WO2018042591A1 - Road shape estimation device, road shape estimation method, and program - Google Patents

Abstract

This road shape estimation device acquires moving body information including location information and lateral acceleration information that relate to a moving body. The road shape estimation device then estimates, on the basis of the location information and the lateral acceleration information, road shape information relating to a road width at a turning point through which the moving body passes.

Description

Road shape estimation device, road shape estimation method, and program

The present invention relates to a technique for estimating a road shape based on an output of a sensor.

Patent Document 1 describes a method for estimating the width of a road on which a vehicle travels based on information from image sensors such as stereo cameras and monocular cameras, and in-vehicle sensors such as millimeter wave radars, laser radars, and ultrasonic sensors.

JP 2009-75645 A

When considering information collection using probe information, the method of Patent Document 1 cannot estimate the road width unless the vehicle is equipped with a camera, radar, or the like, and the vehicles that can collect probe information are limited. There is a problem of end.

The present invention has been made to solve the above-described problems, and an object thereof is to estimate a road shape using an output of a sensor mounted on a general vehicle.

The invention according to claim 1 is a road shape estimation apparatus, an information acquisition unit that acquires position information of a moving body and moving body information including lateral acceleration information applied to the moving body, and the position information And an estimation unit that estimates road shape information related to a road width at a turning point through which the mobile body passes based on the lateral acceleration information.

The invention according to claim 9 is a road shape estimation method executed by an apparatus including a computer, and acquires moving body information including position information of a moving body and lateral acceleration information applied to the moving body. An information acquisition step, and an estimation step of estimating road shape information related to a road width at a turning point where the moving body passes based on the position information and the lateral acceleration information.

The invention described in claim 10 is a program executed by an apparatus including a computer, and an information acquisition unit that acquires moving body information including position information of a moving body and lateral acceleration information applied to the moving body Based on the position information and the lateral acceleration information, the computer is caused to function as an estimation unit that estimates road shape information related to a road width at a turning point where the moving body passes.

1 shows a configuration of an information collection system according to an embodiment. 1 shows a schematic configuration of a server. 1 shows a schematic configuration of a navigation device. It is a figure explaining the direction of the acceleration detected by a sensor. The example of the road shape estimated as the acceleration in the Y-axis direction at the intersection is shown. The other example of the road shape estimated as the Y-axis direction acceleration in an intersection is shown. The other example of the Y-axis direction acceleration in an intersection is shown. The other example of the Y-axis direction acceleration in an intersection is shown. The other example of the Y-axis direction acceleration in an intersection is shown. The other example of the Y-axis direction acceleration in an intersection is shown. The other example of the Y-axis direction acceleration in an intersection is shown. It is a flowchart of the road shape estimation process which concerns on 1st Example. It is a flowchart of the road shape estimation process which concerns on 2nd Example.

In one preferable embodiment of the present invention, the road shape estimation apparatus includes an information acquisition unit that acquires position information of a moving object and moving object information including lateral acceleration information applied to the moving object, and the position information. And an estimation unit that estimates road shape information related to a road width at a turning point through which the mobile body passes based on the lateral acceleration information.

The above road shape estimation apparatus acquires moving body information including position information of the moving body and lateral acceleration information related to the moving body. Based on the position information and the lateral acceleration information, the road shape information related to the road width at the turning point where the moving body passes is estimated. Accordingly, the road shape can be estimated based on the position information and the lateral acceleration information by a sensor mounted on a general vehicle.

In one aspect of the road shape estimation apparatus, the information acquisition unit acquires the mobile body information from a plurality of mobile bodies, and the estimation unit estimates the road shape information by statistical processing. In this aspect, the road shape estimation accuracy can be increased by using the moving body information obtained from a plurality of moving bodies.

In a preferred example, the road shape information includes lane information relating to the number of lanes of the road at the turning point. In another preferred example, the road shape information includes road form information related to a road form at the turning point. The road form includes, for example, a T-shaped road, a cross road, a one-way exit, and the like.

Another aspect of the road shape estimation apparatus includes a transmission unit that transmits the road shape information to the outside. Thereby, road shape information can be transmitted and collected from a plurality of moving bodies to a server or the like.

In another aspect of the road shape estimation apparatus, the moving body information includes acceleration in a vertical direction or a traveling direction of the moving body, and the estimation unit is based on the acceleration in the vertical direction or the traveling direction, Estimate the slope of the road on which the moving body is traveling. In this aspect, it is possible to estimate the gradient of the road on which the mobile body travels before reaching the turning point.

In another aspect of the road shape estimation apparatus, the moving body information includes acceleration in a vertical direction of the moving body, and the estimation unit is configured to determine a road on which the moving body is traveling based on the acceleration. Estimate undulations. In this aspect, the road undulation can be estimated based on the vertical acceleration of the moving body.

In another preferred embodiment of the present invention, the control device includes a receiving unit that receives the road shape information transmitted from the road shape estimation device, and a control that executes control related to driving support based on the road shape information. A section. This control device can receive road shape information and use it for control related to driving assistance such as automatic driving.

In another preferred embodiment of the present invention, a road shape estimation method executed by an apparatus including a computer obtains moving body information including position information on a moving body and lateral acceleration information on the moving body. An information acquisition step, and an estimation step of estimating road shape information related to a road width at a turning point where the moving body passes based on the position information and the lateral acceleration information. By this method, a road shape can be estimated based on position information and lateral acceleration information by a sensor mounted on a general vehicle.

In another preferred embodiment of the present invention, a program executed by a device including a computer is an information acquisition unit that acquires moving body information including position information of a moving body and lateral acceleration information on the moving body. Based on the position information and the lateral acceleration information, the computer is caused to function as an estimation unit that estimates road shape information related to a road width at a turning point where the moving body passes. By executing this program on a computer, the above-described road shape estimation apparatus can be realized. This program can be stored and handled in a storage medium.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[Device configuration]
(Information collection system)
FIG. 1 illustrates a schematic configuration of an information collection system according to an embodiment. The information collection system includes a server 7 and a plurality of navigation devices 1. The navigation device 1 can transmit and receive data to and from the server 7 by wireless communication.

(server)
FIG. 2 shows a schematic configuration of the server 7. The server 7 is a computer device, and includes a communication unit 71, a control unit (CPU) 72, a ROM 73, a RAM 74, a map database (hereinafter referred to as “DB”) 75, a travel history DB 76, Road shape DB77.

The communication unit 71 transmits and receives data to and from the navigation device 1 by wireless communication. The control unit 72 controls the entire server 7. The ROM 73 stores a program executed by the server 7 and the like. The RAM 74 functions as a work memory when the server 7 performs various processes.

The map DB 75 stores road map data. The road map data indicates a road network by intersection nodes and road links.

The travel history DB 76 stores travel history data of the vehicle on which the navigation device 1 is mounted. Specifically, the navigation device 1 measures various information such as the current position of the vehicle, the traveling direction (up / down), time, and speed while the vehicle is traveling at regular time intervals or constant travel distances. . When a predetermined transmission timing arrives while the vehicle is traveling, the traveling history data of the vehicle is transmitted to the server 7. The server 7 receives the travel history data from the plurality of navigation devices 1 and stores it in the travel history DB 76.

The road shape DB 77 stores the road shape information transmitted from the navigation device 1. The road shape information is generated for each point where the vehicle makes a right / left turn or changes its traveling direction (hereinafter referred to as a “direction changing point”). That is, the road shape information is stored in association with points such as intersections on the road network. Further, in addition to the intersection, an entry point from a road to a parking lot or the like may be used as a direction change point, and road shape information about the point may be generated and stored. The server 7 receives and accumulates road shape information about each direction change point from the navigation device 1 mounted on many vehicles. Based on a large number of collected road shape information, the shape of each turning point is determined, and is stored in the map DB 75 as attribute information of map data or the like as necessary.

In the above configuration, the communication unit 71 is an example of an information acquisition unit and a transmission unit of the present invention, and the control unit 72 is an example of an estimation unit of the present invention.

(Navigation device)
FIG. 3 shows the configuration of the navigation device 1. As shown in FIG. 3, the navigation device 1 includes a self-supporting positioning device 10, a GPS receiver 18, a system controller 20, a disk drive 31, a data storage unit 36, a communication interface 37, a communication device 38, a display unit 40, a voice output. A unit 50 and an input device 60 are provided.

The system controller 20, the disk drive 31, the data storage unit 36, the communication interface 37, the display unit 40, the audio output unit 50, and the input device 60 are connected to each other via the bus line 30.

The self-supporting positioning device 10 includes an acceleration sensor 11, an angular velocity sensor 12, and a distance sensor 13. The acceleration sensor 11 is made of, for example, a piezoelectric element, detects vehicle acceleration, and outputs acceleration data. The angular velocity sensor 12 is composed of, for example, a vibrating gyroscope, detects the angular velocity of the vehicle when the direction of the vehicle is changed, and outputs angular velocity data and relative azimuth data. The distance sensor 13 measures a vehicle speed pulse composed of a pulse signal generated with the rotation of the vehicle wheel.

The GPS receiver 18 receives radio waves 19 carrying downlink data including positioning data from a plurality of GPS satellites. The positioning data is used to detect the absolute position of the vehicle (hereinafter also referred to as “current position”) from latitude and longitude information.

The system controller 20 includes an interface 21, a CPU (Central Processing Unit) 22, a ROM (Read Only Memory) 23, and a RAM (Random Access Memory) 24, and controls the entire navigation device 1.

The interface 21 performs an interface operation with the acceleration sensor 11, the angular velocity sensor 12, the distance sensor 13, and the GPS receiver 18. From these, vehicle speed pulses, acceleration data, relative azimuth data, angular velocity data, GPS positioning data, absolute azimuth data, and the like are input to the system controller 20.

CPU 22 controls the entire system controller 20. The ROM 23 includes a nonvolatile memory (not shown) in which a control program for controlling the system controller 20 is stored. The RAM 24 stores various data such as route data preset by the user via the input device 60 so as to be readable, and provides a working area to the CPU 22.

The disk drive 31 reads music and video data from a CD, DVD, etc. (not shown) and outputs them to the display unit 40 and the audio output unit 50.

The data storage unit 36 includes, for example, an HDD and stores various data used for navigation processing such as map data. The communication device 38 performs wireless communication with the server 7 via the network. The communication device 38 may be a dedicated wireless communication unit built in the navigation device 1, and is a unit that connects to a mobile phone by wire or wirelessly and connects to a network using the communication function of the mobile phone. There may be.

The display unit 40 displays various display data on a display device such as a display under the control of the system controller 20. The display unit 40 displays the map data read from the data storage unit 36 by the system controller 20 on the display screen. The display unit 40 includes a graphic controller 41 that controls the entire display unit 40 based on control data sent from the CPU 22 via the bus line 30 and a memory such as a VRAM (Video RAM), and can display image information that can be displayed immediately. A buffer memory 42 that temporarily stores, a display control unit 43 that controls display of a display 44 such as a liquid crystal or a CRT (Cathode Ray Tube) based on image data output from the graphic controller 41, and a display 44 are provided. . The display 44 functions as an image display unit, and includes, for example, a liquid crystal display device having a diagonal size of about 5 to 10 inches and is mounted near the front panel in the vehicle.

The audio output unit 50 is a D / A converter 51 that performs D / A (Digital to Analog) conversion of audio digital data sent from the disk drive 31 or the RAM 24 via the bus line 30 under the control of the system controller 20. , An amplifier (AMP) 52 that amplifies the audio analog signal output from the D / A converter 51, and a speaker 53 that converts the amplified audio analog signal into sound and outputs the sound into the vehicle.

The input device 60 includes keys, switches, buttons, a remote controller, a voice input device, and the like for inputting various commands and data. The input device 60 is disposed around the front panel and the display 44 of the main body of the in-vehicle electronic system mounted in the vehicle. When the display 44 is a touch panel system, the touch panel provided on the display screen of the display 44 also functions as the input device 60.

In the above configuration, the interface 21 is an example of the information acquisition unit of the present invention, and the CPU 22 is an example of the estimation unit of the present invention.

[First embodiment]
(Road shape estimation method)
Next, the road shape estimation method according to the first embodiment will be described. In the first embodiment, the navigation device 1 estimates the road shape based on the acceleration detected by the acceleration sensor 11 when the vehicle passes the turning point. FIG. 4A is a plan view of the vehicle, and FIG. 4B is a side view of the vehicle. 4A and 4B, the traveling direction of the vehicle 5 is the X-axis direction, the width direction of the vehicle 5 is the Y-axis direction, and the vertical direction (vertical direction) of the vehicle 5 is the Z direction. And The system controller 20 of the navigation device 1 obtains accelerations in the X-axis direction, the Y-axis direction, and the Z-axis direction from the acceleration of the vehicle detected by the acceleration sensor 11, and based on these, the road shape at the turning point through which the vehicle passes. Is estimated. A specific example will be described below.

(1) When the graph shape of the right / left turn is almost the same shape FIG. 5A shows a graph of the acceleration G in the Y-axis direction obtained when the vehicle 5 passes a certain intersection. The Y-axis direction acceleration G is information indicating lateral acceleration generated in the vehicle 5 when making a right or left turn. In FIG. 5A, the direction of acceleration when the vehicle 5 makes a left turn is positive (+), and the direction of acceleration when the vehicle 5 makes a right turn is negative (−). FIG. 5A shows a graph obtained when the vehicle 5 makes a right turn and a left turn at the same intersection.

When the vehicle 5 turns left, as shown in the graph 101, the acceleration in the Y-axis direction increases in the positive direction, and then decreases and returns to the original. Conversely, when the vehicle 5 makes a right turn, the acceleration in the Y-axis direction increases in the negative direction as shown in the graph 102, and then decreases to return to the original. Basically, the more the vehicle 5 bends at an acute angle or the more suddenly the turn in time, the greater the amplitude of the acceleration in the Y-axis direction and the greater the peak value of the graph. On the other hand, the peak value of the graph decreases as the vehicle 5 bends at an obtuse angle or as the vehicle 5 turns slowly.

As shown in FIG. 5A, when the graph 101 for the left turn and the graph 102 for the right turn have substantially the same shape, the vehicle 5 draws substantially the same trajectory in both the left turn and the right turn. It is presumed that he drove. Therefore, it is estimated that this intersection is a road having a relatively narrow road width due to a right or left turn. Specifically, as shown in FIG. 5B, this intersection is a T-shaped road with a relatively narrow road width, and the trajectory 103 in the case of a left turn and the trajectory 104 in the case of a right turn have substantially the same shape. As shown in FIG. 5A, it is presumed that the graph 101 in the case of a left turn and the graph 102 in the case of a right turn have substantially the same shape. Thus, the road width of the intersection can be estimated based on the graph of the acceleration in the Y-axis direction at the intersection.

The graph of FIG. 5A shows a case where only the Y-axis direction acceleration is obtained in the case of a left turn and a right turn, but in addition to this, when the Y-axis direction acceleration in the case of straight traveling is also obtained, Since the vehicle 5 is also traveling in the straight direction, it is estimated that this intersection is not a T-shaped road but a crossroad with a relatively narrow width. When the navigation device 1 detects the travel history of the vehicle 5, it may be determined whether the intersection is a T-junction or a crossroad based on the travel history. That is, if there is no straight traveling history, the intersection is determined as a T-shaped road, and if there is a straight traveling history, the intersection is determined as a crossroad. In addition, although there is no straight traveling history, when there is a road based on map data, it is determined that the intersection is a one-way exit.

Thus, the navigation device 1 generates information indicating the width of the road that enters by turning right or left as the road shape information. The road shape information may include road form information indicating a road form such as whether the intersection is a T-shaped road, a crossroad, or a one-way exit.

In addition, since the shape of the acceleration waveform in the Y-axis direction changes depending on the speed, more accurate determination can be made by considering the speed by means such as comparison for each speed or normalization.

(2) When the shape of the graph of right and left turns differs FIG. 6A shows a graph of the acceleration in the Y-axis direction obtained when the vehicle 5 passes through a certain intersection. The graph shown in FIG. 6A is a graph obtained when the vehicle 5 makes a right turn and a left turn at the same intersection.

In the example of FIG. 6A, the graph 105 in the case of a left turn has a short time width, and the graph 106 in the case of a right turn has a long time width. In such a case, it is presumed that the traveling locus in the case of a right turn is longer than that in the case of a left turn, and the vehicle 5 is curved with a large locus. Therefore, at this intersection, it is estimated that the road that enters by turning right or left is a relatively wide road. Specifically, as shown in FIG. 6B, it is estimated that the road 109 to be entered by the right / left turn is wide, and the trajectory 109 for the right turn is longer than the trajectory 108 for the left turn. Furthermore, when the broken line graph 112 shown in FIG. 6A is also obtained at the same intersection, it can be estimated that there are two lanes in the approach direction of the road that enters by turning right. That is, it is presumed that the graph 106 is obtained when entering the near lane by turning right, and the graph 112 is obtained when entering the far lane.

The graph of FIG. 6A shows a case where only the Y-axis direction acceleration is obtained in the case of a left turn and a right turn, but in addition to this, when a Y-axis direction acceleration in the case of straight traveling is also obtained, Since the vehicle 5 is also traveling in the straight direction, it is estimated that this intersection is not a T-shaped road but a crossroad with a relatively wide road as shown in FIG. In addition, when the navigation apparatus 1 is detecting the travel locus of the vehicle 5, it may determine whether it is a T-shaped road or a crossroad based on a travel locus. That is, if there is no straight traveling track, the intersection is determined as a T-shaped road, and if there is a straight traveling track, the intersection is determined as a crossroad. In addition, although there is no straight driving | running | working log | history, when there exists a road based on map data, the intersection is determined to be a one-way exit.

Thus, the navigation device 1 generates information indicating the road width and the number of lanes of the road that enters by turning right or left as the road shape information. The road shape information may include road form information indicating a road form such as whether the intersection is a T-shaped road, a crossroad, or a one-way exit.

In addition, since the shape of the acceleration waveform in the Y-axis direction changes depending on the speed, more accurate determination can be made by considering the speed by means such as comparison for each speed or normalization.

(3) Method of Comparing Graph Shapes at Different Points FIG. 7 shows a graph of Y-axis direction acceleration obtained from the same vehicle 5 at different intersections. In this case, it is considered that the difference in the size of the intersection appears in the peak width 115 and absolute value of the acceleration in the Y-axis direction. The peak width refers to a time width during which the Y-axis direction acceleration value substantially maintains the peak value. Basically, the peak width 115 is considered to be proportional to the road width. Therefore, first, a reference intersection having a known road width is determined in advance based on map data and the like, a graph of acceleration in the Y-axis direction at the reference intersection is measured, and the peak width is prepared in advance. Then, by comparing the peak width obtained at the estimation target intersection with the peak width of the reference intersection, the road width of the estimation target intersection can be estimated.

Similarly, the peak value (absolute value) of acceleration in the Y-axis direction is considered to be proportional to the road width. Therefore, a graph of acceleration in the Y-axis direction at the reference intersection is measured, and the peak value is prepared in advance. Then, by comparing the peak value obtained at the estimation target intersection with the peak value of the reference intersection, the road width of the estimation target intersection can be estimated.

Also, the shape of the intersection can be estimated based on the difference in the peak value of the acceleration in the Y-axis direction (arrow 116 in FIG. 7) and the waveform. For example, the intersection in the time axis direction of the acceleration in the Y-axis direction is almost the same, but an intersection where the peak value of the acceleration in the Y-axis direction is large or a symmetrical waveform without distortion is a relatively good line-of-sight intersection. Alternatively, it is possible to infer that the corner to be turned left is chamfered and the intersection can be turned left at a faster speed than a normal right-angled corner.

Thus, the navigation device 1 generates information indicating the road width and the shape of the intersection of the road that enters by turning left or right as the road shape information.

In addition, since the shape of the acceleration waveform in the Y-axis direction changes depending on the speed, more accurate determination can be made by considering the speed by means such as comparison for each speed or normalization.

(4) When entering a narrow road FIG. 8 shows a graph of acceleration in the Y-axis direction obtained when the vehicle 5 turns left at a certain intersection. In this example, an acceleration in the right direction is temporarily generated prior to a change in acceleration during a normal left turn indicated by the graph 117. In such a case, when the vehicle turns to the left, it can be estimated that the vehicle 5 has once made a left turn after shaking the head of the vehicle 5 in the right direction. As a result, it is possible to estimate that the road to be approached by the left turn is a narrow road.

Thus, the navigation device 1 generates information indicating whether or not the road width of the road that enters mainly by making a left turn is narrow as the road shape information.

(5) Estimation of road gradient (level difference) In addition to the acceleration in the Y-axis direction, the gradient of the road can be estimated by looking at the acceleration in the X-axis direction (traveling direction). FIG. 9 shows a graph of acceleration in the X-axis direction and acceleration in the Y-axis direction when turning right at a flat intersection. In the X-axis direction acceleration, the positive direction indicates acceleration, and the negative direction indicates deceleration (braking). When making a right turn at a flat intersection, first, a constant braking is performed as shown in a graph 120, and then a right turn operation is performed as shown in a graph 121. In addition, prior braking shown in the graph 120x may be performed prior to braking immediately before the right turn shown in the graph 120.

FIG. 10 shows a graph of the acceleration in the X-axis direction and the acceleration in the Y-axis direction when turning right at the intersection ahead of the downhill. When making a right turn at an intersection ahead of a downhill, the degree of braking increases due to the offset of the road gradient as shown in the graph 122, and then a right turn is performed as shown in the graph 123. That is, the braking in the case of a downhill tends to take longer than the case of a flat road, and the absolute value of the acceleration in the X-axis direction tends to increase. Further, as shown in the graph 122x, a larger braking may be performed immediately before the right turn. Furthermore, braking may be continuously performed during a left turn. In this way, when braking is performed larger than in the case of a flat road and a right turn is made after that, the intersection can be estimated to be an intersection ahead of a downhill. Here, although a graph is shown when turning right at an intersection ahead of a downhill, similar estimation can be performed using a graph when turning left at an intersection ahead of a downhill.

FIG. 11 shows a graph of the acceleration in the X-axis direction and the acceleration in the Y-axis direction when turning right at the intersection ahead of the uphill. When making a right turn at an intersection after an uphill, acceleration is performed before the right turn as shown in the graph 124, and then a right turn is performed as shown in the graph 125. At this time, as in FIG. 10, the waveform is added by the offset of the road gradient. In addition, as shown in the graph 124x, acceleration may be further performed immediately before the right turn. In some cases, a slight deceleration is performed just before the right turn. Thus, when acceleration is performed before a right turn and a right turn is performed after that, it can be estimated that the intersection is an intersection ahead of an uphill. Here, a graph when turning right at an intersection ahead of an uphill is shown, but the same estimation can be performed using a graph when turning left at an intersection ahead of an uphill.

In FIGS. 9 to 11, the intersection of the downhill or the uphill is estimated based on the X-axis direction acceleration and the Y-axis direction acceleration, but the Z-axis direction acceleration is used instead of the X-axis direction acceleration. Thus, acceleration or braking may be detected.

Also, the speed may be used together for the determination of the downhill and the uphill. For example, if positive acceleration in the X-axis direction is detected over a relatively long period of time and it is estimated that the vehicle is accelerating, it is estimated that the vehicle is traveling uphill. can do. On the other hand, it can be estimated that the vehicle is traveling downhill when negative acceleration in the X-axis direction larger than normal is detected even though the degree of deceleration of the speed is not so large.

Thus, the navigation device 1 generates, as the road shape information, information indicating the road gradient before the intersection, that is, whether the road is flat, uphill, or downhill.

(6) Estimating road undulations If the acceleration in the Z-axis direction is detected and the fluctuation is greater than or equal to a predetermined value, the road surface is uneven or uneven, the road surface is rough, the road is unpaved, etc. Estimation is also possible. In this case, the navigation device 1 generates, as the road shape information, information indicating whether the road has large unevenness, or whether it is a paved road or an unpaved road.

Also, when acceleration indicating irregularities is detected at regular intervals, it can be estimated that there are crossings of railroad crossings, bridge joints, and step pavements.

(Road shape estimation process)
FIG. 12 is a flowchart of the road shape estimation process according to the first embodiment. In this process, the navigation device 1 generates road shape information and transmits it to the server 7. The process of the navigation device 1 is realized by the CPU 22 executing a program prepared in advance, and the process of the server 7 is realized by the control unit 72 executing a program prepared in advance.

First, the navigation device 1 acquires sensor output information from the acceleration sensor 11 or the like (step S11), and estimates the road shape by the above-described method (step S12). And the navigation apparatus 1 transmits the produced | generated road shape information to the server 7 (step S13). Actually, the navigation device 1 transmits road shape information to the server 7 together with position information indicating a turning point such as an approach to the outside of a road such as a store parking lot in addition to an intersection or a branch point.

Next, the navigation device 1 determines whether or not the vehicle 5 has stopped (step S14). The “stop” means a state in which the vehicle has parked with the engine stopped, and does not include a temporary stop. When the vehicle stops (step S14: Yes), the process ends. On the other hand, when the vehicle is not stopped (step S14: No), the process returns to step S11. Thus, the navigation device 1 continues to generate road shape information for each turning point such as an intersection and transmit it to the server 7 while the vehicle 5 is traveling.

When the server 7 receives the road shape information from the navigation device 1 (step S15), the server 7 stores it in the road shape DB 77 (step S16). Then, the process ends. In this way, the server 7 collects road shape information from the navigation device 1 mounted on a large number of vehicles and stores it in the road shape DB 77.

(How to use road shape information)
The server 7 can generate attribute information of map data such as an intersection based on the road shape information accumulated in the road shape DB 77. For example, attribute information such as a T-junction, a crossroad, and a one-way exit can be added to the intersection information.

Also, the server 7 can transmit road shape information to the autonomous driving vehicle and use it for driving support in the autonomous driving vehicle. Automated drivers analyze and process measurement information from various sensors, etc., and use road shape information to give priority to processing related to high-risk matters or process The amount can be increased, and risk can be read ahead and distributed. Thereby, the processing amount in automatic operation control can be reduced, or processing can be made efficient.

[Second Embodiment]
In the first embodiment, the navigation device 1 estimates the road shape based on the sensor output information, and transmits the result to the server 7. Instead, in the second embodiment, the navigation device 1 does not estimate the road shape and transmits the acquired sensor output information to the server 7. Then, the server 7 estimates the road shape as described above based on the sensor output information received from the navigation device 1 to generate the road shape information.

(Road shape estimation method)
Also in the second embodiment, the road shape can be estimated basically by the same method as in the first embodiment. Furthermore, in the second embodiment, the road shape can be estimated in consideration of the vehicle speed as follows.

The Y-axis direction acceleration (lateral G) is calculated by using the speed “V” of the vehicle 5 and the radius “r” when the vehicle bends.
Horizontal G = V ² / r (1)
It is represented by As shown in equation (1), the graph shape of the acceleration in the Y-axis direction varies depending on the speed of the vehicle 5. Therefore, when estimating the road shape based on the graph shape of the acceleration in the Y-axis direction, consider the speed condition. Thus, the estimation accuracy can be improved. Specifically, the formula (1) can be used in the following two ways.

As a first method, when the speed V can be obtained from a plurality of vehicles 5 and the radius r of the road is known from the map data or the like, the server 7 determines whether or not the speed V of each vehicle 5 is based on the speed V. The graph shape of the acceleration in the Y-axis direction obtained from each vehicle 5 is corrected, and the road shape is estimated based on the corrected graph shape. As a result, it is possible to estimate the road shape by removing the influence of the speed difference of each vehicle based on the Y-axis direction acceleration graph obtained when the plurality of vehicles 5 turn right and left at the intersection at different speeds. Become.

As a second method, when the road radius r is unknown and the speed of each vehicle 5 is substantially constant, the road radius r can be estimated using equation (1). Specifically, in addition to the graph of acceleration in the Y-axis direction from the plurality of vehicles 5, the traveling speed V at that time is acquired. Then, only a graph of the acceleration in the Y-axis direction of the vehicle in which the traveling speed V is within a predetermined range (a range in which the speeds can be regarded as substantially the same) is extracted, and based on the lateral G obtained from the graph and the vehicle speed, The radius r of the road is obtained from (1).

(Road shape estimation process)
FIG. 13 is a flowchart of the road shape estimation process according to the second embodiment. First, the navigation device 1 acquires sensor output information from the acceleration sensor 11 or the like (step S21), and whether or not the transmission timing has arrived. Is determined (step S22). The transmission timing is normally when the vehicle 5 passes a turning point such as an intersection. When the transmission timing arrives (step S22: Yes), the navigation device 1 transmits the sensor output information to the server 7. The navigation device 1 transmits the sensor output information to the server 7 together with position information indicating a turning point such as an intersection.

Next, the navigation device 1 determines whether or not the vehicle 5 has stopped (step S24). The “stop” means a state in which the vehicle has parked with the engine stopped, and does not include a temporary stop. When the vehicle stops (step S24: Yes), the process ends. On the other hand, when the vehicle is not stopped (step S24: No), the process returns to step S21. Thus, the navigation device 1 continues to transmit the sensor output information to the server 7 at each turning point such as an intersection while the vehicle 5 is traveling.

When the server 7 receives the sensor output information from the navigation device 1 (step S25), the server 7 estimates the road shape based on the sensor output information (step S26). At this time, the server 7 estimates the road shape by statistical processing using a plurality of sensor output information received from the plurality of vehicles 5 for the same turning point. And the server 7 preserve | saves the produced | generated road shape information in road shape DB77 (step S27). Then, the process ends. Thus, the server 7 acquires sensor output information from the navigation device 1 mounted on a large number of vehicles, estimates the road shape, and stores the obtained road shape information in the road shape DB 77.

(How to use road shape information)
The method of using the road shape information obtained by the second embodiment is the same as that of the first embodiment.

[Modification]
In the above embodiment, an in-vehicle navigation device is illustrated, but instead, the present invention can also be applied using a mobile terminal such as a smartphone that executes a navigation app as a navigation device. When acceleration information is obtained directly from the vehicle, the information may be used to estimate the road shape.

The present invention can be applied to a vehicle or an in-vehicle device equipped with an acceleration sensor.

1 navigation device 5 vehicle 7 server 22 CPU
72 Control unit 77 Road shape DB

Claims (11)

An information acquisition unit for acquiring mobile body information including position information where the mobile body is located and lateral acceleration information applied to the mobile body;
Based on the position information and the lateral acceleration information, an estimation unit that estimates road shape information related to a road width at a turning point through which the moving body passes;
A road shape estimation device comprising: The road shape estimation apparatus according to claim 2, wherein the road shape information includes lane information related to the number of lanes of the road at the direction change point. The information acquisition unit acquires the moving body information from a plurality of moving bodies,
The road shape estimation apparatus according to claim 1, wherein the estimation unit estimates the road shape information by statistical processing. The road shape estimation apparatus according to any one of claims 1 to 3, wherein the road shape information includes road form information relating to a road form at the turning point. The road shape estimation apparatus according to any one of claims 1 to 4, further comprising a transmission unit that transmits the road shape information to the outside. The moving body information includes acceleration in the vertical direction or the traveling direction of the moving body,
The road shape according to any one of claims 1 to 5, wherein the estimation unit estimates a gradient of a road on which the moving body is traveling based on the acceleration in the vertical direction or the traveling direction. Estimating device. The mobile object information includes vertical acceleration of the mobile object,
The road shape estimation apparatus according to any one of claims 1 to 6, wherein the estimation unit estimates an undulation of a road on which the moving body is traveling based on the acceleration. A receiving unit that receives road shape information transmitted from the road shape estimation device according to any one of claims 1 to 7,
Based on the road shape information, a control unit that executes control related to driving support;
A control device comprising: A road shape estimation method executed by an apparatus including a computer,
An information acquisition step of acquiring mobile body information including position information of the mobile body and lateral acceleration information applied to the mobile body;
Based on the position information and the lateral acceleration information, an estimation step for estimating road shape information related to a road width at a turning point through which the moving body passes,
A road shape estimation method comprising: A program executed by a device including a computer,
An information acquisition unit for acquiring mobile body information including position information where the mobile body is located and lateral acceleration information applied to the mobile body;
Based on the position information and the lateral acceleration information, an estimation unit that estimates road shape information related to a road width at a turning point through which the moving body passes,
A program for causing the computer to function as: A storage medium storing the program according to claim 10.

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