JP5668380B2 - Route search apparatus and program - Google Patents

Description

  The present invention relates to a route search device and program, and more particularly, to a route search device and program for searching for transportation means and a route.

  Conventionally, a route search navigation system using a combination of walking and another engine is known (Patent Document 1). In this system, the cost is calculated using the straight line distance from the departure point and destination point to the transportation station, and all the transportation stations where the cost is within the specified range are determined. Representing the network and searching for the least cost path.

JP 2000-258184 A

  However, the technique described in Patent Document 1 has a problem that the means of transportation is limited to a combination of walking and public transportation.

  The present invention has been made to solve the above problems, and an object thereof is to provide a traffic flow calculation apparatus and program capable of searching for a route when using a combination of various transportation means. .

In order to achieve the above object, the route search device according to the first invention is represented by a plurality of links connecting a plurality of nodes with respect to a plurality of transportation means including a car, a bus, a railroad, and a walk. A plurality of networks including a bus network , a railroad network, a walking network, and a road network, each of the plurality of links including a transfer node, and a link between corresponding transfer nodes in the plurality of networks. Network storage means for storing the hierarchical network data connected in the above and the time table data of departure time or arrival time, departure place, destination, and public transport as input, and based on the hierarchical network data, to the destination Minimizing the total link cost calculated for each means of transportation at each link of the route; And route searching means for searching for a route information representing a link route to target locations, is configured to include a.

A program according to the second invention is a bus network , a railway network, a walking network, represented by a plurality of links connecting a plurality of nodes to a plurality of transportation means including cars, buses, railways, and walking . And a plurality of networks including road networks, each of the plurality of links of the plurality of networks includes a transfer node, and stores hierarchical network data in which the corresponding transfer nodes in the plurality of networks are connected by links. A computer including a network storage means, with the departure time or arrival time, departure place, destination, and public transport timetable data as input, based on the hierarchical network data, at each link of the route to the destination, To the destination that minimizes the total link cost calculated for each mode of transportation It is a program for functioning as a route searching means for searching a route information representing a link of the route.

According to the first and second inventions, a bus network and a railroad network represented by a plurality of links connecting a plurality of nodes with respect to a plurality of transportation means including cars, buses, railroads, and walking. A hierarchical network representing a plurality of networks including a walking network and a road network, wherein each of the plurality of links of the plurality of networks includes a transfer node, and the corresponding transfer nodes in the plurality of networks are connected by a link Data is stored in the network storage means.

  Then, the route search means inputs the departure time or arrival time, the departure place, the destination, and the public transportation timetable data, and based on the hierarchical network data, for each transportation means in each link of the route to the destination. The route information representing the link of the route to the destination that minimizes the total value of the link costs calculated in the above is searched.

  In this way, it is possible to search for a route when using a combination of various means of transportation using hierarchical network data representing a plurality of networks for a plurality of means of transportation in which corresponding transfer nodes are linked by links. it can.

Multiple means of transportation of the above, car, bus, including the railway, and a walk. Thus, a route when a combination of a car, a bus, a railroad, and a walk is used as a transportation means can be searched.

The above route searching means further inputs the personal attributes including car availability, calculates a link cost for the vehicle based on the personal attribute, search for a route information. Accordingly, it is possible to search for a route when a combination of various means of transportation is used in consideration of the availability of a car as a personal attribute.

  The plurality of transportation means include walking, and the route searching means further inputs a personal attribute including age, calculates link cost for walking based on the personal attribute, and searches for route information. Can do. This makes it possible to search for a route when using a combination of various means of transportation in consideration of the cost of walking according to age.

  The route search means searches for route information for a plurality of individuals based on personal data representing departure time or arrival time, departure location, and destination for the plurality of individuals. Traffic flow calculation means for calculating traffic flow including behavior of each of a plurality of individuals in a plurality of networks using personal data for a plurality of individuals and route information for the plurality of individuals searched by the route search means as inputs. Further, it can be included.

  The route search device including the traffic flow calculation means described above is based on the behavior of each individual of the traffic flow calculated by the traffic flow calculation means, and for each individual, the link travel time of each link to the destination, Calculated for the route information searched by the route search means for the total value of the link cost calculated based on the experience information for each individual and the experience information generation means for generating experience information including the degree of congestion or waiting time A change means for changing the route information when the difference or ratio of the total value of the link costs is equal to or greater than a predetermined value, and the traffic flow calculation means further uses a plurality of route information changed by the change means. The traffic flow in the network can be calculated.

  The route search device including the traffic flow calculation means described above is an experience for generating experience information including arrival time at the destination for each individual based on the behavior of each individual of the traffic flow calculated by the traffic flow calculation means. The traffic flow calculation further includes information generation means and, for each individual, a change means for changing the route information or the departure time when the difference of the arrival time of the personal data with respect to the arrival time of the experience information is a predetermined value or more. The means may further calculate the traffic flow in the plurality of networks using the route information or the departure time changed by the changing means.

  The change means can change the individual route information to the route information searched again by the route search means using the experience information for the individual.

  As described above, according to the route search apparatus and program of the present invention, various traffic can be obtained using hierarchical network data representing a plurality of networks for a plurality of transportation means in which corresponding transfer nodes are linked by links. There is an effect that a route when a combination of means is used can be searched.

It is a block diagram which shows the traffic flow calculation apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the example of personal data. It is a figure which shows the example of multi-layer network data. It is a figure which shows the example of the link travel time according to time slot | zone. It is a figure which shows the example of the congestion rate according to time slot | zone. It is a figure which shows the example of the waiting time according to time slot | zone. It is a figure which shows the example of a network. It is a figure which shows the example of the actual link cost according to time slot | zone. It is a figure which shows the initial stage route in the example of a network. It is a figure which shows the path | route after the change in the example of a network. It is a flowchart which shows the content of the simulation process routine in the traffic flow calculation apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart which shows the content of the means and route simultaneous search process routine in the traffic flow calculation apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart which shows the content of the means and route change judgment processing routine in the traffic flow calculation apparatus which concerns on the 1st Embodiment of this invention. It is a block diagram which shows the traffic flow calculation apparatus which concerns on the 2nd Embodiment of this invention. It is a figure which shows the example of personal data. It is a flowchart which shows the content of the means and route simultaneous search process routine in the traffic flow calculation apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart which shows the content of the means and route change judgment processing routine in the traffic flow calculation apparatus which concerns on the 1st Embodiment of this invention.

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. In the embodiment according to the present invention, a case where the present invention is applied to a traffic flow calculation apparatus that simulates a traffic flow will be described.

  As shown in FIG. 1, the traffic flow calculation apparatus 10 according to the first embodiment is composed of a computer having a CPU, ROM, RAM, and HDD, and stores personal data created for each individual. A storage unit 12, a network data storage unit 14 for storing hierarchical network data to be described later, a timetable data storage unit 16 for storing timetable data of public transportation such as railways and buses, and transportation means and routes for each individual A route search unit 18 for simultaneously searching for a route, a route data storage unit 20 for storing route data representing a combination of the searched means of transportation and a route, and a traffic flow simulation unit 22 for simulating a traffic flow. I have.

  As shown in FIG. 2, the personal data storage unit 12 has a personal ID, departure time, generation node (departure place), concentration node (destination), personal attributes (age, license possession, car possession), Personal data composed of a route ID for identifying a route from the generation node to the concentrated node is stored. Here, each of the license possession and the car possession is set to 1 if owned, and set to 0 if not owned.

  As shown in FIG. 3, the network data storage unit 14 is a road network represented by a plurality of links connecting a plurality of nodes with respect to a plurality of transportation means including, for example, a car, a railroad, a walk, and a bus. Multi-layer network data in which a bus network, a railroad network, and a walking network are hierarchized is stored.

  The link of the network of each layer includes a transfer node that is a base point of means change, and the transfer nodes corresponding to each other in a plurality of layers are connected by a transfer link to connect the networks of each layer.

  Since it is hierarchized for each means of transportation, even if nodes representing the same point are different in hierarchy, they are defined as different nodes. For example, although ST1 and N1 in FIG. 3 are the same point on the map, ST1 represents a railway station and N1 represents a terminal node on the road in front of the railway station. For the generation node and the concentration node, all the nodes representing the same point are represented.

  Since all the networks are represented by nodes and links, the route search can be performed regardless of which layer of the network the search is in. In addition, since the network hierarchy can be identified by the node ID, from the node ID column representing the link of the route to the destination obtained as a result of the route search, which transportation means is used and where the transfer is made. Can be determined.

  The road network is a network configured such that intersections or road terminals are nodes, and connections between intersections or road terminals and intersections are links. The railway network is a network configured such that a railway station is a node and a connection between the railway stations is a link. The walking network is a network configured to use a connection between walking nodes as a link.

  As for the bus network, a route search network and a traffic flow calculation network are prepared separately. This is because the vehicle is a special vehicle that has the side that a bus runs on the road network and interferes with other automobile traffic, and the side that only passes the specified route and stops at the bus stop. is there. Accordingly, a network configured so that a bus stop is a node and a connection between the bus stops is a link as a bus network for route search.

  The bus network for traffic flow calculation is a network which is shown on the road network and configured so that the bus stop is a node and the connection between the bus stops is a link. Each link cost obtained by the traffic flow calculation is reflected on the link of the bus network for route search. In the example of FIG. 3, the bus network for traffic flow calculation is shown.

  The bus network is an example of a public transportation network, and the railway network is an example of a public transportation network or an orbital transportation network.

  The network data storage unit 14 also includes signal data indicating the presence / absence / presentation of signals, traffic environment data (link length of each link, road type, gasoline fee, toll), and public traffic data (for example, railway and The bus usage fee is also stored.

  The timetable data storage unit 16 stores bus and railroad timetable data. The railroad timetable data represents the arrival time of each node of the railroad network, and the bus timetable data represents the bus network timetable data. Represents the arrival time of each node.

  The means route search unit 18 performs route search for each individual using the multi-layer network data. Specifically, a route with a minimum total link cost of each link in the route to the destination (concentrated node) is searched using the Dijkstra method. The link cost is obtained by the following equation (1).

However, C represents the link cost, T represents the link travel time, L represents the link length, R _k represents the road type, and F represents the toll (toll, usage fee, gasoline fee). J is the congestion rate, S is the waiting time, E is fatigue, e is the age, and _Nw is the network hierarchy. H is a function that returns a sufficiently large number when there is no license or vehicle, and w0 to w6 are predetermined weighting factors.

  At the time of route search, information on link travel time, link length, road type, fee, congestion rate, and waiting time is given to each link regardless of the network hierarchy. However, in the road network, 0 is given to each link except for link travel time, link length, road type, and fee information. Further, in the bus network and the railway network, 0 is given to each link for information other than the link travel time, link length, fee, and congestion rate. In the walking network, 0 is given to each link for information other than the link travel time and the link length. Also, in the transfer link, 0 is given for information other than the waiting time.

  Since each individual should not know the link travel time for links other than those included in the experienced route, at the time of initial route search or when cost data by time zone described later can not be obtained, The link travel time for each link is given by dividing the link length by a specified speed (for example, 30 km / h for a road network). In the case of a walking network, the link travel time calculated from the speed according to the link length and the attribute of the individual is given to the link.

  In addition, when the initial route search or cost data for each time zone, which will be described later, cannot be obtained, the congestion status and waiting time of the railway and bus are not known. The provisional value given is given.

  Further, values obtained from the traffic environment data and public traffic data stored in the network data storage unit 14 are given as the link length, road type, and fee of each link.

  From the personal data, information on the origin node (departure point), concentration node (destination), age, presence / absence of a license, and presence / absence of a car are input data at the time of the route search.

  Further, the means route searching unit 18 calculates the link cost according to the above equation (1) using the various information described above and the weighting factor possessed by itself. At this time, the function E (•) representing fatigue is a function of age, link travel time, and network hierarchy. Therefore, even when the link travel time is the same, fatigue is greater when moving on a walking network than when moving on a network of another hierarchy. Furthermore, considering that the fatigue level is higher in the standing position than in the sitting position, the congestion rate may be considered in the calculation of fatigue. At this time, it can be determined that if the number of passengers is less than the seat capacity, the seat is seated, and if the number of seats is more than the seat capacity, the seat is standing. The function H is a function that returns a sufficiently large number only when the vehicle is unavailable and the network hierarchy is a road network. That is, it is expressed by the following equation (2).

However, L _N is a predetermined sufficiently large number. δ _{l, c} is a function that determines whether or not a vehicle can be used, and is a function that returns 1 only when a license is held and a vehicle is held, and 0 otherwise. N _w represents the network hierarchy, if a road network, a road.

  By using the Dijkstra method for each link cost, route data (node ID column) representing a link of a route to the destination is, for example, (1) G1 → N2 → N6 → N8 → N9 → N12 → G2, (2) G1-> W2-> W1-> ST1-> ST2-> ST3-> W6-> W7-> G2, (3) G1-> W2-> W3-> BS1-> BS2-> W5-> W7-> G2. With regard to these route data, (1) represents a sequence of a plurality of node IDs in which the transportation means is only a car, and (2) represents a plurality of transportation means changing from walking to railroad to walking. This represents a column of node IDs, and (3) represents a column of a plurality of node IDs obtained by changing the means of transportation from walking to bus to walking. By using this method, transportation means such as park and ride can be easily expressed. For example, when a route of (4) G1-> N2-> N4-> N3-> N1-> ST1-> ST2-> ST3-> W6-> W7-> G2 is searched, the means of transportation is car-> rail-> walk.

The means route search unit 18 stores the searched route data for each individual in the route data storage unit 20 and registers the route ID of the stored route data in the personal data of the individual. Further, it means the route search unit 18, for each individual and stored in memory searched sum of the link cost calculated for the route data (the minimum value of the total value) based cost C _0.

  The traffic flow simulation unit 22 includes individual personal data stored in the personal data storage unit 12, individual personal route data stored in the route data storage unit 20, and multi-layers stored in the network data storage unit 14. Based on the network data and signal data, and the timetable data stored in the timetable data storage unit 16, from the start point (occurrence node) to the end point (concentrated node) on the network of each layer as time passes, The traffic flow including the behavior of each individual is calculated every second, and is repeatedly calculated until a predetermined time (for example, a predetermined time zone of one day) is reached. The traffic flow simulation unit 22 calculates the link travel time of each individual, the congestion rate of public traffic, and the waiting time of public transport based on the calculated behavior of each individual for a predetermined time.

  The simulation model is a traffic flow model in which individuals sorted according to departure time are generated in order, and vehicles, people (walking), railroads, and buses are moved at every scanning interval (= 1 second). The traffic flow model moves buses and railways on the corresponding hierarchical network based on the timetable data, and moves each vehicle on the road network data according to each individual route data. Move on the network, bus network, walking network, calculate and output the travel time of each link experienced by each individual.

  The traffic flow calculation device 10 further generates experience information for each individual based on the traffic flow calculated by the traffic flow simulation unit 22 and calculates the cost data for each time zone. And a cost data storage unit 26 that stores cost data for each time zone, and a change determination unit 28 that determines whether or not to change route data based on experience information.

  The experience information generation unit 24 collects the link travel time of each individual, the congestion rate of public transport, and the waiting time of public transport output by the traffic flow simulation unit 22, and each link travel on the route for each individual. Experience information is generated that includes time, bus or rail congestion rate for each link, and bus or rail latency for each transfer link.

  Further, the experience information generation unit 24, based on the experience information of all individuals, the average travel time (see FIG. 4), the average congestion rate (see FIG. 5), and the average waiting time (see FIG. 6) is generated and stored in the cost data storage unit 26.

  Although the network type is specified in the examples of FIGS. 4 to 6 described above, if the link ID is uniquely determined, it is not necessary to specify the network type. Also, the time zone width is determined arbitrarily. Since the average congestion rate is a cost related only to public transport network data, as shown in FIG. 5, it may be set to 0 other than the public transport network data, or only the public transport network data may be used as cost data in the first place. May be output as

  Further, since the average waiting time is a cost related only to the transfer link, as shown in FIG. 6, it may be set to 0 other than the transfer link, and the average waiting time only for the transfer link is output as cost data in the first place. You may make it do.

  Further, for each individual, the experience information generation unit 24 calculates the actual link cost according to the above equation (1) using the generated experience information as shown in FIG. 7, and as shown in FIG. The link cost of each link for each time zone is stored in the cost data storage unit 26.

  The change determination unit 28 compares, for each individual, the reference cost stored in the memory and the total value of the actual link costs, and determines whether or not to change the route data of the individual.

Here, when the total value of the actual link costs obtained by the n-th traffic flow calculation (the number of repetitions from the newest search of the target individual) obtained by iterative calculation is C _n , the condition that the route data is changed Is defined as follows:

1. When the ratio between the actual cost C _n and the reference cost C ₀ exceeds the threshold value T _hl

2. When the same route is used continuously for d days and the average cost ratio exceeds the threshold _Th2

However, T _h2 <T _h1 . When the above condition 1 or 2 is satisfied, it is determined to change the route data to the route data re-searched in consideration of the personal experience information.

  When it is determined that the route data is changed as described above, the route search unit 18 re-searches the route data for the target individual as follows.

  First, using the cost data for each time zone representing the average travel time, the average congestion rate, the average waiting time of each link for each time zone, and the personal experience information stored in the cost data storage unit 26, Search for new route data. That is, the link cost is calculated by using the link travel time, the congestion rate, and the waiting time of the link included in the experience information in preference to the contents of the cost data for each time zone, and the route search is performed.

  Here, an example in which route data in the network shown in FIG. 9 is changed will be described. N1 to N5 in FIG. 9 indicate nodes. Although not shown in the figure, a link connecting two nodes is represented as L12 (N1 → N2 link) from the start point and end point numbers of the nodes. In FIG. 9, the number written beside each link represents the link cost. Here, for the sake of simplicity, elements constituting the link cost such as the required time and the congestion rate are not considered.

FIG. 9 shows the initial link cost (link cost calculated during route search) before the traffic flow calculation. When a route that minimizes the total value of link costs in this network is searched, a route that passes through L12 → L23 → L34 is searched, and the reference cost C _{0 at} that time is 10.

  Next, when the traffic flow is calculated, the actual link cost of each link is obtained from the experience information passing through the link.

Assume that the ratio of the reference cost C ₀ to the actual cost C ₁ of a certain individual A exceeds the threshold value, and it is determined that the route data is to be changed. At this time, the link travel time, congestion rate, and waiting time of L12, L23, and L34 are replaced with the value of the cost data classified by time zone output by the traffic flow calculation from the personal A experience information. The new link cost reflecting experience information is shown in FIG. When a route that minimizes the link cost is searched using this link cost, a new route of L15 → L54 is searched and changed to the searched route.

  Next, the operation of the traffic flow calculation apparatus 10 according to the first embodiment will be described.

  When a simulation start instruction is input by the operator, a simulation processing routine shown in FIG.

  First, in step 100, each individual personal data stored in the personal data storage unit 12, multi-layer network data stored in the network data storage unit 14, and timetable data stored in the timetable data storage unit 16. And read.

  In step 102, for each individual, route data representing a means of transportation and a route to the destination is searched, and the searched route data is stored in the route data storage unit 20. In the next step 104, each individual's personal data stored in the personal data storage unit 12, each individual's route data stored in the route data storage unit 20, and the multi-layer network stored in the network data storage unit 14 Based on the data and signal data and the timetable data stored in the timetable data storage unit 16, the traffic flow in a predetermined time zone of the day is calculated.

  In step 106, based on the behavior of each individual in the traffic flow calculated in step 104 above, for each individual, experience information including the link travel time, congestion rate, and waiting time of each link to the destination is generated. To do.

  In the next step 108, for each individual, the actual link cost of each link to the destination is calculated based on the personal experience information generated in step 106 and stored in the cost data storage unit 26. .

  In step 110, based on the experience information of all the individuals generated in step 106, the average link travel time, congestion rate, and average waiting time of each link for each time zone are calculated, and the cost is calculated. The cost data for each time zone stored in the data storage unit 26 is updated.

  In step 112, based on the actual link cost calculated in step 108, it is determined whether or not the route data is to be changed for each individual. In the next step 114, it is determined whether or not the repeated end condition is satisfied. If the end condition is not satisfied, the process returns to step 102 to calculate the traffic flow for the next day. If the condition is satisfied, the simulation processing routine is terminated. Here, the end condition may be set as the number of repetitions, or may be set as a condition such as when the ratio of route changers falls below a threshold. In the following, a case will be described as an example in which the end condition is that the number of repetitions r is equal to or greater than a threshold value, and the process is ended when the equilibrium state as a whole is reached.

  By repeating the traffic flow calculation, means / route change judgment and means / route simultaneous search by the above simulation processing routine, the route data of each individual converges to a certain value, and an overall balance occurs. The traffic situation is reproduced.

  Step 102 is realized by the means / route simultaneous search processing routine shown in FIG.

  In step 120, an individual to be processed is determined, and in step 122, it is determined whether or not the search is for an initial route. If the search is an initial route, the process proceeds to step 126. On the other hand, if the search is a second or subsequent route search, the route data is changed in step 112 for the individual to be processed in step 124. It is determined whether or not it has been determined. If it is determined that the route data is to be changed, the process proceeds to step 126. On the other hand, if it is not determined to change the route data, the process proceeds to step 134 described later.

  In step 126, a variable r indicating the number of times the process has been repeated without changing the route is set to zero. Then, in step 128, the transportation means and route to the destination are simultaneously searched for the individuals to be processed based on the personal data, the cost data for each time zone, and the multi-layer network data. If it is determined to change the route data for the target person, the stored experience information is used in preference to the cost data for each time zone, and the means of transportation and route to the destination. Search simultaneously.

  In the next step 130, the total value of the link costs calculated for the route searched in step 128 is stored in the memory as a reference cost. In step 132, the route data searched in step 128 is stored in the route data storage unit 20 as route data of the individual to be processed.

  In step 134, the variable r is incremented. In step 136, it is determined whether or not the processing in steps 120 to 134 has been completed for all individuals. If it is determined that the processing has been completed for all individuals. Then, the means / route simultaneous search processing routine is terminated. On the other hand, when there is an individual who has not completed the processing of Step 120 to Step 134, the process returns to Step 120, and the individual is set as a processing target individual.

  The step 112 is realized by the means / route change determination processing routine shown in FIG.

  In step 140, an individual to be processed is determined, and in step 142, the actual cost is calculated from the total value of the actual link costs for the individual to be processed, and the ratio of the reference cost to the actual cost according to the above equation (3). Is determined to be greater than or equal to a threshold value. If the cost ratio is greater than or equal to the threshold value, the process proceeds to step 146, which will be described later. On the other hand, if the cost ratio is less than the threshold value, in step 144, according to the above equation (4), d days It is determined whether the average value of the ratio of the reference cost to the actual cost is equal to or greater than a threshold value. If the average value of the cost ratio is greater than or equal to the threshold value, the process proceeds to step 146. On the other hand, if the average value of the cost ratio is less than the threshold value, the process proceeds to step 150 described later.

  In step 146, it is set that the route data is changed as a determination result for the individual to be processed, and in step 148, the experience information generated in step 106 for the individual to be processed is the cost for route search. The data is stored in the data storage unit 26.

  In step 150, it is determined whether or not the processing in steps 140 to 148 has been completed for all individuals. If it is determined that the processing has been completed for all individuals, the means / route change determination processing routine is terminated. To do. On the other hand, if there is an individual who has not completed the processing of Steps 140 to 148, the process returns to Step 140, and the individual is set as the individual to be processed.

  As described above, according to the traffic flow calculation apparatus according to the first embodiment, multi-layer network data representing a plurality of networks for a plurality of transportation means in which corresponding transfer nodes are connected by a transfer link. By using the route search based on the link cost, it is possible to search for a route when using a combination of transportation means such as a car, a bus, a railway, and a walk.

  Moreover, in order to feed back the result of traffic flow calculation to an individual, the output result of the traffic flow calculation (travel time, traffic congestion rate, etc.) can be accumulated as experience information. Therefore, it is possible to handle behavioral changes such as changing the means of transportation or the route because the route cost to the destination has increased.

  In addition, it is possible to reproduce the traffic situation in which each individual's means of transportation / route converges to a certain value and the equilibrium state as a whole is achieved by repeatedly calculating the traffic flow and judging the change of means of transportation / route. .

  Further, as a result of searching for the minimum cost route, since the transportation means is included, the combination of the transportation means is not limited, and various combinations of the transportation means are searched simultaneously with the route.

  In addition, because it has the function to generate each vehicle and calculate the behavior per hour, it is possible to express the link travel time per hour, and the waiting time of public transportation per hour, The congestion rate, the degree of fatigue of the moving subject, etc. can be calculated. In addition, since it has a function for simultaneously searching for means and routes using costs, it can also simulate selection behavior.

  Next, a second embodiment will be described. In addition, about the part which becomes the structure similar to 1st Embodiment, the same code | symbol is attached | subjected and description is abbreviate | omitted.

  The second embodiment is different from the first embodiment in that a route search is performed based on the arrival time of personal data.

  As shown in FIG. 14, the traffic flow calculation apparatus 210 according to the second embodiment includes a personal data storage unit 12, a network data storage unit 14, a timetable data storage unit 16, a means route search unit 18, and A route data storage unit 20, a departure time determination unit 212 that determines a departure time based on the searched route data, a traffic flow simulation unit 22, an experience information generation unit 24, a cost data storage unit 26, An arrival time data storage unit 214 that stores arrival time data and a change determination unit 28 are provided.

  As shown in FIG. 15, the personal data storage unit 12 has a personal ID, an arrival time, a departure time, a generation node (departure place), a concentrated node (destination), a personal attribute (age, license possession, vehicle). Possessed) and personal data composed of route IDs. The departure time is not given in advance, but the arrival time is given in advance.

  The means route searching unit 18 simultaneously searches for the means of transportation and the route for each individual by tracing the route from the destination node to the starting point node in the same manner as in the first embodiment. In the route search, the link cost is calculated by referring to the cost data for each time zone while calculating back the time from the arrival time.

  The departure time determination unit 212 determines the departure time by back-calculating the departure time from the arrival time based on the searched route data for each individual, and determines the determined departure time in the personal data of the individual. sign up.

  The experience information generation unit 24 acquires the arrival time of the destination (concentrated node) for each individual based on the calculated behavior of each person in the traffic flow, and uses the arrival time data that records the arrival time for each individual. And stored in the arrival time data storage unit 214.

  The change determination unit 28 determines whether or not to change the route data for each individual based on the conditions of the expressions (3) and (4). Further, the change determination unit 28 changes the departure time to be advanced by the delay time when the delay time calculated from the arrival time of the personal data and the arrival time of the arrival time data is equal to or greater than the threshold. .

  Next, a means / route search processing routine according to the second embodiment will be described with reference to FIG. In addition, about the process similar to 1st Embodiment, the same code | symbol is attached | subjected and detailed description is abbreviate | omitted.

  In step 120, an individual to be processed is determined, and in step 122, it is determined whether or not the search is for an initial route. If the search is for an initial route, the process proceeds to step 126. In the case of the subsequent route search, in step 124, it is determined whether or not it is determined in step 122 that the route data is changed for the individual to be processed. If it is determined that the route data is to be changed, the process proceeds to step 126. On the other hand, if it is not determined to change the route data, the process proceeds to step 134.

In step 126, the variable r is set to 0. In step 128, the transportation means to the destination and the personal data, the cost data for each time zone, and the multi-layer network data for the individual to be processed In step 130, the total link cost calculated for the route searched in step 128 is stored in the memory as a reference cost. In step 250, the departure time is calculated backward based on the route data searched in step 128 and the arrival time of the personal data of the individual to be processed, and the departure time is added to the personal data in the personal data storage unit 12. Remember.

  In step 132, the route data searched in step 128 is stored in the route data storage unit 20.

  In step 134, the variable r is incremented. In step 136, it is determined whether or not the processing in steps 120 to 134 has been completed for all individuals. If it is determined that the processing has been completed for all individuals. Then, the means / route simultaneous search processing routine is terminated.

  A means / route change determination processing routine according to the second embodiment will be described with reference to FIG.

  In step 140, an individual to be processed is determined, and in step 142, it is determined whether or not the ratio of the reference cost to the actual cost is equal to or greater than a threshold value. If the cost ratio is greater than or equal to the threshold, the process proceeds to step 146. On the other hand, if the cost ratio is less than the threshold, in step 144, the average of the ratio of the reference cost to the actual cost for d days is calculated. It is determined whether or not the value is greater than or equal to a threshold value. When the average value of the cost ratio is equal to or greater than the threshold value, the process proceeds to step 146. On the other hand, when the average value of the cost ratio is less than the threshold value, the process proceeds to step 260.

  In step 260, based on the arrival time data generated based on the traffic flow calculation, the delay time of the arrival time in the traffic flow calculation result with respect to the arrival time of the personal data is greater than or equal to the threshold for the individual to be processed. It is determined whether or not there is. If the delay time is less than the threshold, the process proceeds to step 150. On the other hand, if the delay time is equal to or greater than the threshold, in step 262, the departure time of the personal data of the individual to be processed is set as the delay time. The process is changed so as to be advanced only, and the process proceeds to step 150.

  In step 146, it is set that the route data is changed as a determination result for the individual to be processed, and in step 148, the experience information generated in step 106 for the individual to be processed is the cost for route search. The data is stored in the data storage unit 26.

  In step 150, it is determined whether or not the processing in steps 140 to 148, 260, and 262 has been completed for all individuals. If it is determined that the processing has been completed for all individuals, means / route change determination processing is performed. End the routine. On the other hand, if there is an individual who has not completed the processes in steps 140 to 148, 260, and 262, the process returns to step 140, and the individual is set as an individual to be processed.

  In addition, since the other structure and effect | action of the traffic flow calculation apparatus which concern on 2nd Embodiment are the same as that of 1st Embodiment, description is abbreviate | omitted.

  As described above, according to the traffic flow calculation apparatus according to the second embodiment, the departure time is re-established by using experience information such as travel time and the congestion rate of public transportation determined by the traffic flow calculation. By calculating, a change in departure time can be expressed.

  Moreover, in order to feed back the result of traffic flow calculation to an individual, the output result of traffic flow calculation can be accumulated as experience information. For this reason, it is possible to handle behavioral changes such as changing the departure time because the arrival time scheduled by the individual is significantly delayed.

  In the above embodiment, the case where the departure time is changed when the arrival time delay time is equal to or greater than the threshold value has been described as an example. However, the present invention is not limited to this, and the arrival time delay time is not limited thereto. May be re-searched using experience information. Further, the departure time may be changed and the route may be searched again.

  In the first embodiment and the second embodiment described above, the case where the route data is searched for each individual and the traffic flow is calculated based on the route data has been described as an example. It is not limited, and for each individual, a plurality of route data candidates may be created at the time of route search, and the route data of each individual may be dynamically selected at the time of departure in the calculation of traffic flow. . As a method of creating a plurality of route data candidates, a method of selecting the route from the route with the smallest route cost to the kth route by the Dijkstra method may be used. Furthermore, in the calculation of traffic flow, a route search may be performed during movement to change the route depending on traffic conditions.

  In addition, the case where it is determined to change the route when the ratio between the actual cost and the reference cost is equal to or greater than the threshold has been described as an example, but the present invention is not limited to this. When the difference is equal to or greater than the threshold value, it may be determined to change the route. Further, when it is determined that the route is to be changed, the route data may be re-searched based on the cost data for each time zone without using the experience information.

  Moreover, although the case where a plurality of means of transportation is assumed to be a car, a bus, a railroad, and a walk has been described as an example, the present invention is not limited to this, and any combination of a car, a bus, a railroad, and a foot It is also possible to use other transportation means, or other transportation means may be combined.

10, 210 Traffic flow calculation device 12 Personal data storage unit 14 Network data storage unit 16 Timetable data storage unit 18 Means route search unit 20 Route data storage unit 22 Traffic flow simulation unit 24 Experience information generation unit 26 Cost data storage unit 28 Change Judgment unit 212 Departure time determination unit 214 Arrival time data storage unit

Claims (7)

A plurality of networks including a bus network, a railway network, a walking network, and a road network represented by a plurality of links connecting a plurality of nodes for a plurality of transportation means including a car, a bus, a railroad, and a walking Each of the plurality of links of the plurality of networks includes a transit node, and network storage means for storing hierarchical network data in which the corresponding transit nodes in the plurality of networks are linked by a link;
Links calculated for each means of transportation in each link of the route to the destination based on the hierarchical network data with the departure time or arrival time, the departure place, the destination, and the timetable data of public transportation as input Route search means for searching for route information representing a link of a route to the destination, which minimizes the total cost,
A route search device including :
The route search device is further provided with a personal attribute including whether or not a vehicle can be used as an input, calculates a link cost for the vehicle based on the personal attribute, and searches for the route information. It said route search means further inputs the personal attributes including age, calculates a link cost for walk based on the personal attribute, route searching apparatus according to claim 1, wherein searching the route information. The route search means searches the route information for the plurality of individuals based on personal data representing departure time or arrival time, departure point, and destination for the plurality of individuals,
Using the personal data for the plurality of individuals and the route information for the plurality of individuals searched by the route search means as inputs, the traffic flow including the behavior of each of the plurality of individuals in the plurality of networks is calculated. The route search device according to claim 1 or 2 , further comprising a traffic flow calculation means. Based on the behavior of each individual of the traffic flow calculated by the traffic flow calculating means, for each individual, generation of experience information including the link travel time of each link to the destination, the degree of congestion of public transportation or the waiting time Experience information generating means to
For each individual, a difference or ratio of the total value of the link costs calculated for the route information searched by the route search means with respect to the total value of the link costs calculated based on the experience information is a predetermined value. If it is above, it further includes a changing means for changing the route information,
The route search device according to claim 3, wherein the traffic flow calculation means calculates the traffic flow in the plurality of networks by further using the route information changed by the changing means. Experience information generating means for generating, for each individual, experience information including arrival time at the destination based on the behavior of each individual of the traffic flow calculated by the traffic flow calculating means;
A change means for changing the route information or the departure time when the difference in arrival time of the personal data with respect to the arrival time of the experience information is equal to or greater than a predetermined value for each individual;
Said traffic flow calculating means, the route searching apparatus according to claim 3 or 4, wherein calculating the traffic flow in the plurality of networks further using the changed the route information or the departure time by said changing means. 6. The route search apparatus according to claim 4 or 5 , wherein the change unit changes the route information of the individual to the route information searched again by the route search unit using the experience information for the individual. A plurality of networks including a bus network, a railway network, a walking network, and a road network represented by a plurality of links connecting a plurality of nodes for a plurality of transportation means including a car, a bus, a railroad, and a walking A plurality of links in each of the plurality of networks including a transfer node, and a computer including network storage means for storing hierarchical network data in which each of the transfer nodes in the plurality of networks is connected by a link;
Links calculated for each means of transportation in each link of the route to the destination based on the hierarchical network data with the departure time or arrival time, the departure place, the destination, and the timetable data of public transportation as input A program for functioning as a route search means for searching for route information representing a link of a route to a destination, which minimizes the total cost .
The route search means further receives a personal attribute including whether or not a vehicle is available, calculates a link cost for the vehicle based on the personal attribute, and searches for the route information.

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