Mobile control system and mobile control method

Abstract

To secure accuracy for controlling travel of a moving body so as to follow a target route in a predetermined area.SOLUTION: A moving-body control system controls travel of a moving body in a predetermined area. The moving-body control system estimates a position of the moving body, based on a steering angle and a speed of the moving body, and executes a travel control process for controlling travel of the moving body so as to follow a target route, based on the estimated position of the moving body. The moving-body control system obtains at least road surface condition information indicating slipperiness of a target road surface on the target route around the moving body. Further, the moving-body control system executes a deviation inhibition process of dynamically changing a control parameter used in the travel control process in accordance with the slipperiness of the target road surface so that the deviation of the moving body from the target route is inhibited.SELECTED DRAWING: Figure 13

Description

Technical Field

[0001] The present disclosure relates to a technique for controlling the travel of a moving body so as to follow a target path in a predetermined area.

Background Art

[0002] Patent Document 1 discloses a vehicle control device that performs Lane Keeping Assist. The vehicle travel control device determines a travel area in which the vehicle travels, determines a road surface condition in the travel area, and also recognizes road surface unevenness in the travel area. Then, the vehicle control device changes the travel area based on the road surface condition and the road surface unevenness in the travel area. When the road surface condition is a wet state, the changeable range of the travel area is set narrower or the vehicle speed is decreased as compared with the case where the road surface condition is a dry state.

[0003] Patent Documents 2, 3, and 4 disclose parking assistance technologies for assisting parking of a vehicle.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Patent Document 2

Patent Document 3

Patent Document 4

Summary of the Invention

Problems to be Solved by the Invention

[0005] Consider controlling the travel of a moving body so as to follow a target path in a predetermined area. Such travel control processing requires information on the position of the moving body. Here, a movement amount (displacement amount) may be calculated based on the steering angle and speed of the moving body, and the position of the moving body may be estimated based on the movement amount. Such a method is also called dead reckoning.

[0006] When the moving body travels on a slippery road surface, the probability of slip or tire spin occurring is high. When slip or tire spin occurs, the movement amount calculated from the steering angle and speed deviates from the actual movement amount. Therefore, the position estimation accuracy decreases. When the position estimation accuracy decreases, the accuracy of the travel control processing for causing the moving body to follow the target path also decreases, and there is a risk that the moving body will deviate from the target path.

[0007] One object of the present disclosure is to provide a technique capable of ensuring the accuracy of controlling the travel of a moving body so as to follow a target path in a predetermined area.

Means for Solving the Problems

[0008] The first aspect relates to a movement control system that controls the travel of a moving body in a predetermined area. The movement control system includes one or more processors. The one or more processors perform a position estimation process for estimating the position of the moving body based on the steering angle and speed of the moving body, perform a travel control process for controlling the travel of the moving body so as to follow a target path based on the estimated position of the moving body, perform a road surface state acquisition process for acquiring road surface state information indicating at least the slipperiness of a target road surface on the target path around the moving body, and perform a deviation suppression process for dynamically changing control parameters used in the travel control process according to the slipperiness of the target road surface so that deviation of the moving body from the target path is suppressed. are configured to execute.

[0009] The second aspect relates to a movement control method for controlling the travel of a moving body in a predetermined area. The movement control method includes a position estimation process for estimating the position of the moving body based on the steering angle and speed of the moving body, a travel control process for controlling the travel of the moving body to follow a target route based on the estimated position of the moving body, a road surface state acquisition process for acquiring road surface state information indicating at least the slipperiness of a target road surface on the target route around the moving body, and a deviation suppression process for dynamically changing control parameters used in the travel control process according to the slipperiness of the target road surface so that deviation of the moving body from the target route is suppressed.

Advantages of the Invention

[0010] According to the present disclosure, the position of the moving body is estimated based on the steering angle and speed of the moving body, and a travel control process is performed based on the estimated position so that the moving body follows the target route. In the travel control process, the slipperiness of the target road surface on the target route is considered. More specifically, the control parameters used in the travel control process are dynamically set according to the slipperiness of the target road surface so that deviation of the moving body from the target route is suppressed. Thereby, deviation of the moving body from the target route is suppressed. That is, the accuracy of the travel control process is ensured.

Brief Description of the Drawings

[0011]

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Mode for Carrying Out the Invention

[0012] Embodiments of the present disclosure will be described with reference to the accompanying drawings.

[0013] Consider the control of a moving body. Examples of the moving body include a vehicle, a robot, etc. Examples of the robot include a logistics robot, a delivery robot, a work robot, etc. The moving body may be provided with an autonomous driving function. The vehicle may be an autonomous driving vehicle. As an example, in the following description, the case where the moving body is a vehicle will be considered. In the case of generalization, the "vehicle" in the following description shall be read as "moving body".

[0014] 1. Outline of Vehicle Control System FIG. 1 is a conceptual diagram for explaining the outline of the vehicle control system 10 according to the present embodiment. The vehicle control system 10 controls the running of the vehicle 1. For example, the vehicle control system 10 is mounted on the vehicle 1. Alternatively, at least a part of the vehicle control system 10 may be arranged in an external device outside the vehicle 1 to remotely control the vehicle 1.

[0015] In particular, the vehicle control system 10 controls the running of the vehicle 1 so as to follow the target route TP in a predetermined area AR. Examples of the predetermined area AR include a parking lot, a single town (smart city), etc. The target route TP is a set of target positions. For each target position, a target position and a target speed may be associated. The target route TP may be predetermined. The process of controlling the running of the vehicle 1 so as to follow the target route TP is hereinafter referred to as "running control process".

[0016] Information on the current position of the vehicle 1 is required for the running control process. Therefore, the vehicle control system 10 executes a "position estimation process" for estimating the position of the vehicle 1 in the predetermined area AR. Then, the vehicle control system 10 executes a running control process based on the estimated position of the vehicle 1 and the target route TP so that the vehicle 1 follows the target route TP.

[0017] According to the present embodiment, the steering angle and the vehicle speed (wheel speed) of the vehicle 1 are used for the position estimation process. The steering angle and the vehicle speed are detected by a steering angle sensor and a vehicle speed sensor (wheel speed sensor) mounted on the vehicle 1, respectively. The vehicle control system 10 calculates the movement amount (displacement amount) of the vehicle 1 based on the steering angle and the vehicle speed of the vehicle 1, and estimates the position of the vehicle 1 based on the movement amount. Such a method is also called "dead reckoning".

[0018] To further improve the position estimation accuracy, a marker M (landmark) arranged in a predetermined area AR may be used. More specifically, the vehicle 1 is equipped with a recognition sensor for recognizing the situation around the vehicle 1. Typically, the recognition sensor includes a camera for imaging the surroundings of the vehicle 1. The vehicle control system 10 can recognize the marker M around the vehicle 1 by using the recognition sensor and grasp the relative positional relationship between the vehicle 1 and the marker M. Also, the vehicle control system 10 holds map information indicating the installation position of the marker M in the predetermined area AR. The vehicle control system 10 estimates the position of the vehicle 1 in the predetermined area AR by the above-mentioned dead reckoning. Further, the vehicle control system 10 corrects the estimated position of the vehicle 1 based on the estimated position of the vehicle 1, the relative positional relationship between the vehicle 1 and the marker M, and the installation position of the marker M in the predetermined area AR. By repeatedly performing position estimation by dead reckoning and position correction using the marker M, a highly accurate vehicle position can be continuously obtained. The highly accurate position estimation process described above is also called "Localization processing".

[0019] FIG. 2 is a conceptual diagram for explaining an example of the vehicle control system 10. In the example shown in FIG. 2, the vehicle control system 10 includes an in-vehicle system 10V (mobile body side system) mounted on the vehicle 1 and a management system 10M outside the vehicle 1. The in-vehicle system 10V is configured to control at least the running of the vehicle 1. On the other hand, the management system 10M manages a predetermined area AR in which the vehicle 1 runs. The in-vehicle system 10V and the management system 10M communicate with each other and exchange necessary information. The functions of the vehicle control system 10 are realized by the cooperation of these in-vehicle system 10V and management system 10M.

[0020] For example, a management system 10M that manages a predetermined area AR determines a target route TP of the vehicle 1 in the predetermined area AR. Then, the management system 10M notifies the in-vehicle system 10V of the determined target route TP. The in-vehicle system 10V performs a travel control process so that the vehicle 1 follows the target route TP determined by the management system 10M.

[0021] The position estimation process is performed, for example, by the in-vehicle system 10V. As another example, the in-vehicle system 10V may send information (steering angle, speed, recognition result of the marker M) necessary for the position estimation process to the management system 10M, and the management system 10M may execute the position estimation process and notify the in-vehicle system 10V of the estimated position.

[0022] As yet another example, the management system 10M may execute the travel control process remotely.

[0023] Note that the configuration of the vehicle control system 10 is not limited to that shown in FIG. 2. The entire vehicle control system 10 may be included in the vehicle 1.

[0024] 2. Travel control process considering road surface conditions FIG. 3 shows a situation where the vehicle 1 is traveling on a road surface where it is easy to slip (low μ road). On a road surface where it is easy to slip, the probability that the vehicle 1 slips or the tires of the vehicle 1 spin increases. When slip or tire spin occurs, the amount of movement of the vehicle 1 calculated from the steering angle and vehicle speed (wheel speed) deviates from the actual amount of movement. Therefore, the position estimation accuracy decreases. When the position estimation accuracy decreases, the accuracy of the travel control process for causing the vehicle 1 to follow the target route TP also decreases, and there is a risk that the vehicle 1 may deviate from the target route TP. For example, even when it is determined that the estimated position of the vehicle 1 coincides with the target route TP, the actual position of the vehicle 1 may deviate from the target route TP. In other words, there is a possibility that it may be erroneously determined that the vehicle 1 is following the target route TP even though the actual position of the vehicle 1 has deviated from the target route TP.

[0025] Therefore, this embodiment proposes a technology capable of ensuring the accuracy of driving control processing even on a slippery road surface.

[0026] 2-1. Road Surface Condition Acquisition Processing The road surface on the target route TP within the predetermined area AR is hereinafter referred to as the "target road surface". The vehicle control system 10 acquires road surface condition information 260 indicating the "slipperiness S" of the target road surface. The slipperiness S is inversely proportional to the road surface friction coefficient (μ). The road surface condition information 260 indicates at least the slipperiness S of the target road surface around the vehicle 1. The road surface condition information 260 may indicate the slipperiness S of the target road surface over the entire target route TP. The process of acquiring the road surface condition information 260 is hereinafter referred to as the "road surface condition acquisition process".

[0027] FIG. 4 is a conceptual diagram for explaining various examples of the road surface condition acquisition process.

[0028] 2-1-1. First Example The vehicle 1 is equipped with an in-vehicle camera 21. The in-vehicle camera 21 images the situation around the vehicle 1. The vehicle control system 10 acquires the image captured by the in-vehicle camera 21. Then, the vehicle control system 10 recognizes the road surface condition of the target road surface around the vehicle 1 (particularly in front of the vehicle 1) by analyzing the image. For example, the vehicle control system 10 analyzes the image using an image recognition AI (Artificial Intelligence) obtained by machine learning to recognize the road surface condition of the target road surface.

[0029] The road surface condition is at least classified into a "dry state" and a "wet state". In the dry state, the vehicle 1 is relatively non-slippery, and the slipperiness S is set to a relatively low value. On the other hand, in the wet state, the vehicle 1 is relatively slippery, and the slipperiness S is set to a relatively high value. The dry state may be further divided into multiple levels. Similarly, the wet state may be further divided into multiple levels.

[0030] In this way, the vehicle control system 10 determines whether the target road surface is in a dry state or a wet state based on the image of the target road surface captured by the in-vehicle camera 21. Then, the vehicle control system 10 sets the slipperiness S of the target road surface based on whether the target road surface is in a dry state or a wet state, and acquires the road surface state information 260.

[0031] Note that the first example of the road surface state acquisition process described above may be executed by the in-vehicle system 10V or may be executed by the management system 10M. In the latter case, the management system 10M communicates with the in-vehicle system 10V and acquires the image captured by the in-vehicle camera 21 from the in-vehicle system 10V.

[0032] 2-1-2. Second Example An infrastructure camera 31 is installed in the predetermined area AR. The infrastructure camera 31 captures the situation within the predetermined area AR. The vehicle control system 10 acquires the image captured by the infrastructure camera 31. Then, the vehicle control system 10 recognizes at least the road surface state of the target road surface around the vehicle 1 by analyzing the image. The vehicle control system 10 may recognize the road surface state of the target road surface over the entire target route TP. Otherwise, it is the same as the first example above.

[0033] Note that the second example of the road surface state acquisition process described above is typically executed by the management system 10M.

[0034] 2-1-3. Third Example A weather sensor 32 is installed in the predetermined area AR. Examples of the weather sensor 32 include a rain sensor that detects rainfall and a humidity sensor that detects humidity. The vehicle control system 10 determines whether it is raining in the predetermined area AR based on the detection result of the weather sensor 32. Thereby, the vehicle control system 10 can determine whether the target road surface in the predetermined area AR is in a dry state or a wet state. Then, the vehicle control system 10 sets the slipperiness S of the target road surface based on whether the target road surface is in a dry state or a wet state, and acquires the road surface state information 260.

[0035] Still, the third example of the road surface state acquisition process described above is typically executed by the management system 10M.

[0036] 2-1-4. Fourth Example The vehicle control system 10 acquires weather information distributed from an information service center. The weather information includes information on rainfall conditions and rainfall amount. The vehicle control system 10 determines whether the target road surface within a predetermined area AR is in a dry state or a wet state based on the weather information. Then, the vehicle control system 10 sets the slipperiness S of the target road surface based on whether the target road surface is in a dry state or a wet state, and acquires road surface state information 260.

[0037] Still, the fourth example of the road surface state acquisition process described above may be executed by the in-vehicle system 10V or may be executed by the management system 10M.

[0038] 2-1-5. Fifth Example In the fifth example, in addition to whether the target road surface is in a dry state or a wet state, the vehicle control system 10 also considers the material of the target road surface. For this purpose, the vehicle control system 10 holds road surface material information 270 indicating the material of the road surface within the predetermined area AR for each position.

[0039] FIG. 5 is a diagram showing an example of the relationship among road surface material, road surface state, and road surface friction coefficient. The relationship shown in FIG. 5 is described, for example, at http: / / weekend.nikkouken.com / week47 / 409 / . Examples of road surface materials include asphalt, concrete, and gravel.

[0040] The vehicle control system 10 determines whether the target road surface is in a dry state or a wet state by any one of the methods of the first to fourth examples described above. Further, the vehicle control system 10 obtains the friction coefficient of the target road surface based on whether the target road surface is in a dry state or a wet state, the road surface material information 270, and the relationship shown in FIG. 5. Then, the vehicle control system 10 sets the slipperiness S of the target road surface based on the friction coefficient of the target road surface and obtains the road surface state information 260. The slipperiness S is inversely proportional to the friction coefficient.

[0041] 2-2. Deviation suppression processing The vehicle control system 10 performs running control processing so as to suppress the deviation of the vehicle 1 from the target route TP in consideration of the slipperiness S of the target road surface indicated by the road surface state information 260. More specifically, the "control parameter CP" used in the running control processing is dynamically changed according to the slipperiness S of the target road surface. Examples of the control parameter CP include speed, speed upper limit value, steering speed, steering speed upper limit value, and the like. It is also possible to indirectly change the control parameter CP by changing the target route TP used in the running control processing.

[0042] The vehicle control system 10 dynamically changes the control parameter CP according to the slipperiness S of the target road surface so as to suppress the deviation of the vehicle 1 from the target route TP. In other words, the vehicle control system 10 sets the control parameter CP according to the slipperiness S of the target road surface so as to suppress the deviation of the vehicle 1 from the target route TP. Such processing is hereinafter referred to as "deviation suppression processing".

[0043] The deviation suppression processing may be executed by the in-vehicle system 10V or may be executed by the management system 10M. In the latter case, the management system 10M sets the control parameter CP according to the slipperiness S of the target route TP and notifies the in-vehicle system 10V of the set control parameter CP. The in-vehicle system 10V executes the running control processing according to the control parameter CP notified from the management system 10M.

[0044] Examples of deviation suppression processing will be described below.

[0045] 2-2-1. First Example FIG. 6 is a conceptual diagram for explaining a first example of deviation suppression processing. In the first example, as a control parameter CP used in the travel control processing, a speed parameter that is the speed of the vehicle 1 or the speed limit value is considered. The vehicle control system 10 sets the speed parameter at a position where the slipperiness S is high to be lower than the speed parameter at a position where the slipperiness S is low. Thereby, at a position where the slipperiness S is high, slipping and tire spin are suppressed. Therefore, a decrease in position estimation accuracy is suppressed, and the accuracy of the travel control processing is ensured. As a result, deviation from the target path TP of the vehicle 1 is suppressed.

[0046] For example, it is assumed that a default value of the traveling speed in a predetermined area AR is determined in advance. For example, it is assumed that the default value of the traveling speed is set to 7 km / h on a straight road and 5 km / h on a curve. At a position where the slipperiness S is low, the traveling speed is set to the default value. On the other hand, at a position where the slipperiness S is high, the traveling speed is set to a value lower than the default value.

[0047] 2-2-2. Second Example In the example shown in FIG. 6, there is a boundary BD between a high-μ road where the slipperiness S is low and a low-μ road where the slipperiness S is high. The vehicle 1 passes through the boundary BD and enters from the high-μ road to the low-μ road. When the vehicle control system 10 determines the road surface state in front of the vehicle 1 using the in-vehicle camera 21 (see Section 2-1-1), there is a possibility that the presence of the low-μ road is recognized after the vehicle 1 reaches the vicinity of the boundary BD. In that case, the vehicle control system 10 needs to quickly lower the speed parameter.

[0048] FIG. 7 is a conceptual diagram for explaining a second example of the deviation suppression process. In the second example, the management system 10M executes a road surface state acquisition process and acquires road surface state information 260. The management system 10M that manages the predetermined area AR can grasp the road surface state of the entire predetermined area AR. Therefore, the management system 10M can acquire the slipperiness S of the target road surface over the entire target route TP. That is, road surface state information 260 indicating the slipperiness S of the target road surface is obtained over the entire target route TP.

[0049] The management system 10M notifies such road surface state information 260 to the in-vehicle system 10V. Based on the road surface state information 260 received from the management system 10M, the in-vehicle system 10V can recognize the presence of a low-μ road ahead at an early stage. Therefore, the in-vehicle system 10V can execute the deviation suppression process with a margin from before the boundary BD and reduce the speed parameter (prediction control). This is preferable from the viewpoint of vehicle stability.

[0050] Alternatively, the management system 10M may also execute the deviation suppression process based on the road surface state information 260 and set a speed parameter with a margin that does not require sudden deceleration. The management system 10M notifies the set speed parameter to the in-vehicle system 10V. The in-vehicle system 10V executes the travel control process according to the speed parameter notified from the management system 10M. The same effect can be obtained in this case.

[0051] As described above, according to the second example, the management system 10M that manages the predetermined area AR executes the road surface state acquisition process and acquires the road surface state information 260. As a result, road surface state information 260 indicating the slipperiness S of the target road surface is obtained over the entire target route TP. By using such road surface state information 260, it becomes possible to execute the deviation suppression process with a margin. This is preferable from the viewpoint of vehicle stability.

[0052] Further, according to the second example, since the management system 10M executes the road surface condition acquisition process, an effect that the processing load on the in-vehicle system 10V is reduced can also be obtained.

[0053] 2-2-3. Third Example FIG. 8 is a conceptual diagram for explaining a third example of the deviation suppression process. The vehicle control system 10 recognizes a turning position where the vehicle 1 turns. For example, the vehicle control system 10 recognizes, based on the steering angle of the vehicle 1, a position where the steering angle is equal to or greater than a threshold value as the turning position. As another example, the vehicle control system 10 recognizes, based on the target route TP, a position where the curvature of the target route TP is equal to or greater than a threshold value as the turning position. Then, the vehicle control system 10 sets the speed parameter at the turning position to be lower than the speed parameter at positions other than the turning position. Thereby, it becomes possible to more effectively suppress the slip when the vehicle 1 turns.

[0054] In the example shown in FIG. 8, the vehicle 1 enters from a high-μ road to a low-μ road, and the speed parameter decreases. Thereafter, on the low-μ road, the vehicle 1 enters from a straight road to a curved road. As a result, the speed parameter further decreases. By setting the speed parameter at the turning position on the low-μ road to be low, it becomes possible to particularly effectively suppress the slip of the vehicle 1.

[0055] 2-2-4. Fourth Example FIG. 9 is a conceptual diagram for explaining a fourth example of the deviation suppression process. In the fourth example, consider a steering speed parameter that is the steering speed or the upper limit value of the steering speed of the vehicle 1 as the control parameter CP used in the travel control process. The vehicle control system 10 sets the steering speed parameter at a position where the slipperiness S is high to be lower than the steering speed parameter at a position where the slipperiness S is low. Thereby, at a position where the slipperiness S is high, the slip of the vehicle 1 is suppressed. Therefore, a decrease in the position estimation accuracy is suppressed, and the accuracy of the travel control process is ensured. As a result, the deviation of the vehicle 1 from the target route TP is suppressed.

[0056] 2-2-5. Fifth Example FIG. 10 is a conceptual diagram for explaining a fifth example of the deviation suppression process. In the fifth example, assuming the occurrence of slip on a slippery target road surface, the target path TP is corrected inward of the turn in advance.

[0057] More specifically, similar to the case of the third example described above, the vehicle control system 10 recognizes the turning position where the vehicle 1 turns. Further, the vehicle control system 10 corrects the target path TP at the turning position to a corrected target path CTP. The corrected target path CTP is set to be more inward of the turn as the slipperiness S at the turning position increases. Then, the vehicle control system 10 performs a travel control process so that the vehicle 1 follows the corrected target path CTP. By correcting the target path TP to the more inward corrected target path CTP, the control parameter CP used in the travel control process is also indirectly changed.

[0058] Thus, in the fifth example, on a curved road with high slipperiness S, the target path TP is corrected more inward of the turn. Therefore, when slip occurs and the travel trajectory of the vehicle 1 bulges outward of the turn, the travel trajectory of the vehicle 1 approaches the original target path TP. That is, the deviation of the vehicle 1 from the target path TP is suppressed.

[0059] 2-2-6. Sixth Example As long as there is no contradiction, it is also possible to combine two or more of the first to fifth examples of the above-described deviation suppression process.

[0060] 2-3. Effects As described above, according to the present embodiment, the position of the vehicle 1 is estimated based on the steering angle and vehicle speed of the vehicle 1, and a travel control process is performed so that the vehicle 1 follows the target path TP based on the estimated position. In the travel control process, the slipperiness S of the target road surface on the target path TP is considered. More specifically, the control parameter CP used in the travel control process is dynamically set according to the slipperiness S of the target road surface so that the deviation of the vehicle 1 from the target path TP is suppressed. Thereby, the deviation of the vehicle 1 from the target path TP is suppressed. That is, the accuracy of the travel control process is ensured.

[0061] The vehicle control system 10 may be distributed between the in-vehicle system 10V and the management system 10M. At this time, the road surface condition information 260 indicating the slipperiness S of the target road surface on the target route TP may be acquired by the management system 10M. Thereby, the processing load on the in-vehicle system 10V is reduced.

[0062] Also, the management system 10M that manages the predetermined area AR can also acquire road surface condition information 260 indicating the slipperiness S of the target road surface over the entire target route TP. By using such road surface condition information 260, the in-vehicle system 10V can recognize the presence of a target road surface with high slipperiness S at an early stage. As a result, the in-vehicle system 10V can execute deviation suppression processing with a margin (pre-reading control). This is preferable from the viewpoint of vehicle stability.

[0063] 3. Example of Vehicle Control System 3-1. Configuration Example FIG. 11 is a block diagram showing a configuration example of the vehicle control system 10 according to the present embodiment. The vehicle control system 10 includes an in-vehicle sensor 20, an infrastructure sensor 30, a communication device 40, a traveling device 50, and a control device 100.

[0064] The in-vehicle sensor 20 is mounted on the vehicle 1. The in-vehicle sensor 20 includes a recognition sensor 22 and a vehicle state sensor 23.

[0065] The recognition sensor 22 recognizes (detects) the situation around the vehicle 1. The recognition sensor 22 includes an in-vehicle camera 21 that images the situation around the vehicle 1. The recognition sensor 22 may further include a lidar (Laser Imaging Detection and Ranging), a radar, a sonar, etc.

[0066] The vehicle state sensor 23 detects the state of the vehicle 1. Examples of the vehicle state sensor 23 include a vehicle speed sensor (wheel speed sensor), a steering angle sensor, a yaw rate sensor, a lateral acceleration sensor, etc.

[0067] The infrastructure sensor 30 is installed in a predetermined area AR. For example, the infrastructure sensor 30 includes an infra camera 31 that images the situation within the predetermined area AR. The infrastructure sensor 30 may include a weather sensor 32. Examples of the weather sensor 32 include a rain sensor that detects rainfall, a humidity sensor that detects humidity, etc.

[0068] The communication device 40 communicates with the outside of the vehicle control system 10. For example, the communication device 40 communicates with an information service center (see FIG. 4) that distributes weather information.

[0069] The traveling device 50 is mounted on the vehicle 1. The traveling device 50 includes a steering device, a driving device, and a braking device. The steering device steers the wheels of the vehicle 1. For example, the steering device includes an electric power steering (EPS) device. The driving device is a power source that generates a driving force. Examples of the driving device include an engine, an electric motor, an in-wheel motor, etc. The braking device generates a braking force.

[0070] The control device 100 controls the vehicle 1. The control device 100 includes one or more processors 110 (hereinafter simply referred to as the processor 110) and one or more storage devices 120 (hereinafter simply referred to as the storage device 120). The processor 110 executes various processes. For example, the processor 110 includes a CPU (Central Processing Unit). The storage device 120 stores various information 200. Examples of the storage device 120 include a volatile memory, a non-volatile memory, an HDD (Hard Disk Drive), an SSD (Solid State Drive), etc. The control device 100 may be distributed between the in-vehicle system 10V and the management system 10M.

[0071] The vehicle control program PROG is a computer program for controlling the vehicle 1. By the processor 110 executing the vehicle control program PROG, various processes by the control device 100 are realized. The vehicle control program PROG is stored in the storage device 120. Alternatively, the vehicle control program PROG may be recorded on a computer-readable recording medium.

[0072] 3-2. Various Information FIG. 12 is a block diagram showing an example of various information 200 stored in the storage device 120. The various information 200 includes map information 210, surrounding situation information 220, vehicle state information 230, localization information 240, target route information 250, road surface state information 260, road surface material information 270, and the like.

[0073] The map information 210 is map information of a predetermined area AR. The map information 210 indicates the positions of roads and structures within the predetermined area AR. Also, the map information 210 indicates the positions of each marker M installed in the predetermined area AR.

[0074] The surrounding situation information 220 is information indicating the situation around the vehicle 1 and the situation of the predetermined area AR. The surrounding situation information 220 includes the recognition result by the recognition sensor 22 and the detection result by the infrastructure sensor 30. For example, the surrounding situation information 220 includes images captured by the in-vehicle camera 21 and the infrastructure camera 31. As another example, the surrounding situation information 220 may include the detection result by the weather sensor 32.

[0075] In addition, the surrounding situation information 220 includes object information regarding objects around the vehicle 1. Examples of the objects include pedestrians, other vehicles, white lines, marker M, structures, etc. The object information indicates the relative position and relative speed of the object with respect to the vehicle 1. For example, by analyzing the image obtained by the in-vehicle camera 21, the object can be identified and the relative position of the object can be calculated. For example, the control device 100 uses the image recognition AI obtained by machine learning to identify the objects in the image. Also, based on the point cloud information obtained by the lidar mounted on the vehicle 1, the objects can be identified and the relative position and relative speed of the objects can be obtained.

[0076] The vehicle state information 230 is information indicating the state of the vehicle 1 and shows the detection result by the vehicle state sensor 23. Examples of the state of the vehicle 1 include vehicle speed (wheel speed), steering angle, yaw rate, lateral acceleration, etc.

[0077] The localization information 240 indicates the position of the vehicle 1 obtained by the localization process. More specifically, the control device 100 calculates the movement amount (displacement amount) of the vehicle 1 based on the vehicle state information 230 (vehicle speed, steering angle), and estimates the position of the vehicle 1 based on the movement amount. Also, the control device 100 acquires the positions of the markers M in the predetermined area AR from the map information 210, and acquires the relative position of the marker M with respect to the vehicle 1 from the surrounding situation information 220. Then, the control device 100 corrects the estimated position of the vehicle 1 based on the estimated position of the vehicle 1, the relative position relationship between the vehicle 1 and the marker M, and the installation position of the marker M in the predetermined area AR. By repeatedly performing position estimation and position correction, a highly accurate vehicle position can be continuously obtained.

[0078] The target route information 250 indicates the target route TP of the vehicle 1 in the predetermined area AR.

[0079] The road surface condition information 260 indicates the slipperiness S of the target road surface on the target route TP. Various examples of the method for acquiring the road surface condition information 260 are as described in the above Section 2-1. The road surface condition information 260 indicates at least the slipperiness S of the target road surface around the vehicle 1. The road surface condition information 260 may indicate the slipperiness S of the target road surface over the entire target route TP.

[0080] The road surface material information 270 indicates the material of the road surface in the predetermined area AR for each position. The road surface material information 270 is generated in advance.

[0081] 3-3. Driving control process The control device 100 executes a driving control process for controlling the driving of the vehicle 1 regardless of the driver's driving operation. The control device 100 executes the driving control process by controlling the driving device 50 (steering device, driving device, braking device).

[0082] In particular, the control device 100 executes a driving control process so that the vehicle 1 follows the target route TP. For this purpose, the control device 100 calculates the deviation (e.g., lateral deviation, yaw angle deviation) between the vehicle 1 and the target route TP. The position of the vehicle 1 is obtained from the localization information 240. The target route TP is obtained from the target route information 250. Then, the control device 100 controls the driving of the vehicle 1 so that the deviation between the vehicle 1 and the target route TP decreases.

[0083] 3-4. Deviation suppression process FIG. 13 is a flowchart showing the processes related to the deviation suppression process.

[0084] In step S110, the control device 100 acquires the road surface condition information 260 indicating the slipperiness S of the target road surface on the target route TP (see Section 2-1).

[0085] In step S120, the control device 100 performs deviation suppression processing in consideration of the slipperiness S of the target road surface indicated by the road surface state information 260 (see Section 2-2). More specifically, the control device 100 dynamically changes the control parameter CP used in the driving control processing according to the slipperiness S of the target road surface so that the deviation of the vehicle 1 from the target route TP is suppressed. In other words, the control device 100 sets the control parameter CP according to the slipperiness S of the target road surface so that the deviation of the vehicle 1 from the target route TP is suppressed.

[0086] In step S130, the control device 100 performs driving control processing so that the vehicle 1 follows the target route TP based on the control parameter CP.

[0087] 4. Automatic valet parking FIG. 14 is a conceptual diagram for explaining the outline of automated valet parking (AVP). In the example shown in FIG. 14, the predetermined area AR is a parking lot PL. A plurality of markers M are arranged in the parking lot PL. The vehicle 1 is an AVP vehicle corresponding to automated valet parking in the parking lot PL and can automatically drive at least within the parking lot PL.

[0088] The vehicle control system 10 controls the automatic driving of the vehicle 1 in the parking lot PL. More specifically, the vehicle control system 10 includes an in-vehicle system 10V mounted on the vehicle 1 and a management system 10M outside the vehicle 1.

[0089] The management system 10M manages the automatic valet parking in the parking lot PL. The management system 10M can communicate with each vehicle (vehicle 1, parked vehicle 3) in the parking lot PL. For example, the management system 10M may issue an entry instruction or an exit instruction to the in-vehicle system 10V. The management system 10M may provide the map information 210 of the parking lot PL to the in-vehicle system 10V. The management system 10M may assign a parking space to vehicle 1. The management system 10M may generate a target route TP from the entry area to the assigned parking space and provide the information of the target route TP to the in-vehicle system 10V. The management system 10M may grasp the positions of each vehicle (vehicle 1, parked vehicle 3) in the parking lot PL. The management system 10M may remotely operate each vehicle (vehicle 1, parked vehicle 3) in the parking lot PL.

[0090] The in-vehicle system 10V controls the automatic driving of vehicle 1 in the parking lot PL. For example, the in-vehicle system 10V uses the in-vehicle camera 21 to recognize the marker M around vehicle 1. Then, the in-vehicle system 10V performs a localization process based on the recognition result of the marker M and accurately estimates the position of vehicle 1 in the parking lot PL. Also, the in-vehicle system 10V receives the information of the target route TP from the management system 10M. Then, the in-vehicle system 10V controls the driving of vehicle 1 to follow the target route TP based on the position of vehicle 1 and the target route TP. Thereby, vehicle 1 can automatically move from the entry area to the target parking space.

[0091] FIG. 15 is a conceptual diagram for explaining an example of deviation suppression processing in automatic valet parking. The parking lot PL includes a parking area PL-A, a parking area PL-B, and a connecting passage connecting between the parking areas PL-A and PL-B. The road surface material of the parking area PL-A is gravel (simple paving). The road surface material of the parking area PL-B is asphalt (new paving). The road surface material of the connecting passage is concrete (ordinary paving). The friction coefficients of each road surface material are as shown in FIG. 5.

[0092] As an example, consider a case where the vehicle 1 automatically travels from the storage area to the target parking space in the parking area PL-B via the parking area PL-A and the connecting passage. The vehicle control system 10 appropriately performs deviation suppression processing in consideration of the slipperiness S of the target road surface on the target route TP.

[0093] In particular, the management system 10M that manages the parking lot PL grasps the road surface material of the entire parking lot PL and can acquire road surface state information 260 indicating the slipperiness S of the target road surface over the entire target route TP. By using such road surface state information 260, the in-vehicle system 10V can recognize the presence of a target road surface with high slipperiness S at an early stage. As a result, the in-vehicle system 10V can perform deviation suppression processing with a margin (prediction control).

[0094] When roofs are installed in the parking areas PL-A and PL-B and no roof is installed in the connecting passage, the following applies. During rainfall, the slipperiness S of the connecting passage without a roof increases. Therefore, the vehicle control system 10 particularly performs deviation suppression processing in the connecting passage. When the management system 10M that manages the parking lot PL acquires the road surface state information 260, it becomes possible to perform deviation suppression processing with a margin before the vehicle 1 enters the connecting passage.

Explanation of Reference Numerals

[0095] 1 Vehicle 10 Vehicle control system 10M Management system 10V In-vehicle system 20 In-vehicle sensor 21 In-vehicle camera 22 Recognition sensor 23 Vehicle state sensor 30 Infrastructure sensor 31 Infrastructure camera 32 Weather sensor 40 Communication device 50 Travel device 100 Control device 110 Processor 120 Memory device 200 Various information 210 Map information 220 Surrounding situation information 230 Vehicle state information 240 Localization information 250 Target route information 260 Road surface condition information AR Predetermined area TP Target route CTP Corrected target route

Claims

1. A mobile control system for controlling the travel of a mobile body in a predetermined area, comprising one or more processors, wherein the one or more processors perform a position estimation process for estimating the position of the mobile body based on the steering angle and speed of the mobile body, a travel control process for controlling the travel of the mobile body to follow a target route based on the estimated position of the mobile body, a road surface state acquisition process for acquiring road surface state information indicating the slipperiness of a target road surface on the target route at least around the mobile body, and a deviation suppression process for dynamically changing control parameters used in the travel control process according to the slipperiness of the target road surface so as to suppress deviation of the mobile body from the target route and is configured to execute, wherein the one or more processors recognize a turning position where the mobile body turns based on the steering angle of the mobile body or the target route, the deviation suppression process includes changing the control parameters by correcting the target route at the turning position to a corrected target route, and the corrected target route is set more inward of the turn as the slipperiness at the turning position increases mobile control system.

2. The mobile control system according to claim 1, including a mobile body side system mounted on the mobile body and a management system for managing the predetermined area and, wherein the plurality of processors are distributed between the mobile body side system and the management system, and the management system executes at least the road surface state acquisition process mobile control system.

3. The mobile control system according to claim 2, wherein the road surface state information indicates the slipperiness of the target road surface over the entire target route mobile control system.

4. The mobile control system according to claim 2, wherein the mobile body side system executes the position estimation process and the travel control process, and further acquires the road surface state information from the management system and executes the deviation suppression process mobile control system.

5. The mobile control system according to claim 2, wherein in the road surface state acquisition process, the management system Based on at least one of the image of the target road surface captured by the camera, the detection result by the weather sensor installed in the predetermined area, and the weather information distributed from the information service center, determine whether the target road surface is in a dry state or a wet state. Obtain the road surface condition information based on whether the target road surface is in the dry state or the wet state. A movement control system.

6. The movement control system according to claim 5, wherein The management system Holds road surface material information indicating the material of the road surface within the predetermined area. Obtain the road surface condition information based on whether the target road surface is in the dry state or the wet state and the road surface material information. A movement control system.

7. The movement control system according to claim 2, wherein The predetermined area is a parking lot. The moving body corresponds to automatic valet parking in the parking lot. The management system manages the automatic valet parking in the parking lot. A movement control system.

8. The movement control system according to any one of claims 1 to 7, wherein The control parameter used in the travel control process includes a speed parameter that is the speed of the moving body or the upper limit value of the speed of the moving body. The deviation suppression process includes setting the speed parameter at a position where the slipperiness is high to be lower than the speed parameter at a position where the slipperiness is low. A movement control system.

9. The movement control system according to claim 8, wherein The one or more processors recognize a turning position where the moving body turns based on the steering angle of the moving body or the target route. The deviation suppression process includes setting the speed parameter at the turning position to be lower than the speed parameter at positions other than the turning position. A movement control system.

10. The movement control system according to any one of claims 1 to 7, wherein The control parameter used in the travel control process includes a steering speed parameter that is the steering speed of the moving body or the upper limit value of the steering speed of the moving body. The deviation suppression process includes setting the steering speed parameter at a position where the slipperiness is high to be lower than the steering speed parameter at a position where the slipperiness is low. A movement control system.

11. A moving body control method for controlling the travel of a moving body in a specified area, a position estimation process for estimating the position of the moving body based on the steering angle and speed of the moving body, a travel control process for controlling the travel of the moving body so as to follow a target route based on the estimated position of the moving body, a road surface state acquisition process for acquiring road surface state information indicating the slipperiness of a target road surface on the target route at least around the moving body, a deviation suppression process for dynamically changing control parameters used in the travel control process according to the slipperiness of the target road surface so that deviation of the moving body from the target route is suppressed, a process for recognizing a turning position at which the moving body turns based on the steering angle of the moving body or the target route is included, the deviation suppression process includes changing the control parameters by correcting the target route at the turning position to a corrected target route, the corrected target route is set more inside the turn as the slipperiness at the turning position increases Moving body control method.

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