JP6744946B2 - Traffic adjustment support device, traffic adjustment support method, and computer program - Google Patents

Description

Embodiments of the present invention relate to a traffic adjustment support device, a traffic adjustment support method, and a computer program.

BACKGROUND ART A road traffic control system is known, which collects information about road traffic such as traffic jams and accidents and provides it as traffic information to drivers and the like. In recent years, road traffic flow simulations and the like are performed based on the collected information, and information (support information) to be used for future congestion situation prediction and measures for congestion mitigation is also provided. Operators at the Road Traffic Control Center operate signals, road signs, electronic bulletin boards, etc. based on the provided support information, and perform route guidance and inflow control to the road traffic network (traffic adjustment). .. In this way, the safety, comfort and smoothness of road traffic are improved. In addition, it can contribute to alleviating congestion not only on roads but also on roadside facilities such as parking lots, facilities with quick chargers for electric vehicles, and popular spots.

However, the current road traffic control system has a problem that it takes a lot of time for simulation. Further, if the detour provided by the road traffic control system is inconvenient, the driver's dissatisfaction may be increased. Also, the operator who has been presented with such a detour will be at a loss whether to present the detour as it is.

JP, 2011-214930, A Patent No. 5398522 Japanese Patent No. 5194837

An embodiment of the present invention aims to support traffic adjustment in a target area while alleviating congestion in the target area and reducing user dissatisfaction in a road traffic network.

A traffic adjustment support device according to an embodiment of the present invention is a traffic adjustment support device for a target area including at least one entrance, at least one exit, and a plurality of routes connecting the entrance and the exit, A flow rate check unit and a scheduling processing unit are provided.

The flow rate check unit acquires flow rate information regarding a flow rate of a vehicle entering from the entrance and a flow rate of a vehicle exiting from the exit.

The scheduling processing unit is configured such that the congestion degree of each route determined according to the number of vehicles existing in each route and the characteristics of each route, the dissatisfaction degree of the driver when traveling each route, and the vehicles that drive each route. The flow rate of the vehicle traveling on each of the routes is calculated so that the objective function defined by using the

The figure which showed an example of the road traffic network which concerns on 1st Embodiment. The block diagram which shows the schematic structure of a traffic adjustment support system. The figure which showed an example of the traffic flow information. The figure which showed an example of route selection information. The figure which showed an example of the congestion degree in each road section of each time zone. The figure which showed an example of the amount of change of the congestion amount and congestion degree of each road section in each time zone when one vehicle changes a route. The figure which showed an example of an inconvenience degree. The figure which showed an example of the relation network of a path|route and a flow volume. The figure which showed an example of traffic adjustment information and prediction information. 3 is a flowchart of an operation according to the first embodiment. The figure which showed the other example of traffic adjustment information and prediction information. The figure showing other examples of traffic regulation information and prediction information. The figure which showed an example of the road which concerns on 2nd Embodiment. The figure showing an example of traffic regulation information and prediction information concerning a 2nd embodiment. The figure which showed the other example of traffic adjustment information and prediction information. The figure which showed an example of the road traffic network which concerns on 3rd Embodiment. The figure showing an example of traffic regulation information and prediction information concerning a 3rd embodiment. The figure which shows an example of the hardware constitutions concerning one Embodiment of this invention.

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

(First embodiment)
FIG. 1 shows an example of a road traffic network according to the first embodiment. The road traffic network in FIG. 1 includes a target area (target traffic network) according to the present embodiment and a non-target area outside the target area. Roads in the target area are outlined, and roads in the non-target area are shaded. At the boundary between the target area and the non-target area, there are entrances and exits to the target area. In FIG. 1, the inlet and the outlet are represented by semicircular circumferential curves. In the first embodiment, the boundary between the target area and the non-target area has both the inlet and the outlet, but it is possible to have only one of the inlet and the outlet. In this example, there are a plurality of inlets and a plurality of outlets, but at least one of each may be present. The circled portions in the road traffic network represent confluences such as intersections. A road section is shown between each confluence.

In FIG. 1, a route A indicated by a solid line arrow, a route B indicated by a coarse-pitch broken line arrow, and a route C indicated by a fine-pitch broken line arrow are traveled by the vehicle from the entrance 2 to the exit 7. An example of a route is shown. That is, each of the routes A, B, and C is a route connecting the entrance 2 and the exit 7. The route H indicated by the one-dot long chain line represents an example of a travel route from the entrance 9 to the exit 7. It is assumed that an operator, etc. at the Road Traffic Control Center will make traffic adjustments, such as guidance for route changes, to drivers of vehicles in the target area or non-target areas. For example, by operating signals, road signs, electronic bulletin boards, etc., route guidance and inflow control into the road traffic network can be performed (traffic adjustment). For example, a driver scheduled to travel on the route A can change another route by guiding the operator to another route (route B, route C, or the like). It should be noted that whether to actually change the route depends on the intention of the driver. The traffic adjustment support system according to the present embodiment calculates a traffic adjustment plan for reducing congestion of the road traffic network and reducing driver dissatisfaction according to the traffic conditions in the target area, and the operator It is intended to assist operators in making traffic adjustment decisions.

FIG. 2 is a block diagram showing the traffic adjustment support system according to the present embodiment. The traffic adjustment support system of FIG. 2 includes an entrance sensor 101, an exit sensor 102, a traffic adjustment support device 100, an output unit 109, and an input unit 110. The traffic adjustment support device 100 includes a flow rate check unit 103, an available route calculation unit 104, a route selection information storage unit 105, and a scheduling processing unit 120. The scheduling processor 120 includes a congestion degree calculator 106, an inconvenience degree calculator 107, and a scheduler 108.

The entry sensor 101 and the exit sensor 102 are present on an entrance and an exit of the target area, on a road connecting the entrance and the exit, and detect a vehicle that enters the target area and a vehicle that exits the target area. The vehicle to be detected may include automobiles (electric vehicles, gasoline vehicles, etc.), motorcycles, and any other vehicles that enter or leave the target area. However, only a specific type of vehicle such as an automobile may be the detection target. The electric vehicle may include a hybrid vehicle and a plug-in hybrid vehicle. The entrance sensor 101 and the exit sensor 102 are arranged at all entrances and exits in order to acquire all entrances and exits of the target area.

The flow rate check unit 103 includes a flow rate information storage unit 103A. The flow rate check unit 103 acquires the detection information of the entry sensor 101 and the exit sensor 102 and stores the detection information in the information storage unit 103A. The detection information may be acquired directly from the entry sensor 101 and the exit sensor 102 by wired or wireless communication, or may be acquired from another server that collects the detection information. The flow rate check unit 103 generates information (traffic flow rate information) indicating the traffic flow rate of a vehicle entering or leaving the target area based on the detection information of the approach sensor 101 and the exit sensor 102. The flow rate check unit may create the traffic flow rate information, for example, at regular time intervals from the detection information acquired within the time. The flow rate check unit 103 may store the generated traffic flow rate information in the flow rate information storage unit 103A.

FIG. 3 shows an example of traffic flow information. FIG. 3(A) shows the traffic flow information regarding entry, and FIG. 3(B) shows the traffic flow information regarding exit. The traffic flow information related to the approach can be generated based on the detection information from the approach sensor. The traffic flow amount information regarding exit can be generated based on the detection information from the exit sensor. The traffic flow information in FIG. 3 holds information on the time of entry/exit and information on the entrance or exit, and by this, it is possible to express what time the traffic volume (flow rate) was at which time or time. The traffic flow information may include information other than that shown in FIG. For example, it may include vehicle types such as motorcycles, large vehicles (buses and trucks), electric vehicles, and vehicle information such as license plate information. These pieces of information may be obtained by mounting cameras on the entrance sensor 101 and the exit sensor 102, capturing images when the sensors pass, and reading them from a license plate or the like, or by performing wireless communication with the vehicle. Further, as a part of the vehicle information, information such as a battery type and a battery remaining amount may be acquired from the vehicle (electric vehicle) by wireless communication. Further, future traffic flow prediction information may be generated based on the detection information of the entry sensor and the detection information of the exit sensor, and the prediction information may be included in the traffic flow information. For example, the future traffic flow rate may be predicted assuming that the current traffic flow rate continues for a certain time in the future, or other known prediction methods may be used.

The available route calculation unit 104 holds in advance information about the road traffic network (all road sections, positions of all entrances and exits, distances of each road section, number of lanes, road capacity (described later), average traveling speed, etc.). ing. Alternatively, the information about the road traffic network may be stored in the storage device, and the available route calculation unit 104 may access the storage device and read the information. The available route calculation unit 104 calculates a route from each entrance to each exit of the target area based on the information about the road traffic network.

At this time, the available route calculation unit 104 may calculate the route in consideration of only the entrance and the exit included in the traffic flow information generated by the flow check unit 103. When the routes from all the entrances to all the exits are calculated, the number of routes increases, and the processing load and processing time of each processing unit (congestion degree calculation unit 106, inconvenience degree calculation unit 107, and calculation unit scheduling unit 108) described later increase. Because there is a possibility that For example, the traffic flow information of FIG. 3 includes only the entrance 2, the entrance 2, the entrance 9, the entrance 5 as the entrance, and the exit 7, the exit 8, the exit 4, and the exit 6 as the exits. In this case, the combination of the inlet and the outlet is (2,7), (2,8), (2,4), (2,6), (9,7), (9,8), (9,4). ), (9, 6), (5, 7), (5, 8), (5, 4), (5, 6) in 12 ways, and the available route calculation unit 104 determines the routes of the above combinations. calculate. It should be noted that it is not necessary to consider a combination having the same entrance and exit. Further, when calculating the route, it is not necessary to consider which exit the vehicle that has individually entered is actually heading for. In this way, by calculating routes only for the entrances and exits included in the traffic flow information, the number of calculated routes can be reduced, and the processing load and processing time of each processing unit can be reduced. Of course, if the processing load and the increase in processing time do not pose a problem, it is possible to calculate the route for all the entrances and all the exits of the target area.

The route selection information storage unit 105 stores route selection information relating to the possibility of route selection of which of the routes coupled to the entrance the driver of the vehicle entering from each entrance selects.

FIG. 4 shows an example of the route selection information stored in the route selection information storage unit 105. The route selection information of FIG. 4 has a table format and includes an entrance at which a vehicle enters, a route on which the vehicle travels, and a probability (route selection probability) that the vehicle travels on the route. For example, the top row of FIG. 4 means that a vehicle entering from the entrance 1 travels on the route J with a probability of 50%. The second row means that the vehicle entering from the entrance 1 travels along the route L with a probability of 50%.

This route selection information is calculated from statistical data such as past traffic flow rates and stored in advance. The route selection information may be generated by using the detection information accumulated in the information storage unit 103A.

The congestion degree calculation unit 106 receives information (available route, traffic flow rate, road traffic network information) from the available route calculation unit 104, and based on the information and the route selection information in the route selection information storage unit 105, congestion occurs. Degree calculation processing is performed. In the congestion degree calculation process, the congestion degree of each road section when a vehicle that has entered the target area selects a route according to the route selection information (when traffic adjustment is not performed) is calculated for each time zone of a fixed time interval. In addition, the travel route of the vehicle is instructed without following the route selection information, and the change amount of the congestion degree when traveling on the travel route (that is, when the route is changed by traffic adjustment) Calculate for each road section. The details will be described below.

First, the degree of congestion will be described. The congestion degree indicates how crowded the target road section is, and is determined according to the number of vehicles existing in the road section and the characteristics of the road section. As an example, the congestion degree can be calculated by dividing the number of vehicles existing in the road section (called a congestion amount) by the road capacity of the road section, which is an example of the characteristics of the road section. The road capacity is a numerical value of the capacity related to the number of vehicles that can be accommodated, and has a value according to the distance of the road section or the number of lanes, for example. In the case of the number of lanes, the larger the number of lanes, the larger the road capacity. The road capacity is assumed to be included in the road traffic network information acquired from the available route calculation unit 104. The calculation of the congestion degree described above is an example, and may be calculated by another method. For example, the road capacity may be subtracted from the number of vehicles existing in the target road section. The degree of congestion in this case is particularly called a protrusion amount. In the following, unless otherwise specified, the degree of congestion refers to the number of vehicles existing in the target road section (called the congestion amount) divided by the road capacity of the target road section, and the protrusion amount is the target. The description will be given assuming that the road capacity is subtracted from the number of vehicles existing in the road section.

The congestion degree calculation unit 106 first calculates the congestion amount of each road section in order to calculate the congestion degree of each road section when a vehicle that has entered the target area selects a route according to the route selection information. Specifically, for one vehicle included in the traffic flow information related to the approach, the probability of each route on which the vehicle travels is determined from the route selection information, and the number of vehicles corresponding to the probability is determined for each route. For example, from the top line of the traffic flow information relating to the approach in FIG. 3A, it can be seen that there is a vehicle entering from the entrance 2 at 6:00 on November 18, 2014. Based on the route selection information, this vehicle entering from the entrance 2 selects route A with a probability of 40% and route B with a probability of 60%. Therefore, it is considered that 0.4 vehicles have entered the route A and 0.6 vehicles have entered the route B. In this way, the number of vehicles entering each route is obtained.

It is estimated in which road section 0.4 vehicles that have entered the route A exist in each time zone. For example, it is assumed that the vehicle is traveling at a constant speed, and which road section of the route A is traveling in each time zone is calculated. As the traveling speed, the average traveling speed of each road section in the time zone may be used. It is assumed that this average traveling speed has been calculated by prior statistics. Alternatively, the speed may be set to 80 km/hour for an expressway and 60 km/hour for an urban area. The speed may be different for each road section. The speed may be different depending on the time of day. In this way, it is possible to grasp in which road section 0.4 vehicles that have entered the route A exist in each time zone. Similarly, it is possible to know in which road section 0.6 vehicles that have entered the route B exist in each time zone.

By performing such a process for all vehicles that have entered the target area within a fixed time, it is possible to predict the positions where all the target vehicles are present. Then, the congestion amount of each road section can be calculated by adding up the number of vehicles existing in each road section. The congestion amount of the road section is calculated by dividing the congestion amount by the road capacity of the corresponding road section.

FIG. 5 shows an example of the degree of congestion in each road section in each time period calculated by the degree-of-congestion calculating unit 106. This congestion degree is a congestion degree when a vehicle entering the target area selects a route according to the route selection information (when traffic adjustment is not performed). In this figure, the congestion degree of each road section in the time zone divided at intervals of 30 minutes, such as 7:00 to 7:30, 7:30 to 8:00, 8:00 to 8:30, is shown. There is. The width of each time period may be set arbitrarily. When traffic adjustment is not performed in the road section k (k is an integer from 1 to K, K is an integer from 1 or more) in the time zone t (t is an integer from 1 to T, T is an integer of 1 or more) The congestion degree is represented by dkt. In FIG. 5, the congestion degree of the road section 2 in the time zone from 8:00 to 8:30 is extremely high, which is 200% or more. The road capacity of the road section k is represented by qk.

Next, the amount of change in congestion degree due to traffic adjustment (route change) will be described. FIG. 6 shows an example of the amount of change in the congestion amount and the amount of change in the congestion degree in each road section in each time zone when one vehicle changes the route. The entry time is the time when the vehicle entered, the entrance is the entrance at which the vehicle entered, the exit is the exit at which the vehicle exits, and the route is the route changed by traffic adjustment, etc. without the vehicle following the route selection information ( Change route). The changed route is represented by j (j is an integer from 1 to J, J is an integer of 1 or more), and it is assumed that there are J routes from the same entrance to the same exit. FIG. 6 shows a case where a vehicle entering from the entrance 2 at 6:00 on November 18, 2014 changes the route to the route C according to the traffic adjustment. The calculation of the change amount of the congestion degree will be described in detail below.

First, the congestion degree calculation unit 106 obtains an increase/decrease in the number of vehicles entering each route as the route is changed. At the time of calculating the congestion degree described above, the vehicles that entered from the entrance 2 at 6:00 on November 18, 2014 were 0.4 vehicles on the route A and 0.6 vehicles on the route B. The vehicle was considered to have entered. Therefore, when the vehicle is rerouted to the route C, the route A has 0.4 vehicles, the route B has 0.6 vehicles, and the route C has 1 vehicle. It will be. That is, it can be considered that -0.4 vehicles are traveling on the route A, -0.6 vehicles are traveling on the route B, and +1 vehicles are traveling on the route C. Next, the congestion degree calculation unit 106 estimates in which road section the vehicle that has entered each route exists in each time zone. This may be obtained by the same method as when calculating the congestion degree.

In the example of FIG. 6, the road section 1 corresponds to the first road section of the route A, the road section 2 corresponds to the first road section of the route B, and the road section 3 corresponds to the first road section of the route C. When the vehicle enters the routes A, B, and C, it is assumed that the vehicle is traveling in those road sections during the time period from 7:00 to 7:30. The number is -0.4 (-40 in percentage notation), the number of vehicles in road section 2 is -0.6 (-60 in percentage notation), and the number of vehicles in road section 3 is +1 (+100 in percentage notation). Further, here, since the congestion degree is calculated by the congestion amount/road capacity, the change amount of the congestion degree is calculated by the change amount of the congestion amount/road capacity. Thereby, the change amount of the congestion amount and the change amount of the congestion degree due to the change to the route C are calculated as shown in FIG. Next, in the time zone from 7:30 to 8:00, the vehicle has already passed through the road section 1, and the road sections 2 and 3 are still traveling on those road sections (existing on the road sections 2 and 3). To do. In this case, the amount of change in road section 1 is 0, and the amount of change in road sections 2 and 3 is the same as before. In the time zone from 8:00 to 8:30, if any road section has already been passed, the change amount becomes zero.

As described above, the congestion degree calculating unit 106 determines the change amount ejkt of the congestion degree of each road section k in each time zone t when one vehicle is changed to the route j, for all J routes. Do to. Further, by performing the same process for all the target vehicles, the amount of change in the congestion degree due to the route change can be obtained for each road section in each time zone for all the vehicles and all the route changes.

The inconvenience degree calculation unit 107 calculates the inconvenience degree of each available route based on the information (available route, traffic flow rate, road traffic network) from the available route calculation unit 104. The degree of inconvenience is a numerical value of the inconvenience that the driver feels when passing the route. For example, it may be the reciprocal (unpopularity) of the route selection probability when there is no traffic adjustment, or a normalization of the reciprocal. Alternatively, the distance of each route, the time required for passing, or the time normalized may be used. Alternatively, it may be the minimum required number of times of refueling of fuel or electricity in the selected route, or the amount replenished by the replenishment divided by the number of times of replenishment (replenishment efficiency).
Further, the inconvenience level may be set in advance for each road section, and the inconvenience level of each route may be the sum of the inconvenience levels of each road section constituting the route. For example, the degree of inconvenience of a road section is determined by the number of signals that the road section holds, the number of roads, the number of lanes, the number of service areas, the number of popular spots, the number of gas stations, the number of chargers and quick chargers for electric vehicles, etc. Good. In addition, information about the current situation such as good visibility, weather, the presence or absence of construction or accident in the road section, and road surface condition may be digitized and considered. Further, a plurality of types of inconvenience levels may be calculated, and the total inconvenience level may be calculated from the sum or average value. The degree of inconvenience may be determined by an absolute evaluation for each route. Alternatively, the degree of inconvenience may be determined by relative evaluation within a group in which routes having the same entrance and exit are put together. The inconvenience degree calculation unit 107 may previously calculate the inconvenience degree for all routes in the road traffic network and store the inconvenience degree therein.

FIG. 7 shows an example of the degree of inconvenience. The degree of inconvenience is calculated for each route. In FIG. 7, one inconvenience level corresponds to the route, but a plurality of types of inconvenience levels may be associated.

The scheduler 108 performs a scheduling process for planning the traffic adjustment of vehicles entering the target area so as to balance the congestion in the target area and the dissatisfaction of the driver. The traffic adjustment plan is specifically to calculate the flow rate of a vehicle traveling on each route (yij described later) based on the flow rate of the vehicle at each entrance and each exit.

In the scheduling process, first, a process of generating a relational network between a route and a flow rate (network generation process) is performed. FIG. 8 shows an example of a relational network. In the relational network, there are three types of nodes: an entrance node representing an entrance, an exit node representing an exit, and a route node representing a route. The scheduler 108 generates each entrance node corresponding to the entrance included in the traffic flow information related to the approach. Since the traffic flow information related to the approach of FIG. 3A includes the entrances of the entrance 2, the entrance 2, the entrance 9, and the entrance 5, the scheduler 108 creates the entrance nodes of the entrance 2, the entrance 9, and the entrance 5. To do. Even if the same entrance is included in the traffic flow information related to the approach in duplicate, it is not necessary to create the entrance node in duplicate.

The scheduler 108 creates an exit node corresponding to the exit included in the traffic flow information regarding exit. Since the exit flow amount information in FIG. 3B includes exit 7, exit 8, exit 4, and exit 6, the scheduler 108 causes the exit node of exit 7, exit 8, exit 4, and exit 6 to exit. To create. Even if the same exit is included in the exit traffic volume in duplicate, it is not necessary to create the exit node in duplicate. Further, the scheduler 108 sets the generated egress nodes as a set of groups and generates egress node groups as many as the ingress nodes. In the case of the traffic flow information relating to the approach of FIG. 3A, since there are three entrance nodes, three sets of exit node groups are generated.

The entrance node is connected to each exit node included in the group corresponding to the entrance node by an arc. A set of an entrance node and an exit node connected by this arc represents a set of an entrance and an exit from which the vehicle enters the target area. The scheduler 108 extracts all the routes connecting the entrances and exits from the information about the road traffic network, and generates route nodes representing the extracted routes. Then, the route node is connected to the exit node by an arc.

The scheduler 108 uses the relational network to perform an optimization process of calculating the flow rate (yij described later) of the vehicle traveling on each route so that the congestion reduction in the target area and the dissatisfaction reduction of the driver are both achieved. The optimization process is performed, for example, by solving the following optimization problem.

“Minimize” means to minimize the formula (objective function) described below. "Sub.to" means to comply with the conditions (constraints) described under Sub.to. By solving this optimization problem, the combination of yij that minimizes the objective function αZ+βP+γC is obtained. Although the objective function is minimized here, the objective function may be equal to or less than the threshold value or within a predetermined range. Minimizing the objective function, making it equal to or less than a threshold value, or keeping it within a predetermined range determines the flow rate (yij) of the vehicle traveling on each route so that the value of the objective function satisfies a predetermined condition. Means to calculate.

The above optimization problem, objective function, and constraint conditions will be described in more detail.

Α, β, γ in the objective function are parameters, and are coefficients for weighting Z, P, C. The coefficient value is given in advance.

The variable C is a total value of driver dissatisfaction on each route when the route is changed (traffic adjustment), and is represented by the following formula. Here, the case where traffic is adjusted means a case where the number of vehicles traveling on each route is adjusted as calculated by the optimization process.
yij represents the flow rate via the route j connected to the exit node i when traffic is adjusted.
cij represents the inconvenience of the route at the route node ji connected to the egress node i. Here, the dissatisfaction degree of the driver traveling on the route j is the same as the inconvenience degree on the route j. In addition, when traffic adjustment is not performed, the flow rate via the route j connected to the exit node i is expressed as y0ij.

Hi included in the constraint condition 1 is that if there are I (I is an integer of 1 or more) egress nodes in the relational network, one of the egress nodes i (i is an integer from 1 to I) is Indicates the flow rate at the outlet pointed to. It is assumed that Ji route nodes are connected to the egress node i (i is an integer from 1 to I), and one of the Ji route nodes is denoted by ji. Note that hi may be calculated on the assumption that a route is selected according to the route selection information in the relation network of the route and the flow rate. For example, if there are five vehicles entering from the entrance 2 and 70% of the vehicles heading to the exit 7, a flow rate of 3.5 is set in the exit node 7 connected to the entrance node 2. In this way, the flow rate hi for the outlet node i is obtained.

Here, even if the flow rate of a certain path is increased, the flow rate of the other path (another path having the same inlet and the same outlet as the certain path) decreases, and the flow rate hi of the exit node i does not change. That is, the sum total of the flow rates yij of the respective routes matches the flow rate hi of the exit node i. Therefore, the above constraint condition 1 is satisfied.

The variable P in the objective function represents the sum of the protrusion amounts greater than 0 in the protrusion amount pkt of all road sections in all time zones. That is, P is expressed by the following equation. R+ represents a set of protrusion amounts pkt larger than 0.

The amount of protrusion here is obtained by subtracting the road capacity from the number of vehicles (congestion amount) when traffic is adjusted. The number of vehicles (congestion amount) when traffic is adjusted can be calculated by the product of the congestion degree and the road capacity when traffic is adjusted. The degree of congestion when traffic is adjusted is represented by the sum of the degree of congestion before traffic adjustment and the product of the amount of change in the degree of congestion associated with a route change per vehicle and the number of vehicles whose routes have been changed. The number of vehicles whose routes have been changed is represented by a value obtained by subtracting the flow rate passing through route j when traffic is not adjusted from the flow rate passing through route j when traffic is adjusted. That is, it is represented as yij-y0ij. Therefore, the protrusion amount pkt when traffic is adjusted is expressed by the following equation.

The part surrounded by the outermost brackets (braces) corresponds to the congestion degree when traffic is adjusted.
qkt represents the road capacity of the road section k in the time zone t. dkt represents the congestion degree of the road section k in the time zone t before traffic adjustment. eijkt represents the change amount of the congestion degree of the road section k in the time zone t when one vehicle is changed to the route j for the route j connected to the exit node i. Note that dkt, qk, and eijkt can be acquired from the information received from the congestion degree calculation unit 106.

If the congestion degree dkt and the congestion degree change amount eijkt are expressed as a percentage, the value in the braces of the above equation may be divided by 100.

In addition, the constraint condition 2 (P≦P0) described above is introduced in order to reduce the variable P from the sum P0 of the protrusion amounts larger than 0 before traffic adjustment.

Similar to P, the sum P0 of the protrusion amounts before traffic adjustment before P0 is calculated by calculating the protrusion amount p0kt before traffic adjustment in the road section k in the time zone t, and the sum of p0kt greater than 0. A formula for calculating the protrusion amount p0kt is shown in Formula 5. The formula for calculating P0 is shown in Formula 6.

The variable Z in the objective function is a value obtained by subtracting 1 from the maximum value of the congestion degree in all time zones and all road sections when traffic is adjusted. That is, it is represented by the following formula.
The above "MAX" means a value in which the part enclosed by the curly braces becomes the maximum in all k and all t. Z is for preventing the occurrence of a time zone or a road section where the degree of congestion (or the amount of protrusion) is extremely high. When the congestion degree is displayed as a percentage, 100 may be subtracted instead of 1. The present embodiment can operate even if Z is not included in the objective function.

As will be understood from the above description, the variables Z, P, and C in the objective function are represented by a function having the flow rate yij of each path as a variable. In the above objective function, the total sum P of protrusion amounts larger than 0 when traffic is adjusted is used, but instead of P, the total congestion degree when traffic is adjusted may be used.

It should be noted that the scheduler 108 may distinguish the vehicle capable of traffic adjustment from the vehicle not capable of traffic adjustment based on the approach time of the traffic flow rate related to the approach in the scheduling process. For example, a vehicle that has entered within a certain time (3 minutes, 5 minutes, etc.) from the current time is a vehicle capable of traffic adjustment, and the other vehicles are vehicles not capable of traffic adjustment. This is because, for example, a vehicle that has entered 10 minutes or more before the current time is expected to have passed a merging point where a route can be already selected, and the route cannot be changed. For example, the routes A, B, and C shown in the example of the road traffic network in FIG. 1 cannot be changed to another route after the first confluence point. In this case, in the scheduling process, it is possible to treat the vehicles that can adjust the traffic, and treat the vehicles that cannot adjust the traffic as traveling according to the selection probability of each route.

By solving the optimization problem shown above, the combination of yij that minimizes the objective function αZ+βP+γC is obtained. As described above, yij represents the flow rate via the route j connected to the exit node i when traffic is adjusted.

Another constraint condition may be added to the constraint condition of the optimization problem. For example, a constraint condition that the total amount of change in dissatisfaction does not exceed a certain reference value may be added. Alternatively, each road section may be weighted and a constraint condition may be added so as to avoid an increase in congestion degree of main roads.

The scheduler 108 generates traffic adjustment information based on yij obtained as described above. The format of the traffic adjustment information is not limited to a particular format, but it may be considered that it represents what amount of vehicle has entered from which entrance and on what route.

For example, there is one such as "increase the number of vehicles entering from the entrance 2 and selecting the route C by 50%". In the case of this example, information on “entrance”, “route”, and “increase rate” is required. The “entrance” information may identify the entrance represented by the entrance node in which the arc is connected to the exit node i from the relation network. The “route” may be the route that the route node ji means. The “rate of increase” can be obtained by dividing the value obtained by subtracting y0ij from yij by y0ij.

In addition, as another example of the traffic adjustment information, it is possible to generate such as "Allow 50% of vehicles entering from the entrance 2 to select the route C". In this case, the flow rate flowing through the path C may be divided by the total flow rate entering the entrance node. More specifically, as shown in Expression 8, the flow rate yij flowing through the path j may be divided by the sum of the flow rates of the outlet nodes connected to the inlet node connected to the outlet node i.

The target yij for which the traffic adjustment information is generated may be only yij in which the value obtained by subtracting y0ij from yij is greater than 0, or targeting only the upper X yij in descending order of the value obtained by subtracting y0ij from yij. Alternatively, all yij may be targets, or the target yij may be selected based on other criteria.

Further, the scheduler 108 generates information (prediction information) regarding the congestion degree of the target section and the driver's dissatisfaction degree when the traffic is adjusted according to yij obtained in the optimization process. This may be calculated using the congestion degree and the driver's dissatisfaction degree when the solution of the optimization problem is obtained. For example, as the prediction information, information indicating the congestion degree of each road section when traffic is adjusted may be generated. Further, it is also possible to generate information indicating the total amount of change in driver dissatisfaction, that is, the difference between the total driver dissatisfaction when traffic is adjusted and the total driver dissatisfaction before traffic adjustment. The amount of change in driver's dissatisfaction can be obtained by setting C0 as the total driver's dissatisfaction before traffic adjustment and subtracting C0 from C. Instead of the total change amount of the driver's dissatisfaction level, information indicating the total value of the driver's dissatisfaction level after the traffic adjustment may be generated.

The prediction information in the case where the traffic adjustment is performed only according to the target yij for which the traffic adjustment information is generated may be generated. In this case, except for yij for which the traffic adjustment information is generated, the prediction information may be calculated by fixing to y0ij, calculating the congestion degree and the driver's dissatisfaction degree. As a result, the accuracy of the prediction information can be improved.

The output unit 109 outputs the traffic adjustment information and the prediction information generated by the scheduler 108. The output unit 109 may be a monitor capable of displaying information on a screen, or a communication device that transmits information to a terminal held by an operator by wire or wireless communication.

FIG. 9 shows an example of the traffic adjustment information and the prediction information displayed on the output unit 109. As the first prediction information, in the image of the road traffic network shown in FIG. 1, the congestion degree of each road section is displayed in a color corresponding to the congestion degree. The image of the road traffic network to be displayed may be held by the output unit 109 or the scheduler 108. Further, instead of the image of the road traffic network, a correspondence table of road sections and congestion degrees may be displayed. In this case, the road sections may be displayed in descending order of congestion degree. Further, as the second prediction information, the total amount of change in driver dissatisfaction is displayed. The operator can make actual traffic adjustments by referring to the displayed information. As a concrete method of traffic adjustment, measures such as changing the display of the electronic bulletin board on the road, opening and closing the ramp way, and changing elements that are incentives for route selection such as road tolls and facility usage charges are taken. It may be possible to guide the driver to a desired route. In this way, the traffic adjustment information and the prediction information serve as an index for the operator's judgment for traffic adjustment that both reduces congestion in the target area and reduces driver dissatisfaction.

The input unit 110 is an input device for an operator to input various instructions. The input unit 110 may be any device capable of inputting information, such as a touch panel, a keyboard, or a mouse.
The operator can input an instruction to correct the contents of the traffic adjustment information displayed on the output unit 109. For example, when the traffic adjustment information that “direct 50% of vehicles entering from the entrance 2 to the route C” is displayed, an instruction to increase or decrease the ratio from 50% or a route to be directed from the route C is displayed. It is conceivable to input an instruction to make another route. The input information may be sent to the scheduler 108, the scheduler 108 may add the information as a constraint condition, recalculate the traffic adjustment information and the prediction information, and display them on the output unit 109. The operator can grasp the difference in effect between the two by comparing the predicted traffic adjustment information calculated by the system with the traffic adjustment information corrected by himself.

As another example of the input instruction, it may be instructed not to drive the vehicle on a specific route such as “direct 0% of the vehicle entering from the entrance 2 to the route A”. Then, this may be added as a constraint condition to solve the optimization problem. Accordingly, for example, when the route or the road sections forming the route are closed due to an accident or the like, it becomes possible to predict the congestion degree of each road section in the future.

Moreover, you may input the instruction|indication which changes the kind of inconvenience degree used at the time of optimization processing. For example, the type of the inconvenience level of the route may be changed from the inconvenience level related to the distance of the route to the inconvenience level of the minimum required fuel or electricity replenishment. In this case, the inconvenience degree of the type instructed by the operator is calculated by the inconvenience degree calculation unit 107 as necessary, and the scheduler 108 may perform the optimization process again using the inconvenience degree of the instructed type. ..

Further, the operator may input desired traffic adjustment information for some routes, add the input information as a constraint condition, perform optimization processing, and calculate traffic adjustment information and prediction information. .. Alternatively, the prediction information may be calculated on the assumption that the operator inputs desired traffic adjustment information for a part of the routes and otherwise selects the route according to the route selection information. FIG. 11 shows an example of the prediction information calculated when it is assumed that the operator specifies traffic adjustment information for some routes and the rest is selected according to the route selection information. The operator has instructed 80% of the vehicles entering from the entrance 2 to select the route A. The scheduler 108 calculates the prediction information on the assumption that 80% of the vehicles entering from the entrance 2 select the route A and the other cars select the route according to the route selection information. The remaining 20% of vehicles may select routes at a ratio according to the magnitude of each probability of routes other than route A. In the example of FIG. 11, the total amount of change in dissatisfaction degree is smaller than that in the case of FIG. 8, but the total congestion degree increases.

Alternatively, the operator may input an instruction not to perform traffic adjustment (that is, an instruction to match all yij with y0ij), and the scheduler 108 may calculate the prediction information in that case. FIG. 12 shows an example of the prediction information when the operator gives an instruction not to adjust the traffic. In this case, the scheduler 108 may match the flow rate yij due to traffic adjustment with y0ij to calculate the prediction information. Since traffic adjustment is not performed, the total amount of change in driver dissatisfaction is 0, but the total congestion level increases more than in the cases of FIGS. 8 and 11. Therefore, the operator first confirms the prediction information when traffic adjustment is not performed in this way, and if the total congestion degree is higher than the threshold value, the operator calculates the prediction information by the optimization process of this system and adjusts the traffic adjustment. You may go.

FIG. 10 is a flowchart of the basic processing according to the first embodiment.

Each time the entry sensor 101 and the exit sensor 102 acquire detection information, the detection information is transmitted to the flow rate check unit 103 (S101).

The flow rate check unit 103 generates traffic flow rate information based on the received detection information and sends it to the availability calculating unit 104 (S102). The flow rate check unit 103 may generate the traffic flow rate information at regular intervals, or may generate the traffic flow rate information each time the detection information is received. The traffic flow information may be output at the created timing, every time a certain period of time elapses, or when a command from the available route calculation unit 104 or the scheduler 108 is received.

The available route calculation unit 104 receives the traffic flow information, and calculates the available route based on the entrance and the exit included in the traffic flow information (S103). The available route calculation unit 104 sends the calculated available route, traffic flow information, and information about the road traffic network to the congestion degree calculation unit 106, the inconvenience degree calculation unit 107, and the scheduler 108 (S104).

The congestion degree calculation unit 106 calculates the congestion degree of each route and the amount of change in the congestion degree based on the information received from the available route calculation unit 104 and the route selection information in the route selection information storage unit 105, and the scheduler It sends to 108 (S105).

The inconvenience degree calculation unit 107 calculates the inconvenience degree of each route based on the information received from the available route calculation unit 104 (S106). The inconvenience level calculation unit 107 may calculate a plurality of types of inconvenience levels, calculate a total inconvenience level by combining the plurality of types of inconvenience levels, such as an average or a sum, and use the inconvenience levels.

The scheduler 108 acquires information from the available route calculation unit 104 and performs scheduling processing. Specifically, first, based on the information from the available route calculation unit 104, a relation network between the route and the flow rate is generated (S107). Next, the scheduler 108 performs optimization processing based on the congestion degree, the change amount of the congestion degree, the inconvenience of the route, and the relational network, and generates traffic adjustment information and prediction information (S108). The output unit 109 outputs traffic adjustment information and prediction information on a screen or the like.

As described above, according to the first embodiment, traffic adjustment information is generated and displayed to the operator so as to reduce congestion in the target area and reduce driver dissatisfaction. In addition, prediction information regarding the effect obtained when the traffic adjustment is performed according to the traffic adjustment information is generated and displayed to the operator. By referring to these displayed information, the operator can easily and quickly perform traffic adjustment to alleviate congestion in the target area and reduce driver dissatisfaction.

(Second embodiment)
In the second embodiment, when there are a plurality of facilities along a certain road, the route is distinguished according to which facility to use, and which facility (route) should be used by each vehicle. Create adjustment information. For example, if the vehicle is an electric vehicle and needs to be charged before reaching the exit, the driver stops at a charging area (such as a service area (SA) or a parking area (PA)) equipped with a charger for the electric vehicle. necessary. However, if the charging area to be used is left to the discretion of the driver, the charging area may be concentrated in the charging area just before the electricity runs out or a popular charging area, the facility may be crowded, and the driver may be dissatisfied. Therefore, it becomes possible to create traffic adjustment information that avoids congestion in a specific charging area, and an operator can guide the charging area based on the information. In addition, when the driver has to take a break before reaching the exit because the distance from the entrance to the exit is long, when considering which of the breaks on the route to stop at, If the rest area to be used is left to the discretion of the driver, it may concentrate on the popular rest area, the facility may become crowded, and the driver's dissatisfaction may increase. Therefore, it becomes possible to create traffic adjustment information that avoids congestion at a specific rest area, and the operator can guide the rest area based on that information.

Hereinafter, this embodiment will be described in detail by taking a service area as an example of a facility. At this time, the description will be focused on the parts different from the first embodiment, and the description overlapping with the first embodiment will be omitted.

FIG. 13A, FIG. 13B, and FIG. 13C show an example of a road targeted by the second embodiment. 13(A) to 13(C) all represent the same road (single road), and the stop patterns to the service area (SA) are different. The stop-off patterns shown in FIGS. 13A to 13C are represented as routes A, B, and C, respectively. In the first embodiment, if the roads from the entrance to the exit are the same, they are the same route, but in the second embodiment, even if the roads from the entrance to the exit are the same, which service area is Differentiate routes according to whether they are used. An entrance/exit exists at a portion indicated by a circle in FIG. 13, and a vehicle can enter and exit from the entrance/exit (the circle is indicated at the same location in FIGS. 13A to 13C).

The entrance sensor 101 and the exit sensor 102 are present at all the entrances and exits as in the first embodiment, and the entrance sensor 101, the exit sensor 102, and the flow rate check unit 103 operate in the same manner as in the first embodiment. Vehicle information such as the battery type and the remaining battery level may be acquired from the electric vehicle as part of the detection information. Alternatively, the vehicle information may be acquired from the electric vehicle by real-time wireless communication. If the information such as the remaining travelable distance can be acquired as the vehicle information, the information may be acquired. Alternatively, the device may be equipped with a means for calculating the remaining travelable distance from information such as the remaining battery level. Alternatively, the remaining battery level of the vehicle when entering from each entrance may be set to a fixed value determined from past statistical values or a value according to a statistical distribution (probability distribution, etc.). The road section between the service areas may travel at a speed determined in advance in the same manner as in the first embodiment, and the amount of electricity required to move between the service areas may be predetermined.

As shown in FIGS. 13(A) to 13(C), there are a plurality of service areas on a single road. As described above, the routes in the second embodiment are distinguished according to the facility (service area) to be used. For example, the route A shown in FIG. 13(A) means that “the vehicle enters from the entrance 1 and uses the service area (SA) 3 to exit from the exit 6”. The route B means that the vehicle enters from the entrance 1, uses SA2 and SA5, and exits from the exit 6. The route C means that the vehicle enters from the entrance 1 and exits from the exit 6 using SA1 and SA4. As described above, in the second embodiment, even if the roads to travel on are the same, if the facilities to be used are different, they are treated as different routes.

The available route calculation unit 104 creates an available route, as in the first embodiment. At this time, a condition regarding the number of times the facility (service area) is used may be designated in advance as a constraint, and a route may be generated according to this condition. For example, an electric vehicle may be preset with a limit number of charging up to two times during traveling, and the available routes may be calculated so as to satisfy the condition regarding this limit number. In addition, a condition regarding the distance between the facilities to be used may be designated. The routes shown in FIGS. 13A to 13C show a part of the routes calculated in this way.

The congestion degree calculation unit 106 calculates the congestion degree and the amount of change in the congestion degree using the facility capacity instead of the road capacity in the first embodiment. The facility capacity represents the capacity related to the number of vehicles that can be accommodated, such as the number of electric vehicle chargers, the number of facilities provided in the facility (service area), the allowable number of vehicles, and the allowable number of vehicles. In this embodiment, the congestion relief of the facility is targeted, not the congestion relief of the road.

Similar to the first embodiment, the inconvenience level is set for each route, and the inconvenience level may be calculated in the same manner as in the first embodiment. Alternatively, the inconvenience level is set for each facility, and the inconvenience level of the route may be calculated by adding together the inconvenience levels of the facilities to be used. Also, the facility with a quick charger may be made less convenient than the facility with only a normal charger. The inconvenience level of the facility can be set to a value corresponding to the amount of charge (charge amount), and the inconvenience level can be increased as the amount of charge per charge is smaller.

The scheduler 108 performs the scheduling process as in the first embodiment. Basically, the congestion degree of the road section in the first embodiment may be replaced with the congestion degree of the facility. In this embodiment, a condition regarding charging or a condition regarding staying time in the service area may be set as a constraint condition for the vehicle.

For example, as a constraint condition regarding charging, a constraint condition that charging is performed until the battery remaining amount becomes at least a certain value or a certain SOC (State Of Charge) or reaches an upper limit may be set. When charging up to a certain value or a certain SOC (State Of Charge) or more, how much to charge may be determined from past statistical values, or may be determined according to statistical distribution (probability distribution, etc.) Good. In addition, a constraint condition may be set such that the battery level always stops at a certain value or more (stops charging).

Further, as the constraint condition regarding the staying time in the service area, the staying time may be determined as a function according to the charge amount (charge amount). At this time, the time the driver takes a break may be added. The time to take a break may be set to a fixed value determined from past statistical values or a value according to a statistical distribution (probability distribution, etc.). In order to simplify the processing, the staying time in the service area may be a fixed value, or may be determined according to a statistical distribution (probability distribution or the like).

FIG. 14 shows an example of traffic adjustment information and prediction information in the second embodiment. Similar to the first embodiment, it is possible to generate the traffic adjustment information and the prediction information on the input unit 110 based on the input information from the operator. FIG. 15 shows an example of traffic adjustment information and prediction information generated when the operator receives input information instructing not to perform traffic adjustment. As can be understood by comparing with FIG. 14, it can be confirmed that the congestion degree of the specific facility (SA3) increases without traffic adjustment.

As described above, according to the second embodiment, traffic adjustment information is generated and displayed to the operator so as to reduce driver dissatisfaction and alleviate congestion of facilities. In addition, prediction information that represents the expected effect when traffic adjustment is performed according to the traffic adjustment information is generated and displayed to the operator. By adjusting the traffic with reference to the displayed information, the operator can easily and quickly perform the traffic adjustment that reduces the dissatisfaction of the driver and alleviates the congestion of the facility group.

(Third Embodiment)
The third embodiment is a combination of the first and second embodiments. In the third embodiment, in the road traffic network according to the first embodiment, routes are further distinguished according to facilities used by vehicles. FIG. 16 shows an example of a plurality of routes distinguished according to facilities used by vehicles in the road traffic network according to the third embodiment. When the vehicle enters through the entrance 2 and travels on the same road (the road indicated by the route A (see FIG. 1) in the first embodiment) and exits through the exit 7, which facility is used on the way There are multiple routes depending on whether or not. Route A0 is used when no facility is used, route A1 is used when only facility 1 on the way is used, and route A2 is used when only facility 2 on the way is used. When using both the facilities 1 and 2, the route A3 (not shown) is used.

The items such as the traffic capacity and the congestion degree of the road section are the same as in the first embodiment, and the items such as the facility capacity and the congestion degree of the facility are calculated in the same manner as in the second embodiment. Based on this, the optimization process may be performed. Alternatively, after performing the optimization processing of the congestion degree and the dissatisfaction degree of the road section as in the first embodiment, each route is subdivided for each usage facility as in the second embodiment to obtain the congestion degree of the facility. Also, optimization processing regarding driver dissatisfaction may be performed.

FIG. 17 shows an example of the traffic adjustment information and prediction information calculated in the third embodiment.
As a difference from the first embodiment, a triangular mark representing SA is added to the image of the road traffic network. The triangular mark is colored according to the degree of SA congestion. The routes C, H, and K shown in the traffic adjustment information include entrances, exits, roads to be used, and facilities to stop by.

As described above, in the third embodiment, the traffic adjustment information can be generated in consideration of not only the congestion degree of the road traffic network but also the congestion degree of the facilities along the road.

Each process in the above-described embodiments can be realized by software (program). Therefore, the traffic regulation support device in the above-described embodiment can be realized by using a general-purpose computer device as basic hardware and causing a processor mounted in the computer device to execute a program.

FIG. 18 shows a hardware configuration example including the traffic adjustment support device according to the embodiment of the present invention. The traffic adjustment support device includes a processor 201, a main storage device 202, an auxiliary storage device 203, a communication device 204, a device interface 205, an output device 206, and an input device 207, which are connected via a bus 208 to a computer device. Can be realized as

The processor 201 reads the program from the auxiliary storage device 203, expands the program in the main storage device 202, and executes the program, whereby the flow rate check unit 103, the available route calculation unit 104, the congestion degree calculation unit 106, and the inconvenience degree calculation unit. The functions of 107, the scheduler 108, and the scheduling processing unit 120 can be realized.

The traffic adjustment support device of the present embodiment may be realized by previously installing a program executed by the traffic adjustment support device in a computer device, or by storing the program in a storage medium such as a CD-ROM, Alternatively, it may be realized by being distributed via a network and appropriately installed in a computer device.

The network interface 204 is an interface for connecting to a communication network. Communication between the flow rate check unit 103 and the entry sensor 101, the exit sensor 102, etc. may be realized by the network interface 204. Although only one network interface is shown here, a plurality of network interfaces may be installed.

The device interface 205 is an interface connected to a device such as the external storage medium 209. The external storage medium 209 may be any recording medium such as an HDD, a CD-R, a CD-RW, a DVD-RAM, a DVD-R, and a SAN (Storage area network). The flow rate information storage unit 103A and the route selection information storage unit 105 may be connected to the device interface 205 as the external storage medium 209.

The output device 206 includes a display display such as an LCD (Liquid Crystal Display) and a CRT (Cathode Ray Tube), and realizes the function of the output unit 109.

The input device 207 includes an input device such as a keyboard and a mouse, and realizes the function of the input unit 110. An operation signal for operating the input device from the input unit 207 is output to the processor 201. The input device 207 or the output device 206 may be externally connected to the device interface 205.

The main storage device 202 is a memory device that temporarily stores instructions executed by the processor 201, various data, and the like, and may be a volatile memory such as DRAM or a non-volatile memory such as MRAM. The auxiliary storage device 203 is a storage device that permanently stores programs, data, and the like, and is, for example, an HDD or SSD. The data stored in the flow rate information storage unit 103A, the route selection information storage unit 105, and the like are stored in the main storage device 202, the auxiliary storage device 203, or an external storage medium.

Although one embodiment of the present invention has been described above, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and modifications thereof are included in the scope and the gist of the invention, and are also included in the invention described in the claims and the scope equivalent thereto.

001 Entrance and exit 002 Road section 003 Confluence point 004 Roadside facility 100 Traffic adjustment support device 101 Entry sensor 101 Exit sensor 103 Flow rate check unit 103A Flow rate information storage unit 104 Available route calculation unit 105 Route selection information storage unit 106 Congestion degree calculation unit 107 inconvenience degree calculation unit 108 scheduler 109 output unit 110 input unit 120 scheduling processing unit 201 processor 202 main storage device 203 auxiliary storage device 204 network interface 205 device interface 206 output device 207 input device 208 bus 209 external storage medium

Claims (15)

Generating information about an optimum flow rate of a vehicle that travels a vehicle that travels in a target area including at least one entrance, at least one exit, and a plurality of paths that connect the entrance and the exit As a result, a traffic adjustment support device that supports traffic adjustment for the target area,
A flow rate check unit for obtaining flow rate information regarding a flow rate of a vehicle entering from the entrance and a flow rate of a vehicle exiting from the exit;
A first calculation unit that calculates a congestion degree of each of the routes and a change amount of the congestion degree when the vehicle changes the route, based on the flow rate information and the route selection probability,
Calculating the optimal vehicle flow rate of each route using the calculated congestion degree of each route, the calculated change amount, and the dissatisfaction degree of the driver when traveling on each route 2 calculator
Equipped with
Each of the routes is a route in which at least one facility is arranged between the entrance and the exit,
The congestion degree of each route depends on the congestion degree of the facility calculated based on at least the number of vehicles staying at the facility and the facility capacity related to the number of vehicles that the facility can accommodate. It is a certain degree of congestion,
Traffic adjustment support device. The second calculator calculates the congestion degree, the calculated change amount, and the degree of dissatisfaction so that the objective function defined using the condition satisfies a predetermined condition. The traffic adjustment support device according to claim 1, wherein the flow adjustment amount is calculated. The traffic adjustment support device according to claim 2, wherein the predetermined condition is that the value of the objective function is minimized. The traffic adjustment support device according to claim 2, wherein the predetermined condition is that the value of the objective function is equal to or less than a threshold value or falls within a predetermined range. When the second calculation unit receives a change instruction for the calculated vehicle flow rate of each route, the second calculation unit calculates the vehicle flow rate of each route based on the objective function with the content of the change instruction as a constraint condition. The traffic adjustment support device according to any one of claims 2 to 4. The traffic adjustment support apparatus according to any one of claims 1 to 5, wherein the congestion degree of the facility is calculated by dividing the number of vehicles staying at the facility by the facility capacity. The congestion degree of the facility, the facility from the number of vehicles that stay, the traffic adjustment support device according to any one of claims 1 to 5 is calculated by subtracting the facility capacity. The second calculation unit travels on a road section between the facilities at a speed determined according to the road section, and stays at the facility on the route for a predetermined time. The traffic adjustment support device according to any one of claims 1 to 7, which calculates the number of existing vehicles. The dissatisfaction degree, traffic adjustment support device according to any one of the paths claims 1 is a value corresponding to the inverse of the selection probability 8. The dissatisfaction degree, traffic adjustment support device according to any one of claims 1 to 8 which is a value corresponding to the distance of the path. The second calculation unit calculates the rate of increase in the flow rate of the vehicle in at least one of the plurality of routes based on the calculated optimal flow rate of the vehicle. The traffic adjustment support device according to one item. The second calculating unit, when the rate of increase calculated is achieved, the first prediction information about the congestion degree, and, in claim 11 for generating at least one of the second prediction information regarding dissatisfaction of each driver The described traffic adjustment support device. The traffic adjustment support device according to any one of claims 1 to 12, further comprising: an output unit that outputs a processing result by the second calculation unit. Generating information about an optimum flow rate of a vehicle that travels a vehicle that travels in a target area including at least one entrance, at least one exit, and a plurality of paths that connect the entrance and the exit Thus, in order to support the traffic adjustment for the target area, a traffic adjustment support method executed by a computer,
Acquiring flow rate information regarding a flow rate of a vehicle entering from the entrance and a flow rate of a vehicle exiting from the exit,
Calculating a congestion degree of each of the routes and a change amount of the congestion degree when the vehicle changes the route, based on the flow rate information and the route selection probability,
Using the calculated congestion degree of each route, the calculated change amount, and the dissatisfaction degree of the driver when traveling on each of the routes, calculating an optimal vehicle flow rate of each of the routes When,
Equipped with
Each of the routes is a route in which at least one facility is arranged between the entrance and the exit,
The traffic adjustment support method, wherein the congestion degree of each route is calculated based on at least the number of vehicles staying at the facility and the facility capacity related to the number of vehicles that the facility can accommodate . Generating information about an optimum flow rate of a vehicle that travels a vehicle that travels in a target area including at least one entrance, at least one exit, and a plurality of paths that connect the entrance and the exit By this, a program executed by a computer to support traffic adjustment to the target area,
Acquiring flow rate information regarding a flow rate of a vehicle entering from the entrance and a flow rate of a vehicle exiting from the exit,
Calculating a congestion degree of each of the routes and a change amount of the congestion degree when the vehicle changes the route, based on the flow rate information and the route selection probability,
Using the calculated congestion degree of each route, the calculated change amount, and the dissatisfaction degree of the driver when traveling on each of the routes, calculating an optimal vehicle flow rate of each of the routes When,
Equipped with
Each of the routes is a route in which at least one facility is arranged between the entrance and the exit,
The congestion degree of each route is calculated based on at least the number of vehicles staying at the facility and the facility capacity related to the number of vehicles that the facility can accommodate .