop to start walking when getting off the escalator or elevator. When there is an escalator or elevator inside, it is highly possible that the pedestrian is near the escalator or elevator, and it can be determined that the pedestrian has descended from the escalator or elevator. By associating with the altitude at that time, the position of the pedestrian can be corrected to the feature point, and the floor where the pedestrian is located near the escalator or elevator in the building can be accurately identified.

  In the sixth invention, the position specifying device is within the error range of the estimated position when it is determined that the change in walking speed is stable when the walking behavior is determined to be a change in walking speed. The feature point and the acquired altitude are associated with each other to identify its own position. For example, when a pedestrian moves to an upper floor or a lower floor on an escalator, when walking on the escalator or when getting on the escalator, the walking speed fluctuates as compared to normal walking. And when the pedestrian gets off the escalator, it returns to the normal walking state, so when it is determined that the fluctuation of the walking speed is stable, if there is an escalator within the error range of the estimated position, the pedestrian is near the escalator It can be determined that the pedestrian has descended from the escalator.

  Moreover, when a pedestrian walks the stairs, the walking speed varies as compared to normal walking. And when the pedestrian starts walking on the horizontal floor from the stairs, it returns to the normal walking state, so if there is a stairs within the error range of the estimated position when it is determined that the fluctuation of the walking speed is stable It can be determined that there is a high possibility that the pedestrian is near the stairs and the pedestrian has moved from the stairs to the horizontal floor. By associating with the altitude at the time of such determination, the position of the pedestrian can be corrected to such a characteristic point, and the floor where the pedestrian is near the escalator or the stairs in the building can be accurately identified. .

  In the seventh invention, when the position specifying device determines that the walking behavior is a change in the strength of walking, the error of the estimated position is determined when the change in the strength of the walking is determined to be stable. The feature point in the range is associated with the acquired altitude to identify its own position. For example, when a pedestrian moves to an upper floor or a lower floor on an escalator, when walking on the escalator or when getting on the escalator, the walking strength varies as compared to a normal walk. And when the pedestrian gets off the escalator, it returns to the normal walking state, so when the escalator is within the error range of the estimated position at the time when it is determined that the fluctuation of the walking strength is stable, It is highly possible that the person is near the escalator, and it can be determined that the pedestrian has descended from the escalator.

  Moreover, when a pedestrian walks the stairs, the strength of walking varies as compared to normal walking. And when the pedestrian starts walking on the horizontal floor from the stairs, it will return to the normal walking state, so when there is a stair within the error range of the estimated position when it is determined that the fluctuation of the walking strength is stable It can be determined that there is a high possibility that the pedestrian is near the stairs and the pedestrian has moved from the stairs to the horizontal floor. By associating with the altitude at the time of such determination, the position of the pedestrian can be corrected to such a characteristic point, and the floor where the pedestrian is near the escalator or the stairs in the building can be accurately identified. .

  In the eighth invention, the position specifying device calculates the reliability of the positioning data, and the feature point whose calculated reliability is lower than a predetermined threshold and within the error range of the estimated position is an indoor feature point. If there is, the feature point is specified as its own position. The reliability of positioning data can be, for example, the reliability of positioning data such as a direction sensor such as GPS, base station communication, and geomagnetic sensor. In the case of GPS, the reliability can be set according to the reception level of GPS. In base station communication, the reliability can be set according to the communication level. In addition, the reliability can be set according to the output level of the geomagnetic sensor. Indoors such as inside a building, the GPS reception level or the communication level of base station communication is lowered, or the output level of the geomagnetic sensor changes due to an iron plate or the like included in the building. The position specifying device can determine that the position of the pedestrian is at the indoor feature point when the indoor feature point is within the error range of the estimated position and the reliability of the positioning data is not more than a predetermined value. Thereby, a pedestrian's position can be specified with sufficient accuracy.

  In the ninth invention, when there are a plurality of feature points within the error range of the estimated position, the position specifying device selects one or a plurality of feature points from among the feature points as its own position. For example, when a pedestrian is walking in a building on a plurality of floors, reference is made to the walking path data and altitude information on each floor in the building. When several floors exist as candidates due to errors in altitude information, etc., walks that are closest to the pedestrian's walking trajectory (estimated position trajectory, positioning position trajectory, etc.) by referring to the walking path of each floor A passage can be specified, and thereby the position of a pedestrian can be selected. In addition, when there are a plurality of probable positions, a plurality of positions can be selected. Further, even when there are a plurality of roads or walking paths in the error range, the one closer to the walking trajectory of the pedestrian (such as the trajectory of the estimated position and the trajectory of the positioning position) may be selected. All the selected positions may be displayed, or only one may be displayed.

  When the probability of each feature point within the error range is expressed as the correlation degree, and the position of the pedestrian is specified, the better feature point of the correlation degree may be displayed. In addition, about a feature point with a bad correlation degree, this feature point can be displayed when a correlation degree becomes good according to a pedestrian's walk, without rejecting immediately. Further, when the degree of correlation becomes worse than a predetermined threshold, the feature value point may be rejected. As a result, the position of the most probable pedestrian can be specified, and even if the pedestrian's true position is determined to be temporarily not the position of the pedestrian for some reason, The original position of the pedestrian can be specified while maintaining the position without disappearing.

  In the tenth invention, the position specifying device stores position information of at least one feature point among the stairs, the escalator, the elevator, the ticket machine, the ticket gate, the Ferris wheel, the vending machine, and the boarding / alighting place. Thereby, the position of a pedestrian can be specified by these characteristic points.

  In the present invention, the position of the pedestrian can be specified even when the pedestrian is indoors, such as in an underground city or a building.

  Hereinafter, the present invention will be described with reference to the drawings illustrating embodiments. FIG. 1 is a block diagram showing an example of the configuration of a position specifying device 10 according to the present invention. The position specifying device 10 estimates its own position based on positioning data obtained by positioning, and calculates an error range (estimated position estimation range) indicating a range of estimation error of the estimated position. The position specifying device 10 associates a feature point (a characteristic point on a map where a pedestrian can exist) specified within the calculated error range with a pedestrian's walking behavior and the like, and determines the position of the pedestrian. The position of the pedestrian is specified by correcting to. In this case, specifying (detecting) its own position means specifying (detecting) its own position with higher accuracy than the measured positioning position. Note that the position of the pedestrian can be specified (detected) on the map based on the positioning data, and the specified position can be displayed.

  The position specifying device 10 can be carried by a pedestrian (including a pedestrian who travels by bicycle), and includes a control unit 11 that controls the entire device, a communication unit 12, a positioning unit 13, a map database 14, a storage unit 15, An operation unit 16, a position detection processing unit 17, a display unit 18, an audio output unit 19, a movement method determination unit 20, and the like are provided. The positioning unit 13 includes a GPS 131, a distance sensor 132, an orientation sensor 133, an altitude sensor 134, an orientation correction unit 135, a sensor calibration unit 136, and the like. The position detection processing unit 17 includes a position estimation unit 171, an error calculation unit 172, a walking behavior determination unit 173, a boarding / alight determination unit 174, a position specifying unit 175, a reliability calculation unit 176, an evaluation unit 177, a vibration detection unit 178, and the like. Is provided.

  The communication unit 12 includes an optical beacon, a radio beacon, an RFID or a DSRC, a narrow area communication function for communicating with a road device, a mid-range communication function such as a wireless LAN such as a UHF band or a VHF band, or a mobile phone, A wide-area communication function such as PHS, multiple FM broadcasting, or Internet communication is provided. The communication unit 12 is, for example, an underground entrance for access to a transportation means such as a subway, a place to get on and off the transportation means, a wireless LAN that covers the vicinity of entrances and exits of underground malls, department stores, shopping malls, entertainment facilities, etc. Using mid-range communication, road-to-road communication between roadside devices, road-to-vehicle communication between roadside devices and vehicles, or map information and route information for transportation (for example, railways or buses) Route map, time required between stations or stops), and signal information of traffic lights at intersections. Details of the map information and route information will be described later.

  Other examples of the road device include a traffic information collection device such as an ultrasonic sensor and an image sensor, an information board device that provides traffic information in characters or figures, and a signal control device. Moreover, the communication part 12 can also acquire map information and route information around a pedestrian from a center device such as an information processing center or a traffic control center by using wide-area communication such as a mobile phone.

  The communication unit 12 has a communication function for communicating with a base station, receives radio waves from a plurality of base stations, and outputs reception results to the positioning unit 13. In addition, the communication unit 12 outputs the position information of the communication point obtained by the narrow area communication with the road device to the positioning unit 13.

  The positioning unit 13 measures the position of the pedestrian from time to time (for example, every time 0.5 seconds, 1 second, etc., every 1 m, 2 m, etc.) (determines the positioning position) The moving distance and moving direction (positioning direction) are stored in the storage unit 15 together with the time as a positioning locus.

  The GPS 131 receives radio waves from a plurality of GPS satellites and measures the position of the pedestrian. In addition to the GPS 131, a DGPS (differential GPS) can be mounted. DGPS can receive FM broadcasts or medium waves transmitted from a reference station whose position is known in advance, and can correct the displacement of the positioning position obtained by GPS 131, thereby improving the accuracy of the position of the pedestrian. . Note that it is also possible to perform positioning in a form that combines a method of roughly positioning a position with radio waves from a plurality of base stations of a mobile phone and GPS. As a result, even if it is difficult to receive radio waves from GPS satellites indoors, the probability that a position with poor position accuracy can be obtained is increased.

  The distance sensor 132 includes a speed in a very short time, an acceleration sensor that can detect a moving distance, a step number sensor that can detect a relatively long moving distance, and the like. Here, for example, if an acceleration sensor is used as the step sensor, steep data generated in accordance with the walking pitch can be obtained, and the number of steps and the walking speed can be obtained by counting this number. Also, in this case, when riding a bicycle and stroking the pedal, or when going up and down the stairs of a pedestrian bridge or an underground crossing passage, the characteristics of steep data, for example, peak values (walking strength) are different. Therefore, it is possible to specify a walking place to some extent. Thereby, the position of a pedestrian can be detected for each short-distance and short-distance walk in self-contained navigation. If the GPS satellite positioning accuracy is very good and there are no buildings or the like outside the metropolitan area, the walking distance is calculated based on the difference in GPS positioning without using the step sensor. Also good. In the present application, the walking speed is used as a concept including a walking pitch (the number of steps per unit time).

  The azimuth sensor 133 includes an angular velocity sensor or an angular acceleration sensor (relative azimuth sensor), a two-dimensional or three-dimensional geomagnetic sensor (absolute azimuth sensor), and the like. Thereby, in the self-contained navigation, the moving direction of the pedestrian can be detected for each short time and short distance walking. In addition, the geomagnetic sensor can detect that a pedestrian is present in a building surrounded by reinforcing bars, or that a pedestrian is present near a railroad crossing where there is a strong electric or magnetic field.

  The altitude sensor 134 detects changes in altitude and altitude at the position of the pedestrian using a barometer or an acceleration sensor. Note that the GPS 131, the distance sensor 132, the azimuth sensor 133, and the altitude sensor 134 may not be all provided.

  The azimuth correction unit 135 identifies the road on which the pedestrian walks by map matching, determines the estimated position of the pedestrian, and changes the positioning azimuth (movement azimuth) over a predetermined movement distance (for example, 20 m). If not, the positioning direction is corrected to the direction of the road on the map. Details of the azimuth correction will be described later.

  In the case of the relative azimuth sensor, the sensor calibration unit 136 specifies the scale factor of the relative azimuth sensor when the road or indoor passage where the pedestrian walks is specified by the map matching method and the estimated position of the pedestrian is determined. Calibrate based on the difference from the direction of the passage. In the case of a step sensor, when it is determined that the passage between two points is certain by the map matching method, the step sensor is calibrated from the distance of the road or passage between the two points and the number of steps measured therebetween. Note that the walking distance may be corrected by a positioning locus between two points.

  The positioning unit 13 is based on the measured positioning data, the reception result of the radio wave from the base station obtained via the communication unit 12, or the position information of the communication point obtained by the narrow area communication with the road device. The positioning position and the error range (estimated range) of the positioning position are calculated. Hereinafter, a method for calculating the positioning position and its error range will be described.

FIG. 2 is an explanatory diagram showing an example of the error range of the positioning position. In the orthogonal coordinate system (x direction and y direction), as an example, a position error range detected by narrow-range communication with GPS, a base station, or a road device is a rectangular area (x direction length is 4a, y direction). Is set as 4b). That is, the positioning position is the center position of the rectangular area, and the error range extends from the center position by a range of ± 2a in the x direction and by a range of ± 2b in the y direction. For example, when 2a is set to 2 sigma, the variance in the x direction is a ² and the standard deviation can be set to a. When 2b is set to 2 sigma, the variance in the y direction is b ² and the standard deviation can be set to b.

  Since the error due to the narrow area communication with the road device is smaller than that of the GPS or the base station communication (for example, the error range is several m), the error range is determined by using the narrow area communication with the road device or the GPS. Or, it depends on whether base station communication is used. Further, for example, when using GPS, the error range is temporally determined by environmental conditions, more specifically, GPS reception level, number of captured satellites, 2D or 3D positioning, CEP (Circular Error Probability). To change. In the case of base station communication, the error range varies with time depending on the communication level with the base station, the communication range of the base station, and the like. A predetermined constant in which the error range is set to be large in advance, a constant determined in advance according to the place or time, or the like may be used. The shape of the error range is not limited to a rectangular shape, and may be an arbitrary shape such as a circle or an ellipse. For example, when positioning is performed using only GPS, when the environmental conditions are favorable, an error range of about 10 to 20 m can be set.

  Hereinafter, a method for calculating the positioning position of the pedestrian will be described. The positioning position is expressed by a two-dimensional vector in an orthogonal coordinate system, but in three dimensions, only altitude information is added and can be easily expanded. Further, in the following description, it is formulated by time, but in actual processing, processing may be performed for each unit travel distance instead of processing for each unit time. In the following, capital letters are assumed to be vectors or matrices.

  Assuming that the position P (t) of the pedestrian at time t is Equation (1), walking at time t + 1 (the interval between times t and t + 1 is a predetermined time, for example, 1 second, 0.5 seconds, etc.) The person's position P (t + 1) can be expressed by Expression (2). Alternatively, the time at which a pedestrian walks a predetermined walking distance (for example, 1 m, 2 m, etc.) from time t can be set as time t + 1. Note that “T” added to the vector means transposition. Moreover, Formula (2) shows a pedestrian's dynamic characteristic. Note that the position P (t) of the pedestrian at time t is the true position (actual position) of the pedestrian, and is an unobservable position due to the presence of an unknown error. That is, the positioning position of the pedestrian is to obtain an optimum estimated position with respect to the true position P (t).

  Here, D (t) is expressed by Equation (3), d (t) is the distance that the pedestrian has moved (walked) from time t to time t + 1, and θ (t) is relative to the orthogonal coordinate system. This is the azimuth angle of pedestrian movement (walking). E (t) is expressed by equation (4), and e (t) is an error of the moving distance d (t). Further, the variance Q (t) of the error E (t) is expressed by the equation (5), and q is the error variance in the unit distance movement and can be a constant value.

  In addition, the position S (t) detected by GPS, base station communication, or communication with a road device at time t can be expressed by Equation (6). Here, G (t) is an error of the position S (t), and the covariance matrix R (t) of the error G (t) can be expressed by Expression (7). In Expression (7), a and b are each one-fourth of the length in the x direction and the y direction of the rectangular region that is the error range shown in FIG. That is, the covariance matrix R (t) is composed of variances in the x and y directions when 2a and 2b are 2 sigma. Even if the average value of E (t) and G (t) is 0, generality is not lost.

  The optimum estimated position H (t) of the pedestrian position P (t) at time t is expressed by a recurrence formula as shown in Expression (8) by the Kalman filter.

Here, Γ (t) is a variance of the estimation error of the estimated position H (t), and can be expressed by a recurrence formula like Formula (9). Further, “−1” attached to a matrix means an inverse matrix of the matrix. Further, the estimated position H (0) at the initial time 0 and the variance Γ (0) of the estimation error can be expressed by Expression (10) and Expression (11), respectively. Here, M is a priori information on the initial position of the pedestrian, and Σ is its error variance. If there is no a priori information, M = 0 and Σ ⁻¹ = 0, and the estimated position H (0) at initial time 0 and the variance Γ (0) of the estimated error are respectively expressed by equations (12) and (13). ).

Equation (6) is obtained when a position is detected by GPS, base station communication, or communication with a road device, and therefore, while GPS, base station communication, or communication with a road device is not performed, equation (6) is obtained. Assuming that the errors a and b in (7) are sufficiently large, in Equation (8), if R ⁻¹ (t) = 0, the estimated position is repeatedly calculated using Equation (8) as it is. Can do. That is, in this case, it is equivalent to measuring the position only by the self-contained navigation.

  The error e (t) of the movement distance d (t) varies depending on the type of distance sensor. For example, when a plurality of types of distance sensors are used at the same time, a combined error obtained by combining the errors of the sensors may be set. For example, if the distances obtained by the two types of sensors are d1 and d2, and the variances of the errors are q1 and q2, respectively, the coupling distance is set by the equation (14), and the variance as the coupling error is the equation ( 15).

  In the above formulation, in order to simplify the description, it is assumed that there is no error in the azimuth (azimuth angle) θ, but linear approximation is performed in consideration of the error f (t) in the azimuth (azimuth angle) θ. Thus, the above formulation can be easily extended. In this case, the error variance of the error f (t) is defined similarly to the errors e (t) and G (t). Alternatively, the position error variance can be increased in consideration of the azimuth error.

  For example, when the error F (t) is added to the measured value of the azimuth θ at time t, if the higher-order error is ignored, the expression (2) can be expanded as the expressions (16) and (17). Can do.

  In this case, equation (5) may be replaced with equation (18). Here, u is the variance of the error of the azimuth θ. Note that Q (t) in equation (5) may be set to a larger value instead of equations (16) to (18). In the above mathematical formula, it is formulated as two-dimensional position detection, but it may be formulated in three dimensions by adding a height dimension.

  The map database 14 includes a wide range of map information, for example, map information for detecting the position of a vehicle such as an automobile, an area where a pedestrian walks to detect the position of a pedestrian (if it is outdoors, indoors such as a road). Map information of passages and the like, and route information of transportation facilities, if any. In addition, according to the position of a pedestrian, the map information and route information of the vicinity can also be acquired by communication from the outside, such as a center apparatus or an on-road apparatus, and can be memorize | stored.

  FIG. 3 is a schematic diagram showing an example of map information. When detecting the position of a pedestrian, it becomes more complicated and difficult than when detecting the position of a vehicle. In other words, in the case of a vehicle, the position of the vehicle can be detected by map matching between the estimated position and the roadway on the map, whereas in the case of a pedestrian, walking other than the pedestrian sidewalk is possible. There are various areas where a person can walk. Moreover, the necessity of detecting the position of a pedestrian is high not only outdoors but indoors.

  In addition, when detecting the position of a pedestrian, detailed map matching such as separation of a sidewalk and a roadway is required, so detailed data is also required as map information. However, it is not necessary to store a wide range of map information in the storage unit 15 and may be acquired by communication from the outside such as an information center device or a road device as appropriate according to the position of the pedestrian.

  As shown in FIG. 3, on the map, pedestrian roads (sidewalks), roadways, pedestrian crossings, buildings (including offices, entertainment facilities, etc.), retail stores (for example, including department stores, shopping malls, etc.), There are various areas such as parks and ponds. Therefore, first, the area on the map is divided into a walkable area and a prohibited area. Forbidden areas are areas where entry of pedestrians is generally prohibited, such as restricted areas, rivers, ponds, seas, lakes, swamps, ponds, cliffs, railway sites, imperial palaces, etc. It is.

  Next, the walkable area is divided into, for example, an indoor area, a road area, and other areas. The indoor area is, for example, a building, an underpass, a station building, a store, a retail store, a house, a factory, an underground mall, a building interior, and the like. Road areas include, for example, pedestrian roads, sidewalks in the case of main roads with separate sidewalks and roadways, pedestrian crossings, pedestrian overpasses (pedestrian bridges), underground crossing roads, railroad crossings, and other privately owned roads. Called a road). The other area is, for example, a roadway, a park, a playground, or any other outdoor area that can be freely walked. In addition, in an indoor area or other area, an area where a pedestrian normally walks is set as a passage.

  As shown in FIG. 3, road areas for position detection for pedestrians include pedestrian roads, main road sidewalks, pedestrian crossings, pedestrian overpasses, underground crossing roads (access passages to subway stations, etc.) The indoor areas are buildings, retail stores, and houses, and walkways are set in the retail stores. The map information includes internal map information for each floor indicating the positions of stairs, elevators, escalators, etc. in the retail store. The prohibited areas are ponds, and the other areas are highway roads and parks. Based on the information shown in FIG. 3, roads on the map (road areas, line segments for map matching) can be set. The road area for position detection for vehicles such as automobiles is registered as map information such as main road roads, parks where vehicles can enter, roads in parking lots, private roads in factory premises, etc. be able to.

  FIG. 4 is an explanatory diagram showing a setting example of a road or passage for a pedestrian on a map. As shown in FIG. 4, one or more line segments (standard gait line, road on the map) for map matching are defined for roads, indoor areas, roads or passages in other areas, and each line segment is defined. Set the connection relationship information. A road or a passage on the map can be constituted by a link and a node, or a width corresponding to a road width or a passage width with respect to a line segment can be set. A node is a part of a road or path on the map, and the node defines the connection point of the link, ie the connectivity of the road or path on the map.

  For example, with respect to the example of FIG. 3, roads or passages on the map are set as shown in FIG. The road or passage on the map may include road width or passage width information and connection relation information. In addition, the indoor area and the prohibited area may include information on the range of each area. The other area may include area range information, or if it is determined that the other area is not a road area, indoor area, or prohibited area, do not include the area range information in the other area. May be. Although not shown in FIGS. 3 and 4, a point or a road (passage) connecting the regions may be set on the map. For example, when there is a communication port (stairs, elevator, escalator, etc.) on the road leading to an underground area in an indoor area or a subway station building, etc. Can be corrected.

  FIG. 5 is a schematic diagram showing an example of underground map information near a station. The example of FIG. 5 shows a map near a station such as a subway, FIG. 5 (a) is a map of the first basement level leading from the ground to the subway platform, and FIG. 5 (b) is a map of the platform of the second basement level. It is. As shown in FIG. 5, when the station is in an indoor area such as the basement, access portions such as stairs, escalators, elevators, etc. for moving from the road area on the ground to the indoor area and the platform are connected to or connected to both areas. Can be set as a passage.

  More specifically, from the road on the ground to the platform of the station, the passage can be set in the order of road, stairs, underground access passage, corner, ticket gate, stairs (or escalator, elevator), and platform. In this case, a vector line segment for map matching can be set for the set passage as shown in FIG. The map also includes ticket machines. Identify the location of the pedestrian in relation to the walking behavior of the pedestrian at points such as the above-mentioned pedestrian crossings, pedestrian bridges, underground crosswalks, stairs, elevators, escalators, ticket vending machines, ticket gates, and station platforms. Can be corrected). In addition, although not illustrated in FIG. 5, when there is an underground shopping street having a plurality of floors in the basement, internal map information for each floor may be included. Also, vending machines and the like can be associated with the walking behavior of pedestrians as well as ticket machines and can be included as feature points.

  The above points are included in the feature points. The feature point is a point on the map associated with the walking behavior of the pedestrian. In addition, as feature points, for example, transportation platforms where stations are set in advance (station platforms, stops, boarding areas, boarding areas), roads for vehicles on which vehicles such as passenger cars and taxis run, railroad crossings, rivers, etc. , Ponds, lakes, swamps, etc.

  FIG. 6 is an explanatory diagram showing an example of a railway route map, and FIG. 7 is an explanatory diagram showing an example of the required time between railway stations. The required time of FIG. 7 (for example, an up train) corresponds to the route map of FIG. The route map and required time constitute route information. As shown in FIG. 6, it is assumed that there are a main line, a branch line 1 and a branch line 2 that are branched from the main line. The main line has stations J1 to J12, and the branch line 1 branches from the station J3 and has stations K1 to K6. Further, it is assumed that the branch line 2 branches at the station J7 and there are stations L1 to L3. For example, railways are classified into limited express, express, semi-express, and normal, and the stations where the express stops are J1, J7, J12, and the stations where the express stops are J1, J3, J7, J10, J12. The stations where the semi-express stops are J1, J3, J7, J10, J12, K3, K6, and usually stop at all stations.

  Further, as shown in FIG. 7, the route information includes the position of each station for each of the main line, branch line 1 and branch line 2, the distance between the stations, and the required time between the stations according to the classification of each train. In addition, the above-mentioned division is an example, and is not limited to this, and other divisions such as rapid, commuting rapid, and new rapid may be used, or vehicles stop at all stations like a subway. In such a case, it is not necessary to provide a division. There may also be mutual trains between railways. Moreover, in FIG. 7, although the time required for an up train is illustrated, for example, a down train is also the same.

  Further, as shown in FIG. 5, the access path to the indoor area or road area of each station may be stored in the map database 14 as two-dimensional space or line data map information so that map matching can be performed. It is also possible to store the entire station building as a station area and store only the range (boundary).

  Train categories are stored in advance, such as train speed and vibration characteristics for each category, and by detecting movement speed and vibration characteristics when a pedestrian gets on the train, the category of the train on which the pedestrian gets Can be determined. For example, it can be determined in the order of fast moving speed, such as limited express, express, semi-express, and normal. Further, it can be determined in the order of strong vibration, such as limited express, express, semi-express, and normal.

  In addition, the station from which the train stops is determined by the elapsed time from when the pedestrian gets on the train until the train stops and the required time between the stations. It is also possible to determine the category of the train on which the boarding was made. Alternatively, the train where the pedestrian boarded from the section of the train that passes through the station by obtaining the station that the train passed without stopping by the elapsed time from the time when the pedestrian boarded the train and the required time between stations Can be determined.

  The position of the pedestrian when the pedestrian is on the train can be specified along the route map. For example, the ratio of the elapsed time after boarding to the time required from the boarding station to the next station is proportionally distributed between the boarding station and the next station, and the distance from the boarding station is determined. be able to. For example, in the example of FIG. 6 and FIG. 7, when a pedestrian gets on an express train, assuming that the elapsed time is 5 minutes after getting on from the station J1, the stations J1 and J7 (the station where the express train stops next) ) Is 5/9 (9 minutes is the required time between stations J1 and J7), and the distance from station J1 is the position of the pedestrian.

  In addition, when specifying the position of the pedestrian on the route map, the elapsed time is not only the elapsed time from the boarding point where the pedestrian got on the transportation means, but also when stopping or passing at any station In addition, the elapsed time from the station where the vehicle stopped or passed is included. Thus, the position of the pedestrian may be specified based on the elapsed time starting from the boarding station and the required time to each station, or the elapsed time starting from a certain station and the starting point regardless of the boarding station The position of the pedestrian can be specified based on the required time from the station.

  In the above example, the case of an indoor station building such as a subway was explained, but on the road, such as an outdoor train, train, train, monorail, streetcar, route bus, tram, cable car, ropeway, ship, aircraft, etc. Or, even if there is a boarding / exiting location connected to the road (for example, a station platform, stop, boarding area, boarding area, etc.), the station platform, stop, boarding area, or By setting the required time between the access passage, the route map, and the place of getting on and off, the position of the pedestrian can be similarly specified. If the means of transportation does not travel underground like a subway, there is a possibility that radio waves from GPS satellites can be received at least intermittently, and the position of pedestrians can also be specified using GPS positioning. it can.

  The storage unit 15 stores information associating the walking behavior of the pedestrian with the feature points on the map, the positioning data measured by the positioning unit 13, the processing result processed by the position detection processing unit 17, and the like. When the control unit 11, the position detection processing unit 17 and the like are constituted by a CPU, a RAM, and the like, a computer program that defines the processing procedures of the control unit 11 and the position detection processing unit 17 can be stored.

  The operation unit 16 includes various operation buttons and functions as a user interface between the pedestrian and the position specifying device 10. For example, the operation unit 16 receives an operation for starting or stopping the operation of the position specifying device 10 by an operation of a pedestrian.

  The position detection processing unit 17 may be configured by a dedicated hardware circuit, or may be configured to execute a computer program having a predetermined processing procedure.

  The position estimation unit 171 includes the estimated position calculated last time (for example, may be the latest or may be two or three times before), or the detected position obtained by updating the estimated position, and the positioning calculated by the positioning unit 13. Based on the position trajectory (positioning trajectory), an estimated position on the map (estimated position trajectory) is calculated. More specifically, the trajectory and the estimated position of the estimated position are calculated by obtaining a trajectory along the positioning trajectory from the estimated position or the detection position calculated last time to the positioning position.

  The error calculation unit 172 calculates the error range of the estimated position estimated by the position estimation unit 171. More specifically, the error calculation unit 172 sets the error range of the estimated position to a predetermined value when initially registering the estimated position, as described later, or when updating the estimated position. For example, when the estimated position is initially registered, the error range of the estimated position can be set to an error range of the positioning position (for example, 20 to 200 m). Further, when the estimated position is updated at a characteristic point of a curve, road or passage on the road, the minimum error (for example, a range of about the road width) can be obtained.

  After setting the error range of the initially registered estimated position or the updated estimated position to a predetermined value, the error calculation unit 172 moves the pedestrian's moving distance or movement from the initially registered or updated estimated position to the set predetermined value. An error range is calculated by adding a value corresponding to the direction (for example, an increase in positioning error). As a result, once the position of the pedestrian is determined (confirmed), and after setting the error range at that position to a predetermined value, the positioning error increases with an increase in the positioning trajectory (movement distance or direction) However, an appropriate error range of the estimated position can be obtained according to the positioning locus. Note that the error range can always be an appropriate predetermined constant value (for example, 100 m).

  The walking behavior determination unit 173 determines the walking behavior of the pedestrian based on data obtained by the distance sensor 132, the orientation sensor 133, the altitude sensor 134, and the like of the positioning unit 13. The walking behavior indicates a walking characteristic of a pedestrian and includes a traveling characteristic when riding a bicycle. The walking behavior is, for example, the start of walking, walking speed, fluctuation in walking speed, walking strength (for example, the level intensity indicated by acceleration by the step sensor), fluctuation in walking strength, per unit time The number of steps (in the case of a bicycle, the number of pedaling), the variation in the number of steps, the walking direction, the walking stop, and the like.

  The walking behavior determination unit 173 determines the presence / absence of disturbance in walking based on the walking behavior. For example, when the walking speed is low or the number of steps is small with reference to the predetermined walking speed or the number of steps per unit time, the walking speed is not substantially constant and the walking speed varies frequently, This is the case when there is meandering or circulation, or when the strength of walking is unstable.

  The boarding / alighting determination unit 174 determines boarding / exiting of pedestrians based on the walking behavior determined by the walking behavior determination unit 173 and the data obtained by the distance sensor 132, the direction sensor 133, and the like of the positioning unit 13. . The determination of getting on and off the pedestrian's means of transportation can be determined as having boarded, for example, when a stop of walking and a moving speed equal to or higher than a predetermined speed are detected. An acceleration sensor, a step number sensor, or the like can be used to detect walking stop, moving speed, and the like.

  Moreover, the boarding / alighting determination unit 174 determines boarding / alighting of pedestrians based on the walking behavior determined by the walking behavior determination unit 173 and the vibration characteristics detected by the vibration detection unit 178. The vibration characteristic can be detected by a sensor capable of detecting vibration, such as an acceleration sensor, an angular velocity sensor, or an angular acceleration sensor, and can be obtained as a frequency component of vibration intensity. For example, when a pedestrian is walking, the frequency characteristic of vibration has a peak of intensity at a predetermined frequency and a relatively high level of strength, whereas the pedestrian gets on a means of transportation. The frequency characteristic of vibration has a relatively low level of strength over a wide range of frequencies. For example, when a vibration characteristic having a relatively small intensity level is detected at a walking stop and a wide range of frequencies, it can be determined that the vehicle has got on the transportation means. Further, when vibration characteristics having a relatively large strength level at a predetermined frequency with the start of walking are detected, it can be determined that the vehicle has got off. Thereby, it is possible to accurately determine whether the pedestrian gets on the transportation means or gets off. Even if it is determined that the pedestrian has boarded the means of transportation, and if it can be determined that the pedestrian is on the basis of the moving speed or vibration characteristics, even if the pedestrian temporarily detected What is necessary is just to determine that the pedestrian is getting on.

  The position specifying unit 175 performs initial registration of the estimated position based on the positioning position. Further, the position specifying unit 175 uses the map matching method to update and update the estimated position to a position considered to be walking within the error range based on the estimated position calculated by the position estimating unit 171. The position is specified (detected) as the position of the pedestrian. In this case, the most likely estimated position can be specified as the position of the pedestrian based on the evaluation coefficient calculated by the evaluation unit 177. Details of the evaluation coefficient will be described later. Note that the reciprocal of the evaluation coefficient can be defined as the degree of correlation, and the degree of correlation can be used.

  The position specifying unit 175 determines whether or not there is a feature point related to the walking behavior determined by the walking behavior determination unit 173 within the error range calculated by the error calculation unit 172. The feature point is specified as the position of the pedestrian. For example, if there is a staircase within the error range of the estimated position of the pedestrian when there is a change in the walking speed or walking strength of the pedestrian, the position of the pedestrian is updated by updating the estimated position to the position of the staircase. Can be specified. Thereby, a pedestrian's position can be specified with sufficient accuracy.

  Moreover, when the position determination part 175 determines with the boarding / alighting determination part 174 that the pedestrian got on the transportation means, it is based on the elapsed time from the time of having determined that the pedestrian got on and the required time between the stations of the transportation facility. Then, the position of the pedestrian is specified along the route of transportation.

  The reliability calculation unit 176 calculates the reliability of the positioning data measured by the positioning unit 13. More specifically, the reliability calculation unit 176 performs self-inconsistency of data in a single sensor such as the distance sensor 132, the azimuth sensor 133, and the altitude sensor 134, or inconsistency of data between sensors or inconsistency with map information. The determination of the presence / absence of abnormality such as GPS, the positioning data of the GPS 131 and the calculation of the usage environment index indicating the reliability of base station communication are performed. In addition, when it is determined that there is an abnormality in the sensor or the like, a usable sensor is selected, and for an unusable sensor, a process for making the error variance of the sensor infinite (or increased) is performed. Do. Thereby, the availability of the sensor is always monitored. Hereinafter, details of the processing in the reliability calculation unit 176 will be described.

  The determination of the presence or absence of abnormality of the GPS 131 is performed by, for example, determining whether or not there is self-contradiction in temporal changes such as a positioning position determined based on the positioning data obtained by the GPS 131, a walking speed of the pedestrian, and a moving direction. be able to. If there is an abnormality, the error variance of the GPS 131 data is set to infinity and is not used. Further, when such an abnormal situation continues for a predetermined time and / or a predetermined distance, it is assumed that the reliability of the GPS 131 is low. Further, when such an abnormal situation disappears, the GPS 131 data is used, and if the normal situation continues for a predetermined time or a predetermined distance, the reliability of the GPS is returned to a normal value. .

  As the usage environment index of the GPS 131, for example, if the reception level of the GPS 131, the number of captured satellites, 2D or 3D positioning, and CEP (Circular Error Probability) is below a predetermined standard value, it is determined that the GPS 131 is abnormal. Make the error variance of the data infinite and avoid using it. Further, when such an abnormal situation continues for a predetermined time and / or a predetermined distance, it is assumed that the reliability of the GPS 131 is low. Further, when such an abnormal situation disappears, the GPS 131 data is used, and if the normal situation continues for a predetermined time or a predetermined distance, the reliability of the GPS 131 is returned to a normal value. .

  Base station communication usage environment indicators include, for example, when the communication level with the base station, the communication range of the base station, etc. falls below a predetermined standard value, the error distribution of data due to base station communication is infinite as abnormal And avoid using it. In addition, when such an abnormal situation continues for a predetermined time and / or a predetermined distance, it is assumed that the reliability of base station communication is low. In addition, when such an abnormal situation disappears, the base station communication data is used, and if the normal situation continues for a predetermined time and / or a predetermined distance, the reliability of the base station communication is increased. Return to normal value. In the above description, GPS and base station communication are distinguished from each other, but a positioning method combining GPS and base station communication may be used.

  In the case of a geomagnetic sensor, noise is added to detection data due to the presence of a surrounding iron plate or reinforcing bar, and the presence of an electric field or magnetic field such as a railroad crossing, and the detection accuracy often decreases. In such a case, even if there is no error, the geomagnetic sensor may not be used. Further, since noise is added to the detection data of the geomagnetic sensor in the building (indoor) or in the vicinity of the railroad crossing, it can be determined that there is a high possibility that a pedestrian is present indoors or in the vicinity of the railroad crossing.

  When the reliability calculated by the reliability calculation unit 176 is lower than a predetermined threshold and the feature point within the error range of the estimated position is an indoor feature point, the position specifying unit 175 determines the feature point as its own position. As specified. Indoors such as inside a building, the GPS reception level or the communication level of base station communication is lowered, or the output level of the geomagnetic sensor changes due to an iron plate or the like included in the building. Therefore, when there is an indoor feature point within the error range of the estimated position and the reliability of the positioning data is not more than a predetermined value, it can be assumed that the position of the pedestrian is at the indoor feature point. Thereby, a pedestrian's position can be specified with sufficient accuracy.

  The determination of whether there is a contradiction between the data of the sensors, for example, is obtained by adding the data increment of the relative direction sensor from that time to the current time to the positioning direction (estimated direction) measured at a certain time in the past, If there is a large difference from the data of the geomagnetic sensor, the data of the geomagnetic sensor can be regarded as abnormal and the geomagnetic sensor can not be used. In addition, when such an abnormal situation continues for a predetermined time and / or a predetermined distance, it is assumed that the reliability of the geomagnetic sensor is low. In addition, when such an abnormal situation disappears, the geomagnetic sensor data is used, and if the normal situation continues for a predetermined time and / or a predetermined distance, the reliability of the geomagnetic sensor becomes normal. Return to value.

  Also, when formulating in consideration of azimuth errors, the error variance of the geomagnetic sensor is, for example, infinite (or a sufficiently large value) in the case of abnormality, and standard value (for example, average) in the normal state Error). The error variance of the relative orientation sensor is set to a minimum when calibrated, for example, and increases with time or distance. The error variance by a plurality of sensors may be combined with the variance of each sensor. In addition, as another mutual check, if the estimated position at a certain time in the past and the distance estimated from the step number sensor deviate greatly from the positioning position measured by the GPS 131 at the current time, the positioning data of the GPS 131 Can be considered abnormal.

  The evaluation unit 177 calculates an evaluation coefficient for evaluating the estimated position calculated by the position estimation unit 171 and the estimated position updated by the position specifying unit 175 (in this case, the specified position). The evaluation coefficient is a coefficient for evaluating the certainty of the estimated position. For example, the smaller the evaluation coefficient, the larger the certainty (probability) of the estimated position. The evaluation coefficient is, for example, the positional deviation between the estimated position and the positioning position, the average of the positional deviation between the estimated position and the positioning position at the road or passage characteristic point, the estimated position and the road or passage at the characteristic point of the road or passage. And the average of the positional deviation (distance deviation). Details of the evaluation coefficient will be described later.

  The vibration detection unit 178 detects vibration characteristics by the distance sensor 132, the acceleration sensor in the azimuth sensor 133, the angular velocity sensor, the angular acceleration sensor, or the like.

  FIG. 8 is an explanatory diagram showing an example of detecting walking behavior. In FIG. 8, the horizontal axis represents time, and the vertical axis represents acceleration. FIG. 8A shows an example when a pedestrian is walking. As shown to Fig.8 (a), the acceleration of the up-down direction at the time of a walk appears with a walk. Therefore, the number of steps of the pedestrian can be obtained from the time distribution of the peak with a steep acceleration, and the strength of walking can be determined by the size of the peak. In addition, since the time per step and the number of steps per unit time can be obtained, when the step length per step is known in advance (the step length may be stored in advance, or the walking distance may be The position of the person can be obtained by map matching and calculated in association with the walking behavior of the pedestrian), and the walking speed can be calculated.

  FIG.8 (b) shows the example at the time of swinging the position detection apparatus 10 which a pedestrian carries, for example. As shown in FIG. 8B, when the acceleration data is disturbed, it can be determined that the walking behavior of the pedestrian is abnormal or the movement of the pedestrian is abnormal. Moreover, FIG.8 (c) shows the example when a pedestrian stops walking. In this way, by determining the acceleration peak value and time distribution, etc., the walking behavior of the pedestrian, for example, normal walking, fluctuation in walking speed and stability after fluctuation, fluctuation in walking strength and stability after fluctuation, etc. Stopping walking, starting walking, etc. can be determined. The walking speed can be obtained by frequency analysis of acceleration data, or the walking speed can be obtained by separately acquiring acceleration data in the traveling direction.

  FIG. 9 is an explanatory diagram showing the relationship between feature points and walking behavior. In FIG. 9, information about altitude is also associated. The association shown in FIG. 9 can be stored in the storage unit 15. As illustrated in FIG. 9, examples of the feature point include an elevator, an escalator, a staircase, a boarding / alighting place, a ticket machine, and a ticket gate, but the feature point is not limited thereto. For example, when the feature point is an elevator, the pedestrian stops walking in the elevator, so the walking behavior is stopped walking. Moreover, since it moves to an upper floor or a lower floor by an elevator, there is a change in altitude.

  As for the altitude change, when the atmospheric pressure is about 1013 hPa at a point of 0 m above sea level, the atmospheric pressure is about 1001 hPa at a point of altitude of 100 m. Therefore, it is possible to determine a place where a pedestrian is present (for example, in an elevator, a floor of a floor, etc.) in accordance with a change in atmospheric pressure.

  When the feature point is an escalator, since the pedestrian is likely to stop walking while riding on the escalator, the walking behavior is stopped walking. In addition, since some pedestrians go up and down the escalator while riding on the escalator, the walking behavior changes in walking speed (including walking pitch), changes in walking strength (variation) ). Moreover, since it moves to an upper floor or a lower floor by an escalator, there is a change in altitude.

  When the feature point is a staircase, the pedestrian walks the stairs one step at a time, so the walking behavior is a change (variation) in walking speed (including the walking pitch) and a change (variation) in walking strength. Moreover, since it moves to the upper floor or the lower floor by the stairs, there is a change in altitude.

  When the feature point is a boarding / exiting place, the pedestrian stops walking for a certain period of time to get on and off the transportation means and get on and off the vehicle such as an amusement park. ) The above gait stops (including intermittent gait stops). There is no change in altitude.

  When the feature point is a ticket vending machine, the pedestrian stops walking for a predetermined time or more in order to purchase a ticket at the ticket vending machine, so that the walking behavior is a walking stop (for example, about 5 seconds to 2 minutes) Including intermittent walking stops). There is no change in altitude. In this case, an operation behavior for purchasing a ticket may be determined.

  If the feature point is a vending machine, the pedestrian stops walking for a certain period of time in order to purchase goods with the vending machine, so the walking behavior is walking for a predetermined time (for example, about 5 seconds to 2 minutes). Stop (including intermittent walking stop). There is no change in altitude. In this case, an operation behavior for purchasing a product may be determined.

  If the feature point is a ticket gate, pedestrians may temporarily stop or walk slowly when passing the ticket gate. ) There is no change in altitude. In this case, the operation behavior for reading a ticket or the like into the ticket gate may be determined.

  Hereinafter, a method for specifying the position of a pedestrian in the vicinity of an escalator will be described as an example of a feature point. FIG. 10 is a schematic diagram illustrating an example of a walking trajectory of a pedestrian near the escalator, and FIG. 11 is an explanatory diagram illustrating an example of specifying the position of the pedestrian near the escalator. As shown in FIG. 10, a pedestrian walks from a point P1 on the second floor of the building and moves to a point P5 on the third floor via an escalator landing P2, an escalator halfway point P3, and an escalator landing P4. Suppose that In addition, it is assumed that the position P1 of the pedestrian has been specified at the beginning.

  At the point P1, there is no feature point within the error range of the estimated position, and the walking behavior is normal walking. There is no change in altitude. The position of the pedestrian is the point P1 on the second floor. Depending on the size of the estimated position error, there may be an escalator as a feature point within the error range. In this case, if the walking behavior is normal walking, the pedestrian is at least on the escalator. I understand that there is no.

  If the pedestrian continues walking and comes to the point P2 or the vicinity thereof, it can be determined that there is an escalator that is a characteristic point within the error range of the estimated position. At the escalator platform P2, the walking behavior stops because the pedestrian rides on the escalator. In addition, altitude changes begin as pedestrians move upstairs on escalators. Therefore, if there is an escalator within the error range of the estimated position, the walking behavior is stopping walking, and each condition that the change in altitude starts is satisfied, it can be determined that the pedestrian is in the vicinity of the escalator, particularly at the escalator platform P2. The position of the pedestrian can be corrected to P2 and the position can be specified.

  Next, while the pedestrian is on the escalator and moves to the upper floor, it can be determined that there is an escalator as a feature point within the error range of the estimated position. In addition, since there is a high possibility that the pedestrian has stopped on the escalator, the walking behavior is stopped walking. In addition, when a pedestrian is moving to an upper floor on an escalator, there is a change in altitude. Therefore, if there is an escalator within the error range of the estimated position, the walking behavior is the walking stop, and the conditions that the altitude change continues are satisfied, it is determined that the pedestrian is near the escalator, particularly at the midway point P3 of the escalator. The position of the pedestrian can be corrected to P3 and the position can be specified.

  Next, when it comes to the escalator landing P4, it can be determined that there is an escalator as a feature point within the error range of the estimated position. In the escalator landing P4, the pedestrian descends from the escalator, so the walking behavior starts to walk. Also, since the pedestrian gets off the escalator, the altitude change is stable. Therefore, when there is an escalator within the error range of the estimated position, the walking behavior is the start of walking, and the conditions that the altitude change is stable are satisfied, it is determined that the pedestrian is in the vicinity of the escalator, particularly in the escalator landing P4. And the position of the pedestrian can be corrected to P4 to identify the position.

  After that, when the walking behavior is normal walking and there is no change in altitude, it is assumed that the pedestrian is walking on the third floor, for example, based on the pedestrian's moving distance, moving direction, indoor map information, etc. Thus, the point P5 can be specified as the position of the pedestrian.

  When a pedestrian gets on an escalator, the escalator may walk like a staircase without stopping. In such a case, the walking behavior may be determined as a change in walking speed or a change in walking strength instead of stopping walking.

  For example, when a pedestrian moves to the upper floor or lower floor on an escalator, when walking on the escalator or when getting on the escalator, when walking on the escalator, the walking speed or strength of walking is higher than that of normal walking. fluctuate. And when the pedestrian gets off the escalator, it returns to the normal walking state, so if there is an escalator within the error range of the estimated position at the time when it is determined that the change in walking speed or walking strength is stable, It is highly possible that the pedestrian is near the escalator, and it can be determined that the pedestrian has descended from the escalator (that is, is in the landing P4).

  In the above-described example, the case where the escalator moves to the upper floor has been described. However, the position of the pedestrian can be obtained in the same manner when moving to the lower floor. Moreover, it is not limited to the case of moving from the second floor to the third floor, and the position of the pedestrian can be specified in the same manner when the escalator is used to move two or more floors.

  In the above example, the case of an escalator has been described as a feature point. However, the above-described position specifying method is not limited to the case of an escalator, and other feature points are also within the error range of the estimated position. The position of a pedestrian can be specified by determining conditions such as information on feature points, walking behavior, and altitude.

  Next, a method for selecting one or a plurality of feature points from among the feature points when there are a plurality of feature points within the error range of the estimated position of the pedestrian will be described. In this case, the error range includes not only two-dimensional but also three-dimensional errors.

  FIG. 12 is an explanatory diagram showing an example of a method for selecting a feature point within an error range. The case where a pedestrian moves from the first floor of a high-rise building to an upper floor on an elevator will be described. As shown in FIGS. 12A and 12B, it is assumed that, for example, an elevator on the 30th floor and an elevator on the 31st floor exist within the error range of the estimated position due to an error of the altitude sensor or the like. In this case, as a pedestrian position, an elevator on the 30th floor may be selected and displayed, or an elevator on the 31st floor may be selected and displayed. Alternatively, elevators on the 30th and 31st floors may be selected as pedestrian positions, and one or both may be displayed.

  When the 30th and 31st floor elevators exist as feature points within the error range of the estimated position, as shown in FIG. 12C, the pedestrian's walking trajectory (estimated position trajectory, positioning position trajectory, etc.) ), The closest walking passage can be specified by comparing with the walking passage on each floor. In the example of FIG. 12, the walking trajectory of the pedestrian does not match the 31st floor walking path, and finally only the 30th floor walking path remains as a position detection target.

  That is, when there are a plurality of feature points within the error range of the estimated position, one or a plurality of feature points among the feature points is selected as the position of the pedestrian. For example, when a pedestrian is walking in a building on a plurality of floors, reference is made to the walking path data and altitude information on each floor in the building. When several floors exist as candidates due to errors in altitude information, etc., walks that are closest to the pedestrian's walking trajectory (estimated position trajectory, positioning position trajectory, etc.) by referring to the walking path of each floor A passage can be specified, and thereby the position of a pedestrian can be selected. In addition, when there are a plurality of probable positions, a plurality of positions can be selected. Further, not only in the building but also in the case where there are a plurality of roads or walking paths in the error range, it is only necessary to select the one closer to the pedestrian's walking locus (estimated position locus, positioning position locus, etc.). . All the selected positions may be displayed, or only one may be displayed.

  In addition, when the probability of each feature point within the error range is expressed as a correlation degree, and the position of the pedestrian is specified, the better feature point of the correlation degree may be displayed. In addition, about a feature point with a bad correlation degree, this feature point can be displayed when a correlation degree becomes good according to a pedestrian's walk, without rejecting immediately. Further, when the degree of correlation becomes worse than a predetermined threshold, the feature value point may be rejected. As a result, the position of the most probable pedestrian can be specified, and even if the pedestrian's true position is determined to be temporarily not the position of the pedestrian for some reason, The original position of the pedestrian can be specified while maintaining the position without disappearing.

  13, FIG. 14 and FIG. 15 are explanatory diagrams showing examples of vibration characteristics. In the figure, the horizontal axis indicates the frequency (Hz), and the vertical axis indicates the strength of vibration. These vibration characteristics can be obtained by detecting the acceleration in the vertical direction with an acceleration sensor. FIG. 13A shows vibration characteristics when a pedestrian normally walks (for example, gentle walking, fast walking, etc.). In this case, since the number of steps is about 2 steps per second, the intensity of vibration (power spectrum) near 2 Hz increases. In addition, since there is a case of walking slowly, the strength of vibration increases even in the vicinity of 4 Hz and 6 Hz.

  FIG. 13B shows vibration characteristics when a pedestrian goes up the stairs. When a pedestrian goes up the stairs, the intensity of vibration increases at around 3 Hz, 4 Hz, and 5 Hz next to around 2 Hz. Although it approximates the case of normal walking, the strength of vibration is a small value as a whole.

  FIG. 13C shows vibration characteristics when a pedestrian goes down the stairs. When a pedestrian goes down the stairs, the vibration characteristics are similar to those of normal driving and going up the stairs, but the vibration strength is large overall, and the vibration strength is large around 2 Hz, 4 Hz, and 6 Hz. Become. In particular, in the vicinity of 2 Hz, the intensity of vibration is the largest compared with the case of normal traveling and climbing stairs.

  FIG. 14A shows vibration characteristics when a pedestrian is running (running). When a pedestrian is running, the intensity of vibration becomes very large around 3 Hz. In addition, at other frequencies, no peak is observed in the strength of the vibration, and the characteristics are gentle as a whole.

  FIG. 14B shows vibration characteristics when a pedestrian is riding on a bicycle. When a pedestrian is riding a bicycle, the vibration intensity is greater near the frequency corresponding to the timing of pedaling the bicycle and the strength is greater at many frequencies than when walking or running. A peak is observed. In particular, vibration peaks appear prominently in the vicinity of 2 Hz to 4 Hz and 6 Hz to 8 Hz. As shown in FIGS. 13 and 14, the walking state during walking can also be specifically determined by the vibration characteristics.

  FIG. 15A shows vibration characteristics when a pedestrian gets on a transportation means such as a subway, a train such as a train, or a streetcar. When a pedestrian gets on a transportation means such as a railcar or a tram, the frequency characteristics of vibration have no intensity peak at a specific frequency, and the intensity level is relatively small over a wide range of frequencies.

  FIG. 15B shows vibration characteristics when a pedestrian gets on a transportation means such as a bus. When a pedestrian gets on a transportation means such as a bus, the intensity of vibration is small as a whole, but the intensity of vibration is relatively large in the vicinity of 1 Hz to 2 Hz. In addition, although the intensity of vibration is small even at other frequencies, the characteristic has many peaks. FIGS. 15A and 15B show vibration characteristics when the pedestrian gets on the transportation means and the transportation means is moving. FIG. 15C shows vibration characteristics when a pedestrian gets on a transportation means such as a subway or a train and the transportation means is stopped.

  As shown in FIG. 15C, when the transportation means is stopped, the frequency characteristics of vibration are at a very small level as a whole.

  In addition to the vibration characteristics, by detecting the horizontal speed with an acceleration sensor, it is possible to determine whether the walking is normal walking, running, or running by bicycle with higher accuracy. For example, it is about 4 km / h for normal walking, about 10 km / h for normal running, and about 5 to 10 km / h for traveling by bicycle. In addition, when a pedestrian gets on a transportation means, the traveling speed may differ depending on the transportation means, and the traveling means (movement method) used by the pedestrian is determined by detecting the traveling speed. can do. Details will be described later.

  The display unit 18 is a liquid crystal display panel, for example, and displays its position on a map to a pedestrian.

  When the pedestrian's position is displayed on the display unit 18, the audio output unit 19 outputs audio or sound to notify the pedestrian of necessary information or to call attention.

  The movement method determination unit 20 specifies a feature point within the error range calculated by the error calculation unit 172, and also uses the specified feature point, the walking behavior of the pedestrian obtained by the walking behavior determination unit 173, and the boarding / alighting determination unit 174. The moving means (moving method) used by the pedestrian is determined by associating the determination result of boarding / exiting with the vibration characteristics detected by the vibration detecting unit 178 and the like.

  FIG. 16 is an explanatory view showing an example of the moving means. As shown in FIG. 16, the moving means (moving method) can be classified into three categories. Note that the classification example is an example, and the present invention is not limited to this. The first moving means is a transportation means (first transportation means) having a route where a boarding / exiting location is determined in advance, and the second moving means is a transportation means other than the first transportation means (second transportation means). The third moving means is walking or bicycle.

  As the first moving means, for example, a railway vehicle such as a subway, a train, a train or a train, a boat such as a boat, a pleasure boat, a ferry or a sightseeing boat, a monorail, a cable car, a ropeway, an airplane, a route bus or a tram is there. Moreover, as a 2nd moving means, it is a private car, a motorbike, a taxi, a truck, a sightseeing bus, or a charter bus etc., for example.

  Next, the determination method of a moving means is demonstrated. FIG. 17 is an explanatory diagram showing an example of determining a transportation facility having a route where a boarding / alighting place is determined. As shown in FIG. 17, as described above, the first transportation means (first moving means, first moving method) having a route in which a boarding / alighting place is defined are railway vehicles, ships, monorails, cable cars, ropeways, There are airplanes, route buses, trams, etc., and each of these transportation facilities has a dedicated boarding / exiting place. For this reason, when the position of a pedestrian is estimated, if a boarding / alighting place can be specified as a feature point in the error range of the estimated position, the possibility that the pedestrian uses a transportation means corresponding to the boarding / alighting place increases. . In this case, if it can be determined that the pedestrian has boarded the transportation means, it can be determined which transportation means is used, and the pedestrian's movement means (movement method) can be determined.

  As shown in FIG. 17, for example, in the case of a railway vehicle, the walking behavior is walking stop. The characteristic point in the error range of the estimated position of the pedestrian is a place where the railway vehicle gets on and off, and the vibration characteristic is continuous weak vibration different from walking as in the example of FIG. The moving speed is 50 km / h or more, and there is no change in altitude. When all or some of these conditions are met, the pedestrian moving means can be determined to be a rail vehicle.

  In the case of a ship, the walking behavior is walking stop. The characteristic points in the error range of the estimated position of the pedestrian are the place where the ship gets on / off or a river, sea, lake, swamp, and the like. The moving speed is 1 km / h or more, and there is no change in altitude. When all or some of these conditions are met, the pedestrian moving means can be determined to be a ship.

  In the case of a monorail, the walking behavior is stop walking. The characteristic point in the error range of the estimated position of the pedestrian is a monorail boarding / alighting place, the moving speed is 10 km / h or more, and there is no change in altitude. If all or some of these conditions are met, the pedestrian's moving means can be determined to be a monorail.

  In the case of a cable car, the walking behavior is stopping walking. The characteristic point in the error range of the estimated position of the pedestrian is the place where the cable car gets on and off, the moving speed is 10 km / h or more, and there is a change in altitude. If all or some of these conditions are met, the pedestrian's moving means can be determined to be a cable car.

  In the case of the ropeway, the walking behavior is walking stop. The characteristic point in the error range of the estimated position of the pedestrian is the place where the ropeway gets on and off, the moving speed is 10 km / h or more, and there is a change in altitude. If all or some of these conditions are met, the pedestrian's moving means can be determined to be a ropeway.

  In the case of an aircraft, the walking behavior is walking stop. The characteristic point in the error range of the estimated position of the pedestrian is the place where the aircraft gets on and off, the moving speed is 300 km / h or more, and there is a change in altitude. When all or some of these conditions are met, the pedestrian moving means can be determined to be an aircraft.

  In the case of a route bus, the walking behavior is walking stop. The characteristic point in the error range of the estimated position of the pedestrian is the place of getting on and off the route bus, and the vibration characteristic is 1 Hz to the whole although the intensity of vibration is small as in the example of FIG. The intensity of vibration is relatively large in the vicinity of 2 Hz. In addition, although the intensity of vibration is small even at other frequencies, the characteristic has many peaks. The moving speed is 10 km / h or more, and there is no change in altitude. If all or some of these conditions are met, the pedestrian's moving means can be determined to be a route bus.

  In the case of a tram, the walking behavior is stopping walking. The characteristic point in the error range of the estimated position of the pedestrian is the place where the tram is getting on and off, and the vibration characteristic is continuous weak vibration different from walking as in the example of FIG. The moving speed is 10 km / h or more, and there is no change in altitude. When all or some of these conditions are met, the pedestrian moving means can be determined to be a tram. Note that the example of FIG. 17 is an example, and the present invention is not limited to this. For example, the condition for determination may be another condition.

  On the other hand, the second moving means (second moving method) has a dedicated boarding place unlike the first moving means, and can be boarded from any point such as a general road or a parking lot (second transportation means). ). For this reason, when the position of a pedestrian is estimated, if a road on which a vehicle such as an automobile can pass as a feature point can be specified in the error range of the estimated position, the pedestrian is likely to use the transportation. Become. In this case, if it can be determined that the pedestrian has boarded the transportation means, it is possible to determine the pedestrian moving means (moving method). Whether or not the pedestrian has boarded the transportation means can be determined to have boarded, for example, when the moving speed exceeds about 5 km / h to 40 km / h.

  In the case of the second transportation system, the vehicle often decelerates, accelerates or stops near the intersection because of the timing of switching the traffic light at the intersection. By detecting these, the moving means can be more accurately detected. Can be determined. Further, in the case of the second transportation, this may be detected because it does not stop at the boarding place for the first transportation. Thereby, the determination accuracy of the movement in the second transportation can be further increased.

  Further, for example, when a walking rhythm with a different cycle from that of a bicycle is detected, or when the moving speed is 5 km / h or less, the moving method can be determined to be walking. Further, when a rhythm having a different period from that of walking is detected and the moving speed is, for example, 20 km / h or less, it can be determined that the pedestrian is moving by bicycle. In this case, it may be determined that the pedestrian is moving on a bicycle when the walking speed is irregularly detected, for example, at a speed of 5 km / h or more, and a walking stop is detected.

  Next, the position detection process by the map matching method of the position specifying device 10 will be described. FIG. 18 is an explanatory diagram showing an example of new registration of an estimated position. The new registration (initial registration) of the estimated position is a process performed when the map matching process is started or when there is no estimated position candidate.

  Whether or not to newly register the estimated position is determined by, for example, the following condition (1) and condition (2). That is, when both the condition (1) and the condition (2) are satisfied, the new registration of the estimated position is not performed, and when either the condition (1) or the condition (2) is not satisfied, the new registration of the estimated position is performed. I do. Condition (1) is a case where the reliability of the sensor or the like is equal to or less than a predetermined threshold value (bad reliability). For example, the reliability of the GPS 131 is bad or the reliability of the geomagnetic sensor is bad. Further, the condition (2) is a case where there is a disturbance of walking over a predetermined range (time and / or distance).

  As shown in FIG. 18, it is determined whether there is a road on the map or a set passage within the error range of the positioning position A. If there is a road (or a passage), the closest to the positioning position A A point on the road or passage is registered as a new estimated position corresponding to the positioning position A. In FIG. 18, since there are two roads (or passages) within the error range, the points M and N that are closest to the positioning position A on each road (or passage) are registered as estimated positions. In this case, it is also possible to register in advance a road (or a passage) whose orientation substantially coincides with the orientation of the positioning locus up to the positioning location A or the positioning orientation at the positioning location A. If there is no road (or passage) in which the orientation of the positioning trajectory or the positioning orientation substantially matches the direction of the road (or passage), until there is a road (or passage) that can be registered within the error range Wait without newly registering the estimated position.

  When the estimated position is newly registered, the error range of the positioning position corresponding to the estimated position is set (registered) as the error range of the newly registered estimated position. In the example of FIG. 18, the error range of the estimated positions M and N inherits the error range of the estimated position A. Further, based on the positional deviation between the newly registered estimated positions M and N and the corresponding positioning position A, evaluation coefficients for the estimated positions M and N are calculated.

  FIG. 19 is an explanatory diagram showing an example of calculation of an evaluation coefficient for a newly registered estimated position. The example of FIG. 19 shows a case where the estimated position M is newly registered in association with the positioning position A. If the coordinates of the positioning position A are (X, Y) and the coordinates of the newly registered estimated position M are (x, y), the evaluation coefficient C of the estimated position M can be C = C1 + C2. Here, C1 = | x−X | and C2 = | y−Y |. That is, the evaluation coefficient C of the estimated position M can be the difference between the x coordinate of the estimated position M and the positioning position A, and the difference of the y coordinate between the estimated position M and the positioning position A. In this case, the smaller the evaluation coefficient, the higher the probability (probability) of the estimated position. The evaluation coefficient C is not only calculated for each x coordinate and each y coordinate, but can also be used as one index by the sum of absolute values of the x coordinate and the y coordinate or the square root of the square sum. Thereby, it is possible to grasp how much the estimated position M is relative to the positioning position A.

  Next, an example of calculating the locus of the estimated position after new registration will be described. FIG. 20 is an explanatory diagram showing an example of calculation of the estimated position trajectory on the ground until the transportation facility is used, and FIG. 21 is an explanatory diagram showing an example of calculating the estimated position locus on the underground until the transportation facility is used. FIG. In the example of FIGS. 20 and 21, map matching is used, and the estimated position is updated (corrected) at the feature point of the road or passage. As shown in FIG. 20, when the underground crossing passage which is a characteristic point exists within the error range of the estimated position, the estimated position is updated to the point of the underground crossing road. Note that the estimated position is not updated to a road at points other than the characteristic points.

  In addition, as shown in FIG. 21, when there are corners, ticket machines, ticket gates, stairs, escalators, elevators, and the like that are characteristic points within the error range of the estimated position, the estimated position is updated to these characteristic points. Note that the estimated position is not updated to a passage at a point other than the feature point.

  FIG. 22 is an explanatory diagram showing another example of the locus calculation of the estimated position on the ground until the transportation facility is used, and FIG. 23 is another diagram of the locus calculation of the estimated position underground until the transportation facility is used. It is explanatory drawing which shows an example. In the examples of FIGS. 22 and 23, the estimated position is always matched on the road or passage unless the walking direction of the pedestrian and the direction of the road or passage exceed a predetermined threshold using map matching.

  Also, as shown in FIG. 22, when an underground crossing passage that is a characteristic point exists within the error range of the estimated position, the estimated position is updated to a point of the underground crossing road. Further, as shown in FIG. 23, when there are a turning point, a ticket machine, a ticket gate, a staircase, an escalator, an elevator, and the like as characteristic points within the error range of the estimated position, the estimated position is updated to these characteristic points.

  As another method, for example, when the estimated position protrudes from the passage (passage area) using map matching, the estimated position can be updated to the passage. In addition, when there are ticket machines, ticket gates, stairs, escalators, elevators, and the like that are feature points within the error range of the estimated position, the estimated position can be updated to these feature points. At points other than the feature points, the estimated position is not updated to the passage unless the estimated position protrudes from the passage. The same applies to the ground.

  In addition, it is possible to use only self-contained navigation without using map matching. For example, in the basement where radio waves from GPS satellites cannot be received, the estimated position is obtained using only self-contained navigation, and ticket machines, ticket gates, stairs, escalators, elevators, etc. that are characteristic points within the estimated position error range If present, the estimated position is updated to these feature points. In addition, in the basement where radio waves from GPS satellites cannot be received, it is possible to obtain the estimated position using only the self-contained navigation and not to update the estimated position at the feature point. Such a method can be used when the size of the error range of the estimated position can be tolerated to some extent, such as the location of the station building or the like that makes it easy to identify the point where the pedestrian gets on or off the transportation means.

  In the above-described example, the example of entering the underground from the road and getting on the transportation means has been described. However, the estimated position from the transportation means to the road and exiting on the road can be similarly identified and tracked. Therefore, for example, it is possible to identify and track the position of a pedestrian continuously (continuously) on all routes from the platform until getting on the transportation means, getting off after getting on, and getting off after getting off the road. It becomes possible.

  The error range of the estimated position can be a positioning error (for example, a range of 20 to 200 m) in the new registration (initial registration) of the estimated position. Further, the error range of the estimated position can be set to the minimum error range (for example, about the road width or the passage width) when the estimated position is updated (corrected) at the feature point of the road or the passage. Thereafter, as the pedestrian walks, positioning errors are accumulated, so that the error range of the estimated position can be increased. As a result, once the position of the pedestrian is determined (confirmed), and after setting the error range at that position to a predetermined value, the positioning error increases with an increase in the positioning trajectory (movement distance or direction) However, an appropriate error range of the estimated position can be obtained according to the positioning locus. The error range of the estimated position can always be an appropriate predetermined constant value (for example, 100 m). Thereby, the processing effort of position detection can be reduced.

  Next, a method for updating the estimated position will be described. The update of the estimated position includes, for example, the connection characteristics of the road or passage within the error range of the estimated position, the connection characteristics between the road or passage and other areas, the walking behavior of the pedestrian, the reliability (reliability) of the positioning data, This is performed based on the evaluation coefficient of the estimated position. If the estimated position is not valid, the estimated position is rejected.

  FIG. 24 is an explanatory diagram showing an example of updating the estimated position. As shown in FIG. 24, the estimated position from the estimated position updated last time (for example, may be the latest or may be two or three times before) corresponding to the positioning trajectory up to the positioning position A. It is assumed that there are two estimated positions M and N corresponding to the positioning position A due to the locus. Since a road or a passage exists within the error range of the estimated position M, the estimated position M is updated to a position on the road or the passage. Further, a value corresponding to the positional deviation between the estimated position M and the updated estimated position may be added to the evaluation coefficient of the estimated position M and inherited as the updated estimated coefficient of the estimated position. In addition, at the feature point, the estimated position can be updated by correcting the displacement of the estimated position M, and the evaluation coefficient and error range can be updated. In this case, as the error range to be updated, for example, a minimum value (a range of road width or passage width) can be set. In addition, it is determined whether or not the azimuth difference between the azimuth of the estimated position and the azimuth of the road or the passage is smaller than a predetermined threshold. If the azimuth difference is larger than the threshold, the estimated position is not updated on the road or the passage. You can also

  Within the error range of the estimated position N, the road or passage where the estimated position updated last time is outside the error range, so it is determined whether there is another road or passage within the error range. If another road or passage exists, the estimated position is updated to the position of the road or passage, and the error range of the estimated position N and the error range of the estimated position updated with the evaluation coefficient are taken over as the evaluation coefficient. If it is determined that there is no road or passage to be updated, the estimated position N can be rejected.

  FIG. 25 is an explanatory diagram showing another example of updating the estimated position. The example of FIG. 25 is a case where the road or passage where the estimated position updated last time (for example, may be the latest or may be two or three times before) branches into two roads or passages. It is. Assume that there is one estimated position M corresponding to the positioning position A by the locus of the estimated position from the previously updated estimated position corresponding to the positioning locus up to the positioning position A. Since one branched road or passage exists within the error range of the estimated position M, the estimated position M is updated to a position on the road or the passage. Further, a value corresponding to the positional deviation between the estimated position M and the updated estimated position may be added to the evaluation coefficient of the estimated position M and inherited as the updated estimated coefficient of the estimated position. The estimated position on the other road or passage that is outside the error range of the estimated position M is rejected. In this case as well, at the feature point, the estimated position can be updated by correcting the displacement of the estimated position M, and the evaluation coefficient and error range can be updated.

  FIG. 26 is an explanatory diagram showing another example of updating the estimated position. In the example of FIG. 26 as well, when the road or passage where the estimated position updated last time (for example, the latest or two or three times before) may exist is branched into two roads or passages. It is. Assume that there is one estimated position M corresponding to the positioning position A by the locus of the estimated position from the previously updated estimated position corresponding to the positioning locus up to the positioning position A. Since both branched roads or paths exist within the error range of the estimated position M, the estimated position M is updated to a position on each road or path. The updated estimated position is set as the estimated position of the first candidate and the estimated position of the second candidate. Further, a value corresponding to the positional deviation between the estimated position M and the estimated position of the first candidate and the estimated position of the second candidate is added to the evaluation coefficient of the estimated position M, and the estimated position of the first candidate and the second candidate You may make it inherit as an evaluation coefficient of an estimated position. In this case as well, at the feature point, the estimated position can be updated by correcting the displacement of the estimated position M, and the evaluation coefficient and error range can be updated.

  Next, a method for calculating the evaluation coefficient of the estimated position at the feature point will be described. FIG. 27 is an explanatory diagram illustrating an example of calculation of the evaluation coefficient of the estimated position at the feature point. In the example of FIG. 27, it is assumed that there are estimated positions M1, M2, and M3 that are updated to positions on the road or passage corresponding to the positioning positions A1, A2, and A3 at the feature points B1, B2, and B3. The feature points B1 to B3 are, for example, a pedestrian crossing, a pedestrian bridge, an underground crossing passage, a staircase, an elevator, an escalator, a ticket machine, a ticket gate, a station platform, and a corner. The positional deviation between the positioning position A1 and the estimated position M1 is (x1, y1), the positional deviation between the positioning position A2 and the estimated position M2 is (x2, y2), and the positional deviation between the positioning position A3 and the estimated position M3 is Let (x3, y3). In addition, the positional deviation between the estimated position updated last time (for example, the latest position or a plurality of previous times such as two times or three times) and the corresponding positioning position is (x0, y0). The evaluation coefficient of the estimated position (for example, estimated position M3) can be obtained as an average value of the difference in positional deviation between the estimated position and the positioning position.

  That is, the average value of the difference in positional deviation in the x direction is {| x1-x0 | + | x2-x1 | + | x3-x2 |} / 3, and the average value of the positional deviation in the y direction is { | Y1-y0 | + | y2-y1 | + | y3-y2 |} / 3. It can be said that as the positional deviation at each of the feature points B1, B2, and B3 is equal, the evaluation coefficient becomes smaller and the probability (probability) of the estimated position is larger. Thereby, it is possible to grasp how much the estimated position is relative to the positioning position.

  In addition, as an evaluation coefficient, the square of the difference of the position shift in each feature point is totaled and averaged, and the square root of the average value can be obtained. Further, instead of the average value, other statistical values such as a median value and a numerical value that is a half of the sum of the maximum value and the minimum value can be used.

  FIG. 28 is an explanatory diagram showing another example of calculating the evaluation coefficient of the estimated position at the feature point. In the example of FIG. 28, it is assumed that there are estimated positions M1, M2, and M3 corresponding to the positioning positions A1, A2, and A3 at the feature points B1, B2, and B3. The positional deviation (distance) between the position of the point B1 and the estimated position M1 is d1, the positional deviation (distance) between the position of the point B2 and the estimated position M2 is d2, and the positional deviation between the position of the point B3 and the estimated position M3. Let (distance) be d3. The evaluation coefficient of the estimated position (for example, estimated position M3) can be obtained as an average value (d1 + d2 + d3) / 3 of the positional deviation (distance) between the feature point on the road or the passage and the estimated position.

  That is, it can be said that the shorter the distance between the estimated position and the position of the road or passage, the smaller the evaluation coefficient and the greater the probability (probability) of the estimated position. Thereby, it can be grasped how much the estimated position is relative to the road or the passage.

  FIG. 29 is an explanatory diagram showing another example of the evaluation coefficient of the estimated position. When obtaining the evaluation coefficient of the estimated position, the present invention is not limited to the configuration in which the evaluation coefficient is calculated at a point where there is an obvious azimuth change, such as a characteristic point as shown in the examples of FIGS. As shown in Fig. 5, it is possible to evaluate the matching between the locus of the estimated position or the positioning locus and the road shape or the passage shape on the map. In addition, it is possible to evaluate using any one of the plurality of types of evaluation coefficients as described above. Alternatively, the plurality of types of evaluation coefficients may be appropriately weighted and combined to be used as one evaluation coefficient. it can.

  Next, a method for updating (correcting) the evaluation coefficient of the estimated position will be described. When the estimated position updated to the position on the road is at or near the pedestrian crossing, if the increase of the walking speed of the pedestrian or the stop of walking is detected, the probability that the pedestrian is in the pedestrian crossing or near the pedestrian crossing Assuming that the evaluation coefficient is high, the evaluation coefficient is updated to be small by adding a predetermined numerical value of 1 or less (for example, m1 = 1/3) to the evaluation coefficient of the estimated position. When updating the evaluation coefficient so that the evaluation coefficient becomes smaller by adding a numerical value of 1 or less to the evaluation coefficient, actually, data of the evaluation coefficient and the numerical value (default value is 1) is prepared. The stored value of the evaluation coefficient is kept as it is, and the numerical value to be integrated is changed, and the above integrated value can be used as an apparent evaluation coefficient when comparing with other estimated positions. Thereby, subsequent calculation of the evaluation coefficient can be performed without contradiction.

  When the estimated position updated to the position on the road is at or near the pedestrian crossing, the evaluation coefficient is updated according to the walking behavior at the start of the green light or the walking behavior at the start of the red signal. For example, if the walking starts from the stop when the green light starts, it is assumed that the pedestrian is walking on a pedestrian crossing, and the calculated evaluation coefficient is a predetermined numerical value of 1 or less (for example, m2 = 1/5). ) Is updated so that the evaluation coefficient becomes smaller. Further, if there is an increase in walking speed at the start of the red signal, it is assumed that the probability that the pedestrian is walking on the pedestrian crossing is high, and the calculated evaluation coefficient is a predetermined numerical value of 1 or less (for example, m3 = 1/5). ) Is updated so that the evaluation coefficient becomes smaller.

  In addition, when the estimated position updated to the position on the road is on the pedestrian overpass, if the pedestrian walks on the pedestrian overpass when a change in walking speed or a change in walking strength is detected during stair walking As a result, the evaluation coefficient is updated so that the evaluation coefficient becomes smaller by adding a predetermined numerical value of 1 or less (for example, m4 = 1/5) to the calculated evaluation coefficient. In this case, it is determined whether or not there is an increase or decrease in altitude. If there is an increase or decrease in altitude, the evaluation coefficient can be updated to be smaller.

  Also, when the estimated position updated to the position on the road is in the vicinity of the railroad crossing, if a pedestrian stoppage is detected, or if noise is added to the detection level of the geomagnetic sensor, the pedestrian will Assuming that there is a high probability of stopping before this, the evaluation coefficient is updated to be small by adding a predetermined numerical value of 1 or less (for example, m5 = 1/3) to the calculated evaluation coefficient.

  In addition, when the estimated position updated to the position on the passage moves from the road to the underground crossing passage (access passage to the station), when detecting fluctuations in walking speed or walking strength in stairs walking, Assuming that the probability that a pedestrian is walking in the underground crossing passage is high, the evaluation coefficient is updated to be small by adding a predetermined numerical value of 1 or less (for example, m6 = 1/5) to the calculated evaluation coefficient. . In this case, for example, m5 = 1/5 is used as a predetermined numerical value due to low reliability of the sensor such as GPS 131, low reliability of the geomagnetic sensor, fluctuation in walking speed or fluctuation in walking strength, and the like. it can. It is also possible to determine whether or not there is an increase or decrease in altitude, and when there is an increase or decrease in altitude, the evaluation coefficient can be updated to be smaller.

  In addition, when the estimated position updated to the position on the aisle is in the vicinity of the elevator, when the pedestrian stops walking, changes in altitude or atmospheric pressure, or the reliability of sensors such as GPS 131 decreases, the pedestrian Assuming that the probability of being in the elevator is high, the evaluation coefficient is updated to be small by adding a predetermined numerical value of 1 or less (for example, m7 = 1/5) to the calculated evaluation coefficient.

  Also, when the estimated position updated to the position on the passage is in the vicinity of the escalator, the walking stop of the pedestrian, the fluctuation of the walking speed or the fluctuation of the walking strength, the change of the altitude or the atmospheric pressure, the reliability of the sensor such as the GPS 131 When a decrease in sex is detected, it is assumed that a pedestrian is likely to be on the escalator, and the evaluation coefficient is reduced by adding a predetermined numerical value of 1 or less (for example, m8 = 1/5) to the calculated evaluation coefficient. Update as follows. In addition, as another walking behavior for distinguishing between an escalator and an elevator, for example, when there is a change in acceleration in the vertical direction, it is determined that the pedestrian is in the elevator and the acceleration is performed not only in the vertical direction but also in the horizontal direction. If there is a change, it may be determined that the pedestrian is on the escalator.

  In addition, when the estimated position updated to the position on the aisle is in the vicinity of the station platform, stop, boarding area, boarding area, etc., the pedestrian stops walking for a predetermined time or more, and the reliability of the sensor such as GPS 131 decreases. Is detected, it is assumed that there is a high probability that the pedestrian is in the platform, stop, boarding area, boarding area of the station, and a predetermined numerical value of 1 or less (for example, m9 = 1/5) is added to the calculated evaluation coefficient. As a result, the evaluation coefficient is updated to be smaller.

  In addition, when the estimated position updated to the position on the passage is in the vicinity of the ticket vending machine, if the pedestrian detects a temporary stoppage of the pedestrian or a decrease in the reliability of the sensor such as the GPS 131, the pedestrian Assuming that the probability of being in the vicinity is high, the evaluation coefficient is updated to be small by adding a predetermined numerical value of 1 or less (for example, m10 = 1/3) to the calculated evaluation coefficient.

  In addition, when the estimated position updated to the position on the aisle is in the vicinity of the ticket gate, if a pedestrian's instantaneous walking stop or disorder of walking is detected, there is a probability that the pedestrian is near the ticket gate. Assuming that the value is high, the evaluation coefficient is updated to be small by adding a predetermined numerical value of 1 or less (for example, m11 = 1/3) to the calculated evaluation coefficient.

  The association between the feature point of the road or the passage and the walking behavior of the pedestrian or the association between the feature point and the reliability of the sensor may be stored in the storage unit 15 in advance.

  As described above, it is possible to update the evaluation coefficient so as to decrease, to increase the certainty of the estimated position, and to determine the accuracy of position detection. Further, when detecting the own position based on the estimated position, it is possible to continue detecting the own position based on the most likely estimated position even when there are a plurality of estimated position candidates. Instead of reducing the value of the evaluation coefficient, all other estimated positions may be rejected. This corresponds to specifying the initial position of the estimated position.

  When there are a plurality of estimated position candidates, the estimated position having the smallest evaluation coefficient among the estimated position candidates is regarded as the position of the pedestrian, and the estimated position having an evaluation coefficient larger than a predetermined threshold is rejected from the candidate target. be able to. In addition, when the estimated position of the other region and the estimated position of the road or passage exist at a walking distance that is equal to or greater than the threshold, the estimated position of the other region may be rejected as having a low existence probability. Furthermore, the estimated position that is outside the error range of the positioning position can be rejected. In addition, when there is only one estimated position and the estimated position is on a road or a passage for a predetermined time and / or a predetermined distance, the estimated position is determined as a pedestrian position, The evaluation coefficient for the determined estimated position is set to zero. Further, when there is no estimated position, a position obtained by accumulating the positioning position or the positioning locus from the latest estimated position until a new estimated position is obtained is set as a temporary estimated position (temporary position). Can do.

  Next, the correction of the positioning direction will be described. When the map matching method identifies the road or passage and its estimated position, and the positioning direction does not change more than a predetermined walking distance (for example, 20 m), the positioning direction is changed to the road or passage direction on the map. It can be corrected. The timing for correcting the positioning direction is, for example, when a situation where the specified estimated position is unique continues for a predetermined time (for example, 1 minute) or a predetermined distance (for example, 50 m), or for all specified positions The situation where the road or passage direction on the map corresponding to the estimated position is within a predetermined threshold (for example, 2 degrees) is within a predetermined time (for example, 1 minute) and / or a predetermined distance (for example, 50 m) This is a case where the above is continued and the positioning azimuth has not changed more than a predetermined walking distance (for example, 20 m).

  Further, the following correction timing conditions can be added. As the condition (1), if the difference between the estimated position and the positioning position is within a predetermined threshold (for example, 50 m) for a predetermined time (for example, 1 minute) or a predetermined distance (for example, 50 m), (2) When the probability that the geomagnetic sensor is normal for a predetermined time (for example, 1 minute) or a predetermined distance (for example, 50 m) is low, for example, continuous for a predetermined walking distance (for example, 20 m) or more When the geomagnetic sensor is not normal, as the condition (3), when the probability that the GPS 131 is normal for a predetermined time (for example, 1 minute) and / or a predetermined distance (for example, 50 m) is low, for example, This is a case where the GPS 131 is not normal continuously for a predetermined walking distance (for example, 50 m). The correction of the positioning direction may be limited to the case where the road direction or the passage direction on the map is straight.

  Next, a display example for displaying the position of a pedestrian on a map will be described. When the position of the pedestrian is displayed on the display unit 18, when there is no estimated position, the positioning position or the temporary position is displayed, and when there is an estimated position, the estimated position (including the updated estimated position) is displayed. .

  FIG. 30 is an explanatory diagram showing an example of the display of the position of the pedestrian. When there is one estimated position on the road or passage, the estimated position (or including the updated estimated position) is displayed on the map, and the error range of the displayed estimated position is also displayed. When there are a plurality of estimated positions, one estimated position with the smallest evaluation coefficient can be displayed.

  FIG. 31 is an explanatory diagram showing another example of the display of the position of the pedestrian. When there are a plurality of estimated positions, an area including the plurality of estimated positions is displayed as the estimated position. In this case, a range including the error range of each estimated position may be displayed. In addition, the estimated position and its error range can be displayed at the same time after expanding or reducing the size of the error range of the estimated position in accordance with the magnitude of the evaluation coefficient of the estimated position. When there are a plurality of ranges, a range including an error range of each estimated position may be displayed. Moreover, you may display the gravity center position of several estimated position.

  FIG. 32 is an explanatory diagram showing another example of the display of the position of the pedestrian. When there are a plurality of estimated positions, each estimated position is displayed, and the error range of each estimated position or the rank of probability is simultaneously displayed. In FIG. 32, the estimated position of the first candidate is the position of the pedestrian with the highest probability, and the estimated position of the second candidate indicates the position of the pedestrian with the next highest probability. In addition, when there are a plurality of estimated positions and there are a plurality of estimated positions of evaluation coefficients smaller than the predetermined threshold, only the positions where the evaluation coefficients are smaller than the threshold can be displayed. Thereby, the pedestrian can easily determine his / her position and can know not only the most likely position but also a possible position.

  FIG. 33 is an explanatory view showing another example of the display of the position of the pedestrian. In FIG. 33, when the display surface of the display unit 18 is small and the map information cannot be displayed in detail (for example, when the scale of the map cannot be increased), the road or passage is displayed as a line segment. Thus, the position of the pedestrian can be displayed as a single point.

  As described above, when the position specified (detected) by updating the estimated position is displayed as the position of the pedestrian, when there are a plurality of specified positions, it is most certain according to the magnitude of the calculated or corrected evaluation coefficient. The specific positions may be displayed, or a plurality of specific positions may be displayed, or some of the specified positions may be selected and displayed. Also, at a certain point in the process of detecting the position of the pedestrian, the position cannot be detected temporarily with high accuracy, and if the evaluation coefficient increases and the detected position is displayed, the pedestrian Even if there is a possibility that the wrong position is displayed, if the accuracy of the specific position is sufficiently secured as a result of the subsequent positioning, the position will be identified after the time when the certainty of the position can be secured. The position can also be displayed.

  Next, an example of displaying the position of the pedestrian when the pedestrian gets on the transportation means and is moving will be described. FIG. 34 is an explanatory diagram showing an example of the display of the position of a pedestrian who is moving by means of transportation. As shown in FIG. 34, the route map of the transportation means on which the pedestrian gets on can be displayed on the display unit 18, and the current position of the pedestrian can be displayed along the route map.

  In this case, when an optimum route is guided from the departure point to the destination, a route map between the boarding station and the getting-off station on the route to be guided can be displayed. In addition, when getting on a transportation means and traveling a relatively long distance, a route map near the current position can be displayed.

  FIG. 35 is an explanatory diagram showing another example of the display of the position of a pedestrian who is moving by means of transportation. As shown in FIG. 35, in addition to the route map in the vicinity of the current position, the time required to the next station, information for transfer guidance, and the like can be displayed. Moreover, when performing route guidance, you may display the required time to the station which gets off.

  In the above-described example, the display example of the position of the pedestrian who is moving on the railcar has been described. However, the present invention is not limited to this, and the position is also the same when riding on other transportation means having a route. Can be displayed. Further, in the case of a transportation means that does not have a dedicated boarding place, it is possible to display the position of a pedestrian who is moving by the vehicle along the vehicle road.

  Next, the procedure of the position detection process will be described. 36, 37, 38 and 39 are flowcharts showing the procedure of the position detection process. The control unit 11 performs position detection processing in cooperation with each unit in the position specifying device 10. The control unit 11 determines whether or not a search for an initial position is necessary (S11).

  Unlike in the case of pedestrians, in the case of a vehicle, position detection is almost impossible, and even when the power is turned off, the detected position is saved, so there is almost no need to search for the initial position. There is nothing. However, in the case of a pedestrian, position detection may become impossible after the pedestrian turns off the mobile device or after coming out of the road from the basement, and it is necessary to search for the initial position. is there. The search for the initial position is, for example, when the pedestrian moves by means of transportation, the position of the pedestrian can be tracked along the route map, and is limited to the vicinity of the station where the pedestrian gets off the transportation means By doing so, positioning by the GPS 131 or communication with a normal base station can be performed.

  When the search for the initial position is necessary (YES in S11), the control unit 11 searches for the initial position (S12), and sets the search position as a temporary positioning position (S13). When the search for the initial position is not necessary (NO in S11), that is, when one or more estimated positions are already held, the control unit 11 does not perform the processes of Step S12 and Step S13, but will be described later in Step S14. Perform the process.

  The control unit 11 determines whether or not there is communication with the road device (S14), and when there is communication with the road device (YES in S14), the positioning position is corrected to the communication position (S15), and the estimated that has been held. All positions are rejected (S16). The error due to narrow area communication (local communication) with the on-road device is considerably smaller than GPS etc., and the accuracy is high. Therefore, when the communication position is obtained by local communication, this communication position is the most reliable. It can be an estimated position.

  The control unit 11 registers the corrected positioning position as an estimated position (S17), and registers an error range of the estimated position and an evaluation coefficient (S18). Thereby, the new registration (initial registration) of the estimated position is completed, and the error range of the estimated position and the evaluation coefficient are set. When there is no communication with the road device (NO in S14), the control unit 11 performs the process of step S17 and registers the provisional positioning position as the estimated position.

  The control unit 11 acquires the positioning data (S19), confirms whether the positioning data is abnormal (S20), and calculates the reliability of the positioning data according to the confirmation result (S21). The control unit 11 calculates a positioning position based on the positioning data (S22), and calculates a positioning error of the positioning position (S23). As described above, the positioning position can be calculated by a combination of the independent navigation using the distance sensor 132, the direction sensor 133, and the like and the satellite navigation using the GPS 131 or the like. However, when there is no high obstacle such as a building around and the positioning performance of the GPS satellite is very good, it is possible to perform positioning using only the GPS satellite without using self-contained navigation.

  The control unit 11 acquires the walking behavior of the pedestrian (S24), and determines whether or not the map information and the route information from the external device are updated (S25). When the map information and the route information are updated (YES in S25), the control unit 11 acquires the map information and the route information (S26). When the map information and the route information are not updated (NO in S25), the control unit 11 performs the process of step S27 described later without performing the process of step S26. In addition, you may make it acquire the signal information of the traffic signal around a pedestrian from an external device.

  The control unit 11 determines the movement method (S27), and determines whether there is a feature point within the error range of the estimated position (S28). If there is a feature point within the error range (YES in S28), the control unit 11 determines whether or not the position of the pedestrian has been corrected at the feature point (S29), and if not corrected (in S29). NO), walking behavior is determined (S30), and altitude information is acquired (S31).

  The control unit 11 determines whether or not the determined walking behavior and the acquired altitude information are related to the feature point (S32), and if related (YES in S32), that is, the determined walking behavior and the acquired altitude information. However, if it matches the walking behavior and altitude information associated with the feature point, the position of the pedestrian is corrected to the relevant feature point (S33), and all other estimated positions of the pedestrian are rejected (S34).

  The control unit 11 specifies the position of the pedestrian (updates the estimated position) based on the determined movement method (S35). That is, the control unit 11 can continuously and accurately position the pedestrian without any sense of incongruity regardless of the movement method of the pedestrian based on the map information corresponding to the determined movement method. Can be detected. The control unit 11 calculates an error range and an evaluation coefficient of the specified position (updated estimated position) (S36), and displays the position of the pedestrian on the display unit 18 (S37).

  The control unit 11 determines whether or not the positioning azimuth correction condition is satisfied (S38), and when the condition is satisfied (YES in S38), the positioning azimuth is corrected to the road direction or passage direction on the map (S39). ). When the positioning azimuth correction condition is not satisfied (NO in S38), the control unit 11 performs the process of step S40 described later without performing the process of step S39.

  The controller 11 determines whether or not the sensor needs to be calibrated (S40). If calibration is necessary (YES in S40), the sensor 11 is calibrated (S41). When sensor calibration is not necessary (NO in S40), the control unit 11 performs the process of step S42 described later without performing the process of step S41. The control unit 11 determines whether or not there is an instruction to end the process (S42). If there is no instruction (NO in S42), the process from step S11 is continued, and if there is an instruction (YES in S42), the process ends. .

  When there is no feature point within the error range of the estimated position (NO at S28), when the position of the pedestrian has been corrected at the feature point (YES at S29), or when it is not related to the feature point (NO at S32) The control unit 11 continues the processing from step S35.

  Next, the moving method determination process will be described. 40, 41 and 42 are flowcharts showing the procedure of the movement method determination process. The control unit 11 detects the moving speed of the pedestrian (S101) and detects the vibration characteristics (S102). The control unit 11 determines walking behavior (S103) and detects altitude (S104).

  The control unit 11 determines whether or not the pedestrian is walking or moving by bicycle (S105). That is, the control unit 11 determines whether or not the pedestrian movement method is the third movement method. When it is determined that the pedestrian is walking or moving by bicycle (YES in S105), the control unit 11 determines whether or not the movement method determined most recently is walking or bicycle (S106). If the determined movement method is walking or bicycle (YES in S106), the movement method is determined to be walking or bicycle (S107), and the process is terminated.

  If the most recently determined moving method is not walking or cycling (NO in S106), the control unit 11 determines that the moving method has changed to walking or cycling (S108), and ends the process.

  When it is determined that the pedestrian is not walking or moving by bicycle (NO in S105), the control unit 11 determines whether the most recently determined moving method is walking or bicycle (S109). When the most recently determined movement method is walking or bicycle (YES in S109), the control unit 11 has a boarding / alighting location as a feature point in the error range of the most recently estimated position (or the specified position). It is determined whether or not (S110).

  When there is a boarding / exiting location in the error range (YES in S110), that is, when the boarding / exiting location can be specified in the error range, the control unit 11 determines the determined walking behavior, the detected vibration characteristics, the moving speed, and the altitude change. It is determined whether or not the same as that of the transportation facility corresponding to the specified boarding / alighting place (S111).

  When it coincides with that of the transportation system corresponding to the boarding / exiting place (YES in S111), the control unit 11 determines that the transportation means on which the pedestrian is boarding has a transportation system having a route in which the boarding / exiting place is determined in advance (first It is determined that the travel method has changed to the first travel method (S112), and the process is terminated.

  When there is no boarding place in the error range (NO in S110), or when it does not coincide with that of the transportation system corresponding to the boarding place (NO in S111), the control unit 11 estimates the most recently estimated position (or specified). It is determined whether or not there is a road as a feature point in the error range (which may be a position) (S113).

  When there is a road in the error range (YES in S113), the control unit 11 assumes that the transportation system (second transportation system) does not have a route with a predetermined boarding / exiting location, and the travel method is the second travel method. (S114) and the process ends. If there is no road in the error range (NO in S113), the control unit 11 issues an abnormality notification (S115) and ends the process.

  When the most recently determined movement method is not walking or bicycle (NO in S109), the control unit 11 determines whether or not the most recently determined movement method is the first movement method (S116). When the most recently determined movement method is the first movement method (YES in S116), the control unit 11 determines whether or not there is acceleration / deceleration or stop at the intersection, and whether or not there is a stop at the past boarding / alighting place (S117). ), It is determined whether it corresponds to the first movement method (S118).

  When it corresponds to the first moving method (YES in S118), the control unit 11 ends the process. When it does not correspond to the first movement method (NO in S118), the control unit 11 determines that the movement method is the second movement method (S119), and ends the process.

  When the most recently determined moving method is not the first moving method (NO in S116), the control unit 11 determines whether or not there is acceleration / deceleration or stop at the intersection, and whether or not there has been a stop at the past boarding / alighting location (S120). Then, it is determined whether or not it corresponds to the second movement method (S121).

  When it corresponds to the second movement method (YES in S121), the control unit 11 ends the process. When it does not correspond to the second moving method (NO in S121), the control unit 11 issues an abnormality notification (S122) and ends the process.

  As described above, according to the present invention, the position of a pedestrian can be accurately identified regardless of whether it is outdoors or indoors.

  In the above-described embodiment, when the feature point is a staircase or an escalator, there are places where pedestrians change direction such as landings and escalators on each floor, and the pedestrian walks in that place. Therefore, even if there are some errors in the barometric pressure sensor etc., if you know whether you are moving to the upper floor or the lower floor according to the walking behavior of the pedestrian, you can determine which floor Can be determined.

  In addition, when the feature point is an elevator, if it is difficult to determine the floor of each floor with the resolution of the atmospheric pressure sensor, the floor can be limited by using the acceleration sensor together. For example, according to the determination by the atmospheric pressure sensor, when the probability that the pedestrian is on the fourth floor is 40% and the probability that the pedestrian is on the fifth floor is 60%, the vertical distance (height) obtained from the acceleration sensor is If the probability that a pedestrian is on the third floor is 30%, the probability that the pedestrian is on the fourth floor is 40%, and the probability that the pedestrian is on the fifth floor is 30%, suppose that the confidence level of the barometric sensor is twice that of the acceleration sensor. In the combined determination by both, the probability that the pedestrian is on the third floor is (2 × 0 + 1 × 0.3) /3=0.1 (that is, 10%), and the probability that the pedestrian is on the fourth floor is (2 × 0.4 + 1 × 0.4) /3=0.4 (ie 40%) and the probability of being on the fifth floor is (2 × 0.6 + 1 × 0.3) /3=0.5 (ie 50 %), And it can be determined that the user is on the fifth floor with the highest probability.

  Even if it is not possible to limit the presence of a pedestrian on a certain floor, the floor where the pedestrian is finally found can be determined by map matching with the map information for each floor on each floor. For example, if the probability of being on the 4th floor is 40% and the probability of being on the 5th floor is 50%, the position detection is performed for each of the two candidates without specifying whether the floor is the 4th floor or the 5th floor, You may make it finally determine one by matching with the driving | running | working of the passage in a floor, and map data.

  In addition, the relationship between the atmospheric pressure sensor, the acceleration sensor and the floor of each floor is, for example, the relationship between the floor and the altitude is registered in advance in the map information in a constant table, and thereby, the determination of the floor by the above method, or At least the floor can be limited.

  When a pedestrian gets on the Ferris wheel, it can be determined by stopping walking and changing a predetermined altitude. Here, whether or not the altitude change matches the case of the ferris wheel may be obtained by determining the altitude time change based on the relationship between the atmospheric pressure at the highest point of the ferris wheel and the time for which the ferris wheel makes one round. Also, when a pedestrian rides on an elevator such as a skyscraper, the floor is determined based on the pressure at the height of the top floor of the building and the pressure after the altitude changes over time or changes. be able to.

  In the above example, a case is described in which a pedestrian wears a portable device during normal walking or bicycle riding, but the present invention is not limited to this, and the pedestrian directly wears the portable device. First, store a bag or a portable device in a travel case with wheels, cart, baby carriage, wheelchair, etc., temporarily install or temporarily place it, carry it by a pedestrian, push or pull the car, or rotate the wheel by hand And it may be a case where it is going through the field which a pedestrian can pass. In this case, these conditions may be estimated from the data of the step sensor, and the distance may be calculated by detecting the number of steps of the pedestrian or the period of rotation by hand.

  Further, in the above, a mode is shown in which all the data necessary for position detection is collected in the mobile device and the position detection is performed. However, the present invention is not limited to this, and necessary data is transmitted from the mobile device to a server installed on the road or in the center. The position detection process may be executed by the server, and the result may be transmitted to the mobile device. Or you may share execution of a process. This can reduce the burden on the mobile device.

  The position specifying device described above can be applied to, for example, a mobile phone, a PDA (Personal Digital Assistant), a PHS, a notebook personal computer, a music player, an information terminal device such as a portable game device, or a portable terminal device.

  In the above-described embodiment, the position specifying device may include an inclination angle sensor. As a result, when the device tilts due to vibration or posture change of the device accompanying walking, taking out, operation, etc. of the pedestrian, the function may stop or the performance may be deteriorated depending on the type of the orientation sensor or the distance sensor. . Accordingly, the tilt angle can be detected by the tilt angle sensor, and the azimuth sensor or the distance sensor can be corrected.

  The mathematical formulas for estimating the position of the pedestrian shown in the above-described embodiment are merely examples, and the mathematical formulas are not limited thereto, and mathematical formulas appropriately modified can be used.

  The disclosed embodiments are to be considered in all respects as illustrative and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

It is a block diagram which shows an example of a structure of the position specific apparatus which concerns on this invention. It is explanatory drawing which shows the example of the error range of a positioning position. It is a schematic diagram which shows an example of map information. It is explanatory drawing which shows the example of a setting of the road or channel | path for pedestrians on a map. It is a schematic diagram which shows an example of the underground map information near a station. It is explanatory drawing which shows an example of a route map of a railway. It is explanatory drawing which shows the example of the required time between the stations of a railway. It is explanatory drawing which shows an example which detects a walking behavior. It is explanatory drawing which shows the relationship between a feature point and walking behavior. It is a schematic diagram which shows the example of the walk locus | trajectory of the pedestrian near escalator. It is explanatory drawing which shows an example which pinpoints the position of the pedestrian in the escalator vicinity. It is explanatory drawing which shows an example of the method of selecting the feature point in an error range. It is explanatory drawing which shows an example of a vibration characteristic. It is explanatory drawing which shows an example of a vibration characteristic. It is explanatory drawing which shows an example of a vibration characteristic. It is explanatory drawing which shows the example of a moving means. It is explanatory drawing which shows the example which determines the transport system which has a route in which the boarding / alighting place was defined. It is explanatory drawing which shows an example of the new registration of an estimated position. It is explanatory drawing which shows an example of calculation of the evaluation coefficient of the newly registered estimated position. It is explanatory drawing which shows the example of calculation of the locus | trajectory of the estimated position on the ground until it uses a transportation system. It is explanatory drawing which shows the example of calculation of the locus | trajectory of the estimated position in the basement until it uses a transportation system. It is explanatory drawing which shows the other example of the locus | trajectory calculation of the estimated position on the ground until it uses a transportation system. It is explanatory drawing which shows the other example of the locus | trajectory calculation of the estimated position in the basement until it uses a transportation system. It is explanatory drawing which shows an example of the update of an estimated position. It is explanatory drawing which shows the other example of the update of an estimated position. It is explanatory drawing which shows the other example of the update of an estimated position. It is explanatory drawing which shows an example of calculation of the evaluation coefficient of the estimated position in a feature point. It is explanatory drawing which shows the other example of calculation of the evaluation coefficient of the estimated position in a feature point. It is explanatory drawing which shows the other example of the evaluation coefficient of an estimated position. It is explanatory drawing which shows an example of the display of a pedestrian's position. It is explanatory drawing which shows the other example of a display of the position of a pedestrian. It is explanatory drawing which shows the other example of a display of the position of a pedestrian. It is explanatory drawing which shows the other example of a display of the position of a pedestrian. It is explanatory drawing which shows an example of the display of the position of the pedestrian who is moving by the transportation means. It is explanatory drawing which shows the other example of a display of the position of the pedestrian who the pedestrian is moving by a transportation means. It is a flowchart which shows the procedure of a position detection process. It is a flowchart which shows the procedure of a position detection process. It is a flowchart which shows the procedure of a position detection process. It is a flowchart which shows the procedure of a position detection process. It is a flowchart which shows the procedure of the determination process of a moving method. It is a flowchart which shows the procedure of the determination process of a moving method. It is a flowchart which shows the procedure of the determination process of a moving method.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Position identification apparatus 11 Control part 12 Communication part 13 Positioning part 131 GPS
132 Distance Sensor 133 Direction Sensor 134 Altitude Sensor 135 Direction Correction Unit 136 Sensor Calibration Unit 14 Map Database 15 Storage Unit 16 Operation Unit 17 Position Detection Processing Unit 171 Position Estimation Unit 172 Error Calculation Unit 173 Walking Behavior Determination Unit 174 Getting On / Off Determination Unit 175 Position Identification unit 176 Reliability calculation unit 177 Evaluation unit 178 Vibration detection unit 18 Display unit 19 Audio output unit 20 Movement method determination unit

Claims (12)

In a positioning device that is equipped with positioning means for measuring its own position and is portable by a pedestrian,
Walking behavior determination means for determining the walking behavior of a pedestrian;
Storage means for storing map information including position information of characteristic points associated with the walking behavior;
Estimating means for estimating its own position on a map based on positioning data obtained by positioning by the positioning means;
An error range calculation means for calculating an error range indicating an estimation error range of the estimated position estimated by the estimation means;
When there is a feature point related to the walking behavior determined by the walking behavior determination unit within the error range calculated by the error range calculation unit, a position specifying unit that specifies the feature point as its own position is provided. Feature location device. Equipped with altitude information acquisition means to acquire information about altitude,
The position specifying means includes
The position specifying device according to claim 1, wherein the position specifying device is configured to specify its own position based on information about the altitude acquired by the altitude information acquiring means. The position specifying means includes
When the altitude change is acquired by the altitude information acquisition means, when the walking behavior determination means determines that the walking behavior is stop walking, the feature point within the error range calculated by the error range calculation means is The position specifying device according to claim 2, wherein the position specifying device is specified as the position of the position. When the altitude change is acquired by the altitude information acquisition means, the altitude change determination means for determining whether the altitude change is stable,
The position specifying means includes
When it is determined that the altitude change is stable by the altitude change determining means, the feature point in the error range calculated by the error range calculating means is associated with the altitude acquired by the altitude information acquiring means, The position specifying device according to claim 2, wherein the position specifying device is configured to specify. The position specifying means includes
When the walking behavior determining means determines that the walking behavior is the start of walking, the feature point within the error range calculated by the error range calculating means is associated with the altitude acquired by the altitude information acquiring means, The position specifying apparatus according to claim 4, wherein the position specifying apparatus is specified. The position specifying means includes
When it is determined that the walking behavior is a change in walking speed by the walking behavior determination unit, the characteristic point that is within the error range calculated by the error range calculation unit when it is determined that the change in the walking speed is stable The position specifying device according to claim 4, wherein the position is associated with the height acquired by the height information acquisition unit to specify its own position. The position specifying means includes
When the walking behavior determining means determines that the walking behavior is a fluctuation in walking strength, the error range calculated by the error range calculating means is determined when the walking strength fluctuation is determined to be stable. The position specifying device according to claim 4, wherein the position is associated with the altitude acquired by the altitude information acquiring unit and the position of the position is specified. A reliability calculation means for calculating the reliability of positioning data is provided.
The position specifying means includes
When the reliability calculated by the reliability calculation unit is lower than a predetermined threshold and the feature point within the error range calculated by the error range calculation unit is an indoor feature point, the feature point is set as its own position. The position specifying device according to any one of claims 1 to 7, wherein the position specifying device is configured to specify.   9. The apparatus according to claim 1, further comprising a selection unit that selects one or a plurality of feature points among the feature points as its own position when there are a plurality of feature points within the error range. The position specifying device according to one. The storage means
The position information of at least one characteristic point among stairs, escalators, elevators, ticket vending machines, ticket gates, ferris wheels, vending machines and boarding places is stored. The position specifying device according to any one of the above. In a computer program for causing a computer to identify its position based on positioning data,
Computer
Walking behavior determination means for determining the walking behavior of a pedestrian;
An estimation means for estimating its position on the map based on the positioning data;
An error range calculation means for calculating an error range indicating an estimated error range of the estimated position;
When there is a feature point associated with walking behavior within the calculated error range, a computer program that functions as a position specifying unit that specifies the feature point as its own position. In a position identification method for positioning and identifying its own position,
Store map information including location information of feature points associated with walking behavior,
Determine the walking behavior of the pedestrian,
Estimate your position on the map based on the positioning data obtained by positioning,
Calculate the error range indicating the range of the estimated error of the estimated position,
A position specifying method characterized by specifying a feature point as its own position when there is a feature point related to the determined walking behavior within the calculated error range.

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