Information processing method, information processing device, information processing program, and storage medium

Abstract

The information processing method includes receiving an input of a target path as a target between each node defining a passing position of the autonomous device, and a target speed as the target in autonomous travel of the target path. The information processing method includes causing a display device to display a target path. The display of the target path includes emphasizing a non-permissible section in the display of the target path in which an expected yaw velocity of the autonomous device that tracks the curved target path in association with the target path and the target velocity exceeds a permissible range in which the tracking is permitted to be established.

Description

[0001] Cross-reference of related applications

[0002] This application is based on Japanese Patent Application No. 2023-180473, filed in Japan on October 19, 2023, and incorporates the contents of the base application in its entirety hereby by reference. Technical Field

[0003] This disclosure relates to an information processing technique that performs path generation-related processing associated with the generation of path data, which defines the target path tracked by an autonomous device capable of operating autonomously. Background Technology

[0004] Patent Document 1 discloses a trajectory correction device for correcting the travel trajectory of a vehicle. When the deviation of the vehicle from its travel trajectory exceeds a threshold while the vehicle is traveling at a specified speed or above, the trajectory correction device generates a correction trajectory that smoothly connects the vehicle's current position to a target point, and replaces the portion of the travel trajectory leading to the target point with the correction trajectory to correct the travel trajectory.

[0005] Existing technical documents

[0006] Patent documents

[0007] Patent document 1: Japanese Patent Application Publication No. 2021-75256.

[0008] In the technology of Patent Document 1, the driving trajectory is corrected after the vehicle actually deviates from its driving trajectory. In this case, the tracking delay for the driving trajectory may increase due to the response delay from the detection of the deviation to the start of trajectory correction until the vehicle travels in accordance with the corrected driving trajectory. On the other hand, if path data for a predefined target path is generated in advance, the convenience may be reduced if the user cannot ascertain the actual tracking capability of the autonomous device for the designed target path. Summary of the Invention

[0009] The present disclosure addresses the following: providing an information processing method capable of assessing the actual tracking performance of an autonomous device relative to a designed target path. Another object of this disclosure is to provide an information processing apparatus capable of assessing the actual tracking performance of an autonomous device relative to a designed target path. A further object of this disclosure is to provide an information processing program capable of assessing the actual tracking performance of an autonomous device relative to a designed target path. Finally, a further object of this disclosure is to provide a storage medium capable of assessing the actual tracking performance of an autonomous device relative to a designed target path.

[0010] The following describes the technical means of this disclosure for solving the problem. Furthermore, the symbols in parentheses within the scope of protection of this invention indicate the correspondence between the symbols and the specific components described in the embodiments described in detail below, and do not limit the technical scope of this disclosure.

[0011] The first aspect of this disclosure is an information processing method, executed by a processor, for performing path generation-related processing associated with the generation of path data, which defines a target path tracked by an autonomous device capable of autonomous driving, including:

[0012] Receives inputs of a target path between each node representing the defined location of the autonomous device, and a target speed representing the target during autonomous driving along the target path; and

[0013] Make the display device show the target path.

[0014] The target path is displayed as follows:

[0015] The text emphasizes the unpermitted intervals in the target path, where the autonomous device tracking the curved target path, associated with the target path and target speed, exhibits a yaw rate exceeding the permissible range that allows the tracking to proceed.

[0016] The second aspect of this disclosure is an information processing device equipped with a processor that performs path generation associated processing related to the generation of path data, which defines the target path tracked by an autonomous device capable of autonomous driving.

[0017] The processor is configured to execute:

[0018] Receives inputs of the target path between each node defining the location of the autonomous device, and the target speed as the target during autonomous driving along the target path; and

[0019] Make the display device show the target path.

[0020] The target path is displayed as follows:

[0021] The text emphasizes the unpermitted sections within the target path, where the intended yaw rate of the autonomous device tracking the curved target path, in association with the target path and target speed, exceeds the permissible range that allows the tracking to proceed.

[0022] The third aspect of this disclosure is an information processing program, stored in a storage medium and containing commands executed by a processor, for performing path generation-related processing associated with the generation of path data, which defines the target path tracked by an autonomous device capable of autonomous driving, wherein...

[0023] Commands include:

[0024] Receives inputs of the target path between each node defining the location of the autonomous device, and the target speed as the target during autonomous driving along the target path; and

[0025] Make the display device show the target path.

[0026] The target path is displayed as follows:

[0027] The text emphasizes the unpermitted intervals in the target path, where the autonomous device tracking the curved target path, associated with the target path and target speed, exhibits a yaw rate exceeding the permissible range that allows the tracking to proceed.

[0028] The fourth aspect of this disclosure is a storage medium storing an information processing program containing commands executed by a processor for performing path generation-related processing associated with the generation of path data, which defines a target path tracked by an autonomous device capable of autonomous driving.

[0029] Commands include:

[0030] Receives inputs of the target path between each node defining the location of the autonomous device, and the target speed as the target during autonomous driving along the target path; and

[0031] Make the display device show the target path.

[0032] The target path is displayed as follows:

[0033] The text emphasizes the unpermitted intervals in the target path, where the autonomous device tracking the curved target path, associated with the target path and target speed, exhibits a yaw rate exceeding the permissible range that allows the tracking to proceed.

[0034] According to these first to fourth modes, non-allowed intervals in the target path where the autonomous device tracking the curved target path, associated with the target path and target speed, has a yaw rate exceeding the allowable range for tracking are highlighted. Therefore, by confirming the highlighted non-allowed intervals, the user can understand situations where the autonomous device cannot track the input target path. Thus, the user can assess the actual tracking capability. Attached Figure Description

[0035] Figure 1 This is a schematic diagram illustrating the autonomous device of the first embodiment.

[0036] Figure 2 This is a block diagram showing the structure of the overall system including the information processing apparatus of the first embodiment.

[0037] Figure 3 This is a block diagram illustrating the functional structure of the information processing apparatus according to the first embodiment.

[0038] Figure 4 This is a flowchart illustrating the information processing method of the first embodiment.

[0039] Figure 5 This is a flowchart illustrating the information processing method of the first embodiment.

[0040] Figure 6 This is a schematic diagram representing an example of the screen display in the design of the target path.

[0041] Figure 7 This is a schematic diagram representing an example of the screen display in the design of the target path.

[0042] Figure 8 This is a schematic diagram representing an example of emphasis.

[0043] Figure 9 This is a schematic diagram representing an example of the screen display in the design of the target path.

[0044] Figure 10 This is a graph representing an example of the change in yaw rate corresponding to the distance from the starting node.

[0045] Figure 11 This is a flowchart illustrating the information processing method of the second embodiment.

[0046] Figure 12 This is a flowchart illustrating the information processing method of the third embodiment.

[0047] Figure 13 This is a schematic diagram showing an example of a limit path.

[0048] Figure 14 This is a schematic diagram representing an example of the screen display in the design of the target path.

[0049] Figure 15 This is a schematic diagram showing an example of the next extreme path.

[0050] Figure 16 This is a flowchart illustrating the information processing method of the fourth embodiment.

[0051] Figure 17 This is a flowchart illustrating the information processing method of the fifth embodiment.

[0052] Figure 18 This is a schematic diagram illustrating an example of the sixth embodiment.

[0053] Figure 19This is a schematic diagram illustrating an example of the seventh embodiment. Detailed Implementation

[0054] Hereinafter, several embodiments of the present disclosure will be described with reference to the accompanying drawings. Furthermore, in each embodiment, the corresponding constituent elements are sometimes labeled with the same symbols, and repeated descriptions are sometimes omitted. Additionally, where only a part of the structure is described in each embodiment, the structures of other embodiments described above can be applied to the other parts of that structure. Moreover, not only combinations of structures explicitly shown in the descriptions of each embodiment are possible, but the structures of multiple embodiments can also be partially combined with each other even without explicit description, unless there is a particular obstacle to such combinations.

[0055] (First Implementation)

[0056] The information processing device 100 of the first embodiment controls and Figure 1 The target path P of the autonomous device 1 is shown in the diagram. The autonomous device 1 is an autonomous robot capable of autonomously moving in any direction (forward, backward, left, right). Furthermore, the autonomous device 1 in the first embodiment can also be called an autonomous vehicle. The autonomous device 1 is, for example, a transport vehicle that transports loads by autonomous driving. In addition, the autonomous device 1 can also be used for purposes other than transporting loads (e.g., information collection).

[0057] The autonomous device 1 has a drive source 11, a control unit 13, wheels 14, and axles 15 on its body 10. The drive source 11 is, for example, an electric motor. The communication system 12 acquires communication information available to the control unit 13 via wireless communication. The communication system 12 can also be a positioning type that receives positioning signals from GNSS (Global Navigation Satellite System) satellites existing outside the autonomous device 1. The positioning type communication system 12 is, for example, a GNSS receiver. The communication system 12 can also be a V2X type that transmits and receives communication signals with a V2X system existing outside the autonomous device 1. The V2X type communication system 12 is, for example, at least one of a DSRC (Dedicated Short Range Communications) communicator and a cellular V2X (C-V2X) communicator. The communication system 12 can also be a terminal communication type that transmits and receives communication signals with terminals existing inside or outside the autonomous device 1. The terminal communication type communication system 12 is, for example, at least one of a Bluetooth device, a Wi-Fi device, and an infrared communication device.

[0058] Control unit 13 is a control device that performs autonomous driving control of autonomous device 1, and is an ECU (Electronic Control Unit) including at least one dedicated computer. Control unit 13 enables autonomous device 1 to drive autonomously by autonomously executing acceleration / deceleration control and steering control of autonomous device 1. Control unit 13 controls autonomous driving by tracking target path P based on path data associated with target path P.

[0059] The wheels 14 include a pair of front wheels 14a located at the front of the vehicle body 10 and a pair of rear wheels 14b located at the rear. The axle 15 includes a front axle 15a and a rear axle 15b. The pair of front wheels 14a are fixed at both ends of the front axle 15a so that they can rotate, and the pair of rear wheels 14b are fixed at both ends of the rear axle 15b so that they can rotate. The vehicle body 10 is provided with a loading space 10a for loading cargo. The loading space 10a is formed, for example, as an upwardly opening space, by dividing the vehicle body 10 into front, rear, left, and right sections. The loading space 10a may be formed, for example, as a space with openings on the sides of the vehicle body 10, or it may simply be the space above the upper surface of the loading surface of the vehicle body 10.

[0060] Autonomous device 1 travels by tracking a pre-set target path P from the starting point to the destination, thereby achieving autonomous driving. In addition to autonomous driving, autonomous device 1 can also perform manual driving based on user operation. For example, autonomous device 1 can also have a driver's seat installed in the vehicle body 10, allowing manual driving through the operation of an operating system by a user seated in the driver's seat. The operating system could be, for example, a steering component, accelerator pedal, and brake pedal located in the vehicle body 10. Alternatively, autonomous device 1 can also be manually driven from outside or inside the vehicle body 10 via operation of a control pad that functions as an operating system.

[0061] Before the autonomous device 1 departs, the information processing device 100 displays a target path P to the user of the autonomous device 1 for prior determination. Specifically, the information processing device 100 displays to the user the extreme path PL that the autonomous device 1 is allowed to follow.

[0062] like Figure 2 As shown, the information processing device 100 is connected to the input system 4, the map database (DB) 5, the vehicle DB6, and the display system 7 via at least one of, for example, a LAN (Local Area Network) line, a wiring harness, an internal bus, and a wireless communication line.

[0063] Input system 4 receives user input. Input system 4 is, for example, at least one of a mouse, trackball, keyboard, and touch panel.

[0064] Map DB5 stores map information that can be used by information processing device 100. Map DB5 is configured to include at least one non-transitory tangible storage medium, such as semiconductor memory, magnetic media, or optical media. Map DB5 can also be a database of a locator that estimates its own state quantities, including the position of the main vehicle A. Map DB5 can also be a database of a navigation unit that navigates the driving path of the main vehicle A. Map DB5 can also be composed of a combination of various such databases.

[0065] The map information in map DB5 refers to the installations within the facility area, including at least two-dimensional horizontal position information related to surrounding objects O that could become obstacles when the autonomous device 1 is operating. For example, the map information could also be point group data including a set of reflective points of the surrounding objects O acquired by external sensors such as LiDAR (Light Detection and Ranging / Laser Imaging Detection and Ranging). In this case, each reflective point has position information. Alternatively, the map information could be image data of a set of reflective points projected onto a bird's-eye view plane. Furthermore, the map information could also include three-dimensional position information including height information to the surrounding objects O.

[0066] Vehicle DB6 stores information (vehicle information) related to autonomous device 1 that can be utilized by information processing device 100. Vehicle DB20 is configured as at least one non-transitory physical storage medium, including, for example, semiconductor memory, magnetic media, and optical media. The vehicle information in vehicle DB6 includes information about autonomous device 1 required to display the extreme path PL. For example, the vehicle information includes the size information of autonomous device 1. The size information includes at least the distance L from the vehicle's center of gravity CG to the rear axle 15b. r .

[0067] The vehicle DB6 stores dimensional information in association with the identification information of the autonomous device 1. Here, the identification information is information indicating the vehicle type of the autonomous device 1, such as product name, model number, or machine name. That is, the vehicle DB6 can store various information by referring to the dimensional information corresponding to the vehicle type for the autonomous device 1.

[0068] Display system 7 is a display device that displays information to a user. Specifically, display system 7 displays the target path P together with map information of the target area. Display system 7 is, for example, at least one of a liquid crystal panel and an organic EL panel.

[0069] The information processing device 100 is a computer having at least one memory 101 and one processor 102. The memory 101 is a non-transitory tangible storage medium, such as semiconductor memory, magnetic media, and optical media, that non-transitors programs and data readable by the computer. Here, storage can be the accumulation of data even when the computer is turned on and off, or the temporary storage of data that is eliminated when the computer is turned on and off. The processor 102 includes, for example, at least one of the following as its core: CPU (Central Processing Unit), GPU (Graphics Processing Unit), RISC (Reduced Instruction Set Computer)-CPU, DFP (Data Flow Processor), and GSP (Graphics Streaming Processor).

[0070] In the information processing device 100, the processor 102 executes multiple commands contained in the information processing program stored in the memory 101 to control the display of path data defining the target path P tracked by the autonomous device 1. Thus, the information processing device 100 constructs multiple functional modules for controlling the display of path data defining the target path P tracked by the autonomous device. For example... Figure 3 As shown, the multiple functional modules constructed in the information processing device 100 include an acquisition module 110 and an output module 120.

[0071] The following is based on Figure 4 , 5 This describes the flow of an information processing method in which the information processing device 100 controls the display of path data defining the target path P tracked by the autonomous device 1 through the coordination of these modules 110 and 120. Hereinafter, this processing flow will sometimes be referred to as the information processing flow. This processing flow is repeatedly executed during the startup of the computer of the information processing device 100. Furthermore, each "S" in this processing flow refers to a multiple step executed by multiple commands included in the information processing program.

[0072] First, in S10, the acquisition module 110 acquires map information about the facility area utilized by the autonomous device 1 from the map DB5. Then, in S20, the output module 120 visualizes the acquired map information and displays it as a map of the facility area on the display system 7. This facility map at least displays surrounding objects such as buildings and installations that may become obstacles to the autonomous device 1's movement. Road markings and the like may also be further displayed on the facility map.

[0073] Then, in S30, the acquisition module 110 acquires the vehicle information of the autonomous device 1. Specifically, the acquisition module 110 receives the user's identification information input via the input system 4 and reads the vehicle information of the autonomous device 1 corresponding to the identification information from the vehicle DB6.

[0074] In the following S40, the acquisition module 110 acquires the yaw rate limit value γ. max The limit value of yaw rate γ max The yaw rate γ is the allowable range within which the tracking described later is valid. i The magnitude of yaw rate. In other words, the limit value of yaw rate γ. max It specifies the permissible yaw rate γ of autonomous device 1. i The upper limit threshold of its size. That is, the yaw rate limit γ. max It is hypothetical that if the yaw rate γ is larger than this value... i Or a yaw rate γ greater than or equal to this value i The value at which the target path P is tracked becomes practically impossible. The acquisition module 110 receives, for example, the yaw rate limit γ from the user via the input system 4. max The input is used to obtain the yaw rate limit value γ. max Or, the yaw rate limit γ max It can also be a value that has been predefined and stored in memory 101, etc.

[0075] Then, in S50, such as Figure 6 As shown, the acquisition module 110 receives input from the user-defined starting point node Ns via the input system 4. The starting point node Ns is the starting point of the target path P and is a node that defines the location of the autonomous device 1 on the facility map. For example, the acquisition module 110 receives the input of the starting point node Ns by clicking on any location on the facility map with a mouse or by inputting coordinates from the keyboard.

[0076] Next, in S60, the acquisition module 110 receives, as shown below... Figure 7 The user input shown includes the endpoint node Ne and the path line L connecting the starting node Ns and the endpoint node Ne. The endpoint node Ne is the end point of the target path P and, like the starting node Ns, defines the location of autonomous device 1 on the facility map. The path line L is a linear object connecting the starting node Ns and the endpoint node Ne, defining the location of autonomous device 1 between nodes Ns and Ne.

[0077] By using the user's mouse clicks, coordinate input, etc., the starting node Ns and the ending node Ne are defined on the displayed facility map, thereby automatically inputting the path line L connecting the nodes Ns and Ne onto the facility map. For example, the target path P is displayed as a vector image object with at least the starting node Ns and the ending node Ne as vertices.

[0078] Therefore, by changing the positions of these vertices, the orientation of the vectors from these vertices, and their magnitudes, the shape of the target path P changes to the shape desired by the user. The orientation and magnitude of the vectors from the vertices can be changed, for example, by manipulating a line-like handle (not shown) extending from these vertices using a mouse or similar device. Furthermore, in addition to nodes Ns and Ne, the user can arbitrarily add vertices that define the shape of the target path P. In this embodiment, the target path P is designed through such user input. Through the processing in S40 and S50 above, the target path P is defined by the starting node Ns, the ending node Ne, and the path line L.

[0079] In the following S70, the acquisition module 110 acquires the target velocity V from the autonomous device 1. i Target velocity V i This refers to the speed at which the autonomous device 1 travels along a predetermined target path P. The acquisition module 110 receives the target speed V, for example, via the input system 4. i Input to obtain the target velocity V i Alternatively, the acquisition module 110 can also read a pre-defined target speed V from a storage medium such as memory 101. i To receive input. For example, the acquisition module 110 receives the target velocity V at each specified position on the target path P. i The input is used to obtain multiple target velocities V for a target path P. i .

[0080] Specifically, the acquisition module 110 receives the starting node Ns and the ending node Ne, and the target velocity V at multiple intermediate nodes Ni set on the path line between nodes Ns and Ne. i The input. Additionally, the target velocity V. i It can also be a separate input from the user for each of all nodes. Target speed V i It can also be input by the user for more than one representative node. In this case, the target velocity V of the nodes other than the representative node is... i Based on the target velocity V of the representative node i Interpolation can be performed. Alternatively, the target velocity V i Alternatively, the user can input constant values ​​for each set of multiple nodes. Additionally, the acquisition module 110 can also receive a target speed V for the entire target path P.i Input.

[0081] In the following S80, the acquisition module 110 acquires the target path P and the target speed V. i The autonomous device 1, which correlates with the target path P, tracks the intended yaw rate γ. i The acquisition module 110 acquires multiple yaw rates γ for each node of the target path P. i Specifically, the acquisition module 110 acquires the curvature ρ of the target path P at each node. i and target speed V i Associated yaw rate γ i .

[0082] Here, the curvature ρ of the target path P at each node i It is related to the coordinate position x of each node i y i and yaw angle φ i Related values. Additionally, the yaw angle φ. i It is the coordinate position (x) i y i The angle between the tangent to the target path P at point ) and the x-axis. At curvature ρ i With coordinate position x k y k and yaw angle φ k The following mathematical formula (1) holds true between them. Furthermore, at the yaw rate γ... i With curvature ρ i and target speed V i The following mathematical expression (2) holds true between them.

[0083] [Mathematical Expression 1]

[0084]

[0085] [Mathematical Expression 2]

[0086]

[0087] Therefore, in order to obtain the yaw rate γ i The acquisition module 110 calculates the curvature ρ for each node based on mathematical formula (1). i Based on the mathematical formula (2), the yaw rate γ is calculated. i .

[0088] In the following S90, the output module 120 determines whether a yaw rate γ exists. iThe non-permitted interval S in the target path P that exceeds the permitted range for tracking by the autonomous device 1. For example, the permitted range is the yaw rate γ whose magnitude, i.e., absolute value, converges to the upper limit. i The range. Furthermore, here, convergence to the upper limit means that the size becomes below or less than the threshold.

[0089] For example, for a certain target path P, the yaw rate γ at each node corresponding to the distance from the starting node Ns. i Set as Figure 10 The relationship is shown in the curve. In the presence of yaw rate γ... i Exceeding Figure 10 Given the distance interval within the allowed range shown, output module 120 determines this interval as the non-allowed interval S in the target path P. The yaw rate γ in the target path P... i An interval that is within the allowed range can also be marked as an allowed interval relative to the non-allowed interval S. In addition, the distance Di from the starting node Ns to each node is, for example, the sum of the distances between each node, and is expressed by the following mathematical formula (3).

[0090] [Mathematical Expression 3]

[0091]

[0092] If a non-allowed interval S is determined to exist, the process proceeds to S100. In S90, the output module 120 emphasizes the non-allowed interval S in the target path P displayed by the display system 7 more than other intervals. For example, emphasizing the display includes changing at least one of the following: display color, line type, and line thickness of other intervals.

[0093] As an example, output module 120 outputs the target velocity V. i Relative to yaw rate γ i The color corresponding to the difference in speed that converges to the upper limit of the allowable range is used to display the target path P. Thus, as... Figure 8 As shown, the target path P is displayed in a heatmap format on display system 7. Additionally, in... Figure 8 In this design, the varying shades of dotted shadows represent different display colors, with the darkest dotted shadow representing the target's speed, V. i The unallowed range S exceeding the speed limit. Thus, the output module 120 uses display colors to indicate the target speed V to the user. i The unallowed range S exceeding the speed limit. Output module 120 can also display a corresponding image representing the difference and display color. Through this, with the target speed V... i The associated emphasis is displayed, and the output module 120 presents the target velocity V. iThe speed decreases. Therefore, output module 120 urges the user to achieve the target speed V. i The reduction eliminates the non-allowed interval S.

[0094] In the following S110, the acquisition module 110 receives correction input related to the non-permitted interval S. For example, for each node in the non-permitted interval S, the acquisition module 110 receives, via the input system 4, correction inputs that adjust the target velocity V based on the user. i Reduced correction input. The acquisition module 110 can also receive the user-manually input target velocity V. i The changed input is used as a correction input. Alternatively, the acquisition module 110 can also receive the target velocity V. i The user's permission input is used as the correction input to automatically correct the target speed V. i Until the speed converges to the upper speed limit.

[0095] When receiving correction input and correcting the target speed V i At this point, the process returns to S90. That is, the processes S90, S100, and S110 are repeated until the target speed V is reached. i The correction continues until the non-allowed interval S is removed from the target path P. When it is determined in S90 that there is no non-allowed interval S in the target path P, this process proceeds to... Figure 5 S120 transfer.

[0096] In S120, the acquisition module 110 determines whether the generation of all target paths P up to the final destination is complete. For example, if the user confirms via the input system 4 that the generation of target paths P is complete, the acquisition module 110 determines that the target paths P have been determined. If it is determined that the generation of all target paths P is incomplete, the process proceeds to S130.

[0097] In S130, such as Figure 9 As shown, the acquisition module 110 defines the endpoint node Ne of the target path P input in the previous S60 as the starting node Ns of the next target path P to be input. Specifically, the acquisition module 110 reads the coordinates of the endpoint node Ne of the previous target path P as the coordinates of the next starting node Ns. After that, the process returns to S60.

[0098] On the other hand, when it is determined in S120 that the generation of all target paths P is complete, this process proceeds to S140. In S140, the output module 120 generates path data determined for the target path P. The path data can be data for individual target paths P. The data for individual target paths P may include, for example, at least the position coordinates of each node in the target path P. The path data may be data combining the target path P and the facility map. In S140, the path data related to the determined target path P is output. The path data is output, for example, by storing it in a storage medium such as memory 101 or external memory, or by sending the path data to the autonomous device 1. The information processing device 100 repeats the above process until the user sets the target path P to the final destination of the autonomous device 1.

[0099] According to the first embodiment described above, it is emphasized that the non-permitted interval S is displayed, and within the non-permitted interval S, the target path P and the target speed V are... i The autonomous device 1, which correlates with the target path P in a curved path, has a predetermined yaw rate γ. i The tracking exceeds the permitted range. Therefore, by confirming the highlighted non-permitted range S, the user can understand the situation where the autonomous device cannot track the input target path. Thus, the user can grasp the actual tracking capability.

[0100] Furthermore, according to the first embodiment, the system receives input of a target path P designed manually by the user through node input on the facility map displayed on the display system 7. Therefore, by checking whether there is an emphasis display of non-permitted sections S on the target path P designed by the user through manual node input, it is possible to determine whether the autonomous device 1 can track the target path P during autonomous driving.

[0101] Furthermore, according to the first embodiment, the emphasis display of the non-permitted interval S includes presenting the target velocity V in the non-permitted interval S. i Therefore, for users, without changing the shape of the target path P, it is possible to propose a simpler method for eliminating the non-allowed interval S.

[0102] Furthermore, according to the first embodiment, path data is generated that defines a target path P with the non-allowed intervals S eliminated. This enables the reliable generation of path data with high practical traceability.

[0103] Furthermore, according to the first embodiment, path data is output that defines the target path P by eliminating the non-permitted interval S. Thus, stable autonomous driving of the autonomous device 1 can be achieved through the output path data with high actual trackability.

[0104] (Second Implementation)

[0105] like Figure 11 As shown, the second embodiment is a variation of the first embodiment.

[0106] like Figure 11 As shown, the information processing method in the second embodiment transitions to S51 after processing in S40. In S51, the acquisition module 110 acquires manual driving path data. Manual driving path data is data related to the path actually traveled by the autonomous device 1 through manual driving. The manual driving path data includes at least the position coordinates of each location on the path. The acquisition module 110 receives the input of the manual driving path data through wireless or wired communication with the autonomous device 1, or by reading data from a storage medium such as a memory card. In this embodiment, the target path P is designed through this manual path data acquisition process. Alternatively, the acquisition module 110 may acquire the manual driving path data from the starting point to the destination in one go. Or, the acquisition module 110 may acquire the manual driving path data for each of multiple intervals from the starting point to the destination in multiple steps.

[0107] In the following S61, the output module 120 displays the manual driving path data on the display system 7. The output module 120 sets the coordinate position data in the manual driving path data to the coordinate position data on the facility map, thereby displaying the manually driven path as the target path P.

[0108] According to the second embodiment described above, the system receives an input of a target path P, which is manual driving path data related to the path actually traveled by the autonomous device 1 through manual driving. By checking for the presence or absence of an emphasis display of non-permitted intervals S, the user can determine whether the autonomous device 1 can track the manual driving path data during autonomous driving. This avoids situations where performance limitations related to autonomous driving in the autonomous device 1 prevent the tracking of paths that are essentially the same as those traveled manually.

[0109] (Third implementation method)

[0110] like Figures 12-15 As shown, the third embodiment is a variation of the first embodiment.

[0111] like Figure 12 As shown, the information processing method in the third embodiment transitions to S52 after processing in S50. In S52, the output module 120 defines the limit path PL extending from the starting point node Ns. The limit path PL is a curved path that limits the tracking of the target path P by the autonomous device 1. The limit path PL is defined by the yaw rate limit value and the set speed V, which are the upper limits of the allowable range for tracking. sThe associated path. In other words, the limiting path PL is based on the yaw rate limit and the set speed V. s The prescribed path. More specifically, the extreme path (PL) is a path also prescribed based on vehicle information. Set speed (V) s This refers to, for example, the upper limit speed of the autonomous device 1 when traveling on a predetermined target path P. The set speed V s The value can be input by the user or a predefined value. Set speed V s The speed can vary depending on the distance from the starting node Ns, or it can be a constant speed.

[0112] To define the limiting path PL, output module 120 simulates autonomous device 1 starting from the position of the initial node Ns at a set velocity V. s The coordinate position and yaw angle shift during cornering (spinning) while maintaining the yaw rate limit are calculated. The coordinate system here is an orthogonal coordinate system fixed relative to the road surface. Output module 120 uses the driving trajectory as its simulation result as the limit path PL. Output module 120 performs simulations for both right-hand and left-hand spins starting from the starting node Ns, defining the limit paths PL for both modes. Furthermore, "left" and "right" here refer to left and right when facing the direction of travel of autonomous device 1.

[0113] For example, output module 120 simulates the movement of autonomous device 1 by treating it as a two-wheeled model of a hypothetical two-wheeled vehicle with imaginary front and rear wheels. Output module 120 updates the coordinate position x of the moving autonomous device 1 every predetermined time step ds. k y k and yaw angle φ k Here, x k y k φ k The index k in the table is at the initial position, that is, at the starting node Ns, k=0, and is incremented by 1 natural number with each update.

[0114] Set speed V s Yaw angular velocity limit γ max The distance L from the center of gravity CG to the rear axle 15b is the gyratory distance. r The slip angle β in the autonomous device 1 corresponds to the following mathematical formula (4). In addition, the sign of the right side in mathematical formula (1) is selectively determined by the rotation direction.

[0115] [Mathematical Expression 4]

[0116]

[0117] Furthermore, from the position (x) k y k), yaw angle φ k Starting from the position after time step ds (x) k+1 y k+1 ), yaw angle φ k+1 It corresponds to the following mathematical expressions (5) to (7).

[0118] [Mathematical Expression 5]

[0119]

[0120] [Mathematical Expression 6]

[0121]

[0122] [Mathematical Expression 7]

[0123]

[0124] The output module 120 obtains the coordinate position (x, y) of the autonomous device 1 during rotation while maintaining the yaw rate limit by performing an arbitrary number of updates. k y k The set of data is used as the driving trajectory. Additionally, the time step ds and the number of updates can be set by the user or predefined.

[0125] In the following S53, such as Figure 13 As shown, output module 120 displays the extreme path PL on display system 7. Output module 120 is based on coordinate position (x... k y k The information of the set of coordinates (x, y) is displayed as a curved line object extending from the starting node Ns, showing the extreme path PL. That is, the output module 120 displays the coordinate position (x, y) k y k ) is converted into the position on the display screen in display system 7, by using a curve to adjust the coordinate position (x) k y k Interpolate between the points to display the extreme path PL.

[0126] Therefore, in display system 7, the input allowed area (allowing input to the target path P) and the input prohibited area (prohibiting input to the target path P) are displayed with the extreme path PL as the boundary line. The input allowed area can also be described as the driving allowed area (allowing the autonomous device 1 to drive). Similarly, the input prohibited area can also be described as the driving prohibited area (prohibiting the autonomous device 1 to drive). Furthermore, depending on the time step ds and the number of updates, the extreme path PL is sometimes displayed on the terminal within the display screen. In other words, the extreme path PL is sometimes displayed in an interrupted state within the display screen.

[0127] This process is transferred to S60 after processing in S53. That is, as follows: Figure 14 As shown, the user observes the facility map displaying the extreme path PL while inputting the destination node Ne. If the target path P is defined in the process of S50, the process then proceeds to S61.

[0128] In S61, the acquisition module 110 determines whether the target path P input by the user crosses the limit path PL. If it is determined that the target path P crosses the limit path PL, the process proceeds to S62. In S62, the output module 120 prevents the determination of the target path P.

[0129] For example, output module 120 prohibits input of the next target path P with the current target path P's endpoint node Ne as its starting node Ns, until a correction input for target path P is made. Output module 120 can notify the user via display system 7 that target path P crosses the limit path PL. After S62, the process returns to S60. Thus, the user corrects the target path P that crosses the limit path PL by inputting the endpoint node Ne again. On the other hand, if it is determined in S61 that target path P does not cross the limit path PL, the process proceeds to S70. In addition, in S70 of this embodiment, the set speed V that defines the limit path PL can also be obtained. s As the target velocity V i .

[0130] Furthermore, in this embodiment, after defining the endpoint node Ne of the previously input target path P as the next starting node Ns in S130, the process proceeds to S52. That is, whenever a target path P that does not cross the limit path PL and has no non-allowed interval S is input, the limit path PL extending from the endpoint node Ne of the previously input target path P is displayed as a guide when inputting a new target path P (see reference). Figure 15 ).

[0131] According to the third embodiment described above, the anticipated yaw rate limit γ of the autonomous device 1 is displayed within the upper limit of the allowable range for trajectory establishment. max and set speed V s The associated limit path PL. Therefore, by referring to this limit path PL, the user can confirm whether the target path P is being tracked while inputting the target path P. Thus, the actual tracking capability of the autonomous device 1 can be assessed not only after the user inputs the target path P, but also before the input is completed.

[0132] (Fourth Implementation)

[0133] like Figure 16 As shown, the fourth embodiment is a variation of the first embodiment.

[0134] like Figure 16As shown, the information processing device 100 of the fourth embodiment transfers to S41 after processing in S30. In S41, the acquisition module 110 acquires the lateral acceleration limit value a. lmax To replace the yaw rate limit γ max After S41, this process is transferred to S50.

[0135] In S90 of this embodiment, the output module 120 determines that the lateral acceleration limit value a is being met. lmax Within the associated permissible range, is there an unpermissible interval S? Output module 120 will output the lateral acceleration limit value a. lmax Convert to the yaw rate limit value γ max Here, at the lateral acceleration limit value a lmax With the target velocity V i and the limit value of yaw rate γ max The following mathematical expression (8) holds true between them.

[0136] [Mathematical Expression 8]

[0137]

[0138] Therefore, the output module 120 outputs the lateral acceleration limit value a based on the mathematical formula (8). lmax As for the target velocity V i The associated value is converted into the yaw rate limit γ. max The output module 120 will output based on the lateral acceleration limit value a. lmax The limit value of the yaw rate γ of the conversion max The magnitude is set as a threshold parameter within a specified allowable range. In S90 of this embodiment, the output module 120 determines the value based on the lateral acceleration limit a. lmax Within the specified permissible range, are there any non-permissible intervals S? That is, the yaw rate γ outside the permissible range in this embodiment. i It is the lateral acceleration and the curvature ρ of the target path P i and target speed V i Relatedly exceeding the lateral acceleration limit value a lmax yaw rate γ i The lateral acceleration limit a lmax This is an example of "acceleration limit".

[0139] In the fourth embodiment above, the yaw rate γ outside the permissible range is... i It is the lateral acceleration relative to the target path P and the target velocity V. i Relatedly exceeding the lateral acceleration limit value a lmax yaw rate γ i Therefore, when autonomous device 1 is at a yaw rate γi When driving outside the permitted range in the non-permitted section S, the lateral acceleration acting on autonomous device 1 exceeds the lateral acceleration limit value a. lmax By highlighting the non-permitted interval S to the user, the user can avoid creating a target path P with lateral acceleration that does not enable tracking of the autonomous device 1.

[0140] (Fifth Implementation)

[0141] like Figure 17 As shown, the fifth embodiment is a variation of the first embodiment.

[0142] like Figure 17 As shown, the information processing device 100 of the fifth embodiment transfers to S42 after processing in S30. In S42, the acquisition module 110 acquires the rudder angle limit value δ. max , replacing the yaw rate limit value γ max After S41, this process is transferred to S50.

[0143] In S80 of this embodiment, the output module 120 determines that the rudder angle limit value δ is... max Within the associated permissible range, are there any non-permissible intervals S? Output module 120 will output the rudder angle limit value δ. max Convert to the yaw rate limit value γ max Here, in the two-wheel model, at the rudder angle limit δ max With the target velocity V i and the limit value of yaw rate γ max The following mathematical expression (9) holds true between them. In addition, in mathematical expression (9), B is the wheelbase length of autonomous device 1.

[0144] [Mathematical Expression 9]

[0145]

[0146] Therefore, the output module 120, based on mathematical formula (9), outputs the rudder angle limit value δ. max As for the target velocity V i The associated value is converted into the yaw rate limit γ. max The output module 120 will output according to the rudder angle limit value δ. max The limit value of the yaw rate γ of the conversion max The size is set as a threshold parameter within a specified allowable range. In S90 of this embodiment, the output module 120 determines the value based on the rudder angle limit δ. max Within the specified permissible range, are there any non-permissible intervals S? That is, the yaw rate γ outside the permissible range in this embodiment. i It is the curvature ρ of the rudder angle relative to the target path P iand target speed V i Relatedly exceeding the rudder angle limit value δ max yaw rate γ i Rudder angle limit δ max This is an example of "rudder angle upper limit".

[0147] In the fifth embodiment above, the yaw rate γ outside the permissible range is... i It is the rudder angle and the target path P and target velocity V i Relatedly exceeding the rudder angle limit value δ max yaw rate γ i Therefore, when autonomous device 1 is at a yaw rate γ... i When driving outside the permitted range in the non-permitted section S, the rudder angle acting on autonomous device 1 exceeds the rudder angle limit value δ. max By highlighting the non-permitted zone S to the user, the user can avoid creating an autonomous device 1 to track a target path P that does not meet the required rudder angle.

[0148] (Sixth Implementation Method)

[0149] like Figure 18 As shown, the sixth embodiment is a variation of the first embodiment.

[0150] In the sixth embodiment, the output module 120, during the emphasis display of the non-allowed interval S, appends the display representing the non-allowed interval S to the target path P. For example, as... Figure 18 As shown, output module 120 displays a range indication image Is and a reduction notification image In. The range indication image Is is a display that distinguishes the non-permitted range S within the target path P from the permitted range. The range indication image Is includes, for example, a line-shaped dividing line that distinguishes the boundary between the non-permitted range S and the permitted range, and arrow-shaped range objects arranged between these dividing lines that represent the range of the non-permitted range S. The reduction notification image In notifies that the target speed V needs to be reduced to eliminate the non-permitted range S. i The display objects. Reduce notification images, such as "The set speed for this section needs to be reduced to 5 km / h," and text objects that notify via text messages.

[0151] (Seventh Implementation)

[0152] like Figure 19 As shown, the seventh embodiment is a variation of the first embodiment.

[0153] In the sixth embodiment, the output module 120 will propose reducing the curvature ρ of the non-allowed interval S in the highlighted display of the non-allowed interval S. iThe display is added to the target path P. For example, the output module 120 displays the non-allowed section S in a different color than other parts of the target path P. Additionally, in Figure 19 In the example shown, different display colors are represented by shaded lines. The output module 120 can also, for example, display text messages to notify the user that the curvature ρ needs to be reduced. i The notification image conveys the meaning. Through this emphasized display, the output module 120 urges the user to use the curvature ρ... i The reduction eliminates the non-allowed interval S.

[0154] In addition, when proposing curvature ρ i When the position of the endpoint node Ne is reduced, the acquisition module 110 in S110 receives input indicating a change in at least one of the position of the endpoint node Ne and the shape of the path line, and prohibits changes to the starting node Ns. Thus, the acquisition module 110 avoids shape changes to the previous target path P in areas where the non-allowed interval S has been eliminated.

[0155] According to the seventh embodiment described above, a curvature change of the target path P is proposed in the emphasized display of the non-permitted interval S. Therefore, it is possible to urge the user to proceed via curvature ρ. i The reduction eliminates the non-allowed interval S.

[0156] (Other implementation methods)

[0157] The above describes several embodiments, but this disclosure is not limited to these embodiments. Various embodiments and combinations can be applied without departing from the spirit of this disclosure.

[0158] In a variation of the fourth embodiment, the information processing device 100 may also process the yaw rate γ obtained in S80. i The conversion to lateral acceleration replaces the lateral acceleration limit value a. lmax The limit value of yaw rate γ max Conversion. In this case, in S90, the information processing device 100, at each node, has its lateral acceleration controlled by the lateral acceleration limit value a. lmax If the range is outside the specified allowable range, it is determined to be an unallowable interval S. Similarly, in a variation of the fifth embodiment, the information processing device 100 may also process the yaw rate γ obtained in S80. i Convert to rudder angle.

[0159] In a modified example, the information processing device 100 may also acquire multiple state values, such as the yaw rate limit, the lateral acceleration limit, and the rudder angle limit. In this case, the information processing device 100 determines whether there is an unacceptable interval S based on the state value with the strictest permissible range among the multiple state values. Specifically, the information processing device 100 acquires the lateral acceleration limit value a lmax and rudder angle limit value δ max Based on the conversion to yaw rate, the most stringent limit value among all state values ​​can be selected as the state value within the specified allowable range.

[0160] In a modified example, for each target path P, a new target speed V can be received as input. Additionally, in a modified example, the information processing device 100 can also receive input of the target speed V, which varies according to the travel distance from the starting node Ns.

[0161] In a variation, the computer constituting the information processing device 100 may also have at least one of digital circuitry and analog circuitry as a processor. Here, digital circuitry refers to at least one of, for example, ASIC (Application Specific Integrated Circuit), FPGA (Field Programmable Gate Array), SOC (System on a Chip), PGA (Programmable Gate Array), and CPLD (Complex Programmable Logic Device). Furthermore, such digital circuitry may also have a memory storing programs.

[0162] In a variation, the memory 101 storing the information processing program may also be a portable storage medium removable from the information processing device 100. In this case, the memory 101 may be a storage medium for carrying the information processing program installed on the information processing device 100, which is readablely stored in the information processing device 100, which is a computer. Alternatively, the memory 101 may be a storage medium of a server device that distributes information processing programs to a user's information processing device 100.

[0163] In addition to the descriptions above, the information processing apparatus 100 in the above embodiments and variations may also be implemented as a semiconductor device (e.g., a semiconductor chip).

[0164] (The disclosure of technical ideas)

[0165] This specification discloses several technical ideas described in the following list of items. Some items are sometimes described in a multiple dependent form, whereby an earlier item is selectively referenced in a subsequent item. Furthermore, some items are sometimes described in a multiple dependent form, referring to another multiple dependent form. These items described in multiple dependent forms define a variety of technical ideas.

[0166] (Technical Idea 1)

[0167] An information processing method, executed by a processor (102), is used to perform path generation associated processing related to the generation of path data, which defines a target path (P) tracked by an autonomous device (1) capable of autonomous driving, including:

[0168] Receives inputs of the target path between each node defining the location of the autonomous device, and the target speed as the target during autonomous driving along the target path; and

[0169] The display device (7) displays the target path.

[0170] The target path is shown to include:

[0171] The non-permitted interval (S) in the target path is highlighted, in which the intended yaw rate of the autonomous device tracking the curved target path in association with the target path and the target speed exceeds the permissible range that allows the tracking to occur.

[0172] (Technical Idea 2)

[0173] As described in the information processing method of technical concept 1, the yaw rate outside the allowable range includes the yaw rate where the lateral acceleration is associated with the target path and the target velocity and exceeds the acceleration limit.

[0174] (Technical Idea 3)

[0175] As described in the information processing method of technical idea 1 or technical idea 2, the yaw rate outside the allowable range includes the yaw rate that exceeds the acceleration limit in association with the rudder angle and the target path and the target speed.

[0176] (Technical Idea 4)

[0177] As described in any of technical ideas 1 to 3, the information processing method for receiving the input of the target path and the target speed includes:

[0178] The system receives input of the target path as manual driving path data, which is related to the path actually traveled by the autonomous device through manual driving.

[0179] (Technical Idea 5)

[0180] As described in any of technical ideas 1 to 4, the information processing method for receiving the input of the target path and the target speed includes:

[0181] Receives input of the target path designed by the user through manual input of the nodes, based on a map related to the driving area of ​​the autonomous device displayed on the display device.

[0182] (Technical Idea 6)

[0183] As described in technical concept 5, the information processing method further shows that the target path also includes:

[0184] Displays a curved limit path (PL), which represents the limit of the target path that the autonomous device is allowed to trace from the starting node (Ns) of the manually input target path.

[0185] (Technical Idea 7)

[0186] As described in any of the technical ideas 1 to 6, the information processing method displays the target path as follows:

[0187] In the emphasis display of the non-permitted zone, it is proposed to reduce the target speed in the non-permitted zone.

[0188] (Technical Idea 8)

[0189] As described in any of the technical ideas 1 to 7, the information processing method displays the target path as follows:

[0190] The curvature change of the target path is highlighted in the emphasis display of the non-permitted interval.

[0191] (Technical Idea 9)

[0192] An information processing method as described in any one of technical ideas 1 to 8 includes: generating path data that defines the target path having eliminated the non-allowed intervals.

[0193] (Technical Idea 10)

[0194] The information processing method described in Technical Idea 9 includes: outputting path data that defines the target path for which the non-allowed intervals have been eliminated.

[0195] In addition, the above-mentioned technical ideas 1 to 10 can also be implemented in the form of an information processing device 100, an information processing program, and a storage medium.

Claims

1. An information processing method, executed by a processor (102), for performing path generation associated processing related to the generation of path data, which defines a target path (P) tracked by an autonomous device (1) capable of autonomous driving, characterized in that, include: Receives the target path between each node defining the passing position of the autonomous device, and the target speed as the target during autonomous driving along the target path; as well as The display device (7) displays the target path. The target path is shown to include: The non-permitted interval (S) in the target path is highlighted, in which the intended yaw rate of the autonomous device tracking the curved target path in association with the target path and the target speed exceeds the permissible range that allows the tracking to occur.

2. The information processing method as described in claim 1, characterized in that, The yaw rate outside the permissible range includes yaw rates where the lateral acceleration associated with the target path and the target velocity exceeds the acceleration limit.

3. The information processing method as described in claim 1, characterized in that, The yaw rate outside the permissible range includes the yaw rate that exceeds the acceleration limit in relation to the rudder angle and the target path and the target speed.

4. The information processing method as described in claim 1, characterized in that, Receiving the input of the target path and the target speed includes: The system receives input of the target path as manual driving path data, which is related to the path actually traveled by the autonomous device through manual driving.

5. The information processing method as described in claim 1, characterized in that, Receiving the input of the target path and the target speed includes: Receives input of the target path designed by the user through manual input of the nodes, based on a map related to the driving area of ​​the autonomous device displayed on the display device.

6. The information processing method as described in claim 5, characterized in that, The target path is also displayed as follows: Displays a curved limit path (PL), which represents the limit of the target path that the autonomous device is allowed to trace from the starting node (Ns) of the manually input target path.

7. The information processing method as described in claim 1, characterized in that, The target path is shown to include: In the emphasis display of the non-permitted zone, it is proposed to reduce the target speed in the non-permitted zone.

8. The information processing method as described in claim 1, characterized in that, The target path is shown to include: The curvature change of the target path is highlighted in the emphasis display of the non-permitted interval.

9. The information processing method as described in claim 1, characterized in that, include: Generate path data that defines the target path with the non-allowed intervals eliminated.

10. The information processing method as described in claim 9, characterized in that, include: Output the path data of the target path for which the non-allowed intervals have been eliminated.

11. An information processing apparatus comprising a processor (102) that performs path generation associated processing related to the generation of path data, the path data defining a target path (P) tracked by an autonomous device (1) capable of autonomous driving, characterized in that, The processor is configured to execute: Receives the target path between each node defining the passing position of the autonomous device, and the target speed as the target during autonomous driving along the target path; as well as The display device (7) displays the target path. The target path is shown to include: The non-permitted interval (S) in the target path is highlighted, in which the intended yaw rate of the autonomous device tracking the curved target path in association with the target path and the target speed exceeds the permissible range that allows the tracking to occur.

12. An information processing program, stored in a storage medium (101) and comprising commands executed by a processor (102), for performing path generation associated processing related to the generation of path data, which defines a target path (P) tracked by an autonomous device (1) capable of autonomous driving, characterized in that, The commands include: Receives inputs of the target path between each node defining the location of the autonomous device, and the target speed as the target during autonomous driving along the target path; and The display device (7) displays the target path. The target path is shown to include: The non-permitted interval (S) in the target path is highlighted, in which the intended yaw rate of the autonomous device tracking the curved target path in association with the target path and the target speed exceeds the permissible range that allows the tracking to occur.

13. A storage medium storing an information processing program containing commands executed by a processor (102) for performing path generation-related processing associated with the generation of path data, the path data defining path data of a target path (P) tracked by an autonomous device (1) capable of autonomous driving, characterized in that, The commands include: Receives inputs of the target path between each node defining the location of the autonomous device, and the target speed as the target during autonomous driving along the target path; and The display device (7) displays the target path. The target path is shown to include: The non-permitted interval (S) in the target path is highlighted, in which the intended yaw rate of the autonomous device tracking the curved target path in association with the target path and the target speed exceeds the permissible range that allows the tracking to occur.

Images