Map information storage device, route search device, route search method, route search program, route search device, and vehicle control device

Abstract

The present invention provides a vehicle control device that enables the use of vehicles such as ultra-compact mobility vehicles depending on the surrounding conditions. [Solution] The vehicle control device 1 has a control unit 3 that acquires the degree of congestion around the vehicle 100, which has multiple driving modes in autonomous driving, and restricts driving using at least some of the multiple driving modes based on that degree of congestion. In this way, it is possible to restrict the driving of the vehicle 100 according to the degree of congestion around it.

Description

Technical Field

[0001] The present invention relates to a map information storage device, a route search device, a route search method, a route search program, a route search device, and a vehicle control device for controlling the travel of a vehicle having a plurality of travel modes.

Background Art

[0002] In recent years, research and development of small moving bodies called ultra-small mobility have been underway. This ultra-small mobility has a mobility and loading capacity greater than those of conventional small moving bodies such as bicycles as a single-person low-speed moving means in inconvenient areas where public transportation is not prosperous, and is a more compact moving body than conventional automobiles (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Such ultra-small mobility is also assumed to be able to navigate not only on roadways but also on sidewalks and bicycle lanes, or to be able to travel only in a specific area such as within a theme park.

[0005] Ultra-small mobility may have various travel modes such as autonomous driving, manual driving, single-vehicle travel, and group travel by multiple vehicles. However, for example, it is undesirable for ultra-small mobility to travel unrestrictedly in a theme park crowded with visitors, as it would cause inconvenience to those around.

[0006] As an example of the problems to be solved by the present invention, it is possible to use a vehicle such as ultra-small mobility according to the surrounding situation. [Means for solving the problem]

[0007] To solve the above problems, the invention described in claim 1 is a map information storage device that stores map information divided into a plurality of sections for a specific area, wherein each of the plurality of sections contains at least information based on the density of moving objects, including people moving in each section, with respect to congestion in each section, and the information based on the density is estimated based on point cloud information that represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects. The invention described in claim 2 is a map information storage device that stores map information in which only the road portion within a specific area is divided into a plurality of sections, wherein each of the plurality of sections contains at least information regarding congestion in each section, and the information regarding congestion is estimated based on point cloud information that represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects. The invention described in claim 3 is a map information storage device that stores map information divided into a plurality of sections for a specific area where road network information consisting of links and nodes has not been constructed, wherein each of the plurality of sections contains at least information regarding congestion in that section, and the information regarding congestion is estimated based on point cloud information that represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of those objects.

[0008] The invention described in claim 7 is a path search device characterized by comprising the above-mentioned map information storage device and a search unit that searches for a path to move within the specific area based on the map information.

[0009] The invention described in claim 8 is a pathfinding method performed by a pathfinding device for searching for a path in a specific area, comprising: an acquisition step of acquiring map information which divides the specific area into a plurality of sections, and each of the plurality of sections includes at least information based on the density of moving objects, including people, moving through each section, with respect to congestion in each section; and a search step of searching for a path to move through the specific area based on the map information, wherein the information based on density is estimated based on point cloud information which represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects. The invention described in claim 9 is a pathfinding program characterized by causing a computer to execute the above-described pathfinding method. The invention described in claim 10 is a path search device characterized in that only the road portion within a specific area is divided into a plurality of sections, and each of the plurality of sections is equipped with map information acquisition equipment that acquires map information that includes at least information based on the density of moving objects, including people, moving through each section, with respect to congestion in each section, and a search equipment that searches for a path to move within the specific area based on the map information, wherein the information based on the density is estimated based on point cloud information that represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects. The invention described in claim 11 is a path search device comprising: a map information acquisition unit that acquires map information which divides a specific area into a plurality of sections, and each of the plurality of sections includes at least information based on the density of moving objects, including people, moving through each section, with respect to congestion in each section; and a search unit that searches for a path to move within the specific area based on the map information, wherein the specific area does not have road network information consisting of links and nodes, and the density-based information is estimated based on point cloud information which represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects. The invention described in claim 12 is a vehicle control device comprising: a map information storage device; an acquisition unit that acquires information based on the density of the area around a vehicle based on the map information, having a plurality of driving modes including a destination setting mode in which a destination is set and the vehicle drives along a route to the destination, and a walking mode in which the vehicle drives along a fixed walking route without setting a destination; and a control unit that restricts driving in at least some of the plurality of driving modes based on the information based on the density of the area, wherein the control unit changes the range in which the information based on the density of the area is acquired according to the destination in the destination setting mode, and sets the range in which the information based on the density of the area is acquired to include the entire area of ​​the walking route in the walking mode. The invention described in claim 13 is a vehicle control device comprising: a map information storage device; an acquisition unit that acquires information about congestion around a vehicle having a plurality of driving modes, including a destination setting mode in which a destination is set and the vehicle drives along a route to the destination, and a walking mode in which the vehicle drives along a fixed walking route without setting a destination, based on the map information; and a control unit that restricts driving in at least some of the plurality of driving modes based on the congestion information, wherein the control unit changes the range in which information about congestion is acquired according to the destination in the case of the destination setting mode, and sets the range in which information about congestion is acquired to include the entire walking route in the case of the walking mode. The invention described in claim 14 is a vehicle control device comprising: a map information storage device; an acquisition unit that acquires information based on the density of traffic around a vehicle having a plurality of driving modes based on the map information; and a control unit that restricts driving in at least some of the plurality of driving modes based on the information based on the density of traffic, wherein the control unit changes the range in which the information based on the density of traffic is acquired according to the destination, sets a candidate mode from the plurality of driving modes based on a first density representing the information based on the density of traffic in a first region around the vehicle, and performs a determination process to determine whether it is possible to drive in the candidate mode based on a second density representing the information based on the density of traffic in a second region that is wider than the first region and includes a driving route to the destination in the candidate mode, starts driving in the candidate mode if it is possible, and repeats the determination process by changing the destination or the candidate mode if it is not possible. The invention described in claim 15 is a vehicle control device comprising: a map information storage device; an acquisition unit that acquires information on congestion around a vehicle having a plurality of driving modes based on the map information; and a control unit that restricts driving in at least some of the plurality of driving modes based on the information on congestion, wherein the control unit changes the range in which information on congestion is acquired according to the destination, sets a candidate mode from the plurality of driving modes based on a first congestion level representing information on congestion in a first area around the vehicle, and performs a determination process to determine whether it is possible to drive in the candidate mode based on a second congestion level representing information on congestion in a second area wider than the first area, including the driving route to the destination in the candidate mode, starts driving in the candidate mode if it is possible, and repeats the determination process by changing the destination or the candidate mode if it is not possible. [Brief explanation of the drawing]

[0010] [Figure 1] This is a perspective view of a vehicle having a map information storage device and a vehicle control device according to a first embodiment of the present invention, as seen from the front at an oblique angle. [Figure 2] It is a perspective view seen from the obliquely rear of the vehicle shown in FIG. 1. [Figure 3] It is a perspective view of the vehicle shown in FIG. 1 when it is upright. [Figure 4] It is an explanatory diagram of the longitudinal running mode of the vehicle shown in FIG. 1. [Figure 5] It is an explanatory diagram of the parallel running mode of the vehicle shown in FIG. 1. [Figure 6] It is an explanatory diagram of the attraction mode of the vehicle shown in FIG. 1. [Figure 7] It is a configuration diagram of a system having the vehicle shown in FIG. 1. [Figure 8] It is a functional configuration diagram of the vehicle control device shown in FIG. 7. [Figure 9] It is a functional configuration diagram of the server device shown in FIG. 7. [Figure 10] It is a table showing the relationship between the congestion level and the running mode. [Figure 11] It is a flowchart of the operation of the vehicle control device shown in FIG. 8. [Figure 12] It is a flowchart of the operation of the vehicle control device shown in FIG. 8. [Figure 13] It is a flowchart of the operation of the server device shown in FIG. 9. [Figure 14] It is a flowchart of the operation of the server device shown in FIG. 9. [Figure 15] It is an explanatory diagram showing an example of a map stored in the map information storage device according to an embodiment of the present invention. [Figure 16] It is an explanatory diagram showing an example different from the map shown in FIG. 13. [Figure 17] It is an explanatory diagram of the map data structure stored in the map information storage device according to an embodiment of the present invention. [Figure 18] It is a flowchart of the operation of the route search device according to an embodiment of the present invention. [Figure 19] It is an explanatory diagram showing an example of route search in the flowchart shown in FIG. 18. [Figure 20]It is an explanatory diagram regarding prediction of a congestion area. [Figure 21] It is a flowchart of the operation of a route search device according to an embodiment of the present invention.

Mode for Carrying Out the Invention

[0011] Hereinafter, a vehicle control device according to an embodiment of the present invention will be described. The vehicle control device according to an embodiment of the present invention includes an acquisition unit that acquires the degree of congestion around a vehicle having a plurality of driving modes, and a control unit that restricts driving in at least some of the plurality of driving modes based on the degree of congestion. By doing so, driving in the driving mode of the vehicle can be restricted according to the surrounding degree of congestion. Therefore, vehicles such as ultra-small mobility can be used according to the surrounding situation.

[0012] Further, the plurality of driving modes are driving modes in the autonomous driving of the vehicle, and the control unit may restrict driving in the driving mode in the autonomous driving based on the degree of congestion. By doing so, vehicles such as ultra-small mobility can be used according to the surrounding situation during autonomous driving.

[0013] Further, the control unit may restrict the driving conditions in a specific driving mode according to the degree of congestion. By doing so, for example, the number of vehicles included in a group during group driving can be restricted according to the degree of congestion.

[0014] Further, a vehicle control method according to an embodiment of the present invention includes an acquisition step of acquiring the degree of congestion around a vehicle having a plurality of driving modes, and a control step of restricting driving in at least some of the plurality of driving modes based on the degree of congestion. By doing so, driving in the driving mode of the vehicle can be restricted according to the surrounding degree of congestion. Therefore, vehicles such as ultra-small mobility can be used according to the surrounding situation.

[0015] Furthermore, the vehicle control method described above may be executed by a computer. By doing so, the computer can be used to restrict the vehicle's driving mode according to the degree of surrounding congestion. [Examples]

[0016] A vehicle having a vehicle control device according to the first embodiment of the present invention will be described with reference to Figures 1 to 14. Vehicle 100 is a single-seater ultra-compact mobility vehicle as shown in Figures 1 to 3.

[0017] The vehicle 100 comprises a frame 101, a seat 102, a backrest 103, a footrest 104, wheels 105 (105R, 105L), an armrest 106, an operating unit 107, and a vehicle control device 1 (not shown in Figures 1 to 3).

[0018] The frame 101 is a structural component of the vehicle. The seat 102, backrest 103, footrest 104, wheels 105, armrests 106, etc., are attached to the frame 101. In addition, a number or other identifier for the vehicle is displayed on the upper end of the member 101a that supports the backrest 103 of the frame 101.

[0019] The seat surface 102 is formed in a roughly circular shape, and the user P (see Figure 2) sits on it. When the vehicle 3 transforms from a chair type (Figures 1 and 2) to an upright type (Figure 3), the seat surface 102 supports the lower back and buttocks from behind.

[0020] The backrest 103 is formed in a roughly hexagonal shape and supports the back of user P. The footrest 104 supports the feet of user P.

[0021] The wheel 105 consists of a right wheel 105R and a left wheel 105L, and is rotatably mounted on the left and right ends of the frame 101, respectively, beneath the seat surface 102.

[0022] The armrest 106 is attached to member 101a of the frame 101 and can support the user P's arm as shown in Figure 2. The armrest 106 is provided with an operating unit 107 at its tip. The operating unit 107 is located at the tip of the armrest 106. The operating unit 107 can be used to set the driving mode of the vehicle 100, make various settings during automatic driving, and perform driving operations during manual driving.

[0023] Here, autonomous driving refers to the vehicle 100 being driven autonomously by automatically controlling steering, speed adjustment, braking, etc., using the vehicle control device 1, etc. Manual driving refers to the driver, user P, performing steering, speed adjustment, braking, etc., using the operating unit 107, etc.

[0024] In addition to the vehicle control device 1 described above, the vehicle 100 also has a motor that drives the wheels 105 and a battery that supplies power to the motor. Furthermore, the vehicle 100 has various sensors, such as a gyro sensor, to maintain balance so that it does not tip over even with only two wheels. Alternatively, auxiliary wheels other than the wheels 105 may be provided.

[0025] Furthermore, the vehicle 100 can transform from a chair-type configuration as shown in Figures 1 and 2 to an upright configuration as shown in Figure 3. When transformed into the upright configuration, the angle of the seat surface 102 moves to become closer to perpendicular to the road surface, and the backrest 103 moves upward in accordance with the movement of the seat surface 102. The armrest 106 then transforms to erect the control unit 107, allowing the user P to grasp the control unit 107. Both the chair-type and upright configurations can be operated in either automatic or manual mode. Moreover, both the chair-type and upright configurations can be operated in any of the driving modes described below.

[0026] Figures 4 to 7 show the main driving modes of vehicle 100 during autonomous driving. In other words, vehicle 100 is a vehicle that can selectively set to one of several modes for autonomous driving. Figure 4 shows the tandem driving mode. In this driving mode, multiple vehicles 100 drive in a line, with the leading vehicle 100 acting as the master, followed by the following vehicles 100.

[0027] Figure 5 shows the parallel driving mode. In this driving mode, multiple vehicles 100 drive side by side, with the other vehicles following one of the master vehicles 100.

[0028] Figure 6 shows the attraction mode. This mode of travel incorporates entertainment elements, such as spinning around in place (Figure 7) or zigzagging, and is not intended to move to a specific location. Although Figure 6 shows the vehicle rotating in an upright position, it may also rotate in a chair position.

[0029] In addition to the driving modes shown in Figures 4 to 6, there is also a single-vehicle driving mode in which vehicle 100 drives autonomously by itself. Furthermore, in addition to the attraction mode, the driving modes can be selected from a destination setting mode in which a destination is set and the vehicle drives along the route to that destination, and a strolling mode in which no destination is set and the vehicle drives along a fixed route like a tour.

[0030] Next, the system having the vehicle 100 described above will be explained with reference to Figure 7. As shown in Figure 7, the system includes the vehicle 100 and a server device 50. The vehicle 100 is also equipped with a vehicle control device 1. As shown in Figure 7, the server device 50 is able to communicate with the vehicle control device 1 equipped in the vehicle 100 via a network N such as the Internet.

[0031] Figure 8 shows the functional configuration of the vehicle control device 1. The vehicle control device 1 comprises a communication unit 2, a control unit 3, a storage unit 4, and a GPS receiver 5.

[0032] The communication unit 2 transmits map request information and other data output by the control unit 3 to the server device 50. The communication unit 2 also receives map data distributed from the server device 50. The communication unit 2 also obtains congestion information in its surroundings from the server device 50. Furthermore, the communication unit 2 communicates with other vehicles 100, etc., either directly or via the network N, depending on the driving mode, to send and receive information for the tracking operation described above.

[0033] The control unit 3 is composed of, for example, a microcomputer having a CPU and memory, and controls the driving of the vehicle 100 (steering, speed, braking, etc.). The control unit 3 also requests map data and congestion information of the area around the vehicle 100 from the server device 50 as needed, and stores the map data received by the communication unit 2 as map data 4a in the storage unit 4. Furthermore, based on the driving mode setting information received from the operation unit 107, the control unit 3 sends and receives information for follow-up operations with other vehicles, etc., via the communication unit 2 so that the vehicle drives in the specified driving mode. In addition, the control unit 3 controls the driving of the vehicle 100 based on the congestion information received by the communication unit 2.

[0034] The memory unit 4 stores map data 4a. In other words, the memory unit 4 functions as a map memory device that stores map information. Map data 4a is a map that contains detailed information about roads and surrounding features, such as road width, the content and location of signs, and the location of white lines, in order for the vehicle 100 to drive autonomously.

[0035] The GPS receiver 5 is based on radio waves from GPS (Global Positioning System) satellites. This is a well-known device for detecting the current position of vehicle 100. However, as long as the current position of vehicle 100 can be detected, other methods such as using a gyro sensor or Wi-Fi signals are also acceptable, not just the GPS receiver 5.

[0036] Next, Figure 9 shows the functional configuration of the server device 50. The server device 50 comprises a communication unit 51, a control unit 52, and a storage unit 53.

[0037] The communication unit 51 receives map request information and the like transmitted from the vehicle control device 1. The communication unit 51 also transmits map data read from the storage unit 53 to the vehicle control device 1. The communication unit 51 also receives detection information such as point cloud information and captured images from sensors such as lidars and cameras installed on the site where the vehicle 100 is scheduled to travel. Alternatively, location information may be obtained from terminals held by visitors or others on the site.

[0038] A LiDAR (Light Detection and Ranging) is a sensor that recognizes objects in the surrounding area it scans. It is a well-known sensor that emits electromagnetic waves such as laser light and discretely measures the direction and distance to objects in the scanning range using the reflected waves (reflected light), recognizing the position and shape of those objects as a three-dimensional point cloud. Therefore, the point cloud recognized by the LiDAR is output as point cloud information, which is information about objects in a given space.

[0039] The control unit 52 is composed of a microcomputer, for example, a CPU and memory. The control unit 52 reads the requested map data from the storage unit 53 based on the map request information and outputs it to the communication unit 51. The control unit 52 also estimates the degree of congestion based on the detection information (point cloud information, captured images, etc.) received by the communication unit 51. The degree of congestion is estimated not only based on congestion caused by people, but also based on the density of all moving objects on the ground surface that can move within the site, such as other vehicles 100. The degree of congestion may be estimated for each predetermined section, such as several meters by several meters. Alternatively, a congestion request may be received from a vehicle 100, and the estimation may be performed for a range of several meters around the current position of the requested vehicle 100.

[0040] The memory unit 53 stores map data 53a. Like map data 4a, map data 53a is a map that contains detailed information about roads and surrounding features for the vehicle 100 to drive autonomously. The memory unit 53 also stores congestion level information 53b, which is estimated by the control unit 52.

[0041] Here, the relationship between congestion level and driving mode will be explained with reference to Figure 10. Figure 10 is a table that defines whether driving is possible (○) or impossible (×) depending on the congestion level in each driving mode. In Figure 10, there are two attraction modes, but Attraction 2 is a mode that requires a larger area to drive than Attraction 1.

[0042] In Figure 10, first, if the congestion level is "very high," automatic driving is not allowed, and only manual driving is permitted. Next, if the congestion level is "high," only the automatic driving standalone mode with destination setting mode and manual driving are permitted. If the congestion level is "medium," only Attraction 2 mode is not allowed, and all other modes are permitted. If the congestion level is "low," all modes are permitted.

[0043] The specific numerical ranges for the congestion levels "Extra Large," "Large," "Medium," and "Small" should be set appropriately according to the size of the vehicle (100) and the surrounding environment. Alternatively, numerical values ​​may be used instead of "Extra Large," "Large," "Medium," and "Small."

[0044] Next, the operation (vehicle control method) of the vehicle control device 1 with the above configuration will be explained with reference to the flowcharts in Figures 11 and 12. The flowcharts in Figures 11 and 12 are flowcharts for automatic driving. Furthermore, the flowcharts shown in Figures 11 and 12 can be configured as a vehicle control program by being executed by the CPU of the control unit 3.

[0045] First, in step S101, the control unit 3 obtains the current position from the GPS receiver 5. That is, it obtains the current position of the vehicle 100.

[0046] Next, in step S102, the control unit 3 obtains the congestion level around the current location from the server device 50. In step S102, the control unit 3 sends congestion request information (congestion request information) to the server device 50 via the communication unit 2, and the congestion level around the current location is sent back from the server device 50 in response to the congestion request information. The congestion request information includes the current location information obtained in step S101. In other words, the control unit 3 functions as an acquisition unit that obtains the congestion level around the vehicle 100 which has multiple driving modes.

[0047] Next, in step S103, the control unit 3 displays and announces to user P the available driving modes based on the congestion level acquired in step S102 and the table shown in Figure 10. For example, if the congestion level is "medium," driving modes other than attraction 2 are presented. In other words, the control unit 3 restricts driving to at least some of the multiple driving modes based on the congestion level.

[0048] Next, in step S104, the control unit 3 allows the user P to select one of the driving modes presented in step S103, for example, from the operation unit 107 or the like.

[0049] Next, in step S105, the control unit 3 determines the driving mode selected in step S104. If it includes the destination setting mode, it proceeds to step S106; if it includes the strolling mode, it proceeds to step S107; and if it is the attraction mode, it proceeds to step S109.

[0050] Next, in step S106, the control unit 3 determines that the driving mode selected as a result of the determination in step S105 includes the destination setting mode, and therefore prompts user P to set a destination. User P sets the destination using the operation unit 107, etc.

[0051] Next, in step S107, the control unit 3 obtains from the server device 50 the congestion level over a wide area, including the route to the destination set in step S106, and the walking route if the driving mode selected as a result of the determination in step S105 includes the walking mode. The method for obtaining the congestion level is basically the same as in step S102. However, it requests the congestion level not only for the area around the current location, but also for the route from the current location to the destination or the walking route (route).

[0052] Next, in step S108, the control unit 3 determines whether it is possible to travel along the route to the destination or the walking route. If it is possible (YES), it proceeds to step S109; if it is not possible (NO), it proceeds to step S110. In this step, based on the route to the destination or the walking route and the table in Figure 10, if there are any sections along the route where travel is impossible, it is determined that the route is impassable. In other words, this step also restricts travel using at least some of the multiple travel modes based on the degree of congestion.

[0053] Next, in step S109, the control unit 3 determines that it is possible to drive in step S108, and therefore starts driving in autonomous mode.

[0054] On the other hand, in step S110, the control unit 3 determines whether or not the destination setting mode is included. If the destination setting mode is included, it returns to step S106; otherwise, it returns to step S104. This step is performed to determine the return destination of the process because it was determined in step S108 that driving is impossible.

[0055] In step S111 in Figure 12, which follows step S109, the control unit 3 acquires the congestion level over a wide area, including the area around the vehicle 100, after the vehicle has started moving in step S109. This step and subsequent steps are performed to respond if the congestion level is updated by the server device 50 while the vehicle is moving.

[0056] Next, in step S112, the control unit 3 determines whether the congestion level has changed. If it has not changed (NO), it returns to step S111; if it has changed (YES), it proceeds to step S113.

[0057] Next, in step S113, the control unit 3 determines whether the vehicle 100 can continue to travel. If it can continue (YES), it returns to step S111; otherwise, it proceeds to step S114. Whether or not travel can continue can be determined in the same way as in step S108. In other words, this step also restricts travel using at least some of the multiple travel modes based on the degree of congestion.

[0058] Next, in step S114, the control unit 3 determines in step S113 that it is not possible to continue driving, and therefore performs actions such as switching to manual operation or stopping driving. When performing this step, it is preferable to notify the user P in advance before performing the switching or other actions.

[0059] As is clear from the above explanation, step S102 functions as an acquisition process, and steps S103, S108, and S113 function as control processes.

[0060] Next, the operation of the server device 50 will be explained with reference to the flowcharts in Figures 13 and 14. The flowchart in Figure 13 shows the operation of estimating the congestion level and storing it in the storage unit 53. First, in step S201, the control unit 52 acquires detection information from the lidar, camera, etc. via the communication unit 51.

[0061] Next, in step S202, the control unit 52 estimates the degree of congestion based on the detection information acquired in step S201. The degree of congestion is estimated for each predetermined unit, as described above. If there are areas for which detection information cannot be obtained, the degree of congestion may be estimated from the congestion of areas adjacent to those areas.

[0062] Next, in step S203, the control unit 52 stores the congestion level estimated in step S202 in the storage unit 53 and returns to step S201. Then, by executing step S201 again, the congestion level is updated sequentially.

[0063] The server device 50 may also be controlled to increase the sensing capability of the sensors as the level of congestion increases. For example, the server device may be controlled to increase the resolution of the lidar and camera as the level of congestion increases.

[0064] Figure 14 shows the operation when a congestion level request is received from the vehicle control device 1. First, in step S301, the control unit 52 determines whether or not congestion level request information has been received from the vehicle control device 1. If it has not been received, it waits in this step; if it has been received, it proceeds to step S302.

[0065] Next, in step S302, the congestion level of the area indicated in the congestion request information is read from the storage unit 53. In this step, the congestion level of the area indicated by the current location information and route information included in the congestion request information is read.

[0066] Next, in step S303, the congestion level read in step S302 is transmitted as congestion level information to the vehicle control device 1 via the communication unit 51.

[0067] According to this embodiment, the vehicle control device 1 has a control unit 3 that acquires the degree of congestion around the vehicle 100, which has multiple driving modes during autonomous driving, and restricts driving using at least some of the multiple driving modes based on that degree of congestion. In this way, the driving mode of the vehicle 100 can be restricted according to the degree of congestion around it. Therefore, the vehicle 100, such as an ultra-compact mobility vehicle, can be used according to the surrounding conditions.

[0068] Furthermore, the control unit 3 determines whether or not the vehicle 100 can travel based on the route to the destination and the level of congestion along the walking route. In this way, if it is determined in advance that it will be difficult to reach the destination, the vehicle can be stopped from traveling.

[0069] In the above-described embodiment, steps S107, S108, and S111 were used to obtain congestion levels outside the vicinity of vehicle 100 and determine whether or not to proceed based on the congestion level along the route to the destination. However, these steps may be omitted if the decision is made based only on the congestion level around vehicle 100. In that case, the vehicle can proceed partway to the destination and then turn back, or set a different destination.

[0070] Furthermore, in the above-described embodiment, the driving mode was restricted according to the degree of congestion, but the driving conditions in a specific driving mode may also be restricted. For example, if the degree of congestion changes in the direction of congestion in parallel driving mode, the driving conditions in that driving mode may be changed, such as reducing the number of parallel trains or narrowing the distance between trains 100.

[0071] Furthermore, in the above-described embodiment, the vehicle control device 1 acquired the congestion level and restricted the driving mode, but the server device 50 may also restrict the driving mode. In other words, the server device 50 may acquire information such as the current location and driving mode settings from the vehicle control device 1 and execute the flowchart in Figure 11 based on that information. The judgment result, such as whether driving is possible or impossible, is transmitted to the vehicle control device 1 along with the route to the destination. The server device 50 may also acquire information about the current location from the vehicle control device 1 while driving, execute the flowchart in Figure 12, and if it is not possible to continue driving, send a command to the vehicle control device 1 to switch to manual driving or stop driving. In this case, the control unit 52 of the server device 50 functions as an acquisition unit and a control unit. [Examples]

[0072] Next, a vehicle control device according to a second embodiment of the present invention will be described with reference to Figures 15 to 20. Note that parts identical to those in the first embodiment described above are denoted by the same reference numerals and their descriptions are omitted.

[0073] This embodiment has the same configuration as Figures 1 to 9. This embodiment describes the search for a route traveled by a vehicle 100 in a specific area where road network information consisting of links and nodes such as theme parks and parks has not been established.

[0074] Figure 15 shows a specific area A, for example, the site of a theme park. This specific area A is divided into multiple meshes M (sections) of a predetermined size, as shown in Figure 15. Then, information indicating the difficulty of travel, such as the degree of congestion, is set for each of these meshes M.

[0075] The size of the mesh M is preferably such that it allows for the calculation of the congestion level and other factors described above, and is also appropriate as the travel path for vehicle 100. Furthermore, as shown in Figure 15, the mesh M does not have to be a square, but may be a polygon such as a rectangle, hexagon, or octagon. Also, each mesh M does not have to be the same size.

[0076] Furthermore, as shown in Figure 15, it is not necessary to divide the entire specific area A into mesh M; as shown in Figure 16, only the road (pathway) R portion may be divided into mesh M.

[0077] In this embodiment, information such as congestion level is included in the map data 53a. That is, the server device 50 is a map information storage device that stores map information divided into multiple sections for a specific area A, and each of the multiple sections contains at least information regarding congestion in that section.

[0078] The map data structure according to this embodiment will be explained with reference to Figure 17. As shown in Figure 17, the map data 53a includes a mesh number (No.) 53a1, location information 53a2, congestion level 53a3, and pollution level 53a4.

[0079] The mesh number 53a1 is a unique number assigned to each mesh M. The location information 53a2 is set as, for example, latitude and longitude. The congestion level 53a3 is the degree of congestion in the mesh M indicated by each mesh number 53a1, and can be estimated in the same manner as in the first embodiment. The degree of contamination 53a4 is information indicating the difficulty of driving, separate from the congestion level, and indicates the degree of contamination that should be avoided when driving vehicle 100, such as the presence or absence of dirt or puddles on the road.

[0080] This contamination level 53a4 is estimated by the control unit 52 of the server device 50 based on detection information (point cloud information, captured images, etc.) received by the communication unit 51, similar to the congestion level. The estimated contamination level is stored in the storage unit 53 and included in the map data 53a along with the congestion level.

[0081] Next, the operation (route search method) of the server device 50 according to this embodiment will be explained with reference to the flowchart in Figure 18. In other words, the server device 50 functions as a route search device. Furthermore, the flowchart shown in Figure 18 can be configured as a route search program to be executed by the CPU of the control unit 52.

[0082] First, in step S401, the control unit 52 obtains the current position of the vehicle 100 from the vehicle control device 1.

[0083] Next, in step S402, the control unit 52 obtains the destination from the vehicle control device 1. The vehicle control device 1 prompts the user P to input the destination and transmits the destination set by the operation unit 107, etc., to the server device 50.

[0084] Next, in step S403, the control unit 52 searches for a route from the current position acquired in step S401 to the destination acquired in step S402, based on the map data 53a read from the storage unit 53. That is, the control unit 52 functions as a search unit that searches for a route to move within a specific area A based on map information. Figure 19 shows an example of route search. Figure 19 is a diagram showing the degree of congestion and dirtiness in the specific area A shown in Figure 15. In Figure 19, the symbol S is the current position and the symbol G is the destination. Also, the shaded areas indicate mesh M with a congestion level of "extra large" or "large", and the grid-shaded areas indicate mesh M with a dirtiness level of "large". In this case, the route from the current position S to the destination G is searched in a way that avoids the shaded and grid-shaded mesh Ms described above. In other words, the route is searched to follow mesh Ms other than those where it is difficult for the vehicle 100 to travel.

[0085] In step S403, the route may be searched considering the congestion level settings for each driving mode shown in Figure 10. For example, in single-vehicle driving mode, the route is searched to avoid only mesh M with a congestion level of "extra large," while in parallel driving mode, the route is searched to avoid mesh M with both "extra large" and "large" congestion levels. A table like the one in Figure 10 may also be created for the degree of dirtiness.

[0086] Furthermore, the congestion level set for mesh M does not have to be multi-stage as shown in Figure 10; it can simply be a two-stage system of "crowded" / "not crowded." In this case, the threshold for whether or not it is crowded can be set appropriately according to the size of vehicle 100 and the surrounding environment, as in Figure 10.

[0087] Next, in step S404, the control unit 52 determines whether it is possible to travel to the destination based on the route search results from step S403. If it is possible, it transmits the searched route to the vehicle control device 1 in step S405. On the other hand, if it is not possible to travel, it returns to step S402 and sets the destination again.

[0088] As is clear from the above explanation, step S403 functions as an acquisition step and a search step.

[0089] In this embodiment as well, the congestion level is updated according to the flowchart shown in Figure 13. By doing so, the congestion level can be updated sequentially, making it more useful when the vehicle 100 is in motion. The degree of dirtiness may be updated in the same way. That is, the control unit 52 functions as a congestion information acquisition unit that acquires congestion information for a specific area by executing step S201. In other words, the detected information (point cloud information) becomes the congestion information. Furthermore, the control unit 52 functions as an update unit that updates information regarding the congestion of a section based on the acquired congestion information by executing steps S202 and S203.

[0090] By updating the congestion level, the path search in step S403 can predict changes in the congested mesh M due to the movement of people, etc. For example, as shown in Figure 20, if the shaded mesh M moves up one level (or moves up multiple times), it becomes possible to predict that it will move up further and search for a path accordingly.

[0091] According to this embodiment, the server device 50 is a map information storage device that stores map data 53a divided into multiple meshes M for a specific area A, and each of the multiple meshes M contains at least information regarding congestion in that mesh M. In this way, the congestion status for each section in a specific area can be grasped. Therefore, map information can be provided for vehicle travel even in areas without a road network such as theme parks with nodes or links.

[0092] Furthermore, the server device 50 includes a storage unit 53 and a control unit 52 that searches for a route to travel within a specific area A based on map data 53a. In this way, even in areas without a road network such as theme parks, the system can search for a travel route for the vehicle 100 and guide it along a route suitable for travel.

[0093] Note that in the flowchart shown in Figure 18, the server device 50 searches for the route, but the vehicle control device 1 may also search for the route. Figure 21 shows a flowchart when the vehicle control device 1 searches for the route. First, in step S501, the control unit 3 acquires map data from the server device 50 via the communication unit 2. This map data includes the congestion level and dirt level mentioned above. The acquired map data may be stored in the storage unit 4 as map data 4a.

[0094] Next, in step S502, the control unit 3 acquires the current position of the vehicle 100 detected by the GPS receiver 5.

[0095] Next, in step S503, the control unit 3 sets the destination. That is, it prompts the user P to input the destination, and the destination set by the operation unit 107, etc., is set.

[0096] Next, in step S504, a route from the current location obtained in step S502 to the destination obtained in step S503 is searched based on the map data obtained in step S501. The route search method is the same as in step S403.

[0097] Next, in step S505, based on the route search results from step S504, it is determined whether or not it is possible to travel to the destination. If it is possible, travel begins using the route searched in step S506. On the other hand, if it is not possible to travel, the process returns to step S503 and the destination is set again.

[0098] Furthermore, when the vehicle control device 1 searches for a route, it is possible to store the map data in advance within the vehicle control device 1 instead of acquiring the map data from the server device 50, as shown in the flowchart in Figure 21.

[0099] Furthermore, the present invention is not limited to the embodiments described above. That is, those skilled in the art can implement the invention in various ways, without departing from the core principles, in accordance with prior art knowledge. Such modifications, as long as they still incorporate the map storage device and vehicle control device of the present invention, are of course included within the scope of the present invention. [Explanation of Symbols]

[0100] 1. Vehicle control system 2 Communications Department 3. Control Unit (Acquisition Unit, Map Information Acquisition Unit) 4. Memory Unit (Map Information Storage Device) 4a Map data (map information) 5 GPS receivers 50 Server device (map information storage device) 51 Communications Department 52 Control Unit (Congestion Information Acquisition Unit, Update Unit) 53 Memory section 53a Map data (map information) 53b Congestion level information 100 vehicles

Claims

1. A map information storage device that stores map information divided into multiple sections for a specific area, Each of the aforementioned plurality of sections includes at least information regarding congestion in each section, based on the density of moving objects, including people moving within each section, and the information based on the density is estimated based on point cloud information representing the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects.

2. A map information storage device that stores map information in which only the road portion within a specific area is divided into multiple sections, Each of the aforementioned plurality of sections includes at least information regarding congestion in each section, and the information regarding congestion is estimated based on point cloud information representing the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects.

3. A map information storage device that stores map information divided into multiple sections for a specific area where road network information consisting of links and nodes has not been constructed, Each of the aforementioned plurality of sections includes at least information regarding congestion in each section, and the information regarding congestion is estimated based on point cloud information representing the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects.

4. The map information storage device according to claim 2 or 3, wherein each of the plurality of sections includes at least information relating to congestion in each section, based on the density of moving objects, including people moving through each section.

5. A congestion information acquisition unit that acquires congestion information for the specified area, An update unit updates information regarding congestion in the section based on the acquired congestion information, A map information storage device according to any one of claims 1 to 4, characterized by comprising the above.

6. A map information storage device according to any one of claims 1 to 4, characterized in that it stores a degree of dirtiness that represents the difficulty of driving in each of the aforementioned sections.

7. A map information storage device according to any one of claims 1 to 6, A search unit that searches for a path to move within the specified area based on the map information, A pathfinding device characterized by comprising the following features.

8. A pathfinding method performed by a pathfinding device that searches for a path in a specific region, The acquisition step involves obtaining map information which divides the aforementioned specific area into a plurality of sections, and each of the plurality of sections includes at least information based on the density of moving objects, including people, moving through each section, regarding congestion in that section. A search step of searching for a path to move within the specified area based on the map information, Includes, The pathfinding method is characterized in that the information based on the density is estimated based on point cloud information that represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects.

9. A route search program characterized by causing a computer to execute the route search method described in claim 8.

10. A map information acquisition unit acquires map information which divides only the road portion within a specific area into multiple sections, and each of the multiple sections includes at least information based on the density of moving objects, including people, moving through each section, regarding congestion in that section. A search unit that searches for a path to move within the specified area based on the map information, Equipped with, The pathfinding device is characterized in that the information based on the density is estimated based on point cloud information that represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects.

11. A map information acquisition unit acquires map information that divides a specific area into multiple sections, and each of the multiple sections includes at least information based on the density of moving objects, including people, moving through each section, regarding congestion in that section. A search unit that searches for a path to move within the specified area based on the map information, Equipped with, In the aforementioned specific area, road network information consisting of links and nodes has not been constructed. The pathfinding device is characterized in that the information based on the density is estimated based on point cloud information that represents the position and shape of objects present in each section as a three-dimensional point cloud, or on captured images of the objects.

12. A map information storage device according to claim 1, An acquisition unit that acquires information based on the density of people around a vehicle, based on map information, having multiple driving modes including a destination setting mode in which a destination is set and the vehicle drives along a route to that destination, and a walking mode in which the vehicle drives along a fixed walking route without setting a destination, A control unit that restricts driving in at least some of the multiple driving modes based on the information based on the density, Equipped with, The control unit changes the range for acquiring information based on density according to the destination in the destination setting mode, and sets the range for acquiring information based on density to include the entire walking route in the walking mode. A vehicle control device characterized by the following features.

13. A map information storage device according to claim 2 or 3, An acquisition unit that acquires information about the congestion around a vehicle having multiple driving modes, including a destination setting mode in which a destination is set and the vehicle drives along a route to that destination, and a strolling mode in which the vehicle drives along a fixed strolling route without setting a destination, based on the map information, A control unit that restricts driving in at least some of the multiple driving modes based on the congestion information, Equipped with, The control unit changes the range for acquiring congestion information according to the destination in the destination setting mode, and sets the range for acquiring congestion information to include the entire walking route in the walking mode. A vehicle control device characterized by the following features.

14. A map information storage device according to claim 1, An acquisition unit that acquires information based on the density of the surrounding area of ​​a vehicle having multiple driving modes, based on the map information, A control unit that restricts driving in at least some of the multiple driving modes based on the information based on the density, Equipped with, The control unit changes the range in which information based on the density is acquired according to the destination, sets a candidate mode from among the plurality of driving modes based on a first density representing information based on the density of a first area around the vehicle, and performs a determination process to determine whether it is possible to drive in the candidate mode based on a second density representing information based on the density of a second area that is wider than the first area and includes the driving route to the destination in the candidate mode, starts driving in the candidate mode if it is possible, and repeats the determination process by changing the destination or the candidate mode if it is not possible.

15. A map information storage device according to claim 2 or 3, An acquisition unit that acquires information regarding the congestion around a vehicle having multiple driving modes based on the map information, A control unit that restricts driving in at least some of the multiple driving modes based on the congestion information, Equipped with, The control unit changes the range from which congestion information is acquired according to the destination, sets a candidate mode from among a plurality of driving modes based on a first congestion level representing congestion information in a first area around the vehicle, and performs a determination process to determine whether it is possible to drive in the candidate mode based on a second congestion level representing congestion information in a second area wider than the first area, including the driving route to the destination in the candidate mode, starts driving in the candidate mode if it is possible, and repeats the determination process by changing the destination or the candidate mode if it is not possible.

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