A vehicle turn control method that autonomously changes a radar detection area

Abstract

This invention provides a vehicle turning control method that autonomously changes the radar detection area. It utilizes a vehicle dynamics simulation test analysis model to obtain turning trajectories under different turning conditions, constructing a turning angle-turning blind zone-radar detection angle model. Based on this model, the radar detection angle is obtained by simulating and adjusting radar parameters and installation position, achieving real-time dynamic full-domain monitoring of the blind zone under different turning conditions, thereby obtaining a matching trajectory of inner wheel difference-radar detection angle. A strategy execution module is established, which obtains the vehicle type, the radar detection angle Φ at the moment before turning, and the real-time inner wheel difference ΔR. Based on a standard database module, the vehicle decision data is output through the strategy execution method, including the radar rotation angle Ω.

Description

Technical Field

[0001] This invention relates to the technical field of vehicle turning control methods, and more specifically, to a vehicle turning control method that autonomously changes the radar detection area. Background Technology

[0002] When large vehicles turn, they need to observe their surroundings to turn while avoiding collisions with people or objects. Now, by installing radar detection systems on the vehicles, they can observe their surroundings while turning and thus guide the driver.

[0003] In traditional vehicle radar detection systems, the radar is installed at a fixed angle. Therefore, when a vehicle turns due to the influence of the surrounding environment, the turning angle will vary, which will cause the radar detection range to change. Consequently, when turning in different road conditions, the radar cannot monitor blind spots in real time, resulting in blind spots.

[0004] Therefore, how to dynamically monitor blind spots in real time and across the entire area when vehicles turn in different environments, and avoid the generation of blind spots, has become a problem that urgently needs to be solved in this field. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a vehicle turning control method that autonomously changes the radar detection area. The method obtains the vehicle type, the radar detection angle Φ just before turning, and the real-time inner wheel difference ΔR through the strategy execution module. Based on the standard database module, the method outputs vehicle decision data through the strategy execution method, enabling the radar to rotate at a certain angle to achieve real-time dynamic monitoring of the blind spot and avoid the generation of blind spots.

[0006] One aspect of the present invention provides a vehicle turning control method that autonomously changes the radar detection area, and an adaptive cruise control method based on deep reinforcement learning, the method comprising:

[0007] By using the turning trajectory obtained from the vehicle dynamics simulation test analysis model under different turning conditions, a turning angle-turning blind spot-radar detection angle model is constructed. Based on the turning angle-turning blind spot-radar detection angle model, the radar detection angle is obtained by simulating and adjusting the radar parameters and installation position. Real-time dynamic full-domain monitoring of the blind spot under different turning conditions is realized, thereby obtaining the inner wheel difference-radar detection angle matching trajectory.

[0008] A pre-set database of inner wheel difference-radar detection angle matching data, including vehicle cornering performance data, is provided.

[0009] A pre-defined database of basic vehicle information is established; vehicles are then categorized based on this database.

[0010] Establish a standard database module, which includes a pre-learning standard database;

[0011] A pre-learning standard database is established based on the vehicle turning angle-radar detection angle matching database and the driving vehicle category;

[0012] A data processing module is established based on the principle of inner wheel difference, and the real-time inner wheel difference during turning is obtained through the data processing module.

[0013] A strategy execution module is established, which acquires the vehicle type, the radar detection angle Φ just before turning, and the real-time inner wheel difference ΔR. Based on the standard database module, the strategy execution method outputs vehicle decision data, which includes the radar rotation angle Ω.

[0014] A dynamic simulation test analysis model was established by combining the control model of the large vehicle turning blind spot warning system with PC-Crash and PreScan software. The dynamic simulation test analysis model includes the steering wheel angle, inner wheel difference, radar detection angle parameters, and their interrelationships under the vehicle turning driving conditions.

[0015] First, the inner wheel difference of the vehicle when turning at different angles is simulated and analyzed using PC-Crash software, and the turning blind zone corresponding to different turning angles is determined through simulation data analysis. Then, PreScan simulation is used to determine the radar detection angle required for the turning blind zone under different turning angles, and a turning angle-turning blind zone-radar detection angle model is obtained to realize a real-time response intelligent warning scheme. Finally, the radar parameters and the installation position of the turning angle sensor are determined to obtain the radar detection angle installed on the vehicle.

[0016] SPSS regression analysis was used to obtain the model equations for turning radius and inner wheel difference, resulting in an inner wheel difference-radar turning angle matching database.

[0017] Compared with the prior art, the present invention has the following beneficial effects: by establishing a matching database of inner wheel difference and radar angle of vehicle cornering performance data, a data set matching the inner wheel difference of the vehicle and the radar detection angle is realized under different cornering conditions when full-area detection of blind spots is achieved; by classifying vehicles according to the vehicle basic information database, more accurate guidance on the radar detection angle of the vehicle is achieved.

[0018] The standard database module includes a pre-learning standard database, thereby enabling the establishment of inner wheel difference level databases for different types of vehicles and their corresponding output radar detection angle databases.

[0019] The data processing module obtains different real-time inner wheel differences based on different turning conditions.

[0020] By establishing a strategy execution module, the module obtains the vehicle type and the real-time inner wheel difference ΔR, and then obtains the real-time radar detection angle of the vehicle. By comparing it with the radar detection angle of the previous moment, the module outputs the radar rotation angle. This enables the adjustment of different radar detection angles under different turning conditions, thereby achieving real-time dynamic monitoring of blind spots and avoiding the generation of blind spots.

[0021] Furthermore, the vehicle cornering performance data includes: inner wheel difference ΔR, radar detection angle γ, and vehicle length d.

[0022] Furthermore, the vehicle basic information database includes the vehicle's wheelbase L and front wheel track b. R Rear wheel track b F Vehicle length d; and / or,

[0023] The vehicle basic information database also includes a vehicle classification method, which classifies vehicles into first-class vehicles, second-class vehicles, and third-class vehicles according to their length.

[0024] The vehicle classification method is as follows:

[0025] Vehicles with a length d less than 6 meters are classified as Class I vehicles.

[0026] Vehicles with a length d greater than or equal to 6 meters and less than or equal to 12 meters are classified as Class II vehicles.

[0027] Vehicles with a length d greater than 12 meters are classified as Class III vehicles.

[0028] The advantages of adopting the technical solution in the previous step are that it pre-establishes an inner wheel difference-radar detection angle matching database and classifies vehicles.

[0029] Furthermore, a pre-learning standard database is established based on the inner wheel difference-radar turning angle matching trajectory and the driving vehicle category. The specific method includes the following steps: the pre-learning standard database includes an inner wheel difference level database and an output radar detection angle database.

[0030] The inner wheel difference level database includes a first type of vehicle inner wheel difference level database, a second type of vehicle inner wheel level database, and a third type of vehicle inner wheel level database; the output radar detection angle database includes a first type of vehicle output radar detection angle database, a second type of vehicle output radar detection angle database, and a third type of vehicle output radar detection angle database.

[0031] The first type of vehicle inner wheel difference level database includes the length d range of the first type of vehicle and the inner wheel difference range of the first type of vehicle from level 1 to 360; the second type of vehicle inner wheel difference level database includes the length d range of the second type of vehicle and the inner wheel difference range of the second type of vehicle from level 1 to 360; and the third type of vehicle inner wheel difference level database includes the length d range of the third type of vehicle and the inner wheel difference range of the third type of vehicle from level 1 to 360.

[0032] The database of output radar detection angles for Category I vehicles includes the output radar detection angles corresponding to the inner wheel difference ranges of various classes of Category I vehicles.

[0033] The database of output radar detection angles for Category II vehicles includes the output radar detection angles corresponding to the inner wheel difference range of each class of Category II vehicles.

[0034] The database of output radar detection angles for Category III vehicles includes the output radar detection angles corresponding to the inner wheel difference range of each class of Category III vehicles.

[0035] Furthermore, the ΔR and corresponding radar detection angle γ of each vehicle turning angle-radar detection angle matching trajectory for the three types of vehicles during the turning condition are extracted respectively; the inner wheel difference of each type of vehicle is divided into 1-360 levels, and the difference of the inner wheel difference range of each level is E.

[0036] The specific method for determining the range of inner wheel difference levels for each type of vehicle is as follows:

[0037] Extract ΔR and the corresponding radar detection angle γ from the turning condition in the matching trajectory of each type of vehicle turning angle and radar detection angle.

[0038] The value of E for each vehicle type is obtained by extracting the difference between the maximum and minimum values ​​of ΔR from the matching trajectory of the turning angle and radar detection angle of each vehicle type and dividing it by 360; thus, the inner wheel difference range of each vehicle type from level 1 to 360 is obtained.

[0039] The ΔR of the matching trajectory between the turning angle and the radar detection angle of each type of vehicle is extracted and distributed into a range of 1-360 levels;

[0040] Obtain the radar detection angle γ corresponding to ΔR in the inner wheel difference range of each vehicle class;

[0041] The output radar detection angle corresponding to the inner wheel difference range of each type of vehicle at each level for:

[0042]

[0043] γ′ is the average value of the radar detection angle γ corresponding to ΔR within the inner wheel difference range of each vehicle class; β is a coefficient.

[0044] The beneficial effect of adopting the technical solution in the previous step is that it enables the classification of the inner wheel difference of different types of vehicles under different turning conditions, and assigns different output radar detection angles to different levels of inner wheel difference, thereby realizing the establishment of a pre-learning standard database.

[0045] Through formula This means that the output radar detection angle corresponding to different inner wheel differences can be obtained, and the coefficient β helps to eliminate the impact of human error during operation.

[0046] Furthermore, the data processing module obtains the vehicle's wheelbase L and front wheel track b based on the vehicle basic information database. R Rear wheel track b F And obtain the real-time steering wheel angle S1 when the vehicle turns;

[0047] The data processing module includes an inner wheel difference calculation formula, which is used to calculate the real-time inner wheel difference. The inner wheel difference calculation formula is as follows:

[0048] ΔR=R1-R3

[0049]

[0050]

[0051] The advantage of adopting the technical solution in the previous step is that it enables the real-time inner wheel difference of the vehicle under different turning conditions.

[0052] Furthermore, the strategy execution module compares the acquired real-time inner wheel difference ΔR, the radar detection angle Φ just before turning, and the vehicle category with the standard database module to obtain the vehicle category and the real-time output radar detection angle corresponding to the real-time inner wheel difference ΔR. The radar rotation angle Ω is calculated using the radar rotation angle formula.

[0053] The formula for the radar rotation angle is:

[0054]

[0055] The advantage of adopting the technical solution in the previous step is that it enables the obtaining of the radar rotation angle corresponding to the vehicle's real-time turning when different turning conditions are obtained.

[0056] Furthermore, the strategy execution module also includes an emergency processing module, which obtains the real-time inner wheel difference ΔR of the vehicle through the data processing module;

[0057] When the real-time inner wheel difference ΔR is obtained within 0.5s, β = 1 - 1.02 in the standard database module;

[0058] When two or more real-time inner wheel difference ΔRs are acquired within 0.5 seconds, and the second ΔR is greater than or equal to the first ΔR, the second and subsequent ΔRs within 0.5 seconds are compared with the standard database module to output the radar detection angle. At that time, β = 1 - 1.02 in the standard database module;

[0059] When two or more real-time inner wheel difference ΔRs are acquired within 0.5 seconds, and the second ΔR is less than or equal to the first ΔR, the second and subsequent ΔRs within 0.5 seconds are compared with the standard database module to output the radar detection angle. At that time, β = 1.05-1.1 in the standard database module.

[0060] The advantage of adopting the technical solution in the previous step is that it avoids the misoperation or improper operation of the driver when the vehicle is turning, which could cause the radar detection angle to change.

[0061] Furthermore, the standard database module includes a lateral acceleration standard database, which includes a lateral acceleration standard level database and an output acceleration database.

[0062] Furthermore, the emergency response module acquires the real-time vehicle-side acceleration a. y ;

[0063] When the real-time vehicle side acceleration a is obtained y When the force is ≤0.4g (g is the acceleration due to gravity), the output a = 0;

[0064] When the real-time vehicle side acceleration a is obtained y When the value is greater than 0.4g (where g is the acceleration due to gravity), the output a < 0.

[0065] The beneficial effect of adopting the technical solution in the previous step is that by controlling the lateral acceleration when the vehicle is turning, it avoids the phenomenon of the vehicle overturning when turning, and at the same time, it helps to avoid the radar rotation angle adjustment not being timely due to too sharp a turn, thus avoiding incorrect guidance. Detailed Implementation

[0066] To make the objectives, technical solutions and advantages of the present invention clearer, the various aspects of the present invention will be described in detail below with reference to specific embodiments. However, these specific embodiments are only used to illustrate the present invention and do not constitute any limitation on the scope of protection and the substantive content of the present invention.

[0067] Example 1

[0068] This embodiment provides a vehicle turning control method that autonomously changes the radar detection area, the method including the following steps:

[0069] By using the turning trajectory obtained from the vehicle dynamics simulation test analysis model under different turning conditions, a turning angle-turning blind spot-radar detection angle model is constructed. Based on the turning angle-turning blind spot-radar detection angle model, the radar detection angle is obtained by simulating and adjusting the radar parameters and installation position. Real-time dynamic full-domain monitoring of the blind spot under different turning conditions is realized, thereby obtaining the inner wheel difference-radar detection angle matching trajectory.

[0070] Dynamics were established using a control model combining PC-Crash and PreScan software with a large vehicle turning blind spot warning system.

[0071] The simulation test analysis model and the dynamic simulation test analysis model include the steering wheel angle, inner wheel difference, radar detection angle parameters, and their interrelationships under the vehicle turning driving condition;

[0072] First, the inner wheel difference of the vehicle when turning at different angles is simulated and analyzed using PC-Crash software, and the turning blind zone corresponding to different turning angles is determined through simulation data analysis. Then, PreScan simulation is used to determine the radar detection angle required for the turning blind zone under different turning angles, and a turning angle-turning blind zone-radar detection angle model is obtained to realize a real-time response intelligent warning scheme. Finally, the radar parameters and the installation position of the turning angle sensor are determined to obtain the radar detection angle installed on the vehicle.

[0073] Inner wheel difference data for different turning radii were obtained through simulation:

[0074]

[0075] Inner wheel difference data for different turning radii

[0076] The model equations for turning radius and inner wheel difference were obtained using SPSS regression analysis, resulting in an inner wheel difference-radar turning angle matching database. The model equations for turning radius and inner wheel difference are as follows: y = 35.09x -0.986 R 2 =0.9936.

[0077] A preset database of inner wheel difference-radar detection angle matching data is included, which includes vehicle cornering performance data. The vehicle cornering performance data includes: inner wheel difference ΔR, radar detection angle γ, and vehicle length d.

[0078] A pre-defined database of basic vehicle information is established; vehicles are then categorized based on this database.

[0079] The vehicle basic information database includes the vehicle's wheelbase L and front track width b.R Rear wheel track b F Vehicle length d;

[0080] The vehicle basic information database also includes a vehicle classification method, which classifies vehicles into first-class vehicles, second-class vehicles, and third-class vehicles according to their length.

[0081] The vehicle classification method is as follows:

[0082] Vehicles with a length d less than 6 meters are classified as Class I vehicles.

[0083] Vehicles with a length d greater than or equal to 6 meters and less than or equal to 12 meters are classified as Class II vehicles.

[0084] Vehicles with a length d greater than 12 meters are classified as Class III vehicles.

[0085] Establish a standard database module, which includes a pre-learning standard database;

[0086] A pre-learning standard database is established based on the vehicle turning angle-radar detection angle matching database and the driving vehicle category;

[0087] A pre-learning standard database is established based on the inner wheel difference-radar turning angle matching trajectory and the driving vehicle category. The specific method includes the following steps: the pre-learning standard database includes an inner wheel difference level database and an output radar detection angle database.

[0088] The inner wheel difference level database includes a first type of vehicle inner wheel difference level database, a second type of vehicle inner wheel level database, and a third type of vehicle inner wheel level database; the output radar detection angle database includes a first type of vehicle output radar detection angle database, a second type of vehicle output radar detection angle database, and a third type of vehicle output radar detection angle database.

[0089] The first type of vehicle inner wheel difference level database includes the length d range of the first type of vehicle and the inner wheel difference range of the first type of vehicle from level 1 to 360; the second type of vehicle inner wheel difference level database includes the length d range of the second type of vehicle and the inner wheel difference range of the second type of vehicle from level 1 to 360; and the third type of vehicle inner wheel difference level database includes the length d range of the third type of vehicle and the inner wheel difference range of the third type of vehicle from level 1 to 360.

[0090] The database of output radar detection angles for Category I vehicles includes the output radar detection angles corresponding to the inner wheel difference ranges of various classes of Category I vehicles.

[0091] The database of output radar detection angles for Category II vehicles includes the output radar detection angles corresponding to the inner wheel difference range of each class of Category II vehicles.

[0092] The database of output radar detection angles for Category III vehicles includes the output radar detection angles corresponding to the inner wheel difference range of each class of Category III vehicles.

[0093] ΔR and the corresponding radar detection angle γ are extracted for each vehicle turning angle-radar detection angle matching trajectory of the three types of vehicles when turning; the inner wheel difference of each type of vehicle is divided into 1-360 levels, and the difference of the inner wheel difference range of each level is E.

[0094] The specific method for determining the range of inner wheel difference levels for each type of vehicle is as follows:

[0095] Extract ΔR and the corresponding radar detection angle γ from the turning condition in the matching trajectory of each type of vehicle turning angle and radar detection angle.

[0096] The value of E for each vehicle type is obtained by extracting the difference between the maximum and minimum values ​​of ΔR from the matching trajectory of the turning angle and radar detection angle of each vehicle type and dividing it by 360; thus, the inner wheel difference range of each vehicle type from level 1 to 360 is obtained.

[0097] The ΔR of the matching trajectory between the turning angle and the radar detection angle of each type of vehicle is extracted and distributed into a range of 1-360 levels;

[0098] Obtain the radar detection angle γ corresponding to ΔR in the inner wheel difference range of each vehicle class;

[0099] The output radar detection angle corresponding to the inner wheel difference range of each type of vehicle at each level for:

[0100] γ′ is the average value of the radar detection angle γ corresponding to ΔR within the inner wheel difference range of each vehicle class; β is a coefficient.

[0101] A data processing module is established based on the principle of inner wheel difference. The real-time inner wheel difference during turning is obtained through the data processing module. The data processing module obtains the vehicle's wheelbase L, front wheel track bR, and rear wheel track bF based on the vehicle's basic information database, as well as the real-time steering wheel angle S1 when the vehicle is turning.

[0102] The data processing module includes an inner wheel difference calculation formula, which is used to calculate the real-time inner wheel difference.

[0103] The formula for calculating the inner wheel difference is as follows:

[0104] ΔR=R1-R3

[0105]

[0106]

[0107] A strategy execution module is established, which acquires the vehicle type, the radar detection angle Φ just before turning, and the real-time inner wheel difference ΔR. Based on the standard database module, the strategy execution method outputs vehicle decision data, which includes the radar rotation angle Ω.

[0108] The strategy execution module compares the acquired real-time inner wheel difference ΔR, the radar detection angle Φ just before the turn, and the vehicle type with the standard database module to obtain the vehicle type and the real-time output radar detection angle corresponding to the real-time inner wheel difference ΔR. The radar rotation angle Ω is calculated using the radar rotation angle formula.

[0109] The formula for the radar rotation angle is:

[0110] Example 2

[0111] The content that is the same as in Example 1 will not be repeated here; the differences between this embodiment and Example 1 are as follows:

[0112] This embodiment provides a vehicle turning control method that autonomously changes the radar detection area, and further includes the following steps:

[0113] The strategy execution module also includes an emergency processing module, which obtains the real-time inner wheel difference ΔR of the vehicle through the data processing module.

[0114] When the real-time inner wheel difference ΔR is obtained within 0.5s, β = 1 - 1.02 in the standard database module;

[0115] When two or more real-time inner wheel difference ΔRs are acquired within 0.5 seconds, and the second ΔR is greater than or equal to the first ΔR, the second and subsequent ΔRs within 0.5 seconds are compared with the standard database module to output the radar detection angle. At that time, β = 1 - 1.02 in the standard database module;

[0116] When two or more real-time inner wheel difference ΔRs are acquired within 0.5 seconds, and the second ΔR is less than or equal to the first ΔR, the second and subsequent ΔRs within 0.5 seconds are compared with the standard database module to output the radar detection angle. At that time, β = 1.05-1.1 in the standard database module.

[0117] The standard database module includes a lateral acceleration standard database, which in turn includes a lateral acceleration standard level database and an output acceleration database.

[0118] The emergency response module acquires the real-time vehicle-side acceleration ay;

[0119] When the real-time vehicle side acceleration a is obtained y When the force is ≤0.4g (g is the acceleration due to gravity), the output a = 0;

[0120] When the real-time vehicle side acceleration a is obtained y When the value is greater than 0.4g (where g is the acceleration due to gravity), the output a < 0.

[0121] The present invention has been described above with reference to specific embodiments. These specific embodiments are merely exemplary and should not be construed as limiting the scope of protection of the present invention. Those skilled in the art can make various modifications, changes, or substitutions without departing from the essence of the present invention. Therefore, various equivalent variations made according to the present invention still fall within the scope of the present invention.

Claims

1. A vehicle turning control method that autonomously changes the radar detection area, characterized in that, The method includes: By using the turning trajectory obtained from the vehicle dynamics simulation test analysis model under different turning conditions, a turning angle-turning blind spot-radar detection angle model is constructed. Based on the turning angle-turning blind spot-radar detection angle model, the radar detection angle is obtained by simulating and adjusting the radar parameters and installation position. Real-time dynamic full-domain monitoring of the blind spot under different turning conditions is realized, thereby obtaining the inner wheel difference-radar detection angle matching trajectory. A pre-set database of inner wheel difference-radar detection angle matching data, including vehicle cornering performance data, is provided. A pre-defined database of basic vehicle information is established; vehicles are then categorized based on this database. Establish a standard database module, which includes a pre-learning standard database; A pre-learning standard database is established based on the vehicle turning angle-radar detection angle matching database and the driving vehicle category; A data processing module is established based on the principle of inner wheel difference, and the real-time inner wheel difference during turning is obtained through the data processing module. A strategy execution module is established, which acquires the vehicle type, the radar detection angle Φ just before turning, and the real-time inner wheel difference ΔR. Based on the standard database module, the strategy execution method outputs vehicle decision data, which includes the radar rotation angle Ω.

2. The vehicle turning control method for autonomously changing the radar detection area according to claim 1, characterized in that, The vehicle cornering performance data includes: inner wheel difference ΔR, radar detection angle γ, and vehicle length d.

3. The vehicle turning control method for autonomously changing the radar detection area according to claim 1, characterized in that, The vehicle basic information database includes wheel base L, front wheel track b R , rear wheel track b F , and vehicle length d of the vehicle. and / or The vehicle basic information database also includes a vehicle classification method, which classifies vehicles into first-class vehicles, second-class vehicles, and third-class vehicles according to their length. The vehicle classification method is as follows: Vehicles with a length d less than 6 meters are classified as Class I vehicles. Vehicles with a length d greater than or equal to 6 meters and less than or equal to 12 meters are classified as Class II vehicles. Vehicles with a length d greater than 12 meters are classified as Class III vehicles.

4. The vehicle turning control method for autonomously changing the radar detection area according to claim 3, characterized in that, A pre-learning standard database is established based on the inner wheel difference-radar turning angle matching trajectory and the vehicle category. The specific method includes the following steps: the pre-learning standard database includes an inner wheel difference level database and an output radar detection angle database; the inner wheel difference level database includes a first type of vehicle inner wheel difference level database, a second type of vehicle inner wheel level database, and a third type of vehicle inner wheel level database; the output radar detection angle database includes a first type of vehicle output radar detection angle database, a second type of vehicle output radar detection angle database, and a third type of vehicle output radar detection angle database. The first type of vehicle inner wheel difference level database includes the length d range of the first type of vehicle and the inner wheel difference range of the first type of vehicle from level 1 to 360; the second type of vehicle inner wheel difference level database includes the length d range of the second type of vehicle and the inner wheel difference range of the second type of vehicle from level 1 to 360; and the third type of vehicle inner wheel difference level database includes the length d range of the third type of vehicle and the inner wheel difference range of the third type of vehicle from level 1 to 360. The database of output radar detection angles for Category I vehicles includes the output radar detection angles corresponding to the inner wheel difference ranges of various classes of Category I vehicles. The database of output radar detection angles for Category II vehicles includes the output radar detection angles corresponding to the inner wheel difference range of each class of Category II vehicles. The database of output radar detection angles for Category III vehicles includes the output radar detection angles corresponding to the inner wheel difference range of each class of Category III vehicles.

5. The vehicle turning control method for autonomously changing the radar detection area according to claim 4, characterized in that, ΔR and the corresponding radar detection angle γ are extracted for each vehicle turning angle-radar detection angle matching trajectory of the three types of vehicles when turning; the inner wheel difference of each type of vehicle is divided into 1-360 levels, and the difference of the inner wheel difference range of each level is E. The specific method for determining the range of inner wheel difference levels for each type of vehicle is as follows: Extract ΔR and the corresponding radar detection angle γ from the turning condition in the matching trajectory of each type of vehicle turning angle and radar detection angle. E for each type of vehicle is obtained by extracting the difference between the maximum and minimum values ​​of ΔR in the matching trajectory of the turning angle and radar detection angle of each type of vehicle and dividing it by 360; thus, the inner wheel difference range of each type of vehicle from level 1 to 360 is obtained. The ΔR of the matching trajectory between the turning angle and the radar detection angle of each type of vehicle is extracted and distributed into a range of 1-360 levels; Obtain the radar detection angle γ corresponding to ΔR in the inner wheel difference range of each vehicle class; The output radar detection angle corresponding to the inner wheel difference range of each type of vehicle and each level for: γ′ is the average value of the radar detection angle γ corresponding to ΔR within the inner wheel difference range of each vehicle class; β is a coefficient.

6. The vehicle turning control method for autonomously changing the radar detection area according to claim 3, characterized in that, The data processing module obtains the wheelbase L, the front wheel track b R , the rear wheel track b F of the vehicle based on a vehicle basic information database, and obtains a real-time steering wheel rotation angle S1 of the vehicle when turning. The data processing module includes an inner wheel difference calculation formula, which is used to calculate the real-time inner wheel difference. The formula for calculating the inner wheel difference is as follows: ΔR=R1-R3 7. The vehicle turning control method for autonomously changing the radar detection area according to claim 5, characterized in that, The strategy execution module compares the acquired real-time inner wheel difference ΔR, the radar detection angle Φ just before the turn, and the vehicle type with the standard database module to obtain the vehicle type and the real-time output radar detection angle corresponding to the real-time inner wheel difference ΔR. The radar rotation angle Ω is calculated using the radar rotation angle formula. The formula for the radar rotation angle is:

8. The vehicle turning control method for autonomously changing the radar detection area according to claim 4, characterized in that, The strategy execution module also includes an emergency processing module, which obtains the real-time inner wheel difference ΔR of the vehicle through the data processing module. When the real-time inner wheel difference ΔR is obtained within 0.5s, β = 1 - 1.02 in the standard database module; When two or more real-time inner wheel difference ΔRs are acquired within 0.5 seconds, and the second ΔR is greater than or equal to the first ΔR, the second and subsequent ΔRs within 0.5 seconds are compared with the standard database module to output the radar detection angle. At that time, β = 1 - 1.02 in the standard database module; When two or more real-time inner wheel difference ΔRs are acquired within 0.5 seconds, and the second ΔR is less than or equal to the first ΔR, the second and subsequent ΔRs within 0.5 seconds are compared with the standard database module to output the radar detection angle. At that time, β = 1.05-1.1 in the standard database module.

9. The vehicle turning control method for autonomously changing the radar detection area according to claim 8, characterized in that, The standard database module includes a lateral acceleration standard database, which in turn includes a lateral acceleration standard level database and an output acceleration database.

10. The vehicle turning control method for autonomously changing the radar detection area according to claim 8, characterized in that, The emergency response module acquires the real-time vehicle-side acceleration a. y ; When the real-time vehicle side acceleration a is obtained y When the force is ≤0.4g (g is the acceleration due to gravity), the output a = 0; When the real-time vehicle side acceleration a is obtained y When the value is greater than 0.4g (where g is the acceleration due to gravity), the output a < 0.

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