An automatic parking method based on fixed path memory

Abstract

This invention discloses an automatic parking method based on fixed-path memory. Steps S1: The coordinates of the parking starting point are obtained through GPS or other means; S2: The user drives the vehicle to record the parking path; S3: The user approaches the parking starting point, activates automatic parking, and implements path deviation detection and obstacle detection. This method solves the problem of traditional automatic parking methods requiring the user to drive to the parking space, meets the needs of automatic parking in fixed scenarios, and requires relatively low hardware costs.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic parking, and in particular to an automatic parking method based on fixed path memory. Background Art

[0002] In recent years, with the gradual advancement of technology, cars, as a widely used means of transportation, have become increasingly intelligent and connected. However, due to the complexity of road conditions and the development of regulations, L4 automated parking is not yet practical. However, parking scenarios are relatively simple, mostly confined to a few fixed paths. Therefore, memory parking for fixed-path parking scenarios is increasingly becoming a cornerstone for the implementation of high-level intelligent driving. Summary of the Invention

[0003] The purpose of the present invention is to provide an automatic parking method based on fixed path memory to solve the problem that traditional automatic parking methods require the vehicle to drive to the vicinity of the parking space by itself.

[0004] To solve the above technical problems, the present invention provides a technical solution: an automatic parking method based on fixed path memory, comprising the following steps:

[0005] S1. Obtain the coordinates of the parking starting point;

[0006] S2. The user drives the vehicle to complete the parking path record;

[0007] S201, establishing a local coordinate system, using the parking starting point coordinate position as the origin of the local coordinate system;

[0008] S202: Obtain the vehicle's travel distance and heading angle change using the left and right wheel speed sensors on the rear axle, and then obtain the vehicle's coordinates relative to the parking starting point;

[0009] S203, obtaining the trajectory coordinates generated by the owner's parking process according to a set sampling method;

[0010] S204: After the owner completes parking, the trajectory coordinates are optimized and stored;

[0011] S3: The user approaches the parking starting point and starts automatic parking. The automatic parking process is as follows:

[0012] S301, draw a circle with the vehicle center as the center and the preset preview distance as the radius, use the coordinate position closest to the circle in the trajectory coordinates as the preview coordinate, use the current coordinate and the preview coordinate as input, and use the tracking algorithm to obtain the current required steering wheel angle;

[0013] S302: The vehicle drives according to the steering wheel angle output by the tracking algorithm, thereby completing automatic parking.

[0014] According to the above solution, the method for calculating the coordinates of the vehicle relative to the parking starting point in S202 is as follows:

[0015] Calculate the vehicle heading angle change per unit time, Δθ,

[0016]

[0017] Where ΔSum R ΔSum is the increase in wheel speed pulse count on the right side of the rear axle of the vehicle. L is the increase in wheel speed pulse count on the left side of the vehicle’s rear axle, l s is the distance traveled in a single pulse, l is the rear axle wheelbase;

[0018] The vehicle's front direction at the parking starting point is the positive direction of the X axis, and the left side of the vehicle is the positive direction of the Y axis. The vehicle's heading angle θ during parking is

[0019] θ=∫Δθdt

[0020] Where t is time;

[0021] The distance traveled by the vehicle per unit time Δl is,

[0022]

[0023] The coordinates of the vehicle relative to the starting point based on the change in heading angle Δθ and travel distance Δl per unit time.

[0024] According to the above solution, the sampling method set in S203 is specifically to increase the sampling density around the parking starting point, the end point, and the points where the heading angle change within a unit distance exceeds a certain angle.

[0025] According to the above solution, the tracking algorithm in S301 is specifically:

[0026] The vehicle is simplified into a bicycle model. In this model, the distance between the front wheel and the rear wheel is L. When the front wheel steering angle is δ, the rear wheel moves in a circle with a radius of R, so

[0027]

[0028] The preview coordinate is (g x ,g y ), the angle between the direction of the rear wheel of the vehicle and the line connecting the rear wheel and the preview coordinate is α, and the straight-line distance between the rear wheel and the preview coordinate is l d , the central angle of the arc between the rear wheel position and the preview coordinate is 2α, so

[0029]

[0030] According to the above formula, the steering wheel angle required for the vehicle to move to the preview coordinates is obtained.

[0031] According to the above scheme, the automatic parking process includes driving path verification, specifically,

[0032] The current coordinate position of the vehicle is A(x1,y1), and the two track coordinates closest to the current coordinate position of the vehicle are B(x2,y2) and C(x3,y3);

[0033] Then the following calculation is performed,

[0034]

[0035]

[0036]

[0037] Where D is the perpendicular distance between the vehicle's current position and the line connecting the two trajectory coordinate points mentioned above. When the value of D is greater than the preset value, the vehicle is controlled to stop automatic parking, the vehicle is shifted into P gear and the EPB is pulled up, and the owner is notified that the automatic parking failed.

[0038] According to the above scheme, the automatic parking process includes obstacle detection, specifically,

[0039] When the on-board radar detects an obstacle around the vehicle and the distance between the obstacle and the vehicle body is less than a certain value, automatic parking will be terminated; if the obstacle moves away within a certain period of time, automatic parking will continue, otherwise automatic parking will be stopped, the vehicle will be shifted into P gear and EPB will be pulled up, and the owner will be notified that automatic parking has failed.

[0040] An automatic parking device based on fixed path memory, comprising:

[0041] Positioning module, used to obtain the vehicle's starting coordinates;

[0042] A parking path recording and storage module is used to record, optimize and store the parking path when the owner performs manual parking;

[0043] The automatic parking module is used to perform automatic parking according to the stored parking path and complete path deviation detection.

[0044] The obstacle recognition module is used to identify obstacles around the vehicle and complete obstacle avoidance.

[0045] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the automatic parking method based on fixed path memory described above are implemented.

[0046] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the automatic parking method based on fixed path memory described above.

[0047] A car is provided with the above-mentioned automatic parking device based on fixed path memory.

[0048] The present invention has the following beneficial effects: a local coordinate system is established based on the parking starting point, and the vehicle's coordinate position at different moments during the manual parking process is obtained, thereby forming an automatic parking path. After the automatic parking function is enabled, the stored automatic parking path is read and a tracking algorithm is used to determine the steering wheel angle required for the vehicle to follow the automatic parking path, thereby completing automatic parking. This method solves the problem of traditional automatic parking methods requiring the vehicle to drive to the parking space, meets the needs of automatic parking in fixed scenarios, and has lower additional hardware costs compared to SLAM or LiDAR. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a schematic diagram of an automatic parking system according to an embodiment of the present invention;

[0050] Figure 2 、 Figure 3 is a schematic diagram of a tracking algorithm based on a bicycle model according to an embodiment of the present invention;

[0051] Figure 4 A schematic diagram of the configuration of a vehicle-mounted radar according to an embodiment of the present invention;

[0052] Figure 5 FIG. 1 is a schematic diagram of obstacle detection according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] To make the purpose, technical solutions, and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0054] An automatic parking method based on fixed path memory includes the following steps:

[0055] S1. Obtain the parking starting point coordinates through GPS positioning;

[0056] S2. The user drives the vehicle to record the parking path.

[0057] S201, establishing a local coordinate system, using the parking starting point coordinate position as the origin of the local coordinate system;

[0058] S202: Obtain the vehicle's travel distance and heading angle change using the left and right wheel speed sensors on the rear axle, and then obtain the vehicle's coordinates relative to the parking starting point;

[0059] S203, obtaining the trajectory coordinates generated by the owner's parking process according to a set sampling method;

[0060] S204: After the owner completes parking, the trajectory coordinates are optimized and stored;

[0061] S3: The user approaches the parking starting point and starts automatic parking. The automatic parking process is as follows:

[0062] S301, draw a circle with the vehicle center as the center and the preset preview distance as the radius, use the coordinate position closest to the circle in the trajectory coordinates as the preview coordinate, use the current coordinate and the preview coordinate as input, and use the tracking algorithm to obtain the current required steering wheel angle;

[0063] S302: The vehicle drives according to the steering wheel angle output by the tracking algorithm, thereby completing automatic parking.

[0064] Furthermore, the method for calculating the coordinates of the vehicle relative to the parking starting point in S202 is as follows:

[0065] Calculate the vehicle heading angle change per unit time, Δθ,

[0066]

[0067] Where ΔSum R ΔSum is the increase in wheel speed pulse count on the right side of the rear axle of the vehicle. L is the increase in wheel speed pulse count on the left side of the vehicle’s rear axle, l s is the distance traveled in a single pulse, l is the rear axle wheelbase;

[0068] The vehicle's front direction at the parking starting point is the positive direction of the X axis, and the left side of the vehicle is the positive direction of the Y axis. The vehicle's heading angle θ during parking is

[0069] θ=∫Δθdt

[0070] Where t is time;

[0071] The distance traveled by the vehicle per unit time Δl is,

[0072]

[0073] The coordinates of the vehicle relative to the starting point based on the change in heading angle Δθ and travel distance Δl per unit time.

[0074] Furthermore, the sampling method set in S203 is specifically to increase the sampling density around the parking starting point, the end point, and the point where the heading angle change within a unit distance exceeds a certain angle.

[0075] Furthermore, the tracking algorithm in S301 is specifically:

[0076] See also Figure 2 、 Figure 3 , simplify the vehicle into a bicycle model. In this model, the distance between the front wheel and the rear wheel is L. When the front wheel steering angle is δ, the rear wheel moves in a circle with a radius of R, so we have

[0077]

[0078] The preview coordinate is (g x ,g y ), the angle between the direction of the rear wheel of the vehicle and the line connecting the rear wheel and the preview coordinate is α, and the straight-line distance between the rear wheel and the preview coordinate is l d , the central angle of the arc between the rear wheel position and the preview coordinate is 2α, so

[0079]

[0080] According to the above formula, the steering wheel angle required for the vehicle to move to the preview coordinates is obtained.

[0081] Furthermore, the automatic parking process includes a driving path verification, specifically,

[0082] The current coordinate position of the vehicle is A(x1,y1), and the two track coordinates closest to the current coordinate position of the vehicle are B(x2,y2) and C(x3,y3);

[0083] Then the following calculation is performed,

[0084]

[0085]

[0086]

[0087] Where D is the perpendicular distance between the vehicle's current position and the line connecting the two trajectory coordinate points mentioned above. When the value of D is greater than the preset value, the vehicle is controlled to stop automatic parking, the vehicle is shifted into P gear and the EPB is pulled up, and the owner is notified that the automatic parking failed.

[0088] Furthermore, the automatic parking process includes obstacle detection, specifically,

[0089] When the on-board radar detects an obstacle around the vehicle and the distance between the obstacle and the vehicle body is less than a certain value, automatic parking will be terminated; if the obstacle moves away within a certain period of time, automatic parking will continue, otherwise automatic parking will be stopped, the vehicle will be shifted into P gear and EPB will be pulled up, and the owner will be notified that automatic parking has failed.

[0090] The radar setting scheme in this embodiment can be found in Figure 4 , through 12 radars (4 in the front, 4 in the rear, and 2 on each side) to monitor nearby obstacles in real time. First, according to the calibration, the distance data from the obstacle to the radar installation position is calibrated. Among them, the coordinate information of the obstacle in the vehicle body coordinate system is determined directly based on the distance data fed back by the two radars and the positional relationship between the two radar installation positions. For example Figure 5 For the obstacle represented by the black box, the distance data obtained by the vehicle's radar No. 4 is L4 = 2*a; the distance data obtained by the ultrasonic wave No. 5 is L5 = a + b. Using the simultaneous equations, we can obtain the values ​​of a and b. Based on the position and orientation of radars No. 4 and No. 5, we can determine the obstacle's coordinates. On the side of the vehicle, due to the limited number of radars and their limited detection range, obstacle records are used to predict the obstacle's position. This solution uses a radar on each side of the vehicle, both at the front and rear, to detect obstacles, while the center area is undetectable. When an obstacle appears within the range of the front radar, its hazard to the vehicle is determined based on its distance to the side. When it leaves the front radar's range, its coordinates relative to the vehicle's coordinate system are determined based on its distance to the front radar and the geometry of the front radar's detection range. The obstacle's coordinates are then updated in real time using the vehicle's local coordinate system calculation scheme, ensuring lateral safety. When a recorded obstacle is too close to the vehicle, the vehicle pauses and a timer is set. Once the vehicle detects that the obstacle has left, it will continue to drive. If a certain time has passed and the obstacle is still there, the vehicle will shift into P gear, engage EPB, and notify the driver via the mobile phone APP that parking has failed and ask him to take over the vehicle.

[0091] An automatic parking device with fixed path memory, comprising:

[0092] Positioning module, used to obtain the vehicle's starting coordinates;

[0093] A parking path recording and storage module is used to record, optimize and store the parking path when the owner performs manual parking;

[0094] The automatic parking module is used to perform automatic parking according to the stored parking path and complete path deviation detection.

[0095] The obstacle recognition module is used to identify obstacles around the vehicle and complete obstacle avoidance.

[0096] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the automatic parking method based on fixed path memory described above are implemented.

[0097] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the automatic parking method based on fixed path memory described above.

[0098] A car is provided with the above-mentioned automatic parking device based on fixed path memory.

[0099] The automatic parking system used in this embodiment can be found in Figure 1 The vehicle includes a LAPA controller, an ESC controller (including EPB function), an EMS controller, a TCU controller, an EPS controller, a BCM controller, a GW, a TBOX, and sensing components such as ultrasonic radar and cameras. Among them, ESC acts as an intermediary for the output of LAPA torque instructions, is responsible for calculating the torque at low speeds, and then outputs it to the EMS to achieve torque control. The instrument / MP5 is a component that interacts with the user, completing functions such as enabling and disabling, path selection, and recording. EPS is a component that implements the lateral steering wheel angle instruction of LAPA. Ultrasonic radars and cameras are used to sense obstacles and identify parking lines. BCM and others are used to detect the vehicle status and ensure the safety of function activation.

[0100] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An automatic parking method based on fixed path memory, characterized by: The following steps are included: S1. Obtain the coordinates of the parking starting point; S2. The user drives the vehicle to record the parking path; specifically, S201, establishing a local coordinate system, using the parking starting point coordinate position as the origin of the local coordinate system; S202: Obtain the vehicle's travel distance and heading angle change using the left and right wheel speed sensors on the rear axle, and then obtain the vehicle's coordinates relative to the parking starting point; S203, obtaining the trajectory coordinates generated by the owner's parking process according to a set sampling method; S204: After the owner completes parking, the track coordinates are stored; S3: The user approaches the parking starting point and starts automatic parking. The automatic parking process is as follows: S301, draw a circle with the vehicle center as the center and the preset preview distance as the radius, use the coordinate position closest to the circle in the trajectory coordinates as the preview coordinate, use the current coordinate and the preview coordinate as input, and use the tracking algorithm to obtain the current required steering wheel angle; S302: The vehicle drives according to the steering wheel angle output by the tracking algorithm, and then performs automatic parking; The tracking algorithm in S301 is specifically: The vehicle is simplified into a bicycle model. In this model, the distance between the front wheel and the rear wheel is L. When the front wheel steering angle is δ, the rear wheel moves in a circle with a radius of R, so The preview coordinates are (g x , g y ), the angle between the direction of the rear wheel of the vehicle and the line connecting the rear wheel and the preview coordinate is α, and the straight-line distance between the rear wheel and the preview coordinate is l d , the central angle of the arc between the rear wheel position and the preview coordinate is 2α, so According to the above formula, the steering wheel angle required for the vehicle to move to the preview coordinates is obtained.

2. The automatic parking method based on fixed path memory according to claim 1, characterized in that: The method for calculating the coordinates of the vehicle relative to the parking starting point in S202 is as follows: Calculate the vehicle heading angle change per unit time, Δθ, Where ΔSum R ΔSum is the increase in wheel speed pulse count on the right side of the rear axle of the vehicle. L is the increase in wheel speed pulse count on the left side of the vehicle’s rear axle, l s is the distance traveled in a single pulse, l is the rear axle wheelbase; The vehicle's front direction at the parking starting point is the positive direction of the X axis, and the left side of the vehicle is the positive direction of the Y axis. The vehicle's heading angle θ during parking is θ = ∫Δθdt Where t is time; The distance traveled by the vehicle per unit time Δl is, The coordinates of the vehicle relative to the starting point based on the change in heading angle Δθ and travel distance Δl per unit time.

3. The automatic parking method based on fixed path memory according to claim 1, characterized in that: The sampling method set in S203 is specifically to increase the sampling density around the parking starting point, the end point, and the point where the heading angle change within a unit distance exceeds a certain angle.

4. The automatic parking method based on fixed path memory according to claim 1, characterized in that: The automatic parking process includes driving path verification, specifically, The current coordinate position of the vehicle is A(x1, y1), and the two track coordinates closest to the current coordinate position of the vehicle are B(x2, y2) and C(x3, y3); Then the following calculation is performed, Where D is the perpendicular distance between the vehicle's current position and the line connecting the two trajectory coordinate points mentioned above. When the value of D is greater than the preset value, the vehicle is controlled to stop automatic parking, the vehicle is shifted into P gear and the EPB is pulled up, and the owner is notified that the automatic parking failed.

5. The automatic parking method based on fixed path memory according to claim 1, characterized in that: The automatic parking process includes obstacle detection, specifically, When the on-board radar detects an obstacle around the vehicle and the distance between the obstacle and the vehicle body is less than a certain value, automatic parking will be terminated; if the obstacle moves away within a certain period of time, automatic parking will continue, otherwise automatic parking will be stopped, the vehicle will be shifted into P gear and EPB will be pulled up, and the owner will be notified that automatic parking has failed.

6. An automatic parking device based on fixed path memory for implementing the automatic parking method based on fixed path memory according to any one of claims 1 to 5, characterized in that: include, Positioning module, used to obtain the vehicle's starting coordinates; A parking path recording and storage module is used to record, optimize and store the parking path when the owner performs manual parking; Automatic parking module, used to automatically park according to the stored parking path and complete path deviation detection; The obstacle recognition module is used to identify obstacles around the vehicle and complete obstacle avoidance.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the automatic parking method based on fixed path memory according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the automatic parking method based on fixed path memory according to any one of claims 1 to 5 are implemented.

9. An automobile, characterized in that: It has an automatic parking device based on fixed route memory as claimed in claim 6.

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