JP6687680B2 - Information processing system, information processing server, information processing method, and information processing program - Google Patents

Description

  The present invention relates to an information processing system, an information processing apparatus, an information processing method, and a program, and particularly to an information processing system, an information processing apparatus, an information processing method, and a program that predict congestion of facilities and the like.

  2. Description of the Related Art Conventionally, there is known a system that analyzes a mobile demand such as a congestion situation based on user's search history information.

  For example, Patent Literature 1 discloses a technique of predicting the congestion degree of a target facility based on the number of facility searches in the past predetermined period and displaying the congestion degree on a map.

JP2011-118110A

  However, in the technique disclosed in Patent Document 1, only the date and time when the congestion prediction target is searched is stored in the search history. That is, since the congestion history of the facility at the estimated date and time is predicted using the search history of the user who is not sure when to actually use the facility, there is a problem that the prediction accuracy is low.

  The present invention has been made in view of the above problems, and an object thereof is to provide an information processing system, an information processing server, an information processing method, and an information processing program that enable more accurate movement demand analysis.

  Of the search logs acquired from a plurality of user terminals, a pre-search log storage unit that stores a pre-search log including search location information and date and time setting information after the search execution date and time, an analysis index reception unit that receives an analysis index, Extraction means for extracting the target pre-search log for use in moving demand analysis based on the analysis index from the pre-search log storage means, and movement using the analysis index for the target pre-search log extracted by the extraction means An information processing system, comprising: a mobile demand analysis means for performing demand analysis.

  As described above, according to the present invention, since the travel demand analysis is performed using the data that is highly likely to be actually visited, that is, the advance search log in which the future date and time and the point are designated by the user, it is possible to perform a more accurate analysis. Become.

It is a functional block diagram of the information processing system which concerns on embodiment of this invention. It is a figure which shows an example of the prior search log database 202d of the same embodiment. It is a figure which shows an example of the prior search log database 202d of the same embodiment. It is a flow chart which shows an example of processing of the embodiment. It is a figure explaining an example of the output information of the embodiment. It is a figure explaining an example of the output information of the embodiment. It is a figure explaining an example of the output information of the embodiment.

  An embodiment (information processing system) of the present invention will be described below with reference to FIGS. 1 to 5. However, the embodiments described below exemplify an information processing system for embodying the technical idea of the present invention, and are not intended to specify the present invention to this information processing system. It is equally applicable to information processing systems of other embodiments included in the scope of claims. For example, the form of function distribution on the server side and the terminal side in the information processing system exemplified in the embodiment of the present invention is not limited to the following, and functional or physical units can be used in arbitrary units within a range in which similar effects and functions can be obtained. Can be distributed and integrated into

[Configuration of information processing system]
FIG. 1 shows a functional block diagram of an information processing system according to the present invention. In the figure, the functional unit that performs each function can be referred to as a unit that performs each function.

As shown in FIG. 1, this system is roughly configured by connecting an information processing server 200 and a plurality of terminal devices 100 in a communicable manner. Here, as shown in FIG. 1, the communication includes, for example, remote communication such as wired / wireless communication via the network 300.
Further, each unit of these information processing systems is communicably connected via an arbitrary communication path.

  Here, in FIG. 1, the network 300 may be, for example, the Internet, a telephone line network (such as a mobile terminal line network and a general telephone line network), an intranet, or power line communication (PLC).

[Configuration of information processing server 200]
The information processing server 200 has a function of generating movement demand analysis information for an arbitrary analysis index based on the preliminary search log.

  As shown in FIG. 1, the information processing server 200 of the present embodiment is connected to the terminal device 100 so as to be able to communicate with each other via the network 300 via the communication control interface unit 206, and is stored with the control unit 204. And at least part 202.

  Here, the control unit 204 is a control unit that performs various processes. The communication control interface unit 206 is an interface connected to a communication device (not shown) such as an antenna or a router connected to a communication line or a telephone line, and is provided between the information processing server 200 and the network 300. It has the function of controlling communication. That is, the communication control interface unit 206 has a function of communicating data with the terminal device 100 or the like via a communication line.

  The storage unit 202 is a storage unit such as a fixed disk device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), and various databases (a map information database 202a, a network information database 202b, a POI information database 202c, a pre-existing database). The search log database 202d) is stored.

  Among the respective constituent elements of the storage unit 202, the map information database 202a is a map information storage unit that stores map information regarding a map. Here, the map information database 202a stores map information regarding maps of a plurality of scales or map information that can be applied to maps of a plurality of scales. That is, the map information includes an image for drawing a map in a raster format of a plurality of scales, an image for drawing a map in a vector format, or the like. Further, the map information database 202a may store route map information regarding a route map of public transportation. Further, the map information may include indoor map information such as a floor guide map regarding a building having height information (for example, a station, a department store, etc.). The map information database 202a may store map information and a map ID (for example, a mesh number) that uniquely identifies the map information in association with each other.

  The map information database 202a may further store map object information regarding map objects displayed on the map. Here, the map object information is the shape information (for example, polygon) about the shape of the feature (for example, building, road, railroad, sea, administrative boundary, etc.) displayed on the map, and is displayed on the map. Information such as note information (eg place name, facility name, etc.) and symbol information (eg mountain, police box, convenience store, etc.) displayed on the map (eg icon, etc.) There is.

  The network information database 202b is a network data storage unit that stores network information data that defines a transportation network. Here, the network information stored in the network information database 202b includes in-facility network data and route network data in addition to road network data.

  The road network data stored in the network information database 202b is network data that defines a road network. For example, node data of nodes that are nodes on the road network representation such as stations and intersections, and road sections between nodes. Is network data expressed by a combination of the link data with the link data. The node data includes a node number, position coordinates such as latitude and longitude, a node type, the number of links to be connected, a connecting node number, and an intersection name. The link data includes link numbers, types of roads to be connected, route numbers of national roads, prefectural roads, city roads, etc., line information to be heavily used, attribute information of administrative areas with links, link length, road service status, abnormalities. Including meteorological traffic control sections, vehicle weight restrictions, vehicle height restrictions, width, road width classification, number of lanes, traffic restrictions such as speed limit, link attributes such as overpasses, tunnels and bridges, time required, and name etc. I'm out. Further, the road network data may include traffic regulation data, usage fee data, and the like. Here, the traffic regulation data is data that defines various types of traffic regulation, and includes, for example, general roads such as vehicle closures due to road damage and road construction, and community zones installed to ensure traffic safety. It contains information such as prohibition of vehicles from entering, and prohibition of vehicles from entering due to the connection to private land. Further, the usage charge data is information representing the fuel charge consumed when moving by automobile, motorcycle, etc., the toll of a toll road such as a highway national road, a motorway, etc. In addition, the road network data may store position information such as latitude and longitude information of points such as facilities existing on a route when traveling by car, motorcycle, bicycle, walking, or the like. It should be noted that the network data may store the evaluation information in association with the node number, the link number, or the like in order to evaluate each guide route including the node and the link. As an example, the traffic regulation data as information for evaluation is data that defines various traffic regulations, and for example, a community installed to ensure vehicle safety and traffic closure due to road damage, road construction, etc. Includes information such as prohibition of entry of ordinary vehicles due to zones, etc., and entry of ordinary vehicles due to connection to private land.

  In addition, the route network data stored in the network information database 202b defines the route network of each transportation such as trains, planes, buses, trams, ropeways, monorails, cable cars, and ships (ferries, etc.). Network data, for example, node data of nodes that are nodes in the representation of a route network such as stations, airports, ports, and stops (bus stops, etc.), and railway lines, air routes, routes connecting nodes, And network data represented by a combination with link data of links such as bus routes. The node data includes a node number, position coordinates such as latitude and longitude, a node type, the number of links to be connected, a connected node number, and a name. Further, the link data includes a link number, a type of route to be connected, attribute information of an administrative area in which the link exists, a link length, a traffic regulation section during abnormal weather, a required time, a name and the like. In addition, the route network data includes timetable data of transportation facilities, data of fare used, and the like. Here, the timetable data is, for example, information representing a timetable of each public transportation such as a train, an airplane, a bus, a tram, a ropeway, a monorail, a cable car, and a ship. In addition, the usage fare data is, for example, information representing the usage fare, etc., which occurs when each transportation such as a train, an airplane, a bus, a tram, a ropeway, a monorail, a cable car, and a ship is used. .

  The POI information database 202c is a POI information storage unit that stores POI information including position information of a POI (point of interest). Here, the position (coordinates) information of the POI is the position coordinates of the POI, the telephone number of the POI, the address of the POI, and the location of the point where the POI exists (urban areas, suburbs, harbors, and the vicinity of stations). It also includes usage restrictions. In addition, POI information includes POI name, type (category), URL, business hours, products handled, average price (for example, average usage fee, etc.), reputation, ranking, ease of stopover, recommendation score, photo data, coupon information. , Word-of-mouth (for example, word-of-mouth evaluation and user comments), usage conditions, availability, facility size, POI ID, reference rate such as the number of times or frequency of access to the POI information, and update date and time of the POI information. Contains information about. Here, the POI is a specific point or facility perceived by a person as a convenient place or a place of interest, and is a store (for example, a convenience store, a gas station, a restaurant, etc.), a company, an office. , Public facilities (eg, government offices, schools, stations), entertainment facilities (eg, movie theaters, theaters, amusement parks, etc.), and outdoor facilities (eg, parks, bus terminals, outdoor parking lots, etc.). In addition, the POI may be information regarding a temporarily held event (for example, a festival, a concert, a flea market, a sports match, etc.).

  The pre-search log database 202d is a database that stores the pre-search log among the search logs acquired by the search request acquisition unit 204a from the terminal device 100 via the network 300.

  Here, the pre-search log will be described. The advance search log is a search request acquired by the information processing server 200 from the terminal device 100 via the network, or information obtained as a result of the search by the route information acquisition unit 204b based on the acquired search request. It refers to a search log to which at least some search point information and date / time setting information after the user search execution date / time are attached together.

  The search point information is, for example, information about a point included in a route search request or a route search result, and indicates information set as a departure place, a destination, a waypoint, etc., a passing point, a use station, or the like. In addition, route information related to route sections such as passing roads and railroad lines included in the route search result is also applicable. Further, in the case of facility search or timetable search other than route search, POI information such as stores and stations included in search conditions or search results corresponds to search point information.

  The date / time setting information after the user search execution date / time is date / time setting information specified by the user as a search condition at the time of executing the search, and further indicates a date / time that is later than that at the time of executing the search. For example, it is a future date and time condition designated by the user included in the route search request or the route search result, and the designated departure date and time or the designated arrival date and time are applicable. In addition, information search other than route search may also include date and time setting information. For example, even when a future specific date and time is specified by the user as a search condition at the time of facility search, traffic information search, and timetable search, it can be said that the date and time setting conditions after the user search execution date and time are attached. A search log of a general information search (real-time search) in which the user does not specify the date and time does not correspond to the pre-search log because the date and time setting information after the user search execution date and time is not included.

  An example of the preliminary search request log table stored in the preliminary search log database 202d will be described with reference to FIG. The pre-search request log table is a table that stores the contents of the pre-search request. Here, a pre-search request log table for route search will be described as an example.

  As shown in FIG. 2, the pre-search request log table stores the route search request ID, the search point information, the time designation information, and the search execution date and time, which is the date and time when the user executed the search. For example, the route search request ID: 001 is a search execution date and time: “2013/1/5 10:49” Departure place: N company, destination: S tower, waypoint: GEM station, desired arrival date and time: “2013/1 / 11 20:20 ”and stored. Here, the transit point may be one point as shown in the figure, may be a plurality of points, or may not be.

  The pre-search result log is a log in which the route information acquired by the route information acquisition unit 204b of the information processing server 200 is accumulated based on the route search request information acquired from the terminal device 100 via the network 300, for example. This route information is also included in the search point information.

  The route information is information about a route from a departure place to a destination. Here, the route may be configured by one moving means or may be configured by combining a plurality of moving means. For example, it may be a car route consisting of only a car, or a route that combines foot and public transportation. In addition, the route information is composed of information indicating a point and a road or a route passing from the starting point to the destination.

  A first example of the route information is composed of a link string and a node string such as a combination of link data indicating the searched route. Note that the route information may include position information of the route (for example, a shape point sequence), image data indicating the route (for example, polyline), and the like. In addition, the route information may include information such as latitude, longitude and altitude of a departure place, a destination, and a waypoint. Further, the route information may include route search conditions such as departure time and arrival time, route distance and required time, and transportation means.

  In addition, as a second example of the route information, as shown in FIG. 3, point information (for example, a departure place, a destination, a waypoint) and passage section information (for example, a road in the route, a route in the route), Scheduled arrival date / time information (for example, scheduled departure date / time, estimated arrival date / time, scheduled passage date / time).

  Here, the point information is information about the points included in the route information. That is, it is information about a departure place, a destination, a waypoint, etc. in the route information, and is information such as a POI name, latitude / longitude altitude, address, and telephone number. The information on the waypoints may be information on the waypoints set in the route search request information, or as a result of the route search, a boarding station, alighting station, a boarding / alighting station, an intersection, an IC (interchange), It may be information about a JCT (junction) and a passing point such as a station platform.

  The passage section information is information about the passage section included in the route information. That is, it is information about a section through which a route of public transportation such as a railway route or a bus route or a road such as a general road or an expressway passes, and is information such as a route name, a road name, and a link ID.

  The expected arrival date and time information is information about the time included in the route information. That is, it is date and time information such as the scheduled departure date and time of the departure place, the scheduled arrival date and time of the destination, the scheduled passage date and time of the transit point, and the scheduled passage date and time of the passage section in the route information. Here, the date / time information may be a date / time such as “2013/11/11 19:55” or a period such as “2013/11/11 19:55 to 2013/11/11 20:15”. May be.

FIG. 3 is a diagram showing a route search result table as an example of the pre-search result log table.
The route search result table includes a route search result ID, point information (departure point, destination, transit point) as search point information, transit section information, and expected arrival date / time information (scheduled departure date / time of destination, destination The estimated arrival date and time, the transit point and the estimated passage date and time of the passage section, and the search execution date and time, which is the date and time when the user executed the search, are stored in association with each other. For example, the route search result ID: 101 is the departure place: N company, the scheduled departure date and time: “2013/11/11 19:45”, the destination: S tower, the estimated arrival date and time: “2013/11/11 20:20. , Via point: GEM station, scheduled date / time for transit point 1: “2013/11/11 19:55”, transit point 2: OSA station, scheduled date / time for transit point 2: “2013/11/11 20:15” , Section 1: H line, Section 1 scheduled passage date and time: “2013/11/11 19:55 to 2013/11/11 20:15” are stored in association with each other. Here, the transit points may be a plurality of points as illustrated. Further, here, the section may be one section as shown in the figure, or may be a plurality of sections.

  The control unit 204 has a control program such as an OS (Operating System), a program defining various processing procedures, and an internal memory for storing required data. Then, the control unit 204 performs information processing for executing various processes by using these programs and the like. The control unit 204 functionally and conceptually includes a search request acquisition unit 204a, a route information acquisition unit 204b, an analysis index reception unit 204c, an analysis information generation unit 204d, and an output information generation unit 204e.

Of these, the search request acquisition unit 204a is a search request acquisition unit that acquires a search request based on the search conditions set by the user via the input unit 114 of the terminal device 100.
The search request acquisition unit 204a extracts the pre-search request based on the search execution date / time, the date / time setting information, and the search location information included in the acquired search request, and stores the pre-search request in the pre-search log database 202d. The search execution date and time may be included in the search request, or may be information in which the date and time when the search request acquisition unit 204a acquires the search request is stored on the server side. As described above, each time the search request acquisition unit 204a acquires a search request, only the advance search request log may be extracted and stored in the advance search log database one by one, or all search requests may be temporarily stored. It may be stored in a general search log database (not shown) and only the preliminary search logs may be extracted from the search log group stored in the general search log database to separately create the preliminary search log database 202d. .

  When the search request acquired by the search request acquisition unit 204a is a search request related to a route search, the route information acquisition unit 204b, based on the route search condition included in the search request, from a departure point satisfying the route search condition to a destination. It is a route information acquisition means for acquiring the route information which is the route.

  The route information acquisition unit 204b searches a route from a departure place to a destination that satisfies the route search condition including at least the departure place and the destination based on the network data stored in the network database 206a. Here, the route information acquisition unit 204b uses the route search condition included in the route search request information received from the terminal device 100. Further, the route information acquisition unit 204b may use the route search conditions stored in the storage unit 202 in advance. The route information searched by the route information acquisition unit 204b is configured by information indicating a point and a road or a route passing from the starting point to the destination. For example, it may be configured by combining a link and a node, and the spot information, section information, and arrival date / time information (scheduled departure date / time, estimated arrival date / time, transit point 1 passage scheduled date / time, section, etc.) as shown in FIG. 1 scheduled passage date and time).

  In addition, the route information acquisition unit 204b acquires route information by referring to the preliminary search result log table in the preliminary search log database 202b and extracting a route search history from a departure point to a destination that satisfies the route search condition. You may.

  The analysis index receiving unit 204c is an analysis index receiving unit that acquires the analysis index set by the user via the analysis index setting unit 102b of the terminal device 100 and receives the designation. For example, a specific point, section, date and time, time zone, day of the week, etc. can be designated as an analysis index, and the point is designated by information such as POI name, latitude / longitude, address, and telephone number. In addition, the section accepts designation by information such as a route name, a road name, and a link ID. In addition, the date and time accepts designation by information such as date, time, and period. In addition, time zone, day of the week, day type (weekdays / Saturdays and Sundays), moving body attributes (type of transportation such as railway lines, cars, bicycles, etc.), user attributes (age, gender, age, etc.), weather information, etc. Any information can be used as an analysis index based on the information given to the search log or the information that can be estimated from the pre-search log. Note that one or a plurality of combinations of these analysis indexes may be used. In the present embodiment, the analysis index for congestion prediction is received from the terminal device 100 and the designation is accepted. As the congestion prediction date and time, date and time information stored in advance in the storage unit 202 may be used instead of the information included in the congestion prediction target information received from the terminal device 100. Here, the date and time information stored in advance in the storage unit 202 may be a current date and time, a predetermined date and time or a period, or information that defines a period such as one week before and after the current date and time as a starting point. Good.

The extraction unit 204d is an extraction unit that extracts, from the pre-search database 202b, the target pre-search log that satisfies the condition as the analysis index received by the analysis index receiving unit 204c.
For example, when the analysis index received by the analysis index receiving unit 204c in FIG. 3 is “S tower”, the search result ID 101 and the ID 103 that include “S tower” in the search point information are used as the pre-search log for the analysis target. Extract. Furthermore, the search request ID 001 including “S tower” in the search point information may also be the extraction target by referring to the pre-search request log table. On the other hand, when the analysis index is “2013/11/11 12: 00-24: 00”, the search result ID 101 whose scheduled date and time is “2013/11/11 19:45” satisfies the condition and is extracted. Be the target. Here, the extraction target may be a perfect match with the analysis index, or may have a predetermined width. In particular, if the number of target pre-search logs is less than the predetermined number when the extraction condition is a perfect match, the pre-search logs having similar conditions may be extracted. In the case of the above example, the pre-search log of ID 103 may also be the extraction target.

  The analysis information generation unit 204e generates analysis information that generates analysis information of an analysis point and / or an analysis section based on the target pre-search log extracted by the extraction unit 204d and the analysis index received by the analysis index reception unit 204c. It is a means. Here, when generating the congestion prediction information as an example of the analysis information generation in the present embodiment, the congestion degree index may be calculated based on the number of pre-search logs at the congestion prediction date and time of the congestion prediction point or the congestion prediction section. it can. In addition, the number of target pre-search logs is compared with the number of regular searches held in advance, and an index is calculated based on comparison with information such as the allowable number of people and the number of allowed vehicles at the congestion prediction point or congestion prediction section. Good. Here, the index may be a numerical value indicating a ratio such as 70%, or may be an expression such as a congestion rate (for example, congestion rate: high, congestion rate: medium) based on the numerical value.

Further, by comparing with the POI data stored in the POI database 202c, a more accurate analysis can be performed. Specifically, when an event is scheduled to be held near the analysis target point near the analysis target date and time, which is an analysis index, it can be estimated that there is a high possibility that sudden mobile demand will occur compared to normal times. The value of the congestion degree can be increased by adding a predetermined number to the number of target pre-search logs.
Further, the POI data can be used for estimating the cause of the location where the demand for movement increases. For example, if the number of target pre-search logs at the analysis target point is larger than usual, occurrence of sudden movement demand can be detected, and if an event is held around the analysis target point from the POI database, the sudden movement will occur. It can be estimated that the demand is due to the event. Such an analysis is particularly effective for estimating the cause of the past congestion occurrence location.

  Further, based on the time difference between the analysis date and time set as the analysis index and the date and time setting information included in the target pre-search log, the analysis information may be generated after calculating the expected increase in the number of search logs at the analysis date and time.

  The output information generation unit 204f is a unit that generates output information that is information to be output to the output unit 116 of the terminal device 100. The output information is information for displaying the analysis information generated by the analysis information generation unit 204e. Here, as an example of the output information for displaying the analysis information, as shown in FIG. 5, the analysis information, which is the congestion prediction information for each time of the congestion prediction point or the congestion prediction section, is displayed in a graph form in time series. It was placed in. Further, the output information may be information for displaying a map including the reference point or the current position based on the map information stored in the map information database 202a, or may be retrieved or selected from the POI information database 202c. It may be information for displaying the POI information. The output information may be information for displaying the route information acquired by the route information acquisition unit 204b.

  The output information generation unit 204f may also transmit the generated output information to the terminal device 100 via the communication control interface unit 206.

[Configuration of terminal device 100]
Further, in FIG. 1, the terminal device 100 has a function of receiving the search condition setting and transmitting a search request based on the received search condition to the information processing server 200.

  The terminal device 100 is a device that is connected to the information processing server 200 via the network 300 and is used by a user. For example, it is an information processing device such as a desktop or notebook personal computer, a mobile phone, a smartphone, a mobile terminal device such as PHS and PDA, and a navigation terminal (for example, a car navigation device) for performing travel route guidance and the like. Here, the information processing apparatus 100 may be equipped with an internet browser or the like, and may be equipped with a route guidance application, a transfer guidance application, an information search application, or the like.

  As shown in FIG. 1, the terminal device 100 of the present embodiment schematically includes a control unit 102, a communication control interface unit 104, an input / output control interface unit 106, a position information acquisition unit 112, and an input / output unit (input. At least a section 114 and an output section 116).

  Here, the control unit 102 is a control unit that performs various processes. The communication control interface unit 104 is an interface connected to a communication device (not shown) such as an antenna or a router connected to a communication line or a telephone line, and communication between the terminal device 100 and the network 300. It has a control function. That is, the communication control interface unit 104 has a function of communicating data with the information processing server 200 or the like via a communication line. The position information acquisition unit 112 has a GPS function, an IMES function, and the like so that the current position can be acquired in real time. The position information acquisition unit 112 having the GPS function may receive a signal from the position transmission device 500 such as a GPS satellite to acquire the position information.

  The input unit 114 also includes a voice input unit (for example, a microphone) that inputs voice. Further, the input unit 114 may be provided with operation input means (for example, buttons, switches, etc.) for inputting by pressing. The output unit 116 is a display unit (for example, a display and a monitor including liquid crystal or organic EL) that displays a display screen of an application or the like. The output unit 116 may be a voice output unit (for example, a speaker) that outputs voice data as voice. Here, the display unit of the output unit 116 may be a touch panel or the like and function as the input unit 114. Further, the input / output control interface unit 106 has a function of controlling the output unit 116, the input unit 114, and the like.

  Further, the control unit 102 has a control program such as an OS, a program defining various processing procedures, and an internal memory for storing required data. Then, the control unit 102 performs information processing for executing various processes by using these programs and the like. The control unit 102 functionally conceptually includes a route search condition setting unit 102a, an output information acquisition unit 102b, and a questionnaire response information transmission unit 102c.

  The search condition setting unit 102a is a search condition setting unit that sets information acquisition conditions. The search condition setting unit 102a allows the user to input search conditions via the input unit 114. Further, the search condition setting unit 102a may use the search condition set in advance and stored in the storage unit 202. The types of information search include route search, facility information search, timetable search, and traffic information search.

  When the type of information search is route search, search conditions including at least a departure place, a destination, a desired departure date and time or a desired arrival date and time are set. Further, the search condition setting unit 102a may set the current position of the mobile body such as the user of the terminal device 100 based on the position information acquired by the position information acquisition unit 112 to the departure place. Further, the search condition setting unit 102a may set the desired date and time of departure to the current date and time obtained from a clocking means (not shown) provided in the information processing system. Further, the search condition may include a waypoint and a desired date and time of the waypoint. It may also include information about the means of transportation and user attributes. In addition, priority items (e.g., cost to be evaluated) in the route search may be included such as required time, charge, distance, number of transfers, and the like. The search condition setting unit 102a transmits the obtained search conditions to the information processing server 200, and the search request acquisition unit 204a of the information processing server 200 receives the transmitted search conditions.

  The analysis index setting unit 102b is means for setting an analysis index when performing analysis. The analysis index setting unit 102b sets the analysis index based on the information input by the user via the input unit 114. As the analysis index, for example, a specific point, area, section, date and time, etc. can be set, and the point accepts the setting with information such as POI name, latitude / longitude altitude, address, and telephone number. Further, the section accepts the setting with information such as a route name and a road name. In addition, the date and time accepts the setting with information such as date, time, and period. In addition, it is possible to set all or one of a plurality of pieces of information such as a time zone, a day of the week, a mobile body type, a user attribute, etc. as an analysis index. The analysis index setting unit 102b transmits the set analysis index to the information processing server 200 via the communication control interface unit 104, and the transmitted analysis target information is the analysis index receiving unit 204c of the information processing server 200. To receive.

The output information acquisition unit 102c is an output information acquisition unit that acquires the output information generated by the output information generation unit 204f of the information processing server 200 from the information processing server 200 via the communication control interface unit 104.
This is the end of the description of the example of the configuration of the information processing system according to the present embodiment.

[Processing of information processing system]
Next, an example of processing of the navigation system according to the present embodiment configured as described above will be described in detail below with reference to FIGS. 2 to 5.

  FIG. 4 is a flowchart showing an example of processing of the information processing system in this embodiment.

  First, the analysis index setting unit 102b of the terminal device 100 sets the analysis index based on the information input by the user via the input unit 114 (step SA-1).

  Then, the analysis index setting unit 102b transmits information about the set analysis index to the information processing server 200 via the communication control interface unit 104. (Step SA-2).

  Next, the analysis index receiving unit 204c of the information processing server 200 receives the analysis index information transmitted from the terminal device 100 (step SA-3).

Next, the extraction unit 204d of the information processing server 200 extracts the pre-search log group corresponding to the analysis index from the pre-search log database 202d (step SA-4).
Next, the analysis information generation unit 204e of the information processing server 200 generates analysis information based on the extracted target pre-search log group and the analysis index (step SA-5).

  As a first example of the analysis information generation processing, the analysis information generation unit 204e uses the pre-search log stored in the pre-search log database 202d and the congestion prediction information based on the information regarding the analysis index received by the analysis index receiving unit 204c. To generate.

  An example of a specific process will be described with reference to FIG. The extraction unit 204d extracts, from the pre-search log database 202d, a pre-search log including information indicating a congestion prediction point and information indicating a congestion prediction date and time in the information about the analysis index. For example, when the congestion prediction includes the POI name “S tower” as the index indicating the prediction point and the date “2013/11/11” as the index indicating the congestion prediction date and time, the pre-search log extraction unit 204d extracts a route search request ID: 001 which is a prior search log that includes "S tower" in the search point information and "2013/11/11" in the time designation information. The analysis information generation unit 204e increments the count of the number of pre-search logs at the congestion prediction point by 1, based on the extracted pre-search log. In this way, the number of relevant pre-search logs in the pre-search log database 202d is counted to generate congestion prediction information.

Note that, in the above, an example in which a pre-search log including “S tower” in the search point information is extracted when the POI name is set as the information indicating the congestion prediction point has been described. Not limited to this, the information such as the address and the telephone number corresponding to the POI name "S Tower" is specified by referring to the POI information database 202c, and the pre-search log including the specified information is extracted. Good.
Further, the pre-search log whose date / time setting condition is 2013.1.11 and which can be estimated to pass around the S tower from the section information may be the extraction target.

  As a second example of the congestion prediction information generation processing, the analysis information generation unit 204e refers to the preliminary search result table stored in the preliminary search log database 202d and generates the congestion prediction information.

  Specific processing will be described with reference to FIG. FIG. 3 is a diagram showing an example of a preliminary search result log table stored in the preliminary search log database 202d in the second example of the route information. The extraction unit 204d extracts, from the pre-search log database 202d, a pre-search log including information indicating a congestion prediction section in the analysis index and information indicating a congestion prediction date and time. For example, when the congestion prediction target information includes “Y line” as the information indicating the congestion prediction section and “2013/1/12” as the information indicating the congestion prediction date and time, the pre-search log extraction unit 204d, A pre-search log of a route search result ID: 002 that is a route search result log that includes “Y line” in the section information and “2013/1/12” in the scheduled passage date and time of the section information is extracted. The analysis information generation unit 204e increments the count of the number of pre-search logs in the congestion prediction section by 1, based on the extracted pre-search log. In this way, the number of relevant pre-search logs in the pre-search log database 202d is counted to generate congestion prediction information.

  In addition, when the pre-search log database 202d is configured in the first example form of route information (form that is configured by a link sequence and a node sequence), information or a section indicating a point in the information regarding the analysis index is displayed. The information such as the name included in the information shown is used as a key to search the network information database 202b or the POI information database 202c for the latitude / longitude altitude information of the POI corresponding to the point or section, the link ID, and the node ID, and the searched POI The pre-search log including the latitude / longitude altitude, the link ID, and the node ID may be extracted from the pre-search log database 202d, and the number of pre-search logs may be counted to generate the analysis information.

  Returning to FIG. 4, next, the output information generation unit 204f of the information processing server 200 generates output information based on the analysis information generated by the analysis information generation unit 204e (step SA-6). Here, as shown in FIG. 5, the output information may be information obtained by arranging analysis information for each time of a point or section in a graph along a time series. After that, the output information generation unit 204e transmits the generated output information to the terminal device 100 via the communication control interface unit 206 (step SA-7).

  Next, the output information acquisition unit 102b of the terminal device 100 receives and acquires the output information transmitted via the communication control interface unit 206 of the information processing server 200, and outputs the output information to the output unit 116 (step SA-8).

  This is the end of the description of the example of the processing of the information processing system in the present embodiment.

[Other embodiments]

  In the above embodiment, an example of the form of the output information has been described with reference to FIG. 5, but the output information in the present invention may take other forms. For example, the output information may include congestion prediction information of a plurality of congestion prediction points. As shown in FIG. 6, the congestion prediction information (dotted line) of the S tower, which is a tourist spot, and the congestion prediction information (dotted line) of the T baseball field, which is a tourist spot, are configured to be displayed in the same graph. By doing so, it becomes easy to compare congestion prediction information between each tourist spot at the user's desired date and time, and the user can easily select a vacant tourist spot or a more popular tourist spot. It will be possible.

  The output information may be output together with the analysis information in the analysis index designated by the user, including a steady value. For example, as shown in FIG. 7, the congestion prediction information (solid line) and the average congestion prediction information (broken line) at the congestion prediction date and time are configured to be displayed in the same graph. By doing so, the user can easily compare the usual congestion situation with the congestion situation at the congestion estimated date and time. Then, when the predicted congestion date and time is more crowded than usual, it is possible to make a decision such as canceling the movement schedule. Here, the average congestion prediction information is an average value of the congestion prediction information on dates and times other than the congestion prediction date and time. Further, the average congestion prediction information may be the average value of the congestion prediction information in a predetermined period, or may be the average value of the congestion prediction information of the date and time having the same attribute (eg, day of the week, holiday, weather) as the congestion prediction date and time in the predetermined period. Good. In the above example, the average congestion prediction information is output to facilitate the comparison between the congestion prediction information at the congestion prediction date and time and the usual congestion status, but instead of the average congestion prediction information, the congestion prediction points The average congestion record information, which is the record of past congestion status, may be used.

  In addition, in the above-mentioned embodiment, the case where it is mainly used for congestion prediction has been described as an example of the mobile demand analysis, but in addition, marketing and trade area analysis for businesses, transportation capacity adjustment of transportation businesses, timetable creation, etc. , Can be applied to a wide range of fields. In particular, the movement demand analysis focusing on user attributes and mobile body attributes is effective as marketing data, and can be used for effective analysis of advertisement placement locations. Further, the present invention can be applied not only to the prediction of future mobile demand as described in the above embodiment, but also to analysis such as verification of past congestion events and estimation of causes.

  Now, the embodiments of the present invention have been described so far, but the present invention is not limited to the above-described embodiments, but may be implemented in various different embodiments within the scope of the technical idea described in the claims. It may be carried out. Further, of the processes described in the embodiments, all or part of the processes described as being automatically performed may be manually performed, or the processes described as manually performed may be performed. All or part of the process can be automatically performed by a known method.

  In addition, unless otherwise specified, the processing procedures, control procedures, specific names, information including parameters such as registration data and search conditions for each processing, screen examples, and database configuration shown in the above documents and drawings are excluded. Can be changed arbitrarily.

  Further, regarding the information processing system, the constituent elements shown in the drawings are functionally conceptual and do not necessarily have to be physically configured as illustrated. Further, the specific form of the distribution / integration of the devices is not limited to that shown in the drawings, and all or a part of the devices may be functionally or physically united in arbitrary units according to various additions or functional loads. Can be distributed and integrated. That is, the above-described embodiments may be implemented in any combination, or the embodiments may be selectively implemented.

100 terminal device 102 control unit 102a search condition setting unit 102b analysis index setting unit 102c output information acquisition unit 104 communication control interface unit 106 input / output control interface unit 112 position information acquisition unit 114 input unit 116 output unit 200 information processing server 202 storage unit 202a map information database 202b network information database 202c POI information database 202d advance search log database 204 control unit 204a search request acquisition unit 204b route information acquisition unit 204c analysis index reception unit 204d extraction unit 204e analysis information generation unit 204d output information generation unit 206 communication Control interface unit 300 Network 500 Position transmission device

Claims (9)

Among the route search logs that are acquired from multiple user terminals and that use public transportation, automobiles, motorcycles, or bicycles at least partly from the departure point to the destination, the search point information and the search execution date and time Pre-search log storage means for storing a pre-route search log including date and time setting information,
An analysis index receiving means for receiving an analysis index,
Based on the analysis index, extraction means for extracting a target advance route search log for use in congestion prediction analysis from the advance search log storage means,
Travel demand analysis means for performing congestion prediction analysis on the target advance route search log extracted by the extraction means using the analysis index, and generating an index of the congestion degree of the congestion prediction point and / or the congestion prediction section; ,
Information output means for outputting the index of the congestion degree generated by the movement demand analysis means,
An information processing system comprising:   The information processing system according to claim 1, wherein the analysis index is any one or a combination of a date, a time zone, a day of the week, a point, a road, a route section, information regarding a user attribute and a moving body attribute. An information processing system characterized in that   The information processing system according to claim 1 or 2, wherein the information processing system further comprises POI information storage means, and the movement demand analysis means refers to POI information included in the POI information storage means to analyze congestion prediction. An information processing system characterized by performing.   The information processing system according to any one of claims 1 to 3, wherein the movement demand analysis unit sets a time difference between a predicted congestion date and time set as an analysis index and date and time setting information included in the target advance route search log. An information processing system characterized by calculating an expected increase in the number of advance route search logs at a predicted congestion date and time and performing congestion prediction analysis in consideration of the expected increase. Among the route search logs that are acquired from multiple user terminals and that use public transportation, automobiles, motorcycles, or bicycles at least partly from the departure point to the destination, the search point information and the search execution date and time Pre-search log storage means for storing a pre-route search log including date and time setting information,
An analysis index receiving means for receiving an analysis index,
Based on the analysis index, extraction means for extracting a target advance route search log for use in congestion prediction analysis from the advance search log storage means,
Travel demand analysis means for performing congestion prediction analysis on the target advance route search log extracted by the extraction means using the analysis index, and generating an index of the congestion degree of the congestion prediction point and / or the congestion prediction section; ,
An information processing server comprising: Among the route search logs that are acquired from multiple user terminals and that use public transportation, automobiles, motorcycles, or bicycles at least partly from the departure point to the destination, the search point information and the search execution date and time An information processing method executed in an information processing system comprising a pre-search log storage means for storing a pre-route search log including date / time setting information,
An analysis index receiving step for receiving an analysis index,
An extraction step of extracting a target pre-route search log for use in congestion prediction analysis from the pre-search log storage means based on the analysis index;
A travel demand analysis step of performing congestion prediction analysis on the target advance route search log extracted by the extraction step using the analysis index, and generating an index of congestion degree of a congestion prediction point and / or a congestion prediction section; ,
An information processing method comprising: Among the route search logs that are acquired from multiple user terminals and that use public transportation, automobiles, motorcycles, or bicycles at least partly from the departure point to the destination, the search point information and the search execution date and time An information processing program executed in an information processing system comprising a pre-search log storage unit for storing a pre-route search log including date / time setting information, the program comprising:
An analysis index receiving step for receiving an analysis index,
An extraction step of extracting a target pre-route search log for use in congestion prediction analysis from the pre-search log storage means based on the analysis index;
A travel demand analysis step of performing congestion prediction analysis on the target advance route search log extracted by the extraction step using the analysis index, and generating an index of congestion degree of a congestion prediction point and / or a congestion prediction section; ,
An information processing program for executing. An information processing program executed in a terminal device communicatively connected to an information processing server,
The information processing server,
Of the route search logs related to routes using public transportation, automobiles, motorcycles, or bicycles that are acquired from multiple user terminals and that use at least part of the place of departure to the destination, search point information and search execution date and time Pre-search log storage means for storing a pre-route search log including date and time setting information,
An analysis index receiving means for receiving an analysis index,
Based on the analysis index, extraction means for extracting a target advance route search log for use in congestion prediction analysis from the advance search log storage means,
Travel demand analysis means for performing congestion prediction analysis on the target pre-route search log extracted by the extraction means using the analysis index, and generating an index of the congestion degree of the congestion prediction point and / or the congestion prediction section; ,
Equipped with
The information processing program stores a computer,
An information processing program for functioning as information output means for outputting the congestion degree index generated by the movement demand analysis means. A terminal device communicatively connected to an information processing server,
The information processing server,
Among the route search logs that are acquired from multiple user terminals and that use public transportation, automobiles, motorcycles, or bicycles at least partly from the departure point to the destination, the search point information and the search execution date and time Pre-search log storage means for storing a pre-route search log including date and time setting information,
An analysis index receiving means for receiving an analysis index,
Based on the analysis index, extraction means for extracting a target advance route search log for use in congestion prediction analysis from the advance search log storage means,
Travel demand analysis means for performing congestion prediction analysis on the target advance route search log extracted by the extraction means using the analysis index, and generating an index of the congestion degree of the congestion prediction point and / or the congestion prediction section; ,,
The terminal device includes an information output unit that outputs the congestion degree index generated by the movement demand analysis unit.

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