JP6910667B2 - 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 device, an information processing method, and a program, and more particularly to an information processing system, an information processing device, an information processing method, and a program for predicting congestion of facilities and the like.

Conventionally, a system that analyzes mobile demand such as a congestion status based on a user's search history information has been known.

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

JP 2011-118110

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, there is a problem that the accuracy of the prediction is low because the congestion prediction of the facility at the predicted date and time is performed using the search history of the user who does not know when to actually use the facility.

In view of the above problems, an object of the present invention is to provide an information processing system, an information processing server, an information processing method, and an information processing program capable of more accurate mobile demand analysis.

Among the search logs acquired from a plurality of user terminals, a pre-search log storage means for storing the pre-search log including the search point information and the date and time setting information after the search execution date and time, an analysis index receiving means for receiving the analysis index, and an analysis index receiving means for receiving the analysis index. The target pre-search log for use in the movement demand analysis based on the above analysis index is extracted from the above-mentioned pre-search log storage means, and the target pre-search log extracted by the above-mentioned extraction means is moved using the above analysis index. An information processing system characterized by being provided with a mobile demand analysis means for performing demand analysis.

As described above, according to the present invention, since the movement demand analysis is performed using the data having a high possibility of actual visit, that is, the advance search log in which the future date and time is specified and the point is specified by the user, more accurate analysis is possible. 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 preliminary search log database 202d of the same embodiment. It is a figure which shows an example of the preliminary search log database 202d of the same embodiment. It is a flowchart which shows an example of the process of the same embodiment. It is a figure explaining an example of the output information of the same embodiment. It is a figure explaining an example of the output information of the same embodiment. It is a figure explaining an example of the output information of the same embodiment.

An embodiment (information processing system) of the present invention will be described below with reference to FIGS. 1 to 5. However, the embodiments shown 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 the information processing systems of other embodiments included in the claims. For example, the form of functional distribution on the server side and the terminal side in the information processing system illustrated in the embodiment of the present invention is not limited to the following, and is functionally or physically in any unit within the range in which similar effects and functions can be obtained. Can be distributed and integrated into the configuration.

[Information processing system configuration]
FIG. 1 shows a functional block diagram in the information processing system of the present invention. In the figure, the functional unit that performs each function can be said to be a means for performing 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, as an example, remote communication such as wired / wireless communication via the network 300.
Further, each part 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 (mobile terminal line network, general telephone line network, etc.), an intranet, power line communication (PLC), or the like.

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

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

Here, the control unit 204 is a control means that performs various processes. Further, 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 used between the information processing server 200 and the network 300. It has a function to control 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 fixed disk device such as an HDD (Hard Disk Drive) or a storage means such as an SSD (Solid State Drive), and various databases (map information database 202a, network information database 202b, POI information database 202c, advance). The search log database 202d) is stored.

Among the components of the storage unit 202, the map information database 202a is a map information storage means for storing map information related to the map. Here, the map information database 202a stores map information related to maps of a plurality of scales or map information corresponding to maps of a plurality of scales. That is, the map information includes a plurality of scale raster format map drawing images, a vector format map drawing image, and the like. Further, the map information database 202a may store the route map information related to the route map of public transportation. Further, the map information may include, for example, indoor map information such as a floor guide map for a building having height information (for example, a station, a department store, etc.). Further, the map information database 202a may store the map information in association with the map ID (for example, mesh number or the like) that uniquely identifies the map information.

The map information database 202a may further store map object information regarding the map object displayed on the map. Here, the map object information is displayed on the map as shape information (for example, polygons) about the shape of the features (for example, buildings, roads, railroads, seas, administrative boundaries, etc.) displayed on the map. Includes data such as note information (eg, place name, facility name, etc.) and symbol information (eg, icon, etc.) of symbols (eg, mountains, alternations, convenience stores, etc.) displayed on the map. There is.

The network information database 202b is a network data storage means for storing 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 network data in addition to road network data.

The road network data stored in the network information database 202b is network data that defines the road network, for example, node data of nodes that are nodes in the road network representation such as stations and intersections, and road sections between nodes. It is network data expressed by a combination with the link data of the link. The node data includes position coordinates such as node number and latitude / longitude, node type, number of links to be connected, connection node number, intersection name and the like. In addition, the link data includes link numbers, types of connected roads, route numbers such as national roads, prefectural roads, and city roads, important route information, attribute information of administrative areas where links exist, link lengths, road service status, and abnormalities. Includes traffic restrictions such as weather traffic regulation sections, vehicle weight restrictions, vehicle height restrictions, widths, road width divisions, number of lanes, speed limits, etc., attributes within links such as elevated roads, tunnels and bridges, required time, and names. 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 traffic regulations, for example, general by a community zone established to ensure traffic safety, vehicle closure due to road damage, road construction, etc. It includes information such as prohibition of entry of vehicles and prohibition of entry of general vehicles due to the connection road to private land. In addition, the usage fee data is information representing fuel charges consumed when traveling by automobile, motorcycle, etc., toll roads such as national expressways and motorways, and the like. In addition, the road network data may store location information such as latitude / longitude information of points of facilities and the like existing on the route when moving by automobile, motorcycle, bicycle, walking, or the like. In the network data, evaluation information may be stored in association with a node number, a link number, or the like in order to evaluate each guide route composed of a node and a link. As an example, traffic regulation data as evaluation information is data that defines various traffic regulations. For example, a community set up to ensure vehicle traffic closure due to road damage, road construction, etc., and traffic safety. Includes information such as prohibition of general vehicles from entering due to zones, etc., and prohibition of general vehicles from entering due to the connection road to private land.

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

Further, the POI information database 202c is a POI information storage means for storing POI information including position information of POI (point of interest). Here, the POI position (coordinates) information includes the POI position coordinates, the POI telephone number, the POI address, and the location of the point where the POI exists (urban area, suburbs, port area, station area, etc.). And usage restrictions etc. are included. 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 visiting, recommendation score, photo data, coupon information. , Word-of-mouth (for example, word-of-mouth evaluation and user comments), terms of use, usability, facility scale, POI ID, reference rate such as the number of accesses or access frequency to the POI information, and the update date and time of the POI information, etc. Contains information about. Here, the POI is a specific point or facility that a person perceives 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, or 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.) and the like. The POI may also be information about a temporary event (eg, a festival, a concert, a flea market, a sports match, etc.).

The pre-search log database 202d is a database that stores pre-search logs 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 pre-search log is information as a result of a search request acquired by the information processing server 200 from the terminal device 100 via the network, or a search result searched by the route information acquisition unit 204b based on the acquired search request. It refers to a search log that includes at least some search point information and date and time setting information after the user search execution date and time.

The search point information is, for example, information about a point included in a route search request or a route search result, and refers to information set as a departure point, a destination, a waypoint, etc., a passing point, a station used, or the like. In addition, route information related to route sections such as passing roads and railway lines included in the route search results 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 the search conditions or search results corresponds to the search point information.

The date and time setting information after the user search execution date and time is the date and time setting information specified by the user as a search condition at the time of executing the search, and further, the date and time set in the future from the time of executing the search is specified. For example, it is a future date and time condition specified by the user included in the route search request or the route search result, and corresponds to the specified departure date and time or the specified arrival date and time. In addition, date and time setting information may be included even in information retrieval other than route search. For example, even when a specific future date and time is specified by the user as a search condition in the facility search, the traffic information search, or the timetable search, it can be said that the date and time setting condition after the user search execution date and time is attached. The search log of 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 it does not include the date and time setting information after the user search execution date and time.

An example of the pre-search request log table stored in the pre-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, the 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, in association with each other. For example, the route search request ID: 001 is the search execution date and time: "2013/1/5 10:49" Departure point: Company N, destination: S tower, waypoint: GEM station, desired arrival date and time: "2013/1" It is stored in association with "/ 11 20:20". Here, the waypoints may be one point, a plurality of points, or none as shown in the figure.

The pre-search result log is, for example, 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. This route information is also included in the search point information.

Route information is information about a route from a starting point to a destination. Here, the route may be composed of one means of transportation or may be composed of a combination of a plurality of means of transportation. For example, it may be a car route consisting of only automobiles, or a route combining walking and public transportation. In addition, the route information is composed of information indicating a point passing from the departure point to the destination and a road or a route.

As a first example of route information, it is composed of a link sequence and a node sequence such as a combination of link data indicating a searched route. The route information may include location information of the route (for example, a sequence of shape points), image data indicating the route (for example, a polyline, etc.), and the like. Further, the route information may include information such as the latitude / longitude altitude of the departure place, the destination, and the waypoint. Further, the route information may include a route search condition such as a departure time and an arrival time, a route distance, a required time, a means of transportation, and the like.

Further, as a second example of the route information, as shown in FIG. 3, the point information (for example, the departure point, the destination, the waypoint) and the passing section information (for example, the road in the route, the route in the route) It is composed of scheduled arrival date and time information (for example, scheduled departure date and time, scheduled arrival date and time, scheduled passage date and time).

Here, the point information is information about a point 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 about the waypoints may be the information of the waypoints set in the route search request information, or the boarding station, getting off station, getting on / off station, intersection, IC (interchange) calculated as a result of the route search. Information on passing points such as JCT (junction) and station platforms may be used.

Further, the passing section information is information about the passing section included in the route information. That is, it is information about a section through which a public transportation line such as a railroad line or a bus line or a road such as a general road or an expressway passes, and is information such as a line name, a road name, and a link ID.

The estimated 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 point, 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 passing section in the route information. Here, the date and time information may be a date and time such as "2013/11/11 19:55" or a period such as "2013/1/11 19:55 to 2013/1/11 20:15". You may.

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 contains the route search result ID, point information (departure point, destination, waypoint) as search point information, transit section information, and scheduled arrival date and time information (departure date and time of departure point, destination). The estimated arrival date and time, the estimated passage date and time of the waypoint and the passing 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 scheduled arrival date and time: "2013/1/11 20:20". , Transit point: GEM station, transit point 1 scheduled passage date and time: "2013/1/11 19:55", transit point 2: OSA station, transit point 2 scheduled passage date and time: "2013/1/11 20:15" , Section 1: H line, Scheduled passage date and time of section 1: Stored in association with "2013/1/11 19:55 to 2013/1/11 20:15". Here, the waypoints may be a plurality of points as shown in the figure. Further, here, the section may be one section or a plurality of sections as shown in the figure.

The control unit 204 has a control program such as an OS (Operating System), a program that defines various processing procedures, and an internal memory for storing required data. Then, the control unit 204 performs information processing for executing various processes by these programs and the like. The control unit 204 functionally 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 point information included in the acquired search request and stores it in the pre-search log database 202d. The search execution date and time may be included in the search request, or may be information stored on the server side as the date and time when the search request acquisition unit 204a acquired the search request. As described above, each time the search request acquisition unit 204a acquires a search request, only the pre-search request log may be extracted and stored in the pre-search log database one by one, or all search requests may be temporarily stored. It may be stored in the whole search log database (not shown), and only the pre-search log may be extracted from the search log group stored in the whole search log database to separately create the pre-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 has a route search condition from a departure point to a destination that satisfies the route search condition based on the route search condition included in the search request. It is a route information acquisition means for acquiring the route information which is the route of.

The route information acquisition unit 204b searches for a route from the departure point to the destination that satisfies the route search condition including at least the departure point 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 condition stored in the storage unit 202 in advance. The route information searched by the route information acquisition unit 204b is composed of information indicating a point passing from the starting point to the destination and a road or a route. For example, it may be configured to consist of a combination of a link and a node, or as shown in FIG. 3, the point information, the section information, and the arrival date / time information (scheduled departure date / time, scheduled arrival date / time, waypoint 1 scheduled passage date / time, section). It may be configured to consist of a combination with (1 scheduled passage date and time, etc.).

Further, 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 the route search history from the departure point to the destination that satisfies the route search condition. You may.

The analysis index receiving unit 204c is an analysis index receiving means that acquires an analysis index set by the user via the analysis index setting unit 102b of the terminal device 100 and accepts the designation. For example, a specific point, section, date and time, time zone, day of the week, etc. can be specified as an analysis index, and the point accepts designation by information such as POI name, latitude / longitude, address, and telephone number. In addition, the section accepts designation by information such as route name, road name, and link ID. In addition, the date and time can be specified by information such as date, time, and period. In addition, time zone, day of the week, day type (weekdays / weekends), moving object attributes (types of transportation such as railway lines, automobiles, and bicycles), user attributes (age, gender, age, etc.), weather information, etc. in advance 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. It may be a combination of one or more of these analysis indexes. In this 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, the 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 the current date and time, a predetermined date and time, or a period, and is information that defines a period such as one week before or after the current date and time. May be good.

The extraction unit 204d is an extraction means for extracting the target pre-search log corresponding to the condition as the analysis index received by the analysis index reception unit 204c from the pre-search database 202b.
For example, when the analysis index received by the analysis index reception unit 204c in FIG. 3 is "S tower", the search result ID 101 including "S tower" in the search point information and ID 103 are used as the preliminary search log to be analyzed. Extract. Further, the search request ID 001 that includes "S Tower" in the search point information by referring to the pre-search request log table may also be extracted. On the other hand, when the analysis index is "2013/11/11 12: 00-24: 00", it is extracted assuming that the search result ID 101 whose scheduled date and time is "2013/11/11 19:45" satisfies the condition. Be the target. Here, the extraction target may be an exact match with the analysis index, or may have a predetermined range. In particular, when the number of target pre-search logs is less than a predetermined number when the extraction conditions are exactly the same, the pre-search logs with similar conditions may be extracted. In the case of the above example, the pre-search log of ID 103 may also be extracted.

The analysis information generation unit 204e generates analysis information for generating analysis information of the analysis point and / or the analysis section based on the target advance 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 the congestion prediction information is generated as an example of the analysis information generation in the present embodiment, the index of the degree of congestion can be calculated based on the number of prior search logs at the congestion prediction date and time of the congestion prediction point or the congestion prediction section. can. Furthermore, the index is calculated based on the comparison with the number of target pre-search logs held in advance and the information such as the permissible number of people and the permissible number of vehicles in the congestion prediction point or the congestion prediction section. May be 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 based on the numerical value (for example, congestion rate: high, congestion rate: medium).

Further, by comparing with the POI data stored in the POI database 202c, more accurate analysis is possible. Specifically, if an event is scheduled to be held around 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 movement demand will occur compared to normal times. , The value of the degree of congestion can be increased by adding a predetermined number to the number of target pre-search logs.
The POI data can also be used to estimate the cause of the increase in mobile demand. For example, if the occurrence of sudden movement demand can be detected because the number of target pre-search logs at the analysis target point is larger than usual, and an event is held around the analysis target point from the POI database, the sudden movement It can be estimated that the demand is due to the event. Such an analysis is particularly effective for estimating the cause of traffic congestion in the past.

Further, the analysis information may be generated after calculating the expected increase number of the search log at the analysis date and time 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 advance search log.

Further, the output information generation unit 204f is a means for generating output information which 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 graphed along the time series. It is placed in. Further, the output information may be information for displaying a map including a reference point or the current position based on the map information stored in the map information database 202a, or may be searched or selected from the POI information database 202c. It may be information for displaying the POI information. Further, the output information may be information for displaying the route information acquired by the route information acquisition unit 204b.

Further, the output information generation unit 204f may 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 accepting search condition settings and transmitting a search request based on the accepted search conditions 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 the user. For example, information processing devices such as desktop or notebook personal computers, mobile terminal devices such as mobile phones, smartphones, PHS and PDA, and navigation terminals (for example, car navigation devices) that provide travel route guidance and the like. Here, the information processing device 100 may be equipped with an Internet browser or the like, or may be equipped with a route guidance application, a transfer guidance application, an information retrieval application, or the like.

As shown in FIG. 1, the terminal device 100 of the present embodiment is roughly 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 unit 114 and an output unit 116) are provided.

Here, the control unit 102 is a control means that performs various processes. Further, 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 is a communication between the terminal device 100 and the network 300. It has a function to control. 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. Further, 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 a GPS function may receive a signal from a position transmitting device 500 such as a GPS satellite to acquire the position information.

Further, the input unit 114 includes a voice input means (for example, a microphone or the like) for inputting voice. Further, the input unit 114 may be provided with an operation input means (for example, a button, a switch, etc.) for inputting or the like by pressing the button. Further, the output unit 116 is a display means (for example, a display and a monitor composed of a liquid crystal or an organic EL or the like) for displaying a display screen of an application or the like. Further, the output unit 116 may be an audio output means (for example, a speaker or the like) that outputs audio data as audio. Here, the display means of the output unit 116 may be a touch panel or the like and may 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 that defines various processing procedures, and an internal memory for storing required data. Then, the control unit 102 performs information processing for executing various processes by these programs and the like. The control unit 102 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 means for setting information acquisition conditions. The search condition setting unit 102a causes the user to input the search condition 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. In addition to route search, information search types include facility information search, timetable search, and traffic information search.

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

The analysis index setting unit 102b is a 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 can be set, and the point accepts the setting with information such as the name of POI, latitude / longitude altitude, address, and telephone number. In addition, the section accepts settings based on information such as route names and road names. In addition, the date and time accepts settings based on information such as the date, time, and period. In addition, it may be possible to set one or a combination of all kinds of information such as time zone, day of the week, mobile type, 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 reception unit 204c of the information processing server 200. Receives.

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 completes the description of an example of the configuration of the information processing system according to the present embodiment.

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

FIG. 4 is a flowchart showing an example of processing of the information processing system according to the present 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 the information regarding 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 process, the analysis information generation unit 204e has congestion prediction information based on the advance search log stored in the advance search log database 202d and the information on the analysis index received by the analysis index reception unit 204c. To generate.

An example of a specific process will be described with reference to FIG. The extraction unit 204d extracts a pre-search log including information indicating a congestion prediction point and information indicating a congestion prediction date and time in the information regarding the analysis index from the pre-search log database 202d. For example, when performing congestion prediction, if the POI name "S Tower" is included as an index indicating the prediction point and the date "2013/1/11" is included as an index indicating the congestion prediction date and time, the pre-search log extraction unit The 204d extracts the route search request ID: 001, which is a preliminary search log including "S Tower" in the search point information and "2013/1/11" 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 points by one based on the extracted pre-search logs. In this way, the number of corresponding pre-search logs in the pre-search log database 202d is counted to generate congestion prediction information.

In the above description, when the POI name is set as the information indicating the congestion prediction point, an example of extracting the preliminary search log in which "S tower" is included in the search point information has been described. Then, not limited to this, information such as an address and a telephone number corresponding to the POI name "S Tower" is specified by referring to the POI information database 202c, and a preliminary search log including the specified information is extracted. May be good.
Further, the advance search log whose date and time setting condition is 2013.1.11 and which can be estimated to pass around the S tower from the section information may also be extracted.

As a second example of the congestion prediction information generation process, the analysis information generation unit 204e refers to the pre-search result table stored in the pre-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 pre-search result log table stored in the pre-search log database 202d in the second example of route information. The extraction unit 204d extracts a pre-search log including information indicating a congestion prediction interval and information indicating a congestion prediction date and time in the analysis index from the pre-search log database 202d. For example, when the congestion prediction target information includes "Y line" as information indicating the congestion prediction interval and "2013/1/12" as information indicating the congestion prediction date and time, the advance search log extraction unit 204d may use the advance search log extraction unit 204d. The pre-search log of the route search result ID: 002, which is the route search result log including the "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 interval by one based on the extracted pre-search logs. In this way, the number of corresponding pre-search logs in the pre-search log database 202d is counted to generate congestion prediction information.

When the pre-search log database 202d is configured in the form of the first example of the route information (the form composed of the link column and the node column), the information or section indicating the point among the information related to the analysis index is displayed. Using information such as the name included in the indicated information as a key, the latitude / longitude altitude information of the POI corresponding to the point or section, the link ID, or the node ID is searched from the network information database 202b or the POI information database 202c, and the searched POI is searched. The pre-search log including the latitude / longitude altitude, the link ID, and the node ID of the above may be extracted from the pre-search log database 202d, and the number of the pre-search logs may be counted to generate the analysis information.

Returning to FIG. 4, the output information generation unit 204f of the information processing server 200 then 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 the one in which the analysis information for each time of the point or section is arranged in a graph shape along the 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 an example of the processing of the information processing system in the present embodiment.

[Other Examples]

In the above-described embodiment, an example of the form of 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 (broken line) of the T baseball stadium, which is a tourist spot, are displayed in the same graph. By doing so, it becomes easy to compare the congestion prediction information between each tourist spot at the user's desired date and time, and the user can easily select a more vacant tourist spot or a more popular tourist spot. It will be possible.

Further, the output information may be output including a steady value together with the analysis information in the analysis index specified by the user. 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 estimated congestion date and time. Then, when the estimated congestion date and time is more crowded than usual, it becomes possible to make a decision such as canceling the movement schedule. Here, the average congestion prediction information is an average value of congestion prediction information on a date and time other than the congestion prediction date and time. Further, the average congestion prediction information may be an average value of congestion prediction information in a predetermined period, or may be an average value of congestion prediction information of a date and time having the same attributes as the congestion prediction date and time in a predetermined period (for example, day of the week, holiday, weather). good. In the above example, by outputting the average congestion prediction information, it is easy to compare the congestion prediction information of the congestion prediction date and time with the usual congestion situation, but instead of the average congestion prediction information, the congestion prediction point You may use the average congestion record information which is the actual value of the past congestion situation of.

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

Although the embodiments of the present invention have been described above, the present invention has various different embodiments within the scope of the technical idea described in the claims, in addition to the above-described embodiments. It may be implemented. Further, among the processes described in the embodiments, all or a part of the processes described as being automatically performed can be manually performed, or the processes described as being manually performed can be performed. All or part of it can be done automatically by a known method.

In addition, the processing procedure, control procedure, specific name, information including parameters such as registration data and search conditions of each processing, screen examples, and database configuration shown in the above documents and drawings are not specified unless otherwise specified. Can be changed arbitrarily.

Further, with respect to the information processing system, each component shown in the figure is a functional concept and does not necessarily have to be physically configured as shown in the figure. Further, the specific form of distribution / integration of the device is not limited to the one shown in the drawing, and all or a part thereof may be functionally or physically in an arbitrary unit according to various additions or functional loads. It can be configured in a distributed and integrated manner. That is, the above-described embodiments may be arbitrarily combined and implemented, 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 Pre-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 transmitter

Claims (8)

A pre-search log storage means that stores a pre-route search log that includes search point information and date / time setting information after the search execution date / time among the route search logs from the departure point to the destination, which are acquired from a plurality of user terminals.
Analytical index receiving means for accepting analytical indicators and
An extraction means for extracting a target advance route search log from the advance search log storage means based on the analysis index, and an extraction means.
Congestion prediction information generation means that performs congestion prediction analysis based on the target prior route search log and generates congestion prediction information of analysis points and / or analysis sections.
An information output means for outputting information based on the congestion prediction information and the average congestion information, and
An information processing system characterized by being equipped with. The information processing system according to claim 1, wherein the average congestion information is average congestion prediction information or average congestion actual information. The second aspect of claim 2, wherein the average congestion prediction information is an average value of congestion prediction information in a predetermined period or an average value of congestion prediction information on a date and time having the same attributes as the congestion prediction date and time in a predetermined period. Information processing system. The information processing system according to any one of claims 1 to 3, wherein the information output means displays the congestion prediction information and the average congestion information in a comparable manner. Claims 1 to the analysis index are any one or a combination of information on a date and time, a time zone, a day of the week, a point, a road, a route section, a user attribute, and a moving object attribute. The information processing system according to any one of 4. A pre-search log storage means that stores a pre-route search log that includes search point information and date / time setting information after the search execution date / time among the route search logs from the departure point to the destination, which are acquired from a plurality of user terminals.
Analytical index receiving means for accepting analytical indicators and
An extraction means for extracting a target advance route search log from the advance search log storage means based on the analysis index, and an extraction means.
Congestion prediction information generation means that performs congestion prediction analysis based on the target prior route search log and generates congestion prediction information of analysis points and / or analysis sections.
An information processing server characterized by being equipped with. Equipped with a pre-search log storage means that stores the pre-route search log that is acquired from multiple user terminals and includes the search point information and the date and time setting information after the search execution date and time among the route search logs from the departure point to the destination. It is an information processing method executed in the information processing system.
The analysis index reception step that accepts the analysis index, and the analysis index reception step
An extraction step of extracting the target pre-route search log from the pre-search log storage means based on the analysis index, and
A congestion prediction information generation step that performs congestion prediction analysis based on the target prior route search log and generates congestion prediction information of the analysis point and / or the analysis section.
An information processing method characterized by including. Equipped with a pre-search log storage means that stores a pre-route search log that is acquired from multiple user terminals and includes search point information and date / time setting information after the search execution date / time among the route search logs from the departure point to the destination. An information processing program that is executed in an information processing system and is applied to a computer.
The analysis index reception step that accepts the analysis index, and the analysis index reception step
An extraction step of extracting the target pre-route search log from the pre-search log storage means based on the analysis index, and
A congestion prediction information generation step that performs congestion prediction analysis based on the target prior route search log and generates congestion prediction information of the analysis point and / or the analysis section.
Information processing program to execute.

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