JP2013206406A - Traffic simulation method, traffic simulation device and traffic simulation program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain a valid simulation result.SOLUTION: A traffic simulation device 10 updates recognition link information for which a recognition link to be recognized by a simulated driver is made to correspond in road network information for each simulated driver using a position of a vehicle in which the present device is to be simulated and the road network information. When the recognition link information is updated, the traffic simulation device 10 updates virtual link information for which a virtual link virtually connecting a recognition boundary node and a destination node is made to correspond for each simulated driver. The traffic simulation device 10 generates route candidates from the position of the vehicle to the destination node using the recognition link information and the virtual link information. The traffic simulation device 10 calculates a cost of the recognition link and the virtual link forming the candidates of a route, uses the cost to select at least one route of the route candidates, and updates the position of each vehicle according to the selected route.

Description

  The present invention relates to a traffic simulation method, a traffic simulation device, and a traffic simulation program.

  In order to perform various evaluations related to traffic, traffic simulators that simulate traffic conditions in a virtual space of a computer are known. There are macro traffic simulators that simulate traffic flows as fluids and micro traffic simulators that simulate the behavior of each vehicle. Among these, the micro traffic simulator includes a route selection model that simulates the behavior of the driver selecting a route in order to simulate the behavior of each vehicle.

  An example of such a route selection model is Wardrop's first principle: “Each driver selects the route with the shortest travel time for him. As a result, the time required for each route used is the same, The minimum cost route selection model that selects the route with the lowest cost according to “less than or equal to the required time of the route that has not been performed” is given.

  Another example is a stochastic path selection model to which a discrete selection model represented by a logit model is applied. Such a probabilistic route selection model is based on a stochastic equilibrium distribution model that “information on each route recognized by the driver is inaccurate and includes an error that varies stochastically”. In the stochastic route selection model, a route is stochastically selected from a plurality of route options according to each route cost. Here, as an example of the route cost, a required time, a travel distance, or a value obtained by weighting them is used. Further, the logit model has a dispersion parameter θ that determines the degree of error. The larger the dispersion parameter θ, the closer to the route selection under complete information, and the smaller the θ, the closer to the random route selection.

JP 2000-193470 A

  However, the above-described conventional technique has a problem in that an appropriate simulation result cannot be obtained as described below.

  That is, in the minimum cost route selection model, the vehicle always moves along the shortest route. However, in reality, not all drivers know the route to the destination completely. For this reason, the above route selection model cannot reproduce the behavior of a vehicle that selects an unreasonable route such as getting lost or making a detour. As a result, there is a high possibility that the vehicle will reach its destination in a shorter time than reality and that the number of vehicles simultaneously existing in the virtual world will be underestimated. Therefore, a reasonable simulation result cannot be obtained with the minimum cost route selection model.

  On the other hand, in the above stochastic route selection model, it is conceivable that all routes to the destination are included in the options, and that the random parameter selection is made closer by decreasing the dispersion parameter θ. In large road networks, it is virtually impossible to include every route in the options. Also, the closer to the random route selection, the more expensive the route will be selected, but there is a possibility that route selection that is extremely detoured will be performed by repeating the selection. As a result, it takes a longer time than reality to reach the destination, and there is a high possibility that the number of vehicles simultaneously existing in the virtual world will be overestimated. Therefore, even if the above stochastic route selection model is installed in a micro traffic simulator, an appropriate simulation result cannot be obtained.

  The disclosed technology has been made in view of the above, and an object thereof is to provide a traffic simulation method, a traffic simulation apparatus, and a traffic simulation program capable of obtaining an appropriate simulation result.

  In the traffic simulation method disclosed in the present application, the computer uses a vehicle position simulated by the computer and road network information including nodes and links for each simulated driver who drives the vehicle. In the road network information, the process of updating the cognitive link information associated with the cognitive link recognized by the simulated driver is executed. Further, when the cognitive link information is updated, the computer is a cognitive boundary located at a boundary with a node that is not recognized by the simulated driver among nodes that form the cognitive link for each simulated driver. A process of updating the virtual link information associated with the virtual link that virtually connects the node and the destination node is executed. Further, the computer executes a process of generating a route candidate from the position of the vehicle to the node as the destination using the cognitive link information and the virtual link information. Further, the computer executes a process of calculating the cost of the cognitive link and the cost of the virtual link forming the route candidate. Further, the computer executes a process of selecting at least one route from the route candidates using the cost of the cognitive link and the cost of the virtual link. Further, the computer executes a process of updating the position of each vehicle according to the route.

  According to one aspect of the traffic simulation method disclosed in the present application, there is an effect that an appropriate simulation result can be obtained.

FIG. 1 is a block diagram illustrating a functional configuration of the traffic simulation apparatus according to the first embodiment. FIG. 2 is a diagram illustrating a configuration example of the vehicle state information. FIG. 3 is a diagram illustrating a configuration example of travel history information. FIG. 4 is a diagram illustrating a configuration example of node information. FIG. 5 is a diagram illustrating a configuration example of link information. FIG. 6 is a diagram illustrating a configuration example of the recognition link information. FIG. 7 is a diagram illustrating a configuration example of virtual link information. FIG. 8 is a diagram for explaining a method for updating road recognition information. FIG. 9 is a diagram for explaining a method for updating road recognition information. FIG. 10 is a diagram illustrating an example of the behavior of route selection. FIG. 11 is a diagram illustrating an example of the behavior of route selection. FIG. 12 is a diagram illustrating an example of the behavior of route selection. FIG. 13 is a diagram illustrating an example of the behavior of route selection. FIG. 14 is a diagram illustrating an example of the behavior of route selection. FIG. 15 is a diagram illustrating an example of the behavior of route selection. FIG. 16 is a flowchart (1) illustrating the procedure of the traffic simulation process according to the first embodiment. FIG. 17 is a flowchart (2) illustrating the procedure of the traffic simulation process according to the first embodiment. FIG. 18 is a flowchart illustrating a procedure of road recognition information update processing according to the first embodiment. FIG. 19 is a schematic diagram illustrating an example of a computer that executes a traffic simulation program according to the first and second embodiments.

  Hereinafter, embodiments of a traffic simulation method, a traffic simulation apparatus, and a traffic simulation program disclosed in the present application will be described in detail with reference to the drawings. Note that this embodiment does not limit the disclosed technology. Each embodiment can be appropriately combined within a range in which processing contents are not contradictory.

[Configuration of traffic simulation equipment]
First, the functional configuration of the traffic simulation apparatus according to the present embodiment will be described. FIG. 1 is a block diagram illustrating a functional configuration of the traffic simulation apparatus according to the first embodiment. The traffic simulation apparatus 10 shown in FIG. 1 is equipped with a micro traffic simulator that simulates the behavior of each vehicle in a virtual space, and is particularly unreasonable such as getting lost or making a detour. Reproduce the behavior of the vehicle including the selection of a simple route.

  As shown in FIG. 1, the traffic simulation device 10 includes an input unit 11, a display unit 12, a storage unit 13, and a control unit 15. The traffic simulation apparatus 10 includes various functional units included in a known computer other than the functional units illustrated in FIG. 1, for example, functional units such as a communication interface for performing communication with an external device. It doesn't matter.

  The input unit 11 is an input device that receives various types of information, for example, an instruction input such as a traffic simulation start instruction or a result output instruction. As one aspect of the input unit 11, a keyboard, a mouse, or the like can be applied. The display unit 12 is a display device that displays various types of information, such as simulation results. As an aspect of the display unit 12, a monitor, a display, a touch panel, or the like can be applied. The input unit 11 and the display unit 12 can also provide a pointing device function and a touch panel function by cooperating with each other.

  The storage unit 13 is a storage device that stores various programs such as an OS (Operating System) executed by the control unit 15 and a traffic simulation program. As one aspect of the storage unit 13, a storage device such as a semiconductor memory element such as a flash memory, a hard disk, or an optical disk is given. The storage unit 13 is not limited to the type of storage device described above, and may be a RAM (Random Access Memory) or a ROM (Read Only Memory).

  As an example of data used in the program executed by the control unit 15, the storage unit 13 includes vehicle state information 13a, travel history information 13b, road network information 13c, cognitive link information 13d, and virtual link information 13e. Remember. In addition to the above information, various electronic data useful for traffic simulation, for example, origin and destination (OD: Origin Destination) of automobiles are obtained by questionnaire survey or traffic volume survey of vehicles by area and time zone. Data such as the number of units can also be stored.

  The vehicle state information 13a is various data relating to the state of the vehicle existing in the virtual space. As an example, in the vehicle state information 13a, a record relating to the vehicle is added when the vehicle is generated by a vehicle generation unit 17a described later. The vehicle state information 13a starts with the position of the vehicle as time progresses in the virtual space, and information such as speed is updated by a position updating unit 17g described later. As another example, the vehicle state information 13a is referred to by a road recognition information update unit 17b described later in order to determine whether or not a vehicle generated in the virtual space has passed a node. As a further example, in the vehicle state information 13a, when a vehicle reproduced in the virtual space reaches a destination node, a record relating to the vehicle is deleted by the vehicle generation unit 17a described later. As a result, the vehicle is deleted from the virtual space.

  As an aspect of the vehicle state information 13a, data in which items such as a vehicle ID (identification), position coordinates, and speed are associated can be employed. The “vehicle ID” here refers to identification information for identifying a vehicle. “Position coordinates” refers to information related to the position where the vehicle exists in the virtual space of the computer, and is expressed by latitude and longitude, for example. The “speed” refers to the speed at which the vehicle is traveling.

  FIG. 2 is a diagram illustrating a configuration example of the vehicle state information 13a. In the example of FIG. 2, a vehicle having a vehicle ID “0001” exists at coordinates (x1, y1) including latitude and longitude, and is traveling at a speed of 6 m / s per second. In addition, a vehicle having a vehicle ID “0002” exists at the coordinates (x2, y2) and is traveling at a speed of 11 m / s per second. In the example of FIG. 2, the case where the position coordinates and the speed are associated with each vehicle ID is illustrated, but other information, for example, information on a vehicle type such as a large size, a medium size, and a small size can be further associated.

  The travel history information 13b is various data relating to the travel history of the vehicle simulated by the simulation execution unit 17 described later. As an example, the travel history information 13b is referred to by a vehicle generation unit 17a described later when generating a vehicle in a virtual space. As another example, in the travel history information 13b, when a vehicle generated in the virtual space passes a node, a travel history related to a link including the node is additionally registered by a travel history update unit 17c described later. As a further example, the travel history information 13b is referred to by an evaluation unit 17h described later in order to aggregate traffic according to various points such as intersections, roads, areas, and time zones. Note that the travel history information 13b includes not only the vehicle reproduced in the virtual space but also information related to the vehicle deleted from the virtual space.

  As one aspect of the travel history information 13b, data associated with items such as date, time, link, passage time, and average speed can be employed. FIG. 3 is a diagram illustrating a configuration example of the travel history information 13b. FIG. 3 shows a travel history related to the vehicle with the vehicle ID “0001” shown in FIG. In the example of the first record shown in FIG. 3, it is shown that the vehicle with the vehicle ID “0001” has passed through the node B of the link formed by the node A and the node B at 13:10 on July 7, 2011. Show. Furthermore, the example of the first record shown in FIG. 3 indicates that the vehicle with the vehicle ID “0001” traveled from node A to node B at an average speed of 30 km / h and took 5 minutes to pass. Although the travel history of the vehicle ID “0001” is illustrated here, it is assumed that the travel history of other vehicles is also stored.

  The road network information 13c is data in which a road network is defined by a combination of nodes and links. The term “node” here refers to intersections and nodal points on the road network expression, road structural change points, intersections with the administrative community, and the like. The “link” refers to a line segment connecting nodes on the road network expression, that is, a section of the road. As an example, the road network information 13c is referred to by a road recognition information update unit 17b described later in order to determine whether or not a vehicle generated in the virtual space has passed a node. As another example, the road network information 13c is referred to by a route candidate generation unit 17d described later in order to generate a route candidate until the vehicle reaches the destination. The road network information 13c includes node information defined for nodes and link information defined for links.

  FIG. 4 is a diagram illustrating a configuration example of node information. FIG. 5 is a diagram illustrating a configuration example of link information. In the example of FIG. 4, the intersection of the node A exists at the latitude “36.0476” and the longitude “140.1554”, and the intersection of the node B exists at the latitude “36.0475” and the longitude “140.1600”. Further, in the example of FIG. 5, the length of the link formed by the node A and the node B is 400 m, the number of lanes is two, and the regulation speed is 40 km / h. Furthermore, in the example of FIG. 5, the length of the link formed by the node B and the node C is 150 m, the number of lanes is four, and the regulation speed is 50 km / h. In the example of FIG. 4, the latitude and longitude are exemplified as the information regarding the node. However, other information regarding the signal, for example, the period at which the signal type is switched or the law at the intersection, such as prohibition of turning or prohibition of traveling outside the specified direction. Etc. can also be stored together. Also in the example of FIG. 5, it is also possible to store laws and regulations on the road, such as prohibition of lane change, prohibition of stopping, prohibition of parking, and the like.

  The recognition link information 13d is various information related to the recognition link. The “recognition link” here refers to a link recognized by a simulated driver who drives a vehicle simulated by a computer. As an example, the recognition link information 13d is generated from the travel history information 13b by a vehicle generation unit 17a described later when generating a vehicle in a virtual space. As another example, the recognition link information 13d is updated by a road recognition information update unit 17b described later when a vehicle generated in the virtual space passes a node. As a further example, when a route candidate until the vehicle reaches the destination is generated, it is referred to by a route candidate generation unit 17d described later.

  As one aspect of the cognitive link information 13d, data in which items such as node 1, node 2, travel distance, and travel time are associated can be employed. Here, “node 1” and “node 2” refer to node identification information that identifies a combination of nodes forming a link. FIG. 6 is a diagram illustrating a configuration example of the recognition link information 13d. FIG. 6 shows a recognition link related to the simulated driver of the vehicle ID “0001” shown in FIG. The example of the first record shown in FIG. 6 represents that the simulated driver has traveled the link formed by node A and node B. Further, the example of the first record shown in FIG. 6 indicates that the travel distance when traveling on the link formed by the nodes A and B is 400 m and the travel time is 60 seconds. These travel distance and travel time are actually measured values by simulation, and may be the latest values or statistical values such as averages. In the example of FIG. 6, the cognitive link related to the simulated driver with the vehicle ID “0001” is illustrated, but actually, the cognitive link of each simulated driver registered in the vehicle state information 13a is registered. To do.

  In the following, a case in which a link that the simulated driver has actually traveled, that is, a link registered as the travel history information 13b is used as a cognitive link is illustrated, but the present invention is not limited to this example. For example, the disclosed apparatus can use a link indicated by a sign on a link traveled by a simulated driver as a recognition link, or recognize a link acquired by a car navigation system used by the simulated driver. It can also be used as a link.

  The virtual link information 13e is various information related to the virtual link. The "virtual link" here refers to a link that virtually connects a cognitive boundary node that is located at the boundary of a cognitive node that forms a cognitive link with a node that is not recognized by the simulated driver and a destination node. Point to. Hereinafter, a node that is a destination of a vehicle generated in a virtual space may be referred to as a “destination node”. The existence of such a virtual link means that it is assumed that there is some link that reaches the destination in the direction from the cognitive boundary node to the destination node. Thus, since the virtual link is an imaginary link assumed by the simulated driver, it does not necessarily correspond to the link data of the road network information 13c. For this reason, the simulated driver recognizes the link from the cognitive boundary node to the destination node for the first time when it reaches the cognitive boundary node. In some cases, there is no link in the direction, and a turn, a so-called U-turn or detour, is forced.

  As an example, when the vehicle generated in the virtual space passes through the cognitive boundary node, the virtual link information 13e is deleted by a road cognitive information update unit 17b, which will be described later, with respect to the virtual link including the cognitive boundary node. . As another example, in the virtual link information 13e, when the cognitive link information 13d is updated, a record relating to a virtual link that connects the cognitive boundary node added as the newly added cognitive node and the destination node will be described later. It is registered by the road recognition information update unit 17b.

  As one aspect of the virtual link information 13e, data in which items such as a recognition boundary node, a destination node, and a straight line distance are associated can be employed. FIG. 7 is a diagram illustrating a configuration example of the virtual link information 13e. FIG. 7 illustrates a virtual link when the destination node of the simulated driver with the vehicle ID “0001” illustrated in FIG. The example of the first record shown in FIG. 7 indicates that the simulated driver assumes a 1500 m straight road from the recognition boundary node L to the destination node Z. Furthermore, the example of the second record shown in FIG. 7 indicates that the simulated driver assumes a 600 m straight road from the recognition boundary node M toward the destination node Z. Furthermore, the example of the third record shown in FIG. 7 represents that the simulated driver assumes an 800 m straight road from the recognition boundary node N to the destination node Z. In the example of FIG. 7, the virtual link related to the simulated driver with the vehicle ID “0001” is illustrated, but actually, the virtual link of each simulated driver registered in the vehicle state information 13a is registered. To do.

  In addition, although the case where the virtual link is expressed by the recognition boundary node and the destination node is illustrated here, the destination node is not necessarily included in the virtual link. For example, the disclosed apparatus can also express a virtual link by associating a node set in the direction and distance where the destination node is assumed to exist by the simulated driver from the cognitive boundary node with the cognitive boundary node. In the following description, the recognition link information 13d and the virtual link information 13e may be collectively referred to as “road recognition information”.

  The control unit 15 has an internal memory for storing programs defining various processing procedures and control data, and executes various processes using these. As shown in FIG. 1, the control unit 15 includes a simulation execution unit 17.

  The simulation execution unit 17 is a processing unit that executes a traffic simulation program that is a micro traffic simulator. As shown in FIG. 1, the simulation execution unit 17 includes a vehicle generation unit 17a, a road recognition information update unit 17b, a travel history update unit 17c, a route candidate generation unit 17d, a cost calculation unit 17e, and a route selection unit. 17f, a position update unit 17g, and an evaluation unit 17g. In the following, it is assumed that a periodic scanning method is employed in which time progress is managed so as to update the state of the vehicle at regular time intervals Δt.

  Among these, the vehicle generation part 17a is a process part which generates a vehicle on virtual space. As one aspect, the vehicle generation unit 17a determines whether or not to generate a vehicle in the virtual space based on the vehicle occurrence frequency set for each area every time the simulation time is updated. The occurrence frequency of the vehicle is set based on, for example, the traffic volume by area and time zone obtained by the start / end point survey of the automobile.

  Here, when there is an area where the number of vehicles is insufficient, the vehicle generation unit 17a newly generates a record of the vehicle state information 13a having the nodes included in the area as position coordinates, and then generates the new Are additionally registered in the vehicle state information 13a. At this time, the vehicle generation part 17a can employ | adopt arbitrary nodes as a node additionally registered to the vehicle state information 13a. For example, the vehicle generation unit 17a can adopt a node where the starting point obtained by the starting and ending point investigation of the automobile exists, a node having a famous landmark, a node selected at random, and the like. As the vehicle ID of the newly generated vehicle, an unregistered vehicle ID is selected as the vehicle state information 13a among the vehicle IDs stored as the travel history information 13b.

  Furthermore, when the vehicle generation unit 17a additionally registers a new record in the vehicle state information 13a, the vehicle generation unit 17a initially sets the destination, the recognition link, and the virtual link of the vehicle. For example, the vehicle generation unit 17a initializes, as a destination node, a node in which an end point obtained by an automobile start / end point survey exists, a node having a famous landmark, a node selected at random, or the like. Then, the vehicle generator 17a reads the travel history information 13b having the vehicle ID additionally registered in the vehicle state information 13a. Subsequently, the vehicle generation unit 17a uses the link included in the travel history information 13b read out earlier as the recognition link, and generates the recognition link information using the transit time and the average speed included in each record of the travel history information 13b. To do. That is, the vehicle generator 17a calculates the travel distance from the passage time and the average speed. In addition, the vehicle generation unit 17a registers, in the storage unit 13, the recognition link information 13d in which the travel distance and the passage time corresponding to the travel time calculated previously are associated with each recognition link. And the vehicle generation part 17a produces | generates the virtual link information 13e by matching a recognition boundary node and a destination node among the recognition nodes contained in the recognition link information 13d produced | generated previously. In addition, the vehicle generation unit 17 a registers the previously generated virtual link information 13 e in the storage unit 13.

  In addition, although the case where all the links included in the travel history information 13b are recognized links is illustrated here, even if the link is included in the travel history information 13b, the travel date and time is old and the frequency of the recognition link is low. By excluding it from the setting, it is possible to simulate the driver's forgetting. In addition, the residence information may be stored in the storage unit for each simulated driver, and the surrounding link in which the vehicle generation unit 17a is within a predetermined distance from the simulated driver's residential area may be set as a cognitive link.

  The road recognition information update unit 17b is a processing unit that updates road recognition information. As one aspect, when the simulation time is updated, the road recognition information update unit 17b selects one record from the vehicle state information 13a stored in the storage unit 13. And the road recognition information update part 17b specifies the link where a vehicle drive | works from the position coordinate of vehicle ID contained in the said record, and the road network information 13c. Thereby, the road recognition information updating unit 17b determines whether or not the vehicle having the vehicle ID has passed the node. At this time, when the vehicle passes through the node, the road recognition information update unit 17b further determines whether or not the passing node through which the vehicle has passed is a destination node. The road recognition information update unit 17b does not update the road recognition information when the passing node is the destination node.

  Here, when the passing node is not the destination node, the road recognition information updating unit 17b refers to the virtual link information 13e and determines whether or not the passing node is a recognition boundary node that forms a virtual link. . At this time, if the passing node is a cognitive boundary node, the cognitive boundary node is updated to a simple cognitive node by the current pass. Therefore, the road recognition information update unit 17b deletes the record related to the virtual link including the passage node among the virtual links stored in the virtual link information 13e. Note that if the passing node is not a cognitive boundary node, the cognitive boundary node is not updated, so the record is not deleted.

  Thereafter, the road recognition information update unit 17b selects one connection link from among the connection links connected to the passing node. Then, the road recognition information update unit 17b refers to the recognition link information 13d and determines whether or not the previously selected connection link is a recognition link. At this time, when the connection link is not a recognition link, the road recognition information update unit 17b adds the connection link to the recognition link information 13d as a recognition link. In addition, when the other node that is not a passing node is not a recognition node, the road recognition information update unit 17b sets the other node as a recognition boundary node and sets a virtual link from the recognition boundary node to the destination. Add to the virtual link information 13e. The road recognition information update unit 17b does not update the recognition link information 13d and the virtual link information 13e when the connection link is a recognition link. And the road recognition information update part 17b repeatedly performs update of the recognition link information 13d and the virtual link information 13e about all the connection links.

  8 and 9 are diagrams for explaining a method for updating road recognition information. The example of FIG. 8 represents a state when the simulation time is t1, and the example of FIG. 9 represents a state when the simulation time is t2 after t1. Solid arrows shown in FIGS. 8 and 9 represent cognitive links. The dashed arrows shown in FIGS. 8 and 9 represent virtual links. White circles shown in FIGS. 8 and 9 represent nodes. Moreover, the black circle shown in FIG.8 and FIG.9 represents the destination node.

  As shown in FIG. 8, at the time when the simulation time is t1, the vehicle is traveling toward the node a. Thereafter, when the simulation time reaches t2, the vehicle passes through the node a as shown in FIG. In this case, since the node a which is a transit node is a cognitive boundary node, the virtual link including the transit node a is deleted. Then, the connection link including the transit node a, that is, the connection link of the node a and the node b, the connection link of the nodes a and e, and the connection link of the node a and the node f are added to the recognition link information 13d as a recognition link. . At the same time, a virtual link including the node b and the destination node which are newly recognized boundary nodes, a virtual link including the node e and the destination node which are newly recognized boundary nodes, and a new recognition boundary node. The virtual link including the node f and the destination node is added to the virtual link information 13e.

  The travel history update unit 17c is a processing unit that updates the travel history information 13b. As one aspect, the travel history update unit 17c additionally registers the travel history of the vehicle ID of the vehicle in the travel history information 13b when the vehicle passes the node. For example, the travel history update unit 17c traveled on the date and time that passed through the node, the link formed by the node and the node that passed immediately before, the transit time taken to pass the link, and the link. The travel history associated with the average speed is additionally registered in the storage unit 13.

  The route candidate generation unit 17d is a processing unit that generates a route candidate to the destination node using the recognition link information 13d and the virtual link information 13e. Hereinafter, a route candidate to the destination node may be referred to as a “route candidate”. As an aspect, when the virtual link information 13e is updated, the route candidate generation unit 17d generates a route candidate from the node closest to the current position, that is, the position coordinates of the vehicle state information 13e, to the destination node. Here, in the case where the virtual link information 13e is updated, the virtual link information 13e is updated by the road generation information update unit 17b when the virtual link information 13e is initialized together with the destination node by the vehicle generation unit 17a. Is included. For example, the route candidate generation unit 17d generates a route that passes through the cognitive boundary node as a route candidate. That is, the route candidate generation unit 17d extracts, as route candidates, combinations of cognitive links from the current location to each cognitive boundary node and virtual links that virtually connect each cognitive boundary node and the destination node. . A known technique such as the Dijkstra method can be arbitrarily applied to the route search of the cognitive link. In addition, when there is a route in which all routes from the current location to the destination node are cognitive links, the route candidate generation unit 17d also extracts a route formed only by the cognitive link as a route candidate.

  The cost calculation unit 17e is a processing unit that calculates the cost of the recognition link and the cost of the virtual link that form the route candidate. Here, in the following, it is assumed that the required time is used as an example of the cost. However, in addition to the required time, a travel distance, a fee, and the like can be further combined.

  As one aspect, the cost calculation unit 17e can obtain the required time on the recognition link forming the route candidate on the assumption that the recognition link has traveled at the regulated speed. In addition, the cost calculation part 17e can also obtain | require the required time of a recognition link by totaling the passage time of the recognition link contained in the driving history information 13b. Moreover, the cost calculation part 17e may set a more exact required time, when a recognition link is produced | generated by the car navigation system etc. On the other hand, for the virtual link, the cost calculation unit 17e can obtain the required time that can be estimated as a cost when the simulated driver travels from the recognition boundary node to the destination node. For example, assuming that the required time is approximately proportional to the travel distance, and that the travel distance is proportional to the linear distance between the recognition boundary node and the destination node, the linear distance between the recognition boundary node and the destination node is multiplied by a proportional coefficient α. The calculated value can be calculated as a cost.

  The route selection unit 17f is a processing unit that selects one route from among route candidates using the cost of the cognitive link and the cost of the virtual link. As an aspect, the route selection unit 17f selects, as a route, the route candidate having the smallest cost from the sum of the cost of the cognitive link and the cost of the virtual link calculated for each route candidate by the cost calculation unit 17e. Alternatively, a route selection model such as a logit model can be applied to select a route stochastically according to the sum of the cost of the cognitive link and the cost of the virtual link. Here, the case where the required time is the cost is exemplified, but when the cost is calculated for the travel distance and the fee, the route candidate having the minimum total cost including the required time, the travel distance, and the fee Can also be selected as a route.

  The position update unit 17g is a processing unit that updates the position of the vehicle according to the route selected by the route selection unit 17f. As one aspect, the position update unit 17g is configured such that the vehicle position coordinates and the speed of the vehicle when the simulation time Δt has elapsed based on the traveling direction of the route selected by the route selection unit 17f, the speed and acceleration of the vehicle, and the like. Calculate the state. Then, the position updating unit 17g updates the position coordinates and speed of the record corresponding to the vehicle ID of the vehicle among the records of the vehicle state information 13a.

  The evaluation unit 17h is a processing unit that evaluates traffic conditions using the travel history information 13b. Here, the case where the traffic volume of an intersection is evaluated is assumed as an example. As one aspect, when the simulation time reaches the end time, the evaluation unit 17h reads a record of the travel history information 13b corresponding to the preset time zone and intersection conditions from the storage unit 13. Then, the evaluation unit 17h counts the number of records of the travel history information 13b read from the storage unit 13 for each time zone and each intersection. As a result, the traffic volume by time zone and by intersection can be obtained. Then, the evaluation unit 17h displays the traffic volume for each time zone and each intersection obtained in this manner on the display unit 12.

  Note that various integrated circuits and electronic circuits can be employed for the control unit 15. In addition, a part of the functional unit included in the control unit 15 may be another integrated circuit or an electronic circuit. For example, an ASIC (Application Specific Integrated Circuit) is an example of the integrated circuit. Examples of the electronic circuit include a central processing unit (CPU) and a micro processing unit (MPU).

[Specific Example 1]
Here, the specific example 1 of a traffic simulation is demonstrated using FIGS. 10-12. 10 to 12 are diagrams illustrating an example of route selection behavior. The example of FIG. 10 represents a state when the simulation time is t1, the example of FIG. 11 represents a state when the simulation time is t2 after t1, and the example of FIG. This represents a state when t3 is later than t2. A solid arrow shown in FIGS. 10 to 12 represents a cognitive link. The dashed arrows shown in FIGS. 10 to 12 represent virtual links. White circles shown in FIGS. 10 to 12 represent nodes. Moreover, the black circle shown in FIGS. 10-12 represents the destination node.

  As shown in FIG. 10, at the time when the simulation time is t1, the route having the minimum cost of 180, that is, passes through the nodes in the order of “node a → node b → node c”, from node c to destination node Until then, the route passing through the virtual link is selected. Thereafter, when the simulation time reaches t2, the vehicle reaches the node c. Then, as shown in FIG. 11, the virtual link from the node c to the destination node is deleted, but there is no other connection link, so the recognition link is not added. Therefore, at time t3, as shown in FIG. 12, the route having the minimum cost 280, that is, the node “c” → node b → node d ”passes through the nodes in order, from node d to destination node. The route passing through the virtual link is reselected. As a result, it is possible to simulate a behavior in which the simulated driver gets lost and makes a U-turn at the dead end node c, so-called turning.

[Specific Example 2]
Then, the specific example 2 of a traffic simulation is demonstrated using FIGS. 13-15. 13 to 15 are diagrams illustrating an example of route selection behavior. The example of FIG. 13 represents the state when the simulation time is t1, the example of FIG. 14 represents the state when the simulation time is t2 after t1, and the example of FIG. This represents a state when t3 is later than t2. Solid arrows shown in FIGS. 13 to 15 represent cognitive links. Broken arrows shown in FIGS. 13 to 15 represent virtual links. White circles shown in FIGS. 13 to 15 represent nodes. Moreover, the black circles shown in FIGS. 13 to 15 represent destination nodes.

  As shown in FIG. 13, when the simulation time is t1, the route having the minimum cost of 150, that is, passes through the nodes in the order of “node a → node b → node c”, from node c to destination node Until then, the route passing through the virtual link is selected. Thereafter, when the simulation time reaches t2, the vehicle reaches the node c. Then, as shown in FIG. 14, the virtual link from the node c to the destination node is deleted, and a connection link in a direction different from the virtual link, that is, a link formed by the node c and the node e is added as a cognitive link. Is done. Therefore, at time t3, as shown in FIG. 15, the route having the minimum cost of 220, that is, the node passes in the order of “node c → node e → node g”, from node f to the destination node. The route passing through the virtual link is reselected. As a result, it is possible to simulate a so-called detour in which the road assumed by the simulated driver does not exist, and the vehicle makes a detour and returns to the original direction.

[Process flow]
A processing flow of the traffic simulation apparatus 10 according to the present embodiment will be described. Here, (1) the traffic simulation process executed by the traffic simulation apparatus 10 will be described, and then (2) the road recognition information update process executed as a subflow of the traffic simulation process will be described.

(1) Traffic Simulation Process FIGS. 16 and 17 are flowcharts illustrating the procedure of the traffic simulation process according to the first embodiment. The traffic simulation process is started when a traffic simulation start instruction is received from the input unit 11 or an external device.

  As shown in FIG. 16, first, the traffic simulation apparatus 10 uses the vehicle state information 13a to determine whether there is an area where the number of vehicles is insufficient, for example, an area where the virtual space is divided by administrative jurisdiction. Determination is made (step S101). When there is no area where the number of vehicles is insufficient (No at Step S101), the process proceeds to Step S104.

  At this time, when there is an area where the number of vehicles is insufficient (Yes in step S101), the traffic simulation apparatus 10 executes the following process. That is, the traffic simulation device 10 newly generates a record of the vehicle state information 13a with the node included in the area as a position coordinate, and additionally registers the new record in the vehicle state information 13a (step S102). Thereafter, the traffic simulation device 10 initially sets the destination, the recognition link, and the virtual link of the vehicle (step S103).

  Subsequently, the traffic simulation device 10 selects one record from the vehicle state information 13a stored in the storage unit 13 (step S104). And the traffic simulation apparatus 10 specifies the link which a vehicle drive | works from the position coordinate of vehicle ID contained in the said record, and the road network information 13c. Thereby, it is determined whether or not the vehicle having the vehicle ID has passed the node (step S105).

  At this time, when the vehicle passes through the node (Yes at Step S105), the traffic simulation device 10 further determines whether or not the passing node through which the vehicle has passed is the destination node (Step S106).

  If the passing node through which the vehicle has passed is the destination node (Yes at Step S106), the traffic simulation apparatus 10 sets the vehicle ID of the vehicle that has reached the destination node among the records included in the vehicle state information 13a. The corresponding record is deleted (step S107). Then, the traffic simulation apparatus 10 additionally registers the travel history of the vehicle ID of the vehicle in the travel history information 13b (step S108), and proceeds to the process of step S116 shown in FIG.

  On the other hand, when the passing node through which the vehicle has passed is not the destination node (No at Step S106), the traffic simulation apparatus 10 executes a road recognition information update process for updating the recognition link information 13d and the virtual link information 13e ( Step S109).

  Subsequently, the traffic simulation device 10 determines whether or not the virtual link information 13e has been updated (step S110). Here, the case where the virtual link information 13e is updated includes a case where the virtual link information 13e is initialized together with the destination node in step S103 and a case where the virtual link information 13e is updated in step S109. . When the virtual link information 13e has not been updated (No at Step S110), the process proceeds to Step S115 without executing route selection.

  At this time, when the virtual link information 13e is updated (Yes at Step S110), as shown in FIG. 17, the traffic simulation device 10 starts from the node closest to the current location, that is, the position coordinates of the vehicle state information 13e. A route candidate reaching the node is generated (step S111).

  And the traffic simulation apparatus 10 calculates the cost of the recognition link and the cost of a virtual link which form a route candidate (step S112 and step S113). Then, the traffic simulation apparatus 10 selects a route candidate having the smallest cost as a route from the sum of the cost of the cognitive link and the cost of the virtual link calculated for each route candidate (step S114).

  Subsequently, the traffic simulation device 10 determines the position coordinates of the record corresponding to the vehicle ID of the vehicle among the records of the vehicle state information 13a based on the traveling direction of the route selected in step S114, the speed and acceleration of the vehicle, and the like. The speed is updated (step S115).

  Thereafter, until the position coordinates and speeds of all the vehicle IDs included in the vehicle state information 13a are updated (No at Step S116), the traffic simulation device 10 repeatedly executes the processes from Step S104 to Step S115.

  When the position coordinates and speeds of all vehicle IDs included in the vehicle state information 13a are updated (Yes at Step S116), the traffic simulation apparatus 10 advances the simulation time from t to t + Δt (Step S117).

  Thereafter, until the simulation time t reaches the simulation end time (No at Step S118), the traffic simulation device 10 repeatedly executes the processes from Step S101 to Step S117. When the simulation time t reaches the simulation end time (Yes at step S118), the process is terminated.

(2) Road Recognition Information Update Processing FIG. 18 is a flowchart illustrating a procedure of road recognition information update processing according to the first embodiment. This road recognition information update process is a process corresponding to step S109 shown in FIG. 16, and the process is performed when the vehicle passes the node and the passing node is not the destination node (Yes in step S105 and No in step S106). It is activated.

  As illustrated in FIG. 18, the traffic simulation device 10 refers to the virtual link information 13e and determines whether or not the passing node is a cognitive boundary node that forms a virtual link (step S301).

  At this time, if the passing node is a cognitive boundary node (Yes in step S301), the cognitive boundary node is updated to a simple cognitive node by the current passing. Therefore, the traffic simulation apparatus 10 deletes the record regarding the virtual link including the passage node among the virtual links stored in the virtual link information 13e (step S302). If the passing node is not a cognitive boundary node (No at step S301), the cognitive boundary node is not updated, so the record is not deleted and the process proceeds to step S303.

  Thereafter, the traffic simulation device 10 selects one connection link from among the connection links connected to the passing node (step S303). Then, the traffic simulation device 10 refers to the recognition link information 13d and determines whether or not the previously selected connection link is a recognition link (step S304).

  At this time, when the connection link is not a cognitive link (No in step S304), the traffic simulation apparatus 10 adds the connection link as a cognitive link to the cognitive link information 13d (step S305). If the connection link is a cognitive link (Yes at step S304), the process proceeds to step S307 without updating the cognitive link information 13d and the virtual link information 13e.

  In addition, when the other node that is not a passing node is not a cognitive node, the traffic simulation device 10 uses the other node as a cognitive boundary node, and the virtual link from the cognitive boundary node to the destination is a virtual link. It adds to the information 13e (step S306).

  Thereafter, the processing from step S303 to step S306 is repeatedly executed until the processing is executed for all connection links (No in step S307). When the process is executed for all the connection links (Yes at Step S307), the traffic simulation apparatus 10 additionally registers the travel history of the vehicle ID of the vehicle in the travel history information 13b (Step S308), and ends the process.

[Effect of Example 1]
As described above, the traffic simulation apparatus 10 according to the present embodiment selects a route using the cost of the cognitive link recognized by the simulated driver and the virtual link connecting the cognitive boundary node and the destination. For this reason, in the traffic simulation apparatus 10 according to the present embodiment, it is possible to reproduce an intermediate behavior between a random route selection in a situation where there is no information and a route selection under complete information, for example, a turn or detour behavior.

Therefore, according to the traffic simulation apparatus 10 according to the present embodiment, an appropriate simulation result can be obtained. Furthermore, since the traffic simulation apparatus 10 according to the present embodiment can obtain the reproduced result including the turning and detouring behavior, the traffic evaluation, for example, the improvement of the road, the change of the signal control method, the driver, etc. In addition to the effect of improving traffic jams and the effect of reducing accidents when information is provided, it is also possible to appropriately evaluate environmental impacts such as CO ₂ emissions.

  Although the embodiments related to the disclosed apparatus have been described above, the present invention may be implemented in various different forms other than the above-described embodiments. Therefore, another embodiment included in the present invention will be described below.

[Application example]
In the first embodiment, the virtual link that virtually connects the recognition boundary node and the destination node is illustrated, but it is not always necessary to form a virtual link with the correct destination node. In other words, in the above-described first embodiment, the simulated driver is surely directed in the direction of the destination unless the virtual link is deleted.

  However, a real driver may misrecognize the position of the destination and head in a direction different from the destination. In order to simulate such a situation, the position of the destination can be set to a position shifted from the true position.

  For example, the disclosed apparatus can set a destination at a position that differs by an error determined from the probability distribution. Here, when a normal distribution is considered as a probability distribution, two normal random numbers are obtained by a box-Muller method or the like, and values obtained by multiplying the variance σ by each are set as errors Δx and Δy in the x and y directions. The disclosed device sets the position of the destination recognized by the simulated driver as (x + Δx, y + Δy) where the position of the true destination is (x, y).

  In addition, the disclosed device sets a virtual link to the destination recognized by the simulated driver. Further, as in the first embodiment, the disclosed apparatus uses a value obtained by multiplying the time required to travel the linear distance of the virtual link by the proportional coefficient α. As a result, a route in a direction different from the actual destination is selected. The variance σ may be decreased as the destination is approached. Moreover, since the recognition error varies among individuals, the variance σ may be set for each simulated driver.

  Note that it is conceivable to add not only a value obtained by multiplying the required time of the virtual link by the proportional coefficient α, but also a cost corresponding to the burden of traveling on an unrecognized road. Thereby, since it is uneasy to drive on an unrecognized road, it is possible to simulate the behavior of a driver who tries to drive on the recognized road as much as possible. Since such a psychological burden varies between beginners and skilled persons, a cost may be set for each simulated driver.

[Distribution and integration]
In addition, each component of each illustrated apparatus does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution / integration of each device is not limited to that shown in the figure, and all or a part thereof may be functionally or physically distributed or arbitrarily distributed in arbitrary units according to various loads or usage conditions. Can be integrated and configured. For example, some of the functional units included in the simulation execution unit 17 may be connected as an external device of the traffic simulation device 10 via a network. Moreover, the structure which another apparatus memorize | stores all or one part of the various data memorize | stored in the memory | storage part 13 as a database server is also employable. In this case, the function of the traffic simulation apparatus 10 may be realized by collaborating with a database server connected to the network.

[Traffic simulation program]
The various processes described in the above embodiments can be realized by executing a prepared program on a computer such as a personal computer or a workstation. Therefore, in the following, an example of a computer that executes a traffic simulation program having the same function as in the above embodiment will be described with reference to FIG.

  FIG. 19 is a schematic diagram illustrating an example of a computer that executes a traffic simulation program according to the first and second embodiments. As illustrated in FIG. 19, the computer 100 includes an operation unit 110 a, a speaker 110 b, a camera 110 c, a display 120, and a communication unit 130. Further, the computer 100 includes a CPU 150, a ROM 160, an HDD 170, and a RAM 180. These units 110 to 180 are connected via a bus 140.

  As shown in FIG. 19, the HDD 170 stores in advance a traffic simulation program 170 a that exhibits the same function as each functional unit included in the simulation execution unit 17 described in the first embodiment. The traffic simulation program 170a may be integrated or separated as appropriate, as with each component included in the simulation execution unit 17 shown in FIG. In other words, all data stored in the HDD 170 need not always be stored in the HDD 170, and only data necessary for processing may be stored in the HDD 170.

  Then, the CPU 150 reads the traffic simulation program 170 a from the HDD 170 and develops it in the RAM 180. Accordingly, as shown in FIG. 19, the traffic simulation program 170a functions as a traffic simulation process 180a. The traffic simulation process 180a expands various data read from the HDD 170 in an area allocated to itself on the RAM 180 as appropriate, and executes various processes based on the expanded various data. The traffic simulation process 180a includes processing executed by each functional unit included in the simulation execution unit 17 shown in FIG. 1, for example, processing shown in FIGS. In addition, each processing unit virtually realized on the CPU 150 does not always require that all processing units operate on the CPU 150, and only a processing unit necessary for the processing needs to be virtually realized.

  Note that the traffic simulation program 170a is not necessarily stored in the HDD 170 or the ROM 160 from the beginning. For example, each program is stored in a “portable physical medium” such as a flexible disk inserted into the computer 100, so-called FD, CD-ROM, DVD disk, magneto-optical disk, or IC card. Then, the computer 100 may acquire and execute each program from these portable physical media. In addition, each program is stored in another computer or server device connected to the computer 100 via a public line, the Internet, a LAN, a WAN, etc., and the computer 100 acquires and executes each program from these. It may be.

DESCRIPTION OF SYMBOLS 10 Traffic simulation apparatus 11 Input part 12 Display part 13 Storage part 15 Control part 17 Simulation execution part 17a Vehicle generation part 17b Road recognition information update part 17c Travel history update part 17d Route candidate production | generation part 17e Cost calculation part 17f Route selection part 17g Position Update unit 17h Evaluation unit

Claims (6)

Computer
The simulated driver is included in the road network information for each simulated driver who drives the vehicle, using the position of the vehicle simulated by the computer and road network information including nodes and links. Update the cognitive link information associated with the cognitive link you recognize,
When the cognitive link information is updated, among the nodes that form the cognitive link for each simulated driver, the destination is the cognitive boundary node located at the boundary with the node that is not recognized by the simulated driver. Update the virtual link information associated with the virtual link that virtually connects the node,
Using the cognitive link information and the virtual link information, generate a route candidate from the vehicle position to the destination node,
Calculate the cost of the cognitive link and the cost of the virtual link that form the candidate route,
Selecting at least one path among the path candidates using the cost of the cognitive link and the cost of the virtual link;
The traffic simulation method characterized by performing the process which updates the position of each vehicle according to the said path | route. As a process of updating the cognitive link information,
Performing an update to add to the cognitive link a connection link connected to a transit node through which the vehicle has passed;
As a process of updating the virtual link information,
When the transit node is the cognitive border node, the virtual link including the cognitive border node is deleted, and the other link different from the transit node among the connection links added to the cognitive link and the destination The traffic simulation method according to claim 1, wherein an update is performed to add a virtual link that virtually connects to the node. As a process of updating the cognitive link information,
The traffic simulation according to claim 1, wherein the recognition link information is generated using travel history information in which a travel history of a vehicle driven by the simulated driver is associated with each simulated driver. Method. As a process for calculating the cost,
The cost of a virtual link forming the route candidate is calculated using an estimated value of a length of the virtual link or a time required to travel through the virtual link. 3. The traffic simulation method according to 3. A vehicle state information storage unit for storing the position of the vehicle to be simulated;
A road network information storage unit that stores road network information including nodes and links;
A cognitive link information storage unit that stores cognitive link information associated with a cognitive link recognized by the simulated driver among the road network information for each simulated driver driving the vehicle;
A virtual link that virtually connects a cognitive boundary node located at a boundary with a node that is not recognized by the simulated driver and a node that is the destination among the nodes that form the cognitive link for each simulated driver. A virtual link information storage unit for storing the attached virtual link information;
A road recognition information update unit that updates the virtual link information and the virtual link information using the position of the vehicle and the road network information;
A route candidate generation unit that generates a route candidate from the position of the vehicle to the node as the destination using the cognitive link information and the virtual link information;
A cost calculation unit for calculating the cost of the cognitive link and the cost of the virtual link forming the route candidate;
A route selection unit that selects at least one route among the route candidates using the cost of the cognitive link and the cost of the virtual link;
And a position updating unit that updates the position of each vehicle according to the route. On the computer,
The simulated driver is included in the road network information for each simulated driver who drives the vehicle, using the position of the vehicle simulated by the computer and road network information including nodes and links. Update the cognitive link information associated with the cognitive link you recognize,
When the cognitive link information is updated, among the nodes that form the cognitive link for each simulated driver, the destination is the cognitive boundary node located at the boundary with the node that is not recognized by the simulated driver. Update the virtual link information associated with the virtual link that virtually connects the node,
Using the cognitive link information and the virtual link information, generate a route candidate from the vehicle position to the destination node,
Calculate the cost of the cognitive link and the cost of the virtual link that form the candidate route,
Selecting at least one path among the path candidates using the cost of the cognitive link and the cost of the virtual link;
A traffic simulation program for executing a process of updating the position of each vehicle according to the route.

Images