A vehicle precision parking method and system based on target distance input and a medium
By constructing a real-time distance function and control algorithm, the problem of precise parking of autonomous vehicles in container transshipment scenarios was solved, improving operational efficiency and stability, and reducing human intervention and hardware damage.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 东风悦享科技有限公司
- Filing Date
- 2024-02-29
- Publication Date
- 2026-07-03
AI Technical Summary
Autonomous vehicles cannot achieve precise parking in container transshipment scenarios, resulting in low operational efficiency and frequent human intervention, which affects the lifespan of vehicle hardware.
By constructing a real-time distance function between the vehicle and the target, and combining it with minimum stable speed, deceleration, and maximum braking force control algorithms, precise vehicle parking can be achieved.
It enables precise vehicle parking, improves container operation efficiency, reduces labor costs, and enhances vehicle stability and hardware lifespan.
Smart Images
Figure CN117864116B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of autonomous driving technology, and in particular to a method, system, and medium for precise vehicle parking based on target distance input. Background Technology
[0002] In recent years, with the continuous development of autonomous driving, autonomous driving technology has gradually advanced to Level 4, enabling autonomous driving tasks to be completed without driver intervention in limited scenarios. This allows for the complete separation of driver and vehicle, truly achieving the standard of driverless driving, and has now become a major battleground for manufacturers. Among these, the relatively closed scenario of automated container transshipment in ports has become a pioneering application scenario for autonomous driving.
[0003] Automated container handling places high demands on parking precision. Considering factors such as vehicle performance and target location accuracy, it is difficult to achieve precise alignment through conventional parking methods. Major manufacturers control the vehicle to move a corresponding distance by inputting the desired displacement to achieve precise alignment. Therefore, how to control the vehicle to achieve precise parking at the target displacement is a key issue in improving the efficiency of container operations.
[0004] The initial parking maneuver of an autonomous vehicle often fails to precisely locate the target position, leaving a considerable distance. This necessitates multiple manual interventions in precise parking scenarios such as container handling and automatic charging, leading to decreased operational efficiency. Therefore, it's necessary to request a target distance from the autonomous vehicle to enable precise parking. However, frequent fluctuations in the reference distance input cause repetitive actions. Since precise parking accuracy is often at the centimeter level, using GPS positioning for mileage calculation presents significant challenges. If the distance to the target position is far, using only inch-like movements, while achieving the desired location, results in frequent starts and stops, leading to low efficiency and potential damage to the drive-by-wire chassis hardware from prolonged switching between motor drive and braking. Therefore, mastering the control system to achieve precise parking at the target displacement is crucial. Summary of the Invention
[0005] In view of the above problems, the present invention provides a method, system and medium for precise vehicle parking based on target distance input. It not only solves the problem of precise vehicle parking and improves the work efficiency of container operation, but also eliminates the need for manual intervention during the precise vehicle parking process, reducing labor costs and improving stability, thereby further improving the efficiency of task completion.
[0006] To achieve the above and other related objectives, the present invention provides the following technical solution:
[0007] A method for precise vehicle parking based on a target distance input, the method comprising:
[0008] U1. When the vehicle travels to the target area, data on the target distance is obtained, and the vehicle's location data is obtained in real time based on the onboard laser odometer.
[0009] U2. Based on the vehicle's location data and the target's distance data, a real-time distance function Q between the vehicle and the target is constructed to calculate the distance between the vehicle and the target, thereby obtaining the real-time distance data between the vehicle and the target;
[0010] U3. Based on the real-time distance data between the vehicle and the target, preset thresholds s1 and s2 are set, and s1 is less than s2. If the real-time distance between the vehicle and the target is greater than s2, the minimum stable speed control algorithm is used to control the vehicle to obtain the first control data information of the vehicle.
[0011] U4. Based on the first control data information of the vehicle, if the real-time distance between the vehicle and the target is between s1 and s2, the vehicle deceleration control algorithm is used to control the vehicle to obtain the second control data information of the vehicle.
[0012] U5. Based on the second control data of the vehicle, if the real-time distance between the vehicle and the target is less than s1, then construct the maximum braking force control function G of the vehicle, control the vehicle, and obtain the parking position of the vehicle within the preset deviation range to complete the parking.
[0013] Furthermore, the target distance data information is the distance data information between the center point of the vehicle body and the target position.
[0014] Furthermore, in step U2, the distance function Q between the vehicle and the target is,
[0015] Where α1 and α2 are the vehicle's adaptability factors to the target, (x t ,y t (x0, y0) represents the vehicle's location data, and (x0, y0) represents the target distance data.
[0016] Furthermore, the constraints on the vehicle's adaptability factors α1 and α2 to the target are as follows:
[0017] The vehicle's adaptability factors α1 and α2 to the target are,
[0018]
[0019]
[0020] Where (x0, y0) represents the target distance data.
[0021] Furthermore, in step U3, the minimum stable vehicle speed control algorithm controls the vehicle by including:
[0022] U31. Based on the real-time distance data between the vehicle and the target, timestamps are calibrated and the data is divided into fixed time periods to obtain the divided real-time distance data between the vehicle and the target.
[0023] U32. Based on the real-time distance data between the divided vehicles and the target, establish the minimum stable vehicle speed control function H.
[0024]
[0025] Among them, s t The data represents the real-time distance between the vehicle and the target after the segmentation, v0 represents the initial speed data of the vehicle, and β1 and β2 represent the vehicle speed control adjustment factors.
[0026] U33. Based on the vehicle's minimum stable speed control function H, control the vehicle to obtain the vehicle's first control data information.
[0027] Furthermore, the constraints on the vehicle speed control adjustment factors β1 and β2 are as follows:
[0028]
[0029] The vehicle speed control adjustment factors β1 and β2 are,
[0030]
[0031]
[0032] Where v0 represents the vehicle's initial speed data.
[0033] Furthermore, in step U4, the vehicle deceleration control algorithm controls the vehicle by including:
[0034] U41. Based on the first control data information of the vehicle and the real-time distance data information between the vehicle and the target, obtain the current speed data information of the vehicle and the current distance data information between the vehicle and the target;
[0035] U42. Based on the vehicle's current speed data and the distance data between the vehicle and the target, establish the vehicle's deceleration control function W.
[0036]
[0037] Where s is the distance data between the current vehicle and the target, v1 is the current speed data of the vehicle, and δ and ω are the deceleration control factors of the vehicle.
[0038] U43. Based on the vehicle's deceleration control function W, the vehicle is controlled to obtain the vehicle's second control data information.
[0039] Furthermore, in step U5, the maximum braking force control function G of the vehicle is,
[0040] Where a is the distance between the vehicle and the target, and v2 is the initial speed data after the vehicle decelerates under the second control data information.
[0041] To achieve the above and other related objectives, the present invention also provides a precise parking system for a vehicle with a target distance input, including a computer device programmed or configured to perform the steps of any of the precise parking methods for a vehicle with a target distance input as described above.
[0042] To achieve the above and other related objectives, the present invention also provides a computer-readable storage medium storing a computer program programmed or configured to perform a precise parking method for a vehicle based on a target distance input as described in any one of the claims.
[0043] The present invention has the following positive effects:
[0044] 1. This invention constructs a real-time distance function Q between the vehicle and the target to calculate the distance between them, and combines this with a minimum stable speed control algorithm to control the vehicle, thereby obtaining the vehicle's first control data information. This not only solves the problems of frequent starts and stops in the overall vehicle performance, which is not only inefficient, but also causes some damage to the drive-by-wire chassis hardware due to the long-term switching between motor drive and braking, but also ensures that the vehicle drives smoothly at a low speed, achieving precise parking.
[0045] 2. This invention controls the vehicle by employing a vehicle deceleration control algorithm to obtain the vehicle's second control data information. Combined with the construction of the vehicle's maximum braking force control function G, the vehicle is controlled to ensure that the vehicle's parking position is within a preset deviation range, thus completing the parking process. This not only solves the problem of precise vehicle parking and improves the work efficiency of container operations, but also eliminates the need for manual intervention during the precise parking process, reducing labor costs and demonstrating good stability, further improving the efficiency of task completion. Attached Figure Description
[0046] Figure 1 This is a schematic diagram of the method flow of the present invention;
[0047] Figure 2 This is a flowchart illustrating the minimum stable vehicle speed control algorithm of the present invention.
[0048] Figure 3 This is a flowchart illustrating the vehicle deceleration control algorithm of the present invention. Detailed Implementation
[0049] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.
[0050] Example 1: As Figure 1 As shown, a method for precise vehicle parking based on a target distance input includes:
[0051] U1. When the vehicle travels to the target area, data on the target distance is obtained, and the vehicle's location data is obtained in real time based on the onboard laser odometer.
[0052] U2. Based on the vehicle's location data and the target's distance data, a real-time distance function Q between the vehicle and the target is constructed to calculate the distance between the vehicle and the target, thereby obtaining the real-time distance data between the vehicle and the target;
[0053] U3. Based on the real-time distance data between the vehicle and the target, preset thresholds s1 and s2 are set, and s1 is less than s2. If the real-time distance between the vehicle and the target is greater than s2, the minimum stable speed control algorithm is used to control the vehicle to obtain the first control data information of the vehicle.
[0054] U4. Based on the first control data information of the vehicle, if the real-time distance between the vehicle and the target is between s1 and s2, the vehicle deceleration control algorithm is used to control the vehicle to obtain the second control data information of the vehicle.
[0055] U5. Based on the second control data of the vehicle, if the real-time distance between the vehicle and the target is less than s1, then construct the maximum braking force control function G of the vehicle, control the vehicle, and obtain the parking position of the vehicle within the preset deviation range to complete the parking.
[0056] Among them, the preset thresholds s1 and s2 are,
[0057]
[0058]
[0059] Where (x0, y0) represents the target distance data.
[0060] In this embodiment, the target distance data is the distance between the center point of the vehicle body and the target position.
[0061] In this embodiment, in step U2, the distance function Q between the vehicle and the target is,
[0062]
[0063] Where α1 and α2 are the vehicle's adaptability factors to the target, (x t ,y t (x0, y0) represents the vehicle's location data, and (x0, y0) represents the target distance data.
[0064] In this embodiment, the constraints on the vehicle's and target's adaptability factors α1 and α2 are as follows:
[0065]
[0066] The vehicle's adaptability factors α1 and α2 to the target are,
[0067]
[0068]
[0069] Where (x0, y0) represents the target distance data.
[0070] In this embodiment, as Figure 2 As shown, in step U3, the minimum stable vehicle speed control algorithm controls the vehicle by including:
[0071] U31. Based on the real-time distance data between the vehicle and the target, timestamps are calibrated and the data is divided into fixed time periods to obtain the divided real-time distance data between the vehicle and the target.
[0072] U32. Based on the real-time distance data between the divided vehicles and the target, establish the minimum stable vehicle speed control function H.
[0073]
[0074] Among them, s t The data represents the real-time distance between the vehicle and the target after the segmentation, v0 represents the initial speed data of the vehicle, and β1 and β2 represent the vehicle speed control adjustment factors.
[0075] U33. Based on the vehicle's minimum stable speed control function H, control the vehicle to obtain the vehicle's first control data information.
[0076] In this embodiment, the constraints on the vehicle speed control adjustment factors β1 and β2 are as follows:
[0077] The vehicle speed control adjustment factors β1 and β2 are,
[0078]
[0079]
[0080] Where v0 represents the vehicle's initial speed data.
[0081] Example 2: Based on the vehicle precise parking method with target distance input in Example 1, the present invention will be further explained and described below.
[0082] like Figure 1 As shown, a method for precise vehicle parking based on a target distance input includes:
[0083] U1. When the vehicle travels to the target area, data on the target distance is obtained, and the vehicle's location data is obtained in real time based on the onboard laser odometer.
[0084] U2. Based on the vehicle's location data and the target's distance data, a real-time distance function Q between the vehicle and the target is constructed to calculate the distance between the vehicle and the target, thereby obtaining the real-time distance data between the vehicle and the target;
[0085] U3. Based on the real-time distance data between the vehicle and the target, preset thresholds s1 and s2 are set, and s1 is less than s2. If the real-time distance between the vehicle and the target is greater than s2, the minimum stable speed control algorithm is used to control the vehicle to obtain the first control data information of the vehicle.
[0086] U4. Based on the first control data information of the vehicle, if the real-time distance between the vehicle and the target is between s1 and s2, the vehicle deceleration control algorithm is used to control the vehicle to obtain the second control data information of the vehicle.
[0087] U5. Based on the second control data of the vehicle, if the real-time distance between the vehicle and the target is less than s1, then construct the maximum braking force control function G of the vehicle, control the vehicle, and obtain the parking position of the vehicle within the preset deviation range to complete the parking.
[0088] Among them, the preset thresholds s1 and s2 are,
[0089]
[0090]
[0091] Where (x0, y0) represents the target distance data.
[0092] In this embodiment, as Figure 3 As shown, in step U4, the vehicle deceleration control algorithm controls the vehicle by including:
[0093] U41. Based on the first control data information of the vehicle and the real-time distance data information between the vehicle and the target, obtain the current speed data information of the vehicle and the current distance data information between the vehicle and the target;
[0094] U42. Based on the vehicle's current speed data and the distance data between the vehicle and the target, establish the vehicle's deceleration control function W.
[0095]
[0096] Where s is the distance data between the current vehicle and the target, v1 is the current speed data of the vehicle, and δ and ω are the deceleration control factors of the vehicle.
[0097] U43. Based on the vehicle's deceleration control function W, the vehicle is controlled to obtain the vehicle's second control data information.
[0098] In this embodiment, in step U5, the maximum braking force control function G of the vehicle is,
[0099]
[0100] Where a is the distance between the vehicle and the target, and v2 is the initial speed data after the vehicle decelerates under the second control data information.
[0101] In this embodiment, the present invention also provides a precise parking system for a vehicle with a target distance input, including a computer device programmed or configured to perform the steps of any of the precise parking methods for a vehicle with a target distance input as described above.
[0102] In this embodiment, the present invention also provides a computer-readable storage medium storing a computer program programmed or configured to perform a precise parking method for a vehicle based on a target distance input as described in any one of the embodiments.
[0103] Any references to memory, storage, database, or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.
[0104] In summary, this invention not only solves the problem of precise vehicle parking and improves the efficiency of container operations, but also eliminates the need for manual intervention during precise vehicle parking, reducing labor costs and ensuring good stability, further improving the efficiency of task completion.
[0105] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.
Claims
1. A method for precise vehicle parking based on target distance input, characterized in that, The method includes: U1. When the vehicle travels to the target area, data on the target distance is obtained, and the vehicle's location data is obtained in real time based on the onboard laser odometer. U2. Based on the vehicle's location data and the target's distance data, a real-time distance function Q between the vehicle and the target is constructed to calculate the distance between the vehicle and the target, thereby obtaining the real-time distance data between the vehicle and the target; U3. Based on the real-time distance data between the vehicle and the target, preset thresholds s1 and s2 are set, and s1 is less than s2. If the real-time distance between the vehicle and the target is greater than s2, the minimum stable speed control algorithm is used to control the vehicle to obtain the first control data information of the vehicle. U4. Based on the first control data information of the vehicle, if the real-time distance between the vehicle and the target is between s1 and s2, the vehicle deceleration control algorithm is used to control the vehicle to obtain the second control data information of the vehicle. U5. Based on the second control data of the vehicle, if the real-time distance between the vehicle and the target is less than s1, then construct the maximum braking force control function G of the vehicle, control the vehicle, and obtain the parking position of the vehicle within the preset deviation range to complete the parking. In step U3, the minimum stable vehicle speed control algorithm controls the vehicle by including: U31. Based on the real-time distance data between the vehicle and the target, timestamps are calibrated and the data is divided into fixed time periods to obtain the divided real-time distance data between the vehicle and the target. U32. Based on the real-time distance data between the divided vehicles and the target, establish the minimum stable vehicle speed control function H. ， Wherein, s t is the real-time distance data information between the divided vehicle and the target, v0 is the initial speed data information of the vehicle, and β1 and β2 are speed control adjustment factors. U33. Based on the vehicle's minimum stable speed control function H, control the vehicle to obtain the vehicle's first control data information; In step U4, the vehicle deceleration control algorithm controls the vehicle by including: U41. Based on the first control data information of the vehicle and the real-time distance data information between the vehicle and the target, obtain the current speed data information of the vehicle and the current distance data information between the vehicle and the target; U42. Based on the vehicle's current speed data and the distance data between the vehicle and the target, establish the vehicle's deceleration control function W. ， Where s is the distance data between the current vehicle and the target, v1 is the current speed data of the vehicle, and δ and ω are the deceleration control factors of the vehicle. U43. Based on the vehicle's deceleration control function W, control the vehicle to obtain the vehicle's second control data information; In step U5, the maximum braking force control function G of the vehicle is, ， Where a is the distance between the vehicle and the target, and v2 is the initial speed data after the vehicle decelerates under the second control data information.
2. The precise vehicle parking method based on target distance input according to claim 1, characterized in that: The target distance data is the distance between the center point of the vehicle and the target location.
3. The precise vehicle parking method based on target distance input according to claim 1, characterized in that, In step U2, the distance function Q between the vehicle and the target is, ， wherein a1 and a2 are adaptability factors of the vehicle and the target, (x t ,y t ) is the position data information of the vehicle, and (x0, y0) is the data information of the target distance.
4. The precise vehicle parking method based on target distance input according to claim 3, characterized in that: The constraints on the vehicle's and target's adaptability factors α1 and α2 are as follows: ， The vehicle's adaptability factors α1 and α2 to the target are, ， ， Where (x0, y0) represents the target distance data.
5. The precise vehicle parking method based on target distance input according to claim 1, characterized in that: The constraints on the vehicle speed control adjustment factors β1 and β2 are as follows: ， The vehicle speed control adjustment factors β1 and β2 are, ， ， Where v0 represents the vehicle's initial speed data.
6. A vehicle precision parking system based on target distance input, comprising a computer device, characterized in that, The computer device is programmed or configured to perform the steps of the vehicle precision parking method based on the target distance input as described in any one of claims 1 to 5.
7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is programmed or configured to perform the vehicle precision parking method based on a target distance input as described in any one of claims 1 to 5.