A remote intelligent parking space moving route planning method, device, equipment and storage medium

Abstract

The present application relates to a remote intelligent vehicle parking route planning method, device, equipment and storage medium, which is used for remote vehicle parking route planning when there are obstacles in front of, behind and on one side of the vehicle. It is characterized in that it includes the following steps: obtaining a first information set, where the first information set includes vehicle surrounding information, vehicle parameter information and vehicle initial position information; generating a driving path according to a trajectory constraint algorithm for avoiding collisions or exceeding boundaries, the first information set and the parking guidance information input by the user, and the driving path includes a first steering path, a straight path and a second steering path extending from the vehicle initial position to the vehicle stop position. The final vehicle parking target position depends on the parking guidance information input by the user, thereby enabling the present solution to plan the parking route by directly specifying the parking target position in the surrounding environment without being limited by the available parking positions in the environment when generating the driving path.

Description

Technical Field

[0001] This application relates to the technical field of remote vehicle moving, and particularly to a remote intelligent vehicle moving route planning method, device, equipment and storage medium. Background Art

[0002] With the improvement of living standards, the ownership ratio of private cars has been increasing year by year. During peak commuting hours or holidays, large-scale and long-term congestion often occurs in major parking lots. And it often happens that due to various reasons, even if the current position will block other vehicles, the vehicle owner still chooses to park the vehicle there. As a result, when the subsequent blocked vehicle needs to travel, the vehicle owner needs to rush back to the scene to move the vehicle.

[0003] In the related art, although there is a technology for remotely controlling a vehicle to move based on wireless network communication, in the above scenarios, it is often necessary to collect information about the movable vehicle target positions in the environment, such as the parking space lines of parking spaces, etc. However, when the information of the movable vehicle target positions cannot be successfully collected, such as when the parking space lines are blocked, the movable vehicle target positions cannot be successfully identified, so that a driving path cannot be successfully generated and the driving task cannot be executed. Therefore, such technologies still have great limitations in practical applications. Summary of the Invention

[0004] Embodiments of this application provide a remote intelligent vehicle moving route planning method, device, equipment and storage medium to solve the above problems.

[0005] In a first aspect, a remote intelligent vehicle moving route planning method is provided, adopting the following technical solution:

[0006] A remote intelligent vehicle moving route planning method, which is used for remotely planning a vehicle moving route when there are obstacles in front of, behind and on one side of the vehicle, and includes the following steps:

[0007] Obtain a first information set, where the first information set includes vehicle surrounding information, vehicle parameter information and vehicle initial position information;

[0008] Generate a driving path according to a trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set and the vehicle moving guiding information input by the user, and the driving path includes a first turning path, a straight path and a second turning path extending from the vehicle initial position to the vehicle stop position.

[0009] In some embodiments, before generating the driving path according to the trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set and the vehicle moving guiding information input by the user, it includes:

[0010] Respond to a first selection instruction input by the user and display a first vehicle moving interface;

[0011] Obtain the parking maneuvering trajectory input by the user on the first parking maneuvering interface, where the parking maneuvering trajectory is the parking guidance information.

[0012] In some embodiments, before generating a driving path according to the trajectory constraint algorithm for avoiding collisions or crossing boundaries, the first information set, and the parking guidance information input by the user, it includes:

[0013] In response to a second selection instruction input by the user, display a second parking maneuvering interface;

[0014] Obtain the parking target position input by the user on the second parking maneuvering interface, where the parking target position is the parking guidance information.

[0015] In some embodiments, before generating a driving path according to the trajectory constraint algorithm for avoiding collisions or crossing boundaries, the first information set, and the parking guidance information input by the user, it includes:

[0016] Judge whether the current conditions can generate a driving path according to the trajectory constraint algorithm for avoiding collisions or crossing boundaries and the first information set;

[0017] If a driving path cannot be generated, display a first error message indicating that the driving path cannot be generated;

[0018] If a driving path can be generated, execute the step of generating the driving path.

[0019] In some embodiments, when judging whether the parking guidance information is valid according to the trajectory constraint algorithm for avoiding collisions or crossing boundaries, the first information set, and the parking guidance information input by the user, it includes:

[0020] Judge whether there will be a collision with surrounding obstacles and whether it will exceed the road boundary according to the maximum steering angle of the vehicle, the trajectory constraint algorithm, and the first information set

[0021] If there will be a collision with surrounding obstacles or it will exceed the road boundary, judge that the current conditions cannot generate a driving path; where

[0022] The first steering path and the second steering path are at least partially centrosymmetric, and the straight-line path is the common tangent of the first steering path and the second steering path.

[0023] In some embodiments, generate a driving path according to a preset steering angle, the trajectory constraint algorithm, the first information set, and the parking guidance information, and the preset steering angle is less than the maximum steering angle of the vehicle.

[0024] In some embodiments, if the driving path generated according to the preset steering angle, the trajectory constraint algorithm, the first information set, and the parking guidance information will cause the vehicle to collide with surrounding obstacles or exceed the road boundary, the steering angle is increased and the driving path is generated again.

[0025] In a second aspect, a remote intelligent parking route planning device is provided, adopting the following solution:

[0026] A remote intelligent parking route planning device includes:

[0027] An information collection module for obtaining a first information set, the first information set including vehicle surrounding information, vehicle parameter information, and vehicle initial position information;

[0028] A driving path calculation module for generating a driving path according to a trajectory constraint algorithm, the first information set, and parking guidance information input by a user.

[0029] In a third aspect, a remote intelligent parking route planning device is provided, adopting the following solution:

[0030] A remote intelligent parking route planning device, a memory, a processor, and a remote intelligent parking route planning program stored on the memory and executable on the processor, the remote intelligent parking route planning program configured to implement the steps of the remote intelligent parking route planning method as described above.

[0031] In a fourth aspect, a storage medium is provided, adopting the following solution:

[0032] A storage medium that non-temporarily stores computer-readable instructions that, when executed by a computer, can execute to implement the remote intelligent parking route planning method as described above.

[0033] The beneficial effects brought by the technical solution provided in this application include:

[0034] The embodiments of this application provide a remote intelligent parking route planning method, device, device, and storage medium. By the parking guidance information input by the user, a driving path is generated, and then the vehicle can be remotely controlled to automatically park in the subsequent process, and the parking action of the vehicle can be completed without the user returning to the scene; at the same time, since the final parking target position of the vehicle depends on the parking guidance information input by the user, that is, the end position of the driving path is selected by the user himself in the environment, there is no need to identify and obtain a parkable target position in the environment, such as a parking space, in an automatic parking system in related technologies before generating a driving path for movement. That is, this solution does not need to be limited by the parkable positions in the environment when generating a driving path, and can directly specify a parking target position in the surrounding environment to plan a parking route. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0036] Figure 1 It is a schematic diagram of the hardware structure of the remote intelligent parking route planning device involved in the present application;

[0037] Figure 2 It is a schematic diagram of the overall process provided by some embodiments of the present application;

[0038] Figure 3 It is a schematic diagram of a partial process provided by some embodiments of the present application;

[0039] Figure 4 It is a schematic diagram of the process of steps S101 - S200 in some embodiments of the present application;

[0040] Figure 5 It is a schematic diagram of the process of step S200 in some embodiments of the present application;

[0041] Figure 6 It is a vehicle model diagram in the trajectory constraint algorithm of the present application;

[0042] Figure 7 It is a schematic diagram of the coordinate system of the vehicle traveling the first steering path at the maximum steering angle in the trajectory constraint algorithm of the present application;

[0043] Figure 8 It is a schematic diagram of the coordinate system of the vehicle traveling the shortest straight path at the maximum steering angle in the trajectory constraint algorithm of the present application;

[0044] Figure 9 It is a schematic diagram of the coordinate system of the vehicle traveling the second steering path at the maximum steering angle in the trajectory constraint algorithm of the present application;

[0045] Figure 10 It is a schematic diagram of the functional modules of an embodiment of the intelligent parking route planning device in the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts fall within the scope of protection of this application.

[0047] With the improvement of living standards, the ownership rate of private cars has been increasing year by year. The sharp increase in the number of vehicles in big cities has also triggered a series of "big city problems". "Difficult parking" is a relatively serious problem in big cities at present. During the rush hours of going to and from work or on holidays, large areas and long-time congestion often occur in major parking lots. And it often happens that due to various reasons, even if the current position will block other vehicles, the vehicle owner still chooses to park the vehicle there. As a result, when the blocked vehicle needs to go out later, the vehicle owner needs to rush back to the scene to move the vehicle.

[0048] In the related art, although there is a technology for remotely controlling a vehicle to move based on wireless network communication, in the above scenarios, it is often necessary to collect information on the target positions for vehicle moving in the environment, such as the pictures of parking spaces, etc. However, when the information on the target positions for vehicle moving cannot be successfully collected, such as when the parking space signs or ground markings are blocked, the final target positions for vehicle moving cannot be successfully identified, so that the driving paths cannot be successfully generated and the driving tasks cannot be executed. Therefore, such technologies still have great limitations in practical applications.

[0049] Based on this, the embodiments of this application provide a method, device, equipment, and storage medium for remotely intelligent vehicle moving route planning to solve the problems in the above related technologies.

[0050] In the first aspect, referring to Figure 1 , Figure 1 is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiments of the present invention.

[0051] As Figure 1As shown in the figure, the device may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display) and an input unit such as a keyboard (Keyboard). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM memory or a stable storage (Non-Volatile Memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0052] Those skilled in the art can understand that Figure 1 the device structure shown in the figure does not constitute a limitation on the device, and it may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements.

[0053] As Figure 1 shown in the figure, the memory 1005, as a storage medium, may include an operating system, a network communication module, a user interface module, and a remote intelligent parking route planning program. Among them, the device of the present invention can call the remote intelligent parking route planning program stored in the memory 1005 through the processor 1001 and execute the remote intelligent parking route planning method provided by the embodiments of the present application.

[0054] In a second aspect, a remote intelligent parking route planning method is provided.

[0055] Referring to Figure 2 , a remote intelligent parking route planning method is used for remote parking route planning when there are obstacles in front of, behind, and on one side of the vehicle, and it includes the following steps:

[0056] S100. Obtain a first information set, where the first information set includes vehicle surrounding information, vehicle parameter information, and vehicle initial position information;

[0057] S200. Generate a driving path according to a trajectory constraint algorithm for avoiding collisions or exceeding boundaries, the first information set, and the parking guidance information input by the user, and the driving path includes a first steering path, a straight-line path, and a second steering path extending from the vehicle initial position to the vehicle stop position.

[0058] Among them, the vehicle surrounding information includes the road width on the side of the vehicle away from the blocked vehicle, the widths of the front and rear obstacles, the distances between the vehicle and the front and rear obstacles, and the distance between the vehicle and the obstacle on one side. The front and rear sides of the vehicle and the obstacle on one side are respectively the front obstacle vehicle, the rear obstacle vehicle of the present vehicle, and the blocked vehicle blocked by the present vehicle in this embodiment.

[0059] With such a setting, through the parking guidance information input by the user, a driving path is generated, and then the vehicle can be remotely controlled to automatically park in the subsequent process, and the parking action of the vehicle can be completed without the user returning to the scene. At the same time, since the final parking target position of the vehicle depends on the parking guidance information input by the user, that is, the end position of the driving path is selected by the user himself, there is no need to identify and obtain the available parking target position in the environment, such as a parking space, as in the automatic parking system in the related art, in order to generate a driving path for movement. That is, in this solution, there is no need to be limited by the available parking positions in the environment when generating the driving path, and the parking target position can be directly specified in the surrounding environment to plan the parking route.

[0060] Refer to Figure 3 , in some preferred embodiments, before step S200, it includes:

[0061] S110. Respond to the first selection instruction input by the user and display the first parking interface;

[0062] S120. Obtain the parking trajectory input by the user on the first parking interface, and the parking trajectory is the parking guidance information.

[0063] At the same time, to enable the user to have more diverse control methods when using, in some other embodiments, it may further include:

[0064] S130. Respond to the second selection instruction input by the user and display the second parking interface;

[0065] S140. Obtain the parking target position input by the user on the second parking interface, and the parking target position is the parking guidance information.

[0066] Among them, the above two methods can be set in the same embodiment or different embodiments, and when the parking guidance information is the parking trajectory, the parking target position can also be obtained according to the end of the parking trajectory, so as to implement the subsequent steps of the solution of the present application according to the parking target position.

[0067] Optionally, refer to Figure 4 , before generating the driving path according to the trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set, and the parking guidance information input by the user, it includes:

[0068] S101. Determine whether the current conditions can generate a driving path according to the trajectory constraint algorithm for avoiding collisions or exceeding boundaries and the first information set;

[0069] S102. If a driving path cannot be generated, display a first error message indicating that the driving path cannot be generated;

[0070] S103. If a driving path can be generated, execute the step of generating the driving path.

[0071] Furthermore, the step S101 includes:

[0072] Judge whether there will be a collision with surrounding obstacles and whether the road boundary will be exceeded according to the maximum steering angle of the vehicle, the trajectory constraint algorithm, and the first information set;

[0073] If there will be a collision with surrounding obstacles or the road boundary will be exceeded, it is determined that the current conditions cannot generate a driving path; where

[0074] The first steering path and the second steering path are at least partially centrosymmetric, and the straight-line path is the common tangent of the first steering path and the second steering path.

[0075] In this embodiment, the first steering path and the second steering path are centrosymmetric about the midpoint of the straight-line path.

[0076] When making the judgment in the above step S101, the following steps are included in sequence:

[0077] When making the judgment using the trajectory constraint algorithm, a plane coordinate system is established through the front and rear obstacle vehicles, the blocked vehicle on one side, and the relevant data in the first information set to simplify the vehicle model (see Figure 6 ), and the vehicle model under the driving path is analyzed in the coordinate system:

[0078] Refer to Figure 7 , judge whether the distance between the vehicle B point and the front obstacle vehicle is greater than the minimum safety distance t2 when the vehicle travels from the initial position to the end point P3 of the first steering path P4 - P3 at the maximum steering angle (i.e., the maximum value allowed for the rotation of the front wheel steering angle), that is, when the vehicle B point travels to point B1 (the B point and the c point of the front obstacle vehicle are in the same position in the vehicle width direction); among them, the coordinates of point B1 can be calculated according to other obtained parameters;

[0079] If it is less than the minimum safety distance, the vehicle cannot generate the first steering path in the current environment, that is, it is determined that the current conditions cannot generate a driving path;

[0080] If it is not less than the minimum safety distance, the vehicle can complete the first steering path in the current environment;

[0081] Reference Figure 8 , if the vehicle can complete the first steering path in the current environment, it is determined whether the C point of the vehicle will exceed the road when the vehicle travels along the straight path to point E (the intersection of the extension line of the rear axle of the vehicle and the AB side of the vehicle) and coincides with point B1 during the subsequent process, that is, when the shortest straight path of the third steering path of the vehicle is satisfied, whether it will exceed the other side boundary of the road;

[0082] If it exceeds the other side boundary of the road, the vehicle cannot complete the straight path P3 - P2 and the second steering path P2 - P1 in the current environment;

[0083] If it does not exceed the other side boundary of the road, the vehicle can complete the straight path P3 - P2 and the second steering path P2 - P1 in the current environment, that is, at this time, the vehicle can generate a driving path and can execute the subsequent steps.

[0084] Meanwhile, during the above calculation process, the angle θ by which the center of the rear axle of the vehicle rotates when point B moves to point B1 and the coordinates of point P3 can be calculated according to the maximum steering angle and the minimum safety distance of the vehicle.

[0085]

[0086]

[0087] Referring to the geometric relationship in the figure, the heading angle of the vehicle at point P3

[0088] The path of the P2P3 segment is a straight line segment, and the heading angle remains unchanged, and its slope is tanθ, then the expression of the straight line P2P3 can be obtained as:

[0089]

[0090] Reference Figure 8 , and at the same time, since the B point of the vehicle travels to point B1 and the E point travels to point B1, they are respectively the limit safety distance states that the B point and the E point of the vehicle can maintain with the front obstacle vehicle. Therefore, the minimum values of the respective abscissas and ordinates of P1 and point P can be calculated:

[0091]

[0092]

[0093] Reference Figure 9 , in addition, when the vehicle travels along the P4P3 segment of the first steering path, it is necessary to ensure that all points on the body contour do not exceed the road boundary, that is, only need to ensure that the left front point C of the body does not collide with the road boundary. The upper limit value of the ordinate of point P1 can be calculated according to this condition and the upper limit value of the ordinate of point P2

[0094]

[0095]

[0096] Furthermore, according to the expression of the straight line P2P3, the upper limit value of the abscissa of point P2 can be obtained

[0097]

[0098] Furthermore, the upper limit value of the abscissa of point P1 is obtained It is:

[0099]

[0100] The selection range of the parking space moving end point P1 is:

[0101]

[0102] In the formula, the value range of x is

[0103] Furthermore, after obtaining the value ranges of the abscissa and ordinate of point P1, it is the maximum selection range of the parking space moving target position obtained when the vehicle can generate a driving path with the maximum steering angle in the current environment. That is, when the user inputs the first selection instruction or the second selection instruction within this range, a driving path can be successfully generated under the condition of not exceeding the maximum steering angle.

[0104] Therefore, in some embodiments, before the user inputs the first selection instruction or the second selection instruction, the selectable area of the final position can be obtained first according to the above solution, so that the first selection instruction or the second selection instruction selected within this area can both successfully generate a driving path.

[0105] In some preferred embodiments, referring to Figure 5 , step S200, generating a driving path according to the trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set, and the parking space moving guidance information input by the user, includes:

[0106] S210. Generating a driving path according to a preset steering angle, the trajectory constraint algorithm, the first information set, and the parking space moving guidance information, and the preset steering angle is less than the maximum steering angle of the vehicle.

[0107] Among them, the preset steering angle is an optimally selected steering angle defined manually. The specific value of the optimally selected steering angle can be obtained manually according to the degree of damage to the mechanical structure during the steering process of different vehicle models and in combination with the length of the generated driving path.

[0108] With such a setting, it is realized that the most suitable driving path can be quickly obtained after the user inputs the parking guidance information, so that the vehicle can perform remote parking efficiently and safely.

[0109] However, since the parking target position finally obtained from the parking guidance information input by the user cannot be executed by the preset steering angle, that is, the driving path generated under the condition of the preset steering angle will collide with the vehicle in front or exceed the road boundary. Therefore, the parking guidance information input by such users needs to be further adjusted.

[0110] Furthermore, referring to Figure 5 , after step S210, it further includes:

[0111] S220. If the driving path generated according to the preset steering angle, the trajectory constraint algorithm, the first information set, and the parking guidance information will cause the vehicle to collide with surrounding obstacles or exceed the road boundary, then increase the steering angle and generate the driving path again.

[0112] Among them, when the coordinates of the parking target position corresponding to the parking guidance information input by the user, that is, the coordinates of point P1, cannot generate a driving path under the condition of the preset steering angle, at this time, the preset steering angle will be increased and the driving path will be generated again. The increase amplitude of the steering angle each time is set manually, and it can be increased by 1 degree of the steering angle each time until the steering angle is increased to a value that can smoothly generate a driving path that will not cause the vehicle to collide with surrounding obstacles or exceed the road boundary.

[0113] With such a setting, when the parking target position corresponding to the parking guidance information input by the user, that is, the position of point P1, can generate a driving path with the preset optimally selected steering angle, the optimally selected steering angle is always selected to generate the driving path and control the vehicle to drive, ensuring that the user's vehicle has a better state when driving on the generated driving path most of the time;

[0114] At the same time, when the position of point P1 input by the user cannot be executed with the preset optimally selected steering angle, at this time, the preset steering angle will be automatically increased until it can successfully execute the remote parking task, that is, the vehicle always executes with the minimum steering angle allowed by the current coordinates of point P1 during parking. Ultimately, it ensures that while the user performs remote parking, it effectively protects the vehicle by always executing with a steering angle that causes less damage to the mechanical structure during subsequent parking.

[0115] In a third aspect, a remote intelligent vehicle relocation route planning device is provided.

[0116] Referring to Figure 10 , a remote intelligent vehicle relocation route planning device includes:

[0117] An information acquisition module for obtaining a first information set, where the first information set includes vehicle surrounding information, vehicle parameter information, and vehicle initial position information;

[0118] A driving path calculation module for generating a driving path according to a trajectory constraint algorithm, the first information set, and relocation guidance information input by a user.

[0119] In a fourth aspect, a storage medium is provided.

[0120] The readable storage medium provided by this application stores a remote intelligent vehicle relocation route planning program. When the remote intelligent vehicle relocation route planning program is executed by a processor, the steps of the remote intelligent vehicle relocation route planning method as described above are implemented. The method implemented when the remote intelligent vehicle relocation route planning program is executed can refer to the various embodiments of the remote intelligent vehicle relocation route planning method provided by this application, which will not be elaborated here.

[0121] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

[0122] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc) as described above and includes several instructions for causing a terminal device to execute the methods described in the various embodiments of the present invention.

[0123] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A remote intelligent parking space relocation route planning method, which is used for remote parking space relocation route planning when there are obstacles in front of, behind and on one side of a vehicle, and is characterized in that, It includes the following steps: Obtain a first information set, where the first information set includes vehicle surrounding information, vehicle parameter information, and vehicle initial position information; the vehicle surrounding information includes the road width on the side where the vehicle is away from the blocked vehicle, the widths of the front and rear obstacles, the distances from the front and rear obstacles, and the distance from the obstacle on one side of the vehicle; Generate a driving path according to a trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set, and the parking guidance information input by the user, and the driving path includes a first steering path, a straight-line path, and a second steering path extending from the vehicle initial position to the vehicle stop position; Calculate the selection range of the parking end point according to the vehicle surrounding information, vehicle parameter information, and vehicle initial position information before the user inputs the parking guidance information. When any point within the selection range of the parking end point is used as the parking end point, a driving path can be successfully generated, and the parking guidance information input by the user is based on the selection range of the parking end point; Judge whether there will be a collision with surrounding obstacles and whether the road boundary will be exceeded according to the maximum steering angle of the vehicle, the trajectory constraint algorithm, and the first information set; if there will be a collision with surrounding obstacles or the road boundary will be exceeded, it is judged that the current conditions cannot generate a driving path; wherein, at least part of the first steering path and the second steering path are centrosymmetric, and the straight-line path is the common tangent of the first steering path and the second steering path.

2. The remote intelligent parking space relocation route planning method according to claim 1, wherein Before generating the driving path according to the trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set, and the parking guidance information input by the user, it includes: Respond to the first selection instruction input by the user and display the first parking interface; Obtain the parking trajectory input by the user on the first parking interface, and the parking trajectory is the parking guidance information.

3. The remote intelligent parking space relocation route planning method according to claim 1, wherein, Before generating the driving path according to the trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set, and the parking guidance information input by the user, it includes: Respond to the second selection instruction input by the user and display the second parking interface; Obtain the parking target position input by the user on the second parking interface, and the parking target position is the parking guidance information.

4. The remote intelligent parking space relocation route planning method according to claim 1, characterized in that Generating the driving path according to the trajectory constraint algorithm for avoiding collision or exceeding the boundary, the first information set, and the parking guidance information input by the user includes: Generate a driving path according to a preset steering angle, the trajectory constraint algorithm, the first information set, and the parking guidance information, and the preset steering angle is less than the maximum steering angle of the vehicle.

5. The remote intelligent parking space relocation route planning method according to claim 4, wherein, If the driving path generated according to the preset steering angle, the trajectory constraint algorithm, the first information set, and the parking guidance information will cause the vehicle to collide with surrounding obstacles or exceed the road boundary, increase the preset steering angle and then generate the driving path again.

6. A remote intelligent parking space relocation route planning device, characterized in that, It includes: An information acquisition module, which is used to obtain a first information set, where the first information set includes vehicle surrounding information, vehicle parameter information, and vehicle initial position information; The vehicle surrounding information includes the road width on the side of the vehicle away from the blocked vehicle, the widths of the front and rear obstacles, the distances from the front and rear obstacles, and the distance from the obstacle on one side of the vehicle; A driving path calculation module, which is used to generate a driving path according to a trajectory constraint algorithm for avoiding collisions or exceeding boundaries, the first information set, and the parking guidance information input by the user, and the driving path includes a first steering path, a straight-line path, and a second steering path extending from the initial position of the vehicle to the stop position of the vehicle; Before the user inputs the parking guidance information, calculate the selection range of the parking end point according to the vehicle surrounding information, the vehicle parameter information, and the vehicle initial position information. When any point within the selection range of the parking end point is used as the parking end point, a driving path can be successfully generated, and the parking guidance information input by the user is based on the selection range of the parking end point; Judge whether there will be a collision with surrounding obstacles and whether it will exceed the road boundary according to the maximum steering angle of the vehicle, the trajectory constraint algorithm, and the first information set; if there will be a collision with surrounding obstacles or it will exceed the road boundary, it is determined that the current conditions cannot generate a driving path; wherein, at least part of the first steering path and the second steering path are centrosymmetric, and the straight-line path is the common tangent of the first steering path and the second steering path.

7. A remote intelligent vehicle relocation route planning device, characterized in that, A memory, a processor, and a remote intelligent parking route planning program stored on the memory and executable on the processor, the remote intelligent parking route planning program being configured to implement the steps of the remote intelligent parking route planning method according to any one of claims 1 to 5.

8. A storage medium, characterized in that, Non-temporarily store computer-readable instructions, which, when executed by a computer, implement the remote intelligent parking route planning method according to any one of claims 1-5.

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