Information processing device, vehicle, path determination method, and program

Abstract

An information processing unit (2) according to the present disclosure is provided with a route search unit (23) that performs a determination process in which a traffic light color switching timing is determined on the basis of signal information indicating a light color switching timing of the traffic light and congestion information indicating the occurrence state of congestion, and the traffic light color switching timing is determined on the basis of the signal information indicating the traffic light color switching timing and the congestion information indicating the occurrence state of congestion. And a path search unit (23) that determines whether or not at least one of a first stop, which is a stop of the vehicle (1) due to a light color of a signal light, and a second stop, which is a stop of the vehicle (1) due to a congestion, occurs in path candidates, which are candidates for a path from a riding place to a destination of a user who is riding the vehicle (1). A route on which the vehicle (1) travels is determined from the route candidates.

Description

Technical Field

[0001] This disclosure relates to an information processing apparatus, a vehicle, a route determination method, and a procedure for searching the path of a vehicle. Background Technology

[0002] There are known techniques for searching vehicle paths up to their destination. Patent Document 1 discloses a technique that calculates an estimate of fuel consumption based on the vehicle's travel time and idling time, and then searches for the path with the lowest estimated fuel consumption.

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent No. 5872229 Summary of the Invention

[0006] The problem that the invention aims to solve

[0007] The technology described in Patent Document 1 is capable of searching for paths to suppress fuel consumption. However, the technology described in Patent Document 1 does not consider the viewpoint of preventing users of the vehicle from being involved in crime.

[0008] This disclosure was made in view of the above circumstances, and its purpose is to provide an information processing device that can reduce the possibility of users of vehicles being involved in crimes.

[0009] Methods for solving problems

[0010] To solve the aforementioned problems and achieve the objective, the information processing apparatus of this disclosure includes a route search unit that performs a determination process in which, based on signal information indicating the timing of a traffic light color change and congestion information indicating the occurrence of congestion, it determines whether, among the candidate routes (route candidates) from the passenger's pick-up point to their destination, at least one of a vehicle stop caused by a traffic light color (i.e., a first stop) and a vehicle stop caused by congestion (i.e., a second stop) occurs. The route search unit uses the determination result of the determination process to determine the route the vehicle will travel from the route candidates.

[0011] Invention Effects

[0012] The information processing device disclosed herein has the effect of reducing the likelihood that users of the vehicle will be involved in crime. Attached Figure Description

[0013] Figure 1 This is a diagram showing a structural example of the vehicle according to Embodiment 1.

[0014] Figure 2This is a flowchart illustrating an example of the path determination process in the information processing unit of Embodiment 1.

[0015] Figure 3 This is a diagram illustrating an example of a path determined by the path determination method of Implementation 1.

[0016] Figure 4 This is a diagram illustrating an example of the path determination system of Implementation 1.

[0017] Figure 5 This is a diagram illustrating a structural example of a manually driven vehicle according to Embodiment 1.

[0018] Figure 6 This is a diagram illustrating a structural example of a computer system that implements the information processing unit and information processing apparatus of Embodiment 1.

[0019] Figure 7 This is a flowchart illustrating an example of the path determination process in the information processing unit of Embodiment 2.

[0020] Figure 8 This is a flowchart illustrating an example of the path determination process in the information processing unit of Embodiment 3. Detailed Implementation

[0021] The information processing apparatus, vehicle, route determination method, and procedure of the embodiments will be described in detail below with reference to the accompanying drawings.

[0022] Implementation method 1.

[0023] Figure 1 This diagram illustrates a structural example of the vehicle according to Embodiment 1. The vehicle 1 of this embodiment includes an information processing unit 2, a driving control unit 3, a driving mechanism 4, and a self-positioning unit 5. The vehicle 1 can carry its user and transport the user to their destination. Figure 1 The example shown is of a vehicle capable of autonomous driving, but as described later, this embodiment is not limited to autonomous vehicles and can also be applied to manually driven vehicles driven by a human driver. Furthermore, this embodiment can also be applied to vehicles capable of switching between autonomous and manual driving.

[0024] Information processing unit 2 is an information processing device that searches for the path of vehicle 1 (the path along which vehicle 1 travels). Information processing unit 2 includes an information acquisition unit 21, a receiving unit 22, a path search unit 23, and an information storage unit 24.

[0025] The information acquisition unit 21 receives information from the information providing device 6 and thereby acquires information. For example, the information acquisition unit 21 acquires signal information indicating the timing of the light color switching of the traffic light (traffic signal light), that is, the timing of the switching of the light color of the traffic light, and congestion information indicating the occurrence of congestion from the information providing device 6, and stores the acquired signal information and congestion information in the information storage unit 24.

[0026] Signal information can be, for example, information indicating the length of one cycle of a signal light displaying green, yellow (or flashing green), and red lights, the lighting time of each light color, and a reference time; or it can be information indicating the predetermined times of the transition from green to yellow, from yellow to red, and from red to green. The reference time is, for example, a reference time used to determine the start time of each color's lighting, such as the start time of any one cycle. If the start of one cycle is green, the start time of green lighting in any cycle can be used as the reference time. In this case, the start time of green lighting can be determined by adding an integer multiple of the signal cycle to the reference time. The reference time is not limited to this; it can be set to determine the start time of each color's lighting. The reference time can be a past time or a future time. Furthermore, the signal information can be determined by the system managing the lighting or estimated based on results obtained from sensors such as cameras that detect traffic flow. In addition, the information processing unit 2 may also have an estimation unit (not shown) that estimates signal information. The information acquisition unit 21 acquires the detection results of sensors such as cameras that detect traffic flow. The estimation unit uses the detection results to estimate signal information and saves the estimated signal information in the information storage unit 24.

[0027] Information providing device 6 can be a roadside unit, a management device for managing traffic-related information, or a distribution device that obtains and distributes signal and congestion information from the management device. Furthermore, information processing unit 2 can obtain information sent from information providing device 6 via various networks such as the Internet and mobile phone networks, or it can receive information via other devices not shown. For example, information processing unit 2 can also receive information sent from information providing device 6 via vehicle-to-vehicle communication from other vehicles 1. Furthermore, in Figure 1 The diagram shows one information providing device 6, but there can be multiple information providing devices 6. For example, the information providing device 6 that sends congestion information and the information providing device 6 that sends signal information can be different. Alternatively, each area may have an information providing device 6 that provides signal information and congestion information for that area, and the information acquisition unit 21 acquires signal information and congestion information from multiple information providing devices 6 corresponding to multiple areas respectively.

[0028] The receiving unit 22 accepts the destination input and notifies the route search unit 23 of the accepted destination. The receiving unit 22 can accept destination input from, for example, the user riding in vehicle 1, or from a user other than the user riding in vehicle 1. For example, if the user riding in vehicle 1 is a minor, the destination can also be input by the user's guardian, guide, etc. Furthermore, the receiving unit 22 can accept input directly through the user's operation, or it can receive destination information from a user-operable terminal device such as a portable terminal.

[0029] The information storage unit 24 stores congestion information, signal information, and map information. Map information represents a map containing road-related information, including the location of each road, the number of lanes, the direction of travel for each lane, the location of traffic lights, one-way traffic, temporary stopping restrictions, etc. Furthermore, map information may also include information such as the curvature of road curves, the slope of roads, and the unevenness of road surfaces. Additionally, map information may include information such as crime prevention maps showing the occurrence of past crimes (types and frequencies of crimes) for each tile on the map. Furthermore, map information may also include information indicating the brightness of each tile. Moreover, map information can also be information representing a static map from high-precision three-dimensional map data containing dynamic and quasi-dynamic information, such as dynamic maps. Furthermore, if a dynamic map includes at least one of signal information and congestion information, that information can also be used as the dynamic map.

[0030] The route search unit 23 determines the route of vehicle 1, i.e., the path of vehicle 1, based on the signal information and congestion information stored in the information storage unit 24, in a manner that minimizes stops from the departure point (boarding location) to the destination, and notifies the driving control unit 3 of the determined path. For example, the route search unit 23 performs the following determination process: based on the signal information and congestion information, it determines whether, among the candidate paths from the user's boarding location to the destination, at least one of the following occurs: a first stop due to a traffic light color (i.e., a first stop) or a second stop due to congestion (i.e., a second stop). Then, the route search unit 23 uses the determination result of the determination process to determine the path of vehicle 1 from the candidate paths. Furthermore, for example, the route search unit 23 may also determine the path of vehicle 1 from the candidate paths determined by the determination process to have experienced at least one of the first or second stops, based on at least one of the stopping time and number of stops of vehicle 1 in the path of vehicle 1. In detail, the path search unit 23 can, for example, determine the path candidate with the fewest stops as the path of vehicle 1, or it can determine the path candidate with the smallest maximum stopping time as the path of vehicle 1. The path determination method in the path search unit 23 is not limited to this.

[0031] Furthermore, the starting point may be set to the current position of vehicle 1, as indicated by the location information (described later) received by the route search unit 23 from its own position determination unit 5. However, this is not the only possibility; the receiving unit 22 may also receive input regarding the starting point and notify the route search unit 23 of the starting point. Details regarding the route determination method in the route search unit 23 will be described later.

[0032] The self-positioning unit 5 determines the self-position of vehicle 1 and outputs position information indicating the determined self-position to the driving control unit 3 and the route search unit 23. The self-positioning unit 5 uses, for example, a satellite positioning system such as GPS (Global Positioning System) or GNSS (Global Navigation Satellite System) to determine its own position; however, the method for determining the self-position in the self-positioning unit 5 is not limited to this. Furthermore, if the position information is not used in the route search unit 23, the self-positioning unit 5 may not output position information to the route search unit 23.

[0033] The driving control unit 3 controls the driving mechanism 4 according to the path notified by the path search unit 23, thereby performing driving control based on the autonomous driving of the vehicle 1. For example, the driving control unit 3 controls the driving mechanism 4 based on information obtained by sensors such as obstacle detection cameras, LiDAR (Light Detection and Ranging), and millimeter-wave sensors (illustrated but not shown), position information received from the self-positioning unit 5, and map information stored in the information storage unit 24. Furthermore, the method of controlling the autonomous driving of the vehicle 1 is not limited to this, as long as it involves driving on the path notified by the path search unit 23; any method can be used, and general methods can be employed. Therefore, detailed explanation is omitted.

[0034] Furthermore, the map information used by the driving control unit 3, i.e., the map information for autonomous driving, may differ from the map information stored in the information storage unit 24. In this case, the driving control unit 3 performs driving control based on the map information for autonomous driving stored in the map information storage unit (not shown) within the vehicle 1. For example, the map information stored in the information storage unit 24 may be two-dimensional map information, while the map information for autonomous driving may be a dynamic map. When using a dynamic map as the map information for autonomous driving, the updated information may be obtained by the information acquisition unit 21 or by a transceiver unit (not shown).

[0035] The driving mechanism 4 is a mechanism for driving the vehicle 1, such as an acceleration control device such as an accelerator pedal, a steering device, a brake, and other mechanisms that drive the vehicle 1.

[0036] In this embodiment, the route search unit 23 determines the route of vehicle 1 in a manner that minimizes the need for vehicle 1 to stop until it reaches its destination. Therefore, when vehicle 1 stops, the possibility of the user of vehicle 1 being involved in a crime can be reduced. In particular, when vehicle 1 is an autonomous vehicle and the user of vehicle 1 is a child, measures to prevent children from being involved in crimes become important. In this embodiment, since vehicle 1 can travel in a manner that minimizes the need for vehicle 1 to stop until it reaches its destination, the possibility of children being involved in crimes can be reduced. Furthermore, the user of vehicle 1 is not limited to children.

[0037] Furthermore, in the example described above, the route search unit 23 notifies the driving control unit 3 of the determined route. However, it is not limited to this; the route search unit 23 may also store the route information representing the determined route in the information storage unit 24 or a route information storage unit (not shown) within the vehicle 1. In this case, the driving control unit 3 refers to the route information stored in the information storage unit 24 or the route information storage unit to perform driving control of the vehicle 1.

[0038] Next, the path determination method in the information processing unit 2 of this embodiment will be described. Figure 2 This is a flowchart illustrating an example of the path determination process in the information processing unit 2 of this embodiment. For example... Figure 2 As shown, the information processing unit 2 determines whether there is a destination input (step S1). Specifically, the route search unit 23 determines whether the destination has been notified from the receiving unit 22. Furthermore, as described above, the receiving unit 22 may also accept not only the destination input but also the origin input; in this case, the route search unit 23 is also notified of the origin from the receiving unit 22.

[0039] If there is no destination input (step S1 No), the information processing unit 2 repeats step S1. If there is a destination input (step S1 Yes), the information processing unit 2 acquires signal information and congestion information (step S2). Specifically, the information acquisition unit 21 acquires, for example, signal information and congestion information about the range in which the vehicle 1 can travel from the information providing device 6, and stores the acquired signal information and congestion information in the information storage unit 24. Furthermore, in Figure 2 In this process, step S2 is performed after step S1; however, the timing of step S2 is not limited to this. For example, step S2 can also be performed periodically.

[0040] Information processing unit 2 sets path candidates (step S3). Specifically, path search unit 23 uses map information stored in information storage unit 24 to search for paths from the starting point to the destination, and sets one of the searched paths as a path candidate. In step S3, for example, path search unit 23 can search for paths that minimize costs by treating intersections as nodes and setting costs for the edges connecting the nodes, such as Dijkstra's method or Bellman-Ford method. It can also search for path candidates using a complete search method, a metaheuristic method, or other methods. For example, distance or required time can be used as the cost of Dijkstra's method, but it is not limited to these methods.

[0041] Next, the information processing unit 2 determines whether there is a stopping position among the set route candidates (step S4). Specifically, the route search unit 23 sets a departure time from the starting point and uses the congestion and signal information stored in the information storage unit 24 to determine whether at least one of the following will occur in the set route candidates: a vehicle 1 stopping due to a traffic light color (a stopping due to a red or yellow traffic light) or a stopping due to congestion. The departure time can be a time one hour after the current time or can be specified by the user. Furthermore, in addition to stopping due to a traffic light color (hereinafter also referred to as stopping due to a signal) and stopping due to congestion, the route search unit 23 can also treat temporary stops at locations with temporary stopping restrictions but no signal as stops. Locations with temporary stopping restrictions may not be included as stopping positions. Furthermore, regarding the stopping of vehicle 1 due to congestion, if the congestion information is displayed in the form of a congestion of Y km at location X, it can be anticipated that the stopping will occur at the very end of the congestion, and the very end of the congestion can be designated as the stopping position. Additionally, if the congestion information includes the stopping position and stopping time due to congestion, it can be determined whether a stopping position exists based on this information.

[0042] Furthermore, if a vehicle 1 stops due to a signal, and the stopping can be avoided by changing at least one of the departure time and the travel speed, the route search unit 23 can also change at least one of the departure time and the travel speed. For example, if a traffic light is set to a predetermined standard travel speed for each section of the road as an initial value, and the light is red when traveling at the standard speed but green (green light illuminates) when the travel speed is slightly reduced within a range determined by the limit, the route search unit 23 can also change the travel speed to the speed required to pass through the traffic light when it is green.

[0043] If there is no stopping position (step S4: No), the information processing unit 2 selects a candidate route from the settings as the route (step S5) and ends the processing. Specifically, in step S5, the route search unit 23 selects a candidate route from the settings as the route, thereby determining the route of vehicle 1, and notifies the driving control unit 3 of the determined route. Furthermore, in step S4, if at least one of the departure time and driving speed has changed, the route search unit 23 notifies the driving control unit 3 of the changed departure time and driving speed.

[0044] If there is a stopping position (step S4 is yes), the information processing unit 2 stores the stopping time and the number of stops (step S6). Specifically, the route search unit 23 calculates the stopping time and the number of stops for vehicle 1 at each stopping position in the set route candidates, and stores the calculated stopping time and the number of stops internally. Alternatively, the route search unit 23 saves the calculated stopping time and the number of stops in the information storage unit 24 or a temporary storage unit not shown. Regarding the stopping time of vehicle 1 due to congestion, if the congestion information is shown in the form of a congestion of Y km at location X, the time until passing through the congestion is determined according to a table or the like corresponding to the length of the congestion, and the Y km is converted into a stopping time using the table. Furthermore, if the congestion information includes the time required to pass through the congestion, that time can also be used as the stopping time of vehicle 1 due to congestion. Furthermore, here we will describe an example of the path search unit 23 calculating the stopping time and the number of stops for vehicle 1. However, if the stopping time is not used in the calculation of the stopping index in step S9 described later, the stopping time may not be calculated in step S6. Similarly, if the number of stops is not used in the calculation of the stopping index in step S9 described later, the number of stops may not be calculated in step S6.

[0045] Information processing unit 2 determines whether there are any undefined path candidates (step S7). Specifically, path search unit 23 determines whether there is a path from the origin to the destination other than the defined path candidates. Furthermore, even if there is a path that allows travel from the origin to the destination by a significant detour, the processing time required for path search and the actual travel time of vehicle 1 can sometimes be excessive. Therefore, at least one of the processing time and the travel distance (the distance from the origin to the destination) can be limited. For example, if the processing time exceeds a threshold in the search for paths other than the defined path candidates, path search unit 23 can determine in step S7 that there are no undefined path candidates. Alternatively, for example, if the result of searching for paths other than the defined path candidates is only a solution with a travel distance exceeding a threshold, information processing unit 2 can determine in step S7 that there are no undefined path candidates.

[0046] If there are no unset path candidates (step S7 is yes), the information processing unit 2 sets the next path candidate (step S8) and repeats the processing from step S4. In step S8, specifically, the path search unit 23 searches for paths from the origin to the destination other than the set path candidates, and sets one of the searched paths as a path candidate.

[0047] If there are no unset route candidates (step S7 No), the information processing unit 2 calculates the stopping index for each route candidate (step S9). Specifically, the route search unit 23 uses at least one of the stored stopping time and number of stops for each route candidate to calculate an index related to the stopping of vehicle 1 in the route candidate, namely, the stopping index. The stopping index is an indicator representing the degree of stopping of vehicle 1 in each route candidate. The number of stops is the sum of the number of times vehicle 1 stops due to traffic light colors (first stop), i.e., the first number, and the number of times vehicle 1 stops due to congestion (second stop), i.e., the second number. However, the route search unit 23 may also count the first number and the second number separately.

[0048] The stopping index can be, for example, the number of times vehicle 1 stops in the path candidate (the number of stopping positions), the maximum value of the stopping time at each stopping position in the path candidate, the total value of the stopping time in the path candidate, or a value obtained by weighted summation of the first and second stops. In addition, the stopping index can be an index calculated by combining stopping time and stopping number, or other indices. For example, the stopping index can also be the number of stopping positions in the path candidate with a stopping time of a fixed value or more, that is, the number of stops with a stopping time of a fixed value or more. In addition, for example, when the number of stops with a stopping time of the first time or more is set as A1, the number of stops with a stopping time of the second time or more than the first time is set as A2, the number of stops with a stopping time of the third time or more than the second time is set as A3, w1, w2, and w3 are set as weighting coefficients, and the stopping index is set as C, C can also be calculated by the following formula (1).

[0049]

[0050] For example, if the weighting coefficients w1, w2, and w3 are set to w1 < w2 < w3, then even with the same number of stops, the value of C will increase with a longer stopping time. The stopping index is not limited to the example above. Furthermore, here the stopping index is defined as a smaller value indicating a better evaluation; however, it is not limited to this definition, and the stopping index can also be defined as a larger value indicating a better evaluation.

[0051] Alternatively, the number of right and left turns can also be included as a stopping indicator. When there are right and left turns, the probability of vehicle 1 stopping increases, so it is preferable to choose a path that is as straight as possible. Therefore, for example, the stopping indicator can be further determined based on the number of right and left turns as follows: the stopping number is weighted and added to the number of right and left turns as a stopping indicator, or the term obtained by multiplying the number of right and left turns by a weighting coefficient is further added to the above formula (1).

[0052] Alternatively, when categorizing vehicle 1's stops into stops within presumably high-crime zones and other stops, and calculating the stopping index based on the number of stops and stopping time, the weighting coefficient for stops within presumably high-crime zones is increased compared to other zones. Furthermore, in this case, the map information may include, for example, the number of past crimes, as information used to identify zones presumably high-crime zones. For example, the stopping index can be obtained by weighted summing the number of stops within presumably high-crime zones and the number of stops within other zones; similarly, it can be obtained by weighted summing the maximum stopping time within presumably high-crime zones and the maximum stopping time within other zones. Furthermore, the stopping index can also be obtained by weighted summing the number of stops within presumably high-crime zones and the number of stops within other zones, as well as the maximum stopping time within presumably high-crime zones and the maximum stopping time within other zones.

[0053] Furthermore, at intersections equipped with traffic lights, vehicle 1 may stop due to the traffic lights; therefore, the number of intersections equipped with traffic lights can also be considered in the stopping index. In other words, the stopping index can be further determined based on the number of intersections equipped with traffic lights.

[0054] Next, the information processing unit 2 determines the path candidate to be selected as the path based on the stopping index (step S10), and the process ends. In step S10, specifically, the path search unit 23 uses the stopping index of each path candidate calculated in step S9 to determine the path candidate to be selected as the path. For example, the path search unit 23 determines the path candidate with the smallest stopping index as the path to be selected. Alternatively, it may select the path candidate to be selected from path candidates whose stopping index is below a threshold, based on a selection criterion different from the stopping index. This different selection criterion could be driving distance, required time, or other selection criteria. Furthermore, if the stopping index is defined as a value where a larger value indicates a better evaluation, the path search unit 23, for example, determines the path candidate with the largest stopping index as the path to be selected.

[0055] As described above, the route search unit 23 can, for example, calculate the number of first stops (i.e., the first stop count) and the number of second stops (i.e., the second stop count) among the route candidates based on congestion information and signal information, and use the first stop count and the second stop count to determine the route for vehicle 1 from the route candidates. For example, the route search unit 23 can also determine the route candidate with the smallest total value of the first stop count and the second stop count as the route for vehicle 1. Furthermore, the route search unit 23 can also calculate the stopping time at each location where any of the first and second stops occurs among the route candidates based on congestion information and signal information, and use the calculated stopping time to determine the route for vehicle 1 from the route candidates. For example, the route search unit 23 can also determine the route candidate with the smallest maximum stopping time as the route for vehicle 1.

[0056] In the examples described above, after setting path candidates through path search processing, a stopping index for each path candidate is calculated. Using the calculated stopping index, the path candidate to be selected as the path is determined. However, this is not the only approach; stopping indexes can also be considered in the path search processing. Alternatively, conditions such as reducing stopping time can be considered in the path search processing. For example, in Dijkstra's method and the Bellman-Ford method, costs can be set by increasing the cost of edges where stopping occurs, or by setting costs so that the cost of edges increases if the stopping time increases. Furthermore, costs can be set by increasing the cost of edges including intersections with traffic lights, or by increasing the cost of edges where right and left turns occur. When considering conditions such as reducing stopping indexes or stopping time in the path search processing, alternatives can be used... Figure 2 The path search process is performed in step S3 as shown, but steps S4 to S10 are not implemented.

[0057] The path determination process described above is an example. For example, the path search unit 23 calculates at least one of the number of stops and the stopping time of vehicle 1 in the path candidates based on signal information and congestion information, and uses the calculated value to determine the path. The specific content of the path determination method is not limited to the above example.

[0058] Furthermore, in the examples described above, the process is independent of the user's age. Figure 2 The process illustrated in the example is not limited to this; the path search unit 23 can also determine the path based on the user's age. Figure 2 The example in the text illustrates whether to determine the path using the usual methods or by using the same processing. For example, it could also be done if the user's age is below a threshold. Figure 2The process illustrated herein determines the route. If the user's age is above a threshold, the route is determined using conventional methods. Information indicating the user's age can be input by the receiving unit 22 or estimated by the route search unit 23. This information can be the user's age itself or information indicating whether they are a child or an adult. Alternatively, for example, the user can be photographed by a camera (not shown) installed in vehicle 1, and the route search unit 23 can analyze the captured images to estimate the user's age.

[0059] Figure 3 This diagram illustrates an example of a path determined by the path determination method of this embodiment. Here, as an example, the number of stops is used as a path index. Figure 3 In the example shown, traffic lights 51-1 to 51-7 exist around the departure and destination points, and congestion occurs at locations 54-1 and 54-2. Assume a vehicle departs from the departure point at time T0, and its estimated arrival time at traffic light 51-2 at standard speed is T1. At T1, traffic light 51-2 is green (green light is on). Similarly, assuming traffic light 51-2 is green at T1, therefore, at the intersection with traffic light 51-2, vehicle 1 can proceed straight, turn right, and turn left. Figure 3 In the example shown, when proceeding straight at traffic light 51-2, congestion occurs at congestion location 54-1. Furthermore, when vehicle 1 turns right at traffic light 51-2, traffic light 51-1 is red at the estimated arrival time T2 of vehicle 1; when vehicle 1 turns left at traffic light 51-2, traffic light 51-3 is green at the estimated arrival time T3 of vehicle 1. In this case, when turning right at traffic light 51-2, vehicle 1 stops at traffic light 51-1.

[0060] On the other hand, traffic light 51-3 is green at the estimated arrival time T3, therefore, vehicle 1 does not need to stop. Therefore, the path indicators for the straight-through path at traffic light 51-2 and the right-turn path at traffic light 51-2 are larger than those for the left-turn path at traffic light 51-2. Furthermore, let traffic lights 51-4, 51-5, and 51-6 be green at the estimated arrival time of vehicle 1 at each traffic light, and let traffic light 51-7 be red at the estimated arrival time of vehicle 1 at traffic light 51-7. Regarding the right-turn path at traffic light 51-3, congestion occurs at congestion location 54-2, and traffic light 51-7 is red at the intersection between traffic lights 51-4 and 51-5, therefore, vehicle 1 stops. Furthermore, regarding the right-turn path at traffic light 51-4, a temporary stop sign 53 is provided at the intersection 52 without traffic lights, therefore, a stop due to a temporary stop will occur. Therefore, considering temporary stops as also stops, a stop also occurs on the right-turn path of traffic light 51-4. Based on the above, in Figure 3 In the example shown, path 60, for instance, indicated by a single-dotted line, is determined as the path for vehicle 1. Additionally, a right turn at traffic lights 51-4 can also be determined as the path for vehicle 1, without considering temporary stops as actual stops. Figure 3 This illustrates the concept of a path determination method, where the conditions within each path and the path determination results are not limited to... Figure 3 The example shown.

[0061] In addition, Figure 1 The example described is of vehicle 1 performing the path determination process of this embodiment. However, the path determination process can also be performed by a device different from the vehicle. Figure 4 This diagram illustrates an example of the route determination system of this embodiment. The route determination system of this embodiment includes a vehicle 1a and an information processing device 7, and the route determination processing is performed by the information processing device 7. [The last sentence appears to be incomplete and possibly refers to a different system.] Figure 1 The examples shown use the same labels for structural elements with the same function, and repeated descriptions are omitted.

[0062] Figure 4 The information processing device 7 shown is in Figure 1 The information processing unit 2 shown includes an additional path transmission unit 25. Figure 4 The vehicle 1a shown is from Figure 1 The vehicle shown has had its information processing unit 2 removed, and a transceiver unit 8 and a map information storage unit 9 added. Figure 4In the path determination system shown, the self-position determination unit 5 outputs position information indicating the position of vehicle 1a to the driving control unit 3 and the transceiver unit 8. The transceiver unit 8 then sends the position information to the information processing device 7. Alternatively, if the position information is not used in the path search unit 23, the self-position determination unit 5 may not output the position information to the transceiver unit 8.

[0063] Figure 4 The path search unit 23 in the information processing device 7 shown is... Figure 1 The path search unit 23 of the information processing unit 2 shown also performs path determination processing and outputs path information representing the determined path to the path sending unit 25. The path sending unit 25 sends the path information to the vehicle 1a.

[0064] The transceiver unit 8 of vehicle 1a receives path information from the information processing device 7 and outputs the received path information to the driving control unit 3. The driving control unit 3 controls the driving mechanism 4 based on the path shown by the path information received from the transceiver unit 8, thereby controlling the driving of vehicle 1a. For example, with... Figure 1 Similarly, the driving control unit 3 controls the driving mechanism 4 based on information obtained from sensors (not shown), location information, and map information stored in the map information storage unit 9. The map information stored in the information storage unit 24 of the information processing device 7 and the map information stored in the map information storage unit 9 may be the same or different.

[0065] Furthermore, the functional distinction between vehicles and information processing devices is not limited to Figure 4 The example shown. For example, in Figure 4 In the example shown, the receiving unit 22 is located within the information processing device 7; however, the receiving unit 22 could also be located within the vehicle 1a. In this case, the destination received by the receiving unit 22 is sent to the information processing device 7 by the transceiver unit 8. The destination is received by the receiving unit (not shown) within the information processing device 7 and output to the route search unit 23. Similarly, when the receiving unit 22 receives an input of the departure location, the departure location is also sent to the information processing device 7.

[0066] In addition, Figure 1 and Figure 4 In the example shown, vehicles 1 and 1a are autonomous vehicles; however, this embodiment can also be applied to vehicles driven manually. Figure 5 This is a diagram illustrating a structural example of a manually driven vehicle according to this embodiment. Figure 5 The vehicle 1b shown is a vehicle driven by a driver. Figure 5 As shown, vehicle 1b removes the driving control unit 3 from vehicle 1 and replaces the information processing unit 2 with an information processing unit 2b. For vehicles with... Figure 1The examples shown use the same labels for structural elements with the same function, and repeated descriptions are omitted.

[0067] Information Processing Department 2b, in addition to Figure 1 In addition to the path display unit 26 added to the information processing unit 2 shown, it is also connected to... Figure 1 The information processing unit 2b shown is the same as the path search unit 23 of the information processing unit 2b. Figure 1 The path search unit 23 of the information processing unit 2 also performs path determination processing and outputs path information representing the determined path to the path display unit 26. The path display unit 26 displays the path shown in the path information. The path display unit 26 can also display the path on a map. In this case, the path search unit 23 may read map information from the information storage unit 24 and deliver it to the path display unit 26, or the path display unit 26 may read map information from the information storage unit 24 and display it as a map.

[0068] Additionally, when using a manually driven vehicle, it is also possible to... Figure 4 Similarly, in the example shown, route determination is performed by information processing device 7. In this case, the vehicle takes over. Figure 4 The driving control unit 3 of the vehicle 1a shown has a path display unit 26, which receives path information representing the path determined by the information processing device 7 from the transceiver unit 8, and displays the path shown by the path information by the path display unit 26.

[0069] Next, the hardware structure of the information processing units 2 and 2b and the information processing device 7 in this embodiment will be described. In this embodiment, the information processing units 2 and 2b and the information processing device 7 are respectively executed on a computer system by computer programs, i.e., programs, which describe the processing in the information processing units 2 and 2b. The computer system functions as the information processing units 2 and 2b and the information processing device 7, respectively. Figure 6 This is a diagram illustrating an example of the structure of a computer system that implements the information processing units 2 and 2b and the information processing device 7 in this embodiment. (See diagram below.) Figure 6 As shown, the computer system has a control unit 101, an input unit 102, a storage unit 103, a display unit 104, a communication unit 105, and an output unit 106, which are connected via a system bus 107.

[0070] exist Figure 6In this embodiment, the control unit 101 is, for example, a processor such as a CPU (Central Processing Unit), which executes the program describing the processing described in the information processing units 2 and 2b of this embodiment. The input unit 102 is, for example, composed of a keyboard, buttons, mouse, etc., for allowing the computer system user to input various information. The storage unit 103 includes various memory devices such as RAM (Random Access Memory), ROM (Read Only Memory), and hard disks, storing the program to be executed by the control unit 101, necessary data obtained during processing, etc. In addition, the storage unit 103 is also used as a temporary storage area for the program. The control unit 101 and the storage unit 103 constitute, for example, a processing circuit. The processing circuit can be a single circuit or multiple circuits. The display unit 104 is composed of a display, LCD (Liquid Crystal Display Panel), etc., and displays various screens to the computer system user. Alternatively, a touch panel that integrates the input unit 102 and the display unit 104 can also be used. The communication unit 105 is a receiver and transmitter that performs communication processing. The output section 106 includes speakers, etc. Additionally, Figure 6 For example, the structure of a computer system is not limited to... Figure 6 For example, output section 106 may not be set.

[0071] Here, an example of the operation of a computer system up to the point where it can execute the program of this embodiment will be described. In a computer system with the above structure, for example, a CD-ROM or DVD-ROM drive installed in a CD (Compact Disc)-ROM drive or DVD (Digital Versatile Disc)-ROM drive (not shown) is used to install programs into the storage unit 103. Furthermore, when executing a program, the program read from the storage unit 103 is saved to the main storage area of ​​the storage unit 103. In this state, the control unit 101 executes the processing of the information processing units 2 and 2b and the information processing device 7 of this embodiment according to the program saved in the storage unit 103.

[0072] Furthermore, in the above description, CD-ROM or DVD-ROM is used as the recording medium and a program describing the processing in the information processing unit 2, 2b is provided. However, it is not limited to this. Depending on the structure of the computer system, the capacity of the provided program, etc., a program provided via the communication unit 105 through a transmission medium such as the Internet may be used.

[0073] The procedure of this embodiment, for example, causes the computer system that determines the route of vehicle 1 to perform the following steps: performing a determination process in which, based on signal information and congestion information, it is determined whether, among the candidate routes from the user's pick-up location to the destination of vehicle 1, at least one of the following occurs: a first stop due to the color of a traffic light or a second stop due to congestion; and using the determination result of the determination process, the route to which vehicle 1 travels is determined from the candidate routes.

[0074] Figure 1 , Figure 4 and Figure 5 The path search unit 23 shown is through the path search unit 23 by the path search unit 23. Figure 6 The control unit 101 shown performs the following: Figure 6 The program stored in the storage unit 103 shown is used for implementation. Furthermore, in Figure 1 , Figure 4 and Figure 5 The implementation of the path search unit 23 shown also uses the storage unit 103. Figure 1 The information acquisition unit 21 shown passes through Figure 6 The communication unit 105 shown is used for implementation. The information storage unit 24 is part of the storage unit 103. The receiving unit 22 is implemented by at least one of the input unit 102 and the communication unit 105. Figure 5 The path display unit 26 shown passes through Figure 6 The display unit 104 shown is used to implement this. The control unit 101 can be used in the control of the receiving unit 22, the path display unit 26, and the information acquisition unit 21. The information processing units 2 and 2b and the information processing device 7 can also be implemented using multiple computer systems. Furthermore, for example, the information processing device 7 can also be implemented using a cloud computer system.

[0075] Figure 1 The driving control unit 3 shown Figure 4 The driving control unit 3 and the map information storage unit 9 shown are also implemented through computer systems. Figure 1 The driving control unit 3 shown Figure 4 The driving control unit 3 and map information storage unit 9 shown are, for example, connected by a... Figure 7 This is implemented by a processing circuit consisting of a control unit 101 and a storage unit 103, as illustrated in the example. Furthermore, Figure 1 The driving control unit 3 and information processing unit 2 shown can also be implemented using a single computer system. Furthermore, Figure 1 , Figure 4 and Figure 5 The self-positioning unit 5 shown has a GNSS antenna when it obtains position information through GNSS positioning. It uses the signal received by the GNSS antenna to calculate the position information through the control circuit described above.

[0076] As described above, in this embodiment, the information processing units 2 and 2b and the information processing device 7 determine the route of vehicle 1 in a manner that minimizes the stopping of vehicle 1 until it reaches its destination. Therefore, when vehicle 1 stops, the possibility of the user riding in vehicle 1 being involved in a crime can be reduced. In particular, when vehicle 1 is an autonomous vehicle and the user riding in vehicle 1 is a child, crime prevention measures related to children become important. The route determination method of this embodiment can reduce the possibility of children being involved in a crime.

[0077] Implementation method 2.

[0078] Figure 7 This is a flowchart illustrating an example of the path determination processing in the information processing unit 2 of Embodiment 2. The structure of the vehicle 1 in this embodiment is the same as that in Embodiment 1. Structural elements having the same functions as in Embodiment 1 are labeled with the same reference numerals as in Embodiment 1, and repeated descriptions are omitted. Hereinafter, the features of Embodiment 1 are listed. Figure 1 The operation of this embodiment in vehicle 1, as shown in the structural example, will be explained using this embodiment as an example. However, in embodiment 1... Figure 4 and Figure 5 The same operation of this embodiment can be applied in the structural example shown.

[0079] Figure 7 The steps S1 to S3 shown are the same as those in Implementation Method 1. Figure 2 The example shown is the same. After step S3, the information processing unit 2 determines whether the destination will arrive before the set time (step S11). Specifically, the route search unit 23 determines whether the arrival time of the destination is before the set time if the vehicle 1 is traveling on the set route candidate. The set time refers to the limit time that allows deviation from the target arrival time, such as the time when a certain amount of time has elapsed since the target arrival time (first set time), that is, the time obtained by adding a certain amount of time to the target arrival time, but it is not limited to this. At least one of the target arrival time and the set time can be specified by the user. For example, at least one of the target arrival time and the set time can also be set by the user receiving input through the receiving unit 22. Alternatively, the target arrival time can also be determined based on the straight-line distance between the departure point and the destination.

[0080] If the arrival time is reached before the set time (step S11 Yes), the process after step S4 is executed. If the arrival time is not reached before the set time (step S11 No), the process after step S8 is executed. Steps S4 to S10 are the same as in Implementation Method 1. Figure 2 The example shown is the same.

[0081] In Implementation 1, the route for vehicle 1 is determined in a way that minimizes vehicle 1's stops until it reaches its destination. However, this may result in selecting a route with a longer travel time to the destination. In this implementation, the information processing unit 2 excludes route candidates where vehicle 1 will arrive at the destination after a set time from the list of route candidates to be selected. That is, the information processing unit 2 determines the route so that the arrival time of vehicle 1 at the destination is before the set time. Therefore, it is possible to determine the route so that the vehicle arrives at the destination before the set time. Furthermore, by setting the set time based on the target arrival time specified by the user, it is possible to make the arrival time of vehicle 1 close to the user's desired target arrival time.

[0082] Alternatively, a second set time (a time determined earlier than the target arrival time) can be set, which is the time obtained by subtracting the determined time from the target arrival time. In this case, in step S11, it is determined whether the arrival will occur after the second set time. That is, the information processing unit 2 determines the route of vehicle 1 based on the arrival time of vehicle 1 reaching the destination being before the second set time. This can prevent users of vehicle 1 from arriving too early and can prevent problems such as users being involved in crimes while waiting. Alternatively, a first set time (a time determined earlier than the target arrival time) and a second set time (a determined time elapsed from the target arrival time) can be set as set times, and in step S11, it is determined whether the arrival will occur after the first set time and before the second set time.

[0083] in addition, Figure 7 The processing procedure shown is an example, and is not limited to it. The path search process can also reflect the condition of arriving before a set time. For example, it could be designed such that arriving after the set time would be extremely costly, making it practically difficult to find a path in the path search process. That is, the path search unit 23 can determine the path in a way that vehicle 1 arrives at the destination before the set time and that vehicle 1 does not stop as much as possible before reaching the destination; the specific processing can be arbitrary. Except as described above, the operation of this embodiment is the same as that of Embodiment 1.

[0084] Implementation method 3.

[0085] Figure 8 This is a flowchart illustrating an example of the path determination processing in the information processing unit 2 of Embodiment 3. The structure of the vehicle 1 in this embodiment is the same as that in Embodiment 1. Structural elements having the same function as in Embodiment 1 are labeled with the same reference numerals as in Embodiment 1, and repeated descriptions are omitted. Hereinafter, the features of Embodiment 1 are listed. Figure 1 The operation of this embodiment in vehicle 1, as shown in the structural example, will be explained using this embodiment as an example. However, in embodiment 1... Figure 4 and Figure 5 The same operation of this embodiment can be applied in the structural example shown.

[0086] Figure 8 The steps S1 to S3 shown are the same as those in Implementation Method 1. Figure 2 The example shown is the same. After step S3, the information processing unit 2 determines whether there is a section with poor driving conditions (step S12). In detail, the route search unit 23 uses the map information stored in the information storage unit 24 to determine whether there is a section with poor driving conditions among the set route candidates. A section with poor driving conditions is, for example, at least one of the following: a section that is expected to cause motion sickness, a section that is expected to have poor security, or a dark section, but it is not limited to these.

[0087] The areas anticipated to be prone to motion sickness include at least one of the following: areas with many curves, areas with sharp turns (curves with small curvature), areas with steep road slopes, and areas with large road bumps. In this embodiment, the information indicating these conditions is included in the map information, and the path search unit 23 can determine areas where the information indicating these conditions exceeds a threshold as areas anticipated to be prone to motion sickness. The areas anticipated to have poor security include at least one of the following: areas with a high number of past crimes, areas identified as requiring attention in the crime prevention map, etc. In this embodiment, information about crime occurrences and various information in the crime prevention map are also included in the map information, and the path search unit 23 determines whether an area is anticipated to have poor security based on the map information. Similarly, information indicating the ambient brightness is also included in the map information, and the path search unit 23 determines whether an area is a darker area based on the map information.

[0088] If there are no areas with poor driving conditions (step S12 No), proceed with the processing after step S4. If there are areas with poor driving conditions (step S12 Yes), proceed with the processing after step S8. Steps S4 to S10 are the same as in Implementation Method 1. Figure 2 The example shown is the same. Furthermore, as described in Embodiment 1, the path search unit 23 can also determine whether to perform a path search based on the user's age. Figure 8 The processing shown is still the usual processing.

[0089] In this embodiment, the route is determined by avoiding areas with poor driving conditions. For example, the route search unit 23 determines the route for vehicle 1 based on at least one of the following: the curvature of road curves, the number of curves within a certain range, and the road gradient. This avoids areas anticipated to cause motion sickness, and compared to setting the route without considering areas anticipated to cause motion sickness, the user is less likely to experience motion sickness while riding in vehicle 1, allowing for a more comfortable experience. In particular, when the user of vehicle 1 is a child, who is sometimes prone to motion sickness, by determining the route by avoiding areas anticipated to cause motion sickness, the occurrence of motion sickness in children can be suppressed.

[0090] Furthermore, it is also possible to suppress motion sickness in children during driving control. For example, the driving control unit 3 can perform driving control such as avoiding sudden acceleration / deceleration, setting speed limits, and avoiding sharp turns. For example, limits can be set such that at least one of the absolute value of acceleration, speed, and the amount of change in steering wheel operation is below a threshold. Driving control is then performed. Furthermore, regarding driving control, whether or not to set restrictions on driving control can be determined based on the user's age.

[0091] Furthermore, the route search unit 23 can also determine the route that vehicle 1 travels based on the occurrence of a crime, and by avoiding areas that are expected to have poor public security, it can further reduce the possibility of the user being involved in a crime compared to embodiment 1.

[0092] in addition, Figure 8 The processing procedure shown is an example, and is not limited to it. Conditions such as avoiding sections with poor driving conditions can also be reflected in the path search process. For example, the cost of sections with poor driving conditions can be made very high, making them practically difficult to search as paths in the path search process. That is, the path search unit 23 can determine the path in a way that avoids sections with poor driving conditions and minimizes the stopping of vehicle 1 until reaching the destination; the specific processing can be arbitrary. Except as described above, the operation of this embodiment is the same as that of Embodiment 1.

[0093] Alternatively, embodiment 2 and this embodiment can be combined. For example, it can also be done in... Figure 7 Step S12 is added after step S11 shown.

[0094] The structure shown in the above embodiments is an example that can be combined with other known technologies, and the embodiments can be combined with each other. Furthermore, a part of the structure can be omitted or modified without departing from the spirit of the subject.

[0095] Label Explanation

[0096] 1, 1a, 1b: Vehicle; 2, 2b: Information processing unit; 3: Driving control unit; 4: Driving mechanism; 5: Self-positioning unit; 6: Information providing device; 7: Information processing device; 8: Receiving and transmitting unit; 9: Map information storage unit; 21: Information acquisition unit; 22: Acceptance unit; 23: Route search unit; 24: Information storage unit; 25: Route sending unit; 26: Route display unit.

Claims

1. An information processing device, characterized in that, The information processing device includes a route search unit, which performs the following determination process: in this determination process, based on signal information indicating the timing of traffic light color switching and congestion information indicating the occurrence of congestion, it determines whether, among the candidate routes from the passenger's pick-up point to the destination, at least one of the following occurs: a first stop caused by the traffic light color and a second stop caused by congestion. The route search unit uses the determination result of the determination process to determine the route the vehicle will travel from the candidate routes.

2. The information processing device according to claim 1, characterized in that, The route search unit calculates the number of first stops (i.e., the first stop count) and the number of second stops (i.e., the second stop count) from the route candidates based on the congestion information and the signal information, and uses the first stop count and the second stop count to determine the route for the vehicle to travel from the route candidates.

3. The information processing device according to claim 2, characterized in that, The information processing device determines the path candidate with the smallest sum of the first stop count and the second stop count as the path for the vehicle to travel.

4. The information processing apparatus according to any one of claims 1 to 3, characterized in that, The route search unit calculates the stopping time at each location in the route candidates where either the first stop or the second stop occurs, based on the congestion information and the signal information, and uses the calculated stopping time to determine the route the vehicle will travel from the route candidates.

5. The information processing apparatus according to claim 4, characterized in that, The path candidate with the smallest maximum stopping time among the path candidates is determined as the path for the vehicle to travel.

6. The information processing apparatus according to any one of claims 1 to 5, characterized in that, The route taken by the vehicle is determined by a set time, which is either the earliest allowed arrival time of the vehicle at the destination or the latest allowed arrival time of the vehicle at the destination.

7. The information processing apparatus according to claim 6, characterized in that, The set time is the first set time that has elapsed a defined period of time since the target arrival time specified by the user. The route taken by the vehicle is determined in such a way that the arrival time of the vehicle to the destination is prior to the first set time.

8. The information processing apparatus according to claim 6 or 7, characterized in that, The set time is a second set time that is determined earlier than the target arrival time specified by the user. The route taken by the vehicle is determined by making the arrival time of the vehicle to the destination after the second set time.

9. The information processing apparatus according to any one of claims 1 to 8, characterized in that, The path search unit also determines the path the vehicle travels based on at least one of the following: the curvature of the road curves, the number of curves within a fixed range, and the road gradient.

10. The information processing apparatus according to any one of claims 1 to 9, characterized in that, The path search unit also determines the route the vehicle will take based on the circumstances of the crime.

11. An information processing device, characterized in that, The information processing device has a route search unit, which calculates at least one of the stopping time and the number of stops (i.e., stopping information) of the candidate routes from the passenger's pick-up point to the destination based on signal information indicating the timing of traffic light color switching and congestion information indicating the occurrence of congestion. The route search unit then uses the calculated stopping information to determine the route the vehicle travels.

12. A vehicle that a user can ride in, characterized in that, The vehicle has a route search unit that performs the following determination process: in this determination process, based on signal information indicating the timing of traffic light color switching and congestion information indicating the occurrence of congestion, it determines whether, among the candidate routes (route candidates) from the user's pick-up point to their destination, at least one of the following occurs: a first stop caused by the traffic light color and a second stop caused by congestion. The route search unit uses the determination result of the determination process to determine the route the vehicle will travel from the route candidates.

13. The vehicle according to claim 12, characterized in that, The vehicle has a driving control unit that performs autonomous driving driving control of the vehicle based on the path determined by the path search unit.

14. A path determination method, which is a path determination method in an information processing device for determining the path of a vehicle, characterized in that, It includes the following steps: The following determination process is performed, in which, based on signal information indicating the timing of traffic light color switching and congestion information indicating the occurrence of congestion, it is determined whether, among the candidate routes (i.e., route candidates) from the passenger's pick-up point to their destination, at least one of the following occurs: a first stop due to the traffic light color and a second stop due to congestion. Using the determination result of the determination process, the path for the vehicle to travel is determined from the path candidates.

15. A program, characterized in that, The computer system that determines the vehicle's route performs the following steps: The following determination process is performed, in which, based on signal information indicating the timing of traffic light color switching and congestion information indicating the occurrence of congestion, it is determined whether, among the candidate routes (i.e., route candidates) from the passenger's pick-up point to their destination, at least one of the following occurs: a first stop due to the traffic light color and a second stop due to congestion. Using the determination result of the determination process, the path for the vehicle to travel is determined from the path candidates.

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