Vehicle control method and device, electronic equipment and vehicle

Abstract

The invention relates to a vehicle control method and device, electronic equipment and a vehicle. The method comprises the steps of obtaining road data and real-time meteorological data in a current driving path of a target vehicle; judging whether a road in front of the target vehicle is a crosswind area or not based on the road data and the real-time meteorological data; when it is judged that the road in front of the target vehicle is the crosswind area, influence intensity data of the crosswind area is determined; when it is detected that the target vehicle is about to enter the crosswind area, vehicle parameters of the target vehicle are adjusted according to the influence intensity data; when it is detected that the target vehicle enters the crosswind area, vehicle state data of the target vehicle influenced by crosswind in the crosswind area are obtained, and vehicle parameters of the target vehicle are adjusted according to the vehicle state data. According to the embodiment of the invention, the method achieves the precise judgment of the crosswind region, carries out the vehicle parameter adjustment under the condition that the vehicle does not enter the crosswind region, and avoids the control delay of the vehicle.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, specifically to a vehicle control method, device, electronic equipment, and vehicle. Background Technology

[0002] When a vehicle encounters strong crosswinds while traveling at high speed, its lateral stability decreases. At this time, the vehicle may veer off course, and the driver may panic and make incorrect operating procedures, leading to an accident.

[0003] Current crosswind control methods mainly involve controlling vehicle stability only after the vehicle enters the crosswind zone. This delay in vehicle control can lead to instability when the vehicle enters the crosswind zone. Summary of the Invention

[0004] One objective of this invention is to provide a vehicle control method to solve the problem of vehicle instability when entering a crosswind zone in the prior art; a second objective is to provide a vehicle control device; a third objective is to provide an electronic device; and a fourth objective is to provide a vehicle.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for vehicle control, the method comprising: Acquire road data and real-time weather data along the target vehicle's current driving path; Based on the road data and the real-time weather data, determine whether the road ahead of the target vehicle is a crosswind area; When it is determined that the road in front of the target vehicle is a crosswind area, the influence intensity data of the crosswind area is determined; When the target vehicle is detected to be about to enter the crosswind area, the vehicle parameters of the target vehicle are adjusted according to the influence intensity data; When the target vehicle is detected to have entered the crosswind area, vehicle status data of the target vehicle affected by the crosswind in the crosswind area is obtained, and the vehicle parameters of the target vehicle are adjusted according to the vehicle status data.

[0006] Optionally, determining whether the road ahead of the target vehicle is a crosswind area based on the road data and the real-time weather data includes: Based on the road data and the real-time meteorological data, the wind zone risk value on the target vehicle's driving path is determined, and the wind zone risk value is used to represent the probability that the road in front of the target vehicle is a crosswind area. When the risk value of the wind zone is greater than a preset risk threshold, the road in front of the target vehicle is determined to be a crosswind zone.

[0007] Optionally, the determining the wind area risk value on the target vehicle driving path based on the road data and the real-time meteorological data comprises: acquiring a historical meteorological database corresponding to the current driving path; determining the wind area risk value on the target vehicle driving path based on the road data, the real-time meteorological data and the historical meteorological database.

[0008] Optionally, the determining the wind area risk value on the target vehicle driving path based on the road data, the real-time meteorological data and the historical meteorological database comprises: respectively pre-processing the road data, the real-time meteorological data and the historical meteorological database to obtain target data; determining weight data corresponding to the road data, the real-time meteorological data and the historical meteorological database respectively; respectively weighting and summing the target data according to the weight data to determine the wind area risk value on the target vehicle driving path.

[0009] Optionally, the respectively pre-processing the road data, the real-time meteorological data and the historical meteorological database to obtain target data comprises: pre-processing the road data to determine first matching degree information of the road data and a preset high wind area feature; pre-processing the real-time meteorological data to determine degree information of the real-time meteorological data exceeding a reference threshold corresponding to a crosswind area; pre-processing the historical meteorological data to determine second matching degree information of the target vehicle front being a crosswind area in the historical meteorological database.

[0010] Optionally, the respectively weighting and summing the target data according to the weight data to determine the wind area risk value on the target vehicle driving path comprises: weighting each weight data and corresponding target data to obtain a plurality of weighted data; determining the wind area risk value on the target vehicle driving path based on the plurality of weighted data.

[0011] Optionally, the determining the influence intensity data of the crosswind area when determining that the road in front of the target vehicle is a crosswind area comprises: acquiring driving data of the target vehicle when determining that the road in front of the target vehicle is a crosswind area; determining the influence intensity data of the crosswind area according to the driving data, the road data and the real-time meteorological data.

[0012] Optionally, the determining the influence intensity data of the crosswind area according to the driving data, the road data and the real-time weather data comprises: obtaining a wind direction angle from the real-time weather data, and calculating a wind direction influence coefficient according to the wind direction angle; determining a basic risk value according to the wind direction influence coefficient, a terrain coefficient in the road data and a wind speed data in the real-time weather data; determining a vehicle speed coefficient and a load coefficient according to the driving data, and determining a comprehensive risk value based on the vehicle speed coefficient, the load coefficient and the basic risk value; determining the influence intensity data according to the comprehensive risk value.

[0013] Optionally, the adjusting the vehicle parameters of the target vehicle according to the influence intensity data when it is detected that the target vehicle is about to enter the crosswind area comprises: when it is detected that the target vehicle is about to enter the crosswind area, if the influence intensity data is medium risk or high risk, switching a vehicle mode of the target vehicle from a first mode to a second mode, the second air spring height of the target vehicle in the second mode being lower than the first air spring height of the target vehicle in the first mode, and the second damping coefficient of the electronic shock absorber of the target vehicle in the second mode being greater than the first damping coefficient of the electronic shock absorber of the target vehicle in the first mode; adjusting the vehicle parameters of the target vehicle according to the second mode.

[0014] Optionally, the vehicle state data comprises lateral offset distance, lateral wind force and vehicle torque information, and the adjusting the vehicle parameters of the target vehicle according to the vehicle state data comprises: when the lateral offset distance or the lateral wind force is greater than a first preset threshold value, and the vehicle torque information is less than a torque threshold value, controlling the target vehicle to continue driving according to the vehicle parameters of the first mode; when the lateral offset distance or the lateral wind force is greater than a second preset threshold value, and the vehicle torque information is less than a torque threshold value, controlling the vehicle mode of the target vehicle to switch to a third mode, and performing dynamic parameter adjustment according to the vehicle parameters of the third mode, wherein the first preset threshold value is less than the second preset threshold value.

[0015] Optionally, the performing dynamic parameter adjustment according to the vehicle parameters of the third mode comprises: adjusting the air spring height of the target vehicle in the third mode based on the size of the lateral wind force and the lateral offset distance; adjust, based on the lateral offset distance, a damping coefficient of an electronic shock absorber of the target vehicle in the third mode.

[0016] Optionally, the adjusting, based on the lateral wind force size and the lateral offset distance, of an air spring height of the target vehicle in the third mode comprises: determining, based on the lateral wind force size and the lateral offset distance, a wind speed change value in the crosswind region; determining, according to the wind speed change value, a height change rate of the air spring height of the target vehicle; determining the air spring height according to the height change rate; adjusting the target vehicle according to the air spring height.

[0017] Optionally, the adjusting, based on the lateral offset distance, of the damping coefficient of the electronic shock absorber of the target vehicle in the third mode comprises: determining, based on the lateral offset distance, an offset distance change rate of the target vehicle; obtaining a basic damping coefficient of the target vehicle; determining, according to the basic damping coefficient and the offset distance change rate, a damping adjustment amount; adjusting, according to the damping adjustment amount, the damping coefficient of the electronic shock absorber of the target vehicle in the third mode.

[0018] Optionally, the method further comprises: when the target vehicle is in the second mode or the third mode, if a preset exit event is detected, controlling the target vehicle to switch from the second mode or the third mode to the first mode.

[0019] Optionally, the exit event comprises any one of: a driver-initiated exit event, a crosswind influence-weakened exit event, and a vehicle abnormal state exit event.

[0020] An apparatus for vehicle control, the apparatus comprising: a data acquisition module configured to acquire road data and real-time weather data in a current driving path of a target vehicle; a crosswind region judgment module configured to judge, based on the road data and the real-time weather data, whether a road ahead of the target vehicle is a crosswind region; an influence intensity data determination module configured to, when it is determined that the road ahead of the target vehicle is a crosswind region, determine influence intensity data of the crosswind region; a crosswind front control module configured to adjust vehicle parameters of the target vehicle according to the influence intensity data when it is detected that the target vehicle is about to enter the crosswind area; a crosswind middle control module configured to acquire vehicle state data of the target vehicle affected by the crosswind in the crosswind area when it is detected that the target vehicle enters the crosswind area, and adjust vehicle parameters of the target vehicle according to the vehicle state data.

[0021] An electronic device comprising: a processor; a memory for storing processor-executable instructions; The processor is configured to execute the instructions to implement the vehicle control method described above.

[0022] A computer-readable storage medium, when the instructions in the storage medium are executed by the processor of a mobile terminal, enable the mobile terminal to execute the vehicle control method described above.

[0023] A vehicle comprising the electronic device described above.

[0024] The beneficial effects of the present application are: In the embodiments of the present application, road data and real-time weather data in the current driving path of the target vehicle are acquired; it is determined whether the road in front of the target vehicle is a crosswind area based on the road data and the real-time weather data; influence intensity data of the crosswind area is determined when it is determined that the road in front of the target vehicle is a crosswind area; vehicle parameters of the target vehicle are adjusted according to the influence intensity data when it is detected that the target vehicle is about to enter the crosswind area; vehicle state data of the target vehicle affected by the crosswind in the crosswind area is acquired when it is detected that the target vehicle enters the crosswind area, and vehicle parameters of the target vehicle are adjusted according to the vehicle state data. On the one hand, the crosswind area can be accurately determined according to the road data and the real-time weather data, and on the other hand, vehicle parameter adjustment is performed without entering the crosswind area after determining that the crosswind area is in front, thereby avoiding vehicle control delay. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 A step flowchart of a vehicle control method provided in the embodiments of the present application; Figure 2 A step flowchart of another vehicle control method provided in the embodiments of the present application; Figure 3 A step flowchart of another vehicle control method provided in the embodiments of the present application; Figure 4 A step flowchart of another vehicle control method provided in the embodiments of the present application; Figure 5A structural schematic diagram of a vehicle control device provided in an embodiment of the present application is shown in FIG. 1. Figure 6 A structural schematic diagram of an electronic device provided in an embodiment of the present application is shown in FIG. 1. DETAILED DESCRIPTION

[0026] Other advantages and effects of the present application can be easily understood by those skilled in the art from the above description of the embodiments of the present application. The present application can also be implemented or applied in other different specific embodiments, and various modifications or changes can be made to the details of the present application based on different views and applications without departing from the spirit of the present application. It should be understood that the preferred embodiments are only for illustrating the present application, but not for limiting the protection scope of the present application.

[0027] It should be noted that the embodiments of the present application can involve the use of user data. In actual applications, user-specific personal data can be used in the schemes described herein within the scope permitted by applicable laws and regulations, for example, with the explicit consent of the user, with the actual notification to the user, etc.

[0028] Referring to Figure 1 A step flowchart of a vehicle control method provided in an embodiment of the present application is shown in FIG. 2, which specifically includes the following steps. Step 101, acquiring road data in a current driving path of a target vehicle and real-time weather data; In the embodiments of the present application, in order to enable the vehicle to be safely and smoothly driven in a crosswind area, road data in the current driving path can be collected during the driving of the vehicle, and real-time weather data of the road ahead of the target vehicle in the driving section can also be acquired through networking.

[0029] The road information can include GPS positioning data, navigation path data, and terrain feature data, and the real-time weather data can specifically include real-time wind data, wind direction data, weather warning data, etc.

[0030] In actual applications, the target vehicle can acquire the current position (latitude and longitude information) and driving path (including the current section and the path coordinates ahead) of the vehicle through a GPS module. The target vehicle can also connect to a weather server through a vehicle-mounted communication module (such as 4G / 5G, Wi-Fi) to acquire real-time weather data of the current position and the path ahead of the vehicle, including wind speed, wind direction, wind duration, temperature, humidity, etc.

[0031] Step 102, judging whether the road ahead of the target vehicle is a crosswind area based on the road data and the real-time weather data; After obtaining the road data and real-time weather data, whether the road in front of the target vehicle is a crosswind area can be comprehensively analyzed in combination with the road data and real-time weather data. For example, the road data can determine the current position, driving path, terrain characteristics, etc. of the vehicle, and then the road section in front of the target vehicle can be determined, and then in combination with the real-time weather data, the weather change in the road section in front of the target vehicle in the recent period of time can be determined, so that whether the vehicle is in a crosswind area when it reaches the position can be inferred.

[0032] Step 103, when it is determined that the road in front of the target vehicle is a crosswind area, determining the influence intensity data of the crosswind area; When it is determined that the road in front of the target vehicle is a crosswind area, the influence intensity data in the crosswind area can be further determined, which is used to represent the strength of the crosswind influence. When the crosswind influence area is stronger, the safety of the vehicle is more difficult to guarantee.

[0033] Step 104, when it is detected that the target vehicle is about to enter the crosswind area, adjusting the vehicle parameters of the target vehicle according to the influence intensity data; When it is determined that there is a crosswind area in front of the vehicle, in order to avoid control delay when the vehicle enters the crosswind area, the vehicle parameters of the target vehicle can be adjusted in advance according to the influence intensity data, so as to realize early vehicle control and cope with the crosswind area that will be entered, and ensure that the target vehicle can safely pass through the crosswind area. The vehicle parameters can include suspension parameters such as air spring height, etc.

[0034] Specifically, when it is detected that the distance between the target vehicle and the crosswind area is less than a preset distance, it can be determined that the target vehicle is about to enter the crosswind area, and then the vehicle parameters of the target vehicle can be adjusted according to the influence intensity data.

[0035] Step 105, when it is detected that the target vehicle enters the crosswind area, obtaining the vehicle state data of the target vehicle affected by the crosswind in the crosswind area, and adjusting the vehicle parameters of the target vehicle according to the vehicle state data.

[0036] When the target vehicle has entered the crosswind area according to the adjusted vehicle parameters, the vehicle state data of the target vehicle under the actual influence of the crosswind area can be obtained, wherein the vehicle state data can include lateral offset distance, lateral wind force, vehicle torque information, etc.

[0037] Then, after obtaining the vehicle state data of the target vehicle affected by the crosswind, the vehicle parameters of the target vehicle can be adjusted according to the vehicle state data to cope with the actual crosswind influence and ensure the safe driving of the target vehicle.

[0038] In the embodiment of the present application, on the one hand, the target vehicle can accurately determine the crosswind area according to the road data and real-time weather data, and on the other hand, after determining that the front road is a crosswind area, the vehicle parameter is adjusted before entering the crosswind area, so as to avoid vehicle control delay.

[0039] Referring to Figure 2 , a step flow chart of a vehicle control method provided in the embodiment of the present application is shown, which specifically includes the following steps: Step 201, obtaining road data and real-time weather data in a current driving path of a target vehicle; Step 202, determining a wind area risk value for indicating a probability that a front road of the target vehicle is a crosswind area on a driving path of the target vehicle based on the road data and the real-time weather data; In actual application, after obtaining the road data and the real-time weather data, in order to accurately determine that the front road of the target vehicle is a crosswind area, the road data and the real-time weather data can be taken as reference data to calculate the wind area risk value for indicating the probability that the front road of the target vehicle is a crosswind area based on the road data, the real-time weather data and the crosswind area judgment logic, so that the crosswind area can be determined by quantitative calculation.

[0040] In the embodiment of the present application, step 202 can include the following substeps: obtaining a historical weather database corresponding to the current driving path; determining the wind area risk value on the driving path of the target vehicle based on the road data, the real-time weather data and the historical weather database.

[0041] In actual application, when determining the wind area risk value, the historical weather database can also be introduced, which can be obtained from the local or cloud of the vehicle; the data in the historical weather database can include historical data records of geographical position, season and time period. The historical weather database is stored in the local or cloud server, and by comparing the driving path with the historical crosswind influence area data, the possibility of the crosswind influence area can be further confirmed.

[0042] After obtaining the road data and the real-time weather data, whether the front road of the target vehicle is a crosswind area can be comprehensively analyzed in combination with the road data and the real-time weather data, for example, the road data can determine the current position, driving path, topographic features and the like of the vehicle, and then the position of the front road section of the target vehicle can be determined, and then in combination with the real-time weather data, the weather change in the recent period at the front road section can be determined, so that whether the vehicle is in the crosswind area when reaching the position can be inferred.

[0043] To further accurately determine the crosswind area, meteorological rules and other information of the road section can be analyzed in combination with records in the historical meteorological database, so as to realize the determination of the crosswind area in combination with the road data, the real-time meteorological data and the historical meteorological database.

[0044] In an embodiment of the present application, the determination of the wind area risk value on the driving path of the target vehicle based on the road data, the real-time meteorological data and the historical meteorological database comprises the following sub-steps: Sub-step 11, respectively pre-process the road data, the real-time meteorological data and the historical meteorological database to obtain target data. In actual application, the pre-processing process can comprise the following process: (1) pre-process the road data to determine first matching degree information of the road data and the preset high wind area feature; In actual application, the road data can be compared with the preset high wind area feature to determine the first matching degree information of the two, and the higher the matching degree is, the closer the road data is to the characteristics of the high wind area.

[0045] (2) pre-process the real-time meteorological data to determine degree information of the real-time meteorological data exceeding the reference threshold value corresponding to the crosswind area; Based on the real-time meteorological data, the real-time meteorological data can be compared with the reference threshold value corresponding to the crosswind area, and when the real-time meteorological data exceeds the high reference threshold value, it means that there is a higher possibility of the crosswind area in the front road section, so that the degree information of the real-time meteorological data exceeding the reference threshold value corresponding to the crosswind area can be determined, and the possibility of the crosswind area can be evaluated based on the degree information.

[0046] (3) pre-process the historical meteorological data to determine second matching degree information of the target vehicle in front of the historical meteorological database being the crosswind area.

[0047] Sub-step 12, determine the weight data corresponding to the road data, the real-time meteorological data and the historical meteorological database respectively; Different types of data can be respectively set with weights, the weight value is between 0 and 1 (not including 0 and 1), which can be set according to actual scene. The sum of the plurality of weights is 1.

[0048] For example, the first weight data + the second weight data + the third weight data = 1.

[0049] Sub-step 13, respectively weight and sum the target data according to the weight data to determine the wind area risk value on the driving path of the target vehicle.

[0050] The wind area risk value = weight data 1 * target data 1 +... weight data n * weight data n.

[0051] In an embodiment of the present application, the target vehicle can weight each weight data with the corresponding target data to obtain a plurality of weighted data; and determine the wind area risk value on the driving path of the target vehicle based on the plurality of weighted data.

[0052] According to the foregoing analysis, the wind area risk value = a x (the matching degree of the road data and the high wind area feature) + b x (the degree to which the real-time meteorological data exceeds the reference threshold) + g x (the matching degree of the historical meteorological database).

[0053] Wherein, a is a road data weight factor (i.e. the first weight data), b is a real-time meteorological data weight factor (i.e. the second weight data), and g is a historical meteorological data weight factor (i.e. the third weight data).

[0054] Step 203, when the wind area risk value is greater than a preset risk threshold, determining whether the road in front of the target vehicle is a crosswind area.

[0055] Wherein, the preset risk threshold is a critical value for judging the crosswind area, which can be set according to the actual scene, and is not limited in the embodiment of the present application.

[0056] Step 204, when it is determined that the road in front of the target vehicle is a crosswind area, determining the influence intensity data of the crosswind area. Step 205, when it is detected that the target vehicle is about to enter the crosswind area, adjusting the vehicle parameters of the target vehicle according to the influence intensity data. Step 206, when it is detected that the target vehicle enters the crosswind area, obtaining the vehicle state data of the target vehicle affected by the crosswind in the crosswind area, and adjusting the vehicle parameters of the target vehicle according to the vehicle state data.

[0057] In the embodiment of the present application, the wind area risk value can be quantitatively calculated based on the road data and the real-time meteorological data, so as to accurately determine whether the road in front of the target vehicle is a crosswind area, and further ensure the safety of the vehicle when driving in the crosswind area.

[0058] Referring to Figure 3 , a step flowchart of a vehicle control method provided in an embodiment of the present application is shown, which specifically includes the following steps: Step 301, obtaining road data and real-time meteorological data in the current driving path of a target vehicle; Step 302, determining whether the road in front of the target vehicle is a crosswind area based on the road data and the real-time meteorological data; Step 303, when it is determined that the road in front of the target vehicle is a crosswind area, obtaining driving data of the target vehicle; In the embodiment of the present application, the driving data of the target vehicle can include real-time vehicle speed data, real-time vehicle load data, and an upper limit reference value of stable driving speed.

[0059] Step 304: determining the influence intensity data of the crosswind area according to the driving data, the road data, and the real-time weather data; In actual application, the influence intensity data of the crosswind area can be quantitatively calculated by comprehensively considering the driving data, the road data, and the real-time weather data, so as to better represent the influence of the crosswind area.

[0060] In an embodiment of the present application, the determination of the influence intensity data of the crosswind area according to the driving data, the road data, and the real-time weather data comprises: Step 21: obtaining a wind direction included angle from the real-time weather data, and calculating a wind direction influence coefficient according to the wind direction included angle; In actual application, the real-time weather data can include the crosswind direction, and the wind direction included angle in the current crosswind area can be determined according to the crosswind direction. The wind direction included angle is the included angle value between the vehicle advancing direction and the wind direction.

[0061] The calculation process of the wind direction influence coefficient is as follows: Wind direction influence coefficient = |90°-wind direction included angle| / 90°.

[0062] Step 22: determining a basic risk value according to the wind direction influence coefficient, a terrain coefficient in the road data, and a wind speed data in the real-time weather data; Specifically, the wind speed data in the real-time weather data can include a current wind speed / wind speed upper limit reference value, and the basic risk value can be calculated according to the following formula: Basic risk value = (current wind speed / wind speed upper limit reference value) x wind direction influence coefficient x terrain coefficient. The terrain coefficient can be set according to the terrain type.

[0063] Step 23: determining a vehicle speed coefficient and a load coefficient according to the driving data, and determining a comprehensive risk value based on the vehicle speed coefficient, the load coefficient, and the basic risk value; Comprehensive risk value = basic risk value x (1+vehicle speed coefficient) x (1+load coefficient) The vehicle speed coefficient = current vehicle speed / stable driving speed upper limit reference value, and the load coefficient = actual load / maximum load.

[0064] Step 24: determining the influence intensity data according to the comprehensive risk value.

[0065] In actual application, the influence intensity data can be divided into three levels of low risk influence, medium risk influence, and high risk influence, and each level corresponds to a risk threshold.

[0066] When the comprehensive risk value is less than the low risk threshold, the influence intensity data is determined as low risk influence; when the low risk threshold is less than or equal to the comprehensive risk value and less than the medium risk threshold, the influence intensity data is determined as medium risk influence; and when the medium risk threshold is less than or equal to the comprehensive risk value and less than the high risk threshold, the influence intensity data is determined as high risk influence.

[0067] Step 305: When it is detected that the target vehicle is about to enter the crosswind area, the vehicle parameters of the target vehicle are adjusted according to the influence intensity data. Step 306: When it is detected that the target vehicle enters the crosswind area, the vehicle state data of the target vehicle affected by the crosswind in the crosswind area is obtained, and the vehicle parameters of the target vehicle are adjusted according to the vehicle state data.

[0068] In the embodiment of the present application, the influence intensity data of the crosswind area is quantitatively evaluated by the driving data, the road data and the real-time weather data, so as to more accurately determine the influence in the crosswind area, and thus the safe driving of the vehicle in the crosswind area can be effectively ensured.

[0069] Referring to Figure 4 , a step flowchart of a vehicle control method provided in an embodiment of the present application is shown, which specifically includes the following steps: Step 401: Obtain the road data and the real-time weather data in the current driving path of the target vehicle. Step 402: Determine whether the road in front of the target vehicle is a crosswind area based on the road data and the real-time weather data. Step 403: When it is determined that the road in front of the target vehicle is a crosswind area, determine the influence intensity data of the crosswind area. Step 404: When it is detected that the target vehicle is about to enter the crosswind area, if the influence intensity data is medium risk or high risk, switch the vehicle mode of the target vehicle from the first mode to the second mode. In the second mode, the second air spring height of the target vehicle is lower than the first air spring height of the target vehicle in the first mode, and the second damping coefficient of the electronic shock absorber of the target vehicle in the second mode is greater than the first damping coefficient of the electronic shock absorber of the target vehicle in the first mode. In actual application, the vehicle running mode in the target vehicle can include the first mode, the second mode and the third mode, wherein the first mode is used for daily driving of the vehicle, and the second mode and the third mode are safety driving modes set for the crosswind scene.

[0070] The first mode is the default mode during vehicle driving, and when a crosswind area is detected in front of the vehicle, if the influence intensity data is medium or high risk, the first mode can be switched to the second mode to adapt to the crosswind area in front of the vehicle, so as to ensure the safe driving of the vehicle. When the influence intensity data is low risk, it means that the crosswind influence is not large, and the target vehicle can continue to enter the crosswind area in the first mode.

[0071] Step 405, adjusting the vehicle parameters of the target vehicle according to the second mode; After switching to the second mode, the vehicle parameters of the target vehicle can be adjusted according to the vehicle parameters in the second mode. Specifically, it can include the adjustment of the vehicle suspension parameters.

[0072] For example, if the above crosswind area prediction is medium or high risk, enter the crosswind control mode (i.e. the second mode), and adjust the suspension system in advance; (1) According to the medium risk of crosswind prediction intensity, reduce the height of the air spring (for example, reduce the standard height by 10%-20%), optimize the load distribution under the action of crosswind, and reduce the roll angle of the vehicle; Increase the damping force of the electronic shock absorber (for example, increase the damping coefficient by 10%-20%), enhance the control ability of the suspension system to the vehicle posture, and improve the crosswind stability; (2) According to the high risk of crosswind prediction intensity, reduce the height of the air spring (for example, reduce the standard height by 20%-40%); Increase the damping force of the electronic shock absorber (for example, increase the damping coefficient by 20%-40%).

[0073] Step 406, when the target vehicle enters the crosswind area, obtaining the vehicle state data of the target vehicle affected by the crosswind in the crosswind area; Among them, the vehicle state data includes lateral offset distance, lateral wind force and vehicle torque information; In practical application, the step of real-time monitoring of vehicle state includes: a) Measure the lateral offset distance of the vehicle and the lane line through the camera and radar; b) Real-time measurement of the size and direction change of the lateral wind force acting on the vehicle through the wind force sensor; c) Real-time measurement of the steering wheel angle and operation torque of the driver through the steering wheel angle sensor and steering wheel torque sensor.

[0074] Step 407, when the lateral offset distance or the lateral wind force is greater than the first preset threshold, and the vehicle torque information is less than the torque threshold, controlling the target vehicle to continue driving according to the vehicle parameters of the first mode; The first preset threshold and the torque threshold can be preset by a vehicle system, for example, the lateral offset distance is greater than or equal to 0.5 meters, the lateral wind force is greater than or equal to 300 Newtons, the rotation angle is less than or equal to 5 degrees, and the torque is less than or equal to 10 Newton-meters.

[0075] In step 408, when the lateral offset distance or the lateral wind force is greater than a second preset threshold, and the vehicle torque information is less than a torque threshold, the vehicle mode of the target vehicle is switched to a third mode, and dynamic parameter adjustment is performed according to the vehicle parameters of the third mode, wherein the first preset threshold is less than the second preset threshold.

[0076] The first preset threshold and the torque threshold can be preset by a vehicle system, for example, the second preset threshold: the lateral offset distance is greater than or equal to 1.0 meters, the lateral wind force is greater than or equal to 500 Newtons, the rotation angle is less than or equal to 5 degrees, and the torque is less than or equal to 10 Newton-meters.

[0077] In actual application, after entering the crosswind area, dynamic control can be performed on the target vehicle by monitoring the actual changes of the vehicle in the crosswind area.

[0078] In an embodiment of the present application, the dynamic parameter adjustment according to the vehicle parameters of the third mode includes: In step 31, the air spring height of the target vehicle in the third mode is adjusted based on the lateral wind force and the lateral offset distance. In actual application, the air spring height of the target vehicle in the third mode can be dynamically adjusted according to the real-time lateral wind force and the lateral offset distance of the vehicle.

[0079] In an embodiment of the present application, the determination process of the air spring height in the third mode is as follows: based on the lateral wind force and the lateral offset distance, the wind speed change value in the crosswind area is determined; the height change rate of the air spring height of the target vehicle is determined according to the wind speed change value; the air spring height is determined according to the height change rate; and the target vehicle is adjusted according to the air spring height.

[0080] In an embodiment of the present application, the air spring height can be gradually reduced based on the lateral wind force and the offset distance. Specifically, the wind speed change rate can be calculated, and then the air spring height of the target vehicle that should be adjusted is determined according to the relationship between the wind speed change rate and the height change rate, so as to optimize the vehicle load distribution and the crosswind resistance. For example, for every 10 m / s increase in wind speed, the height is reduced by 5%.

[0081] In step 32, the damping coefficient of the electronic shock absorber of the target vehicle in the third mode is adjusted based on the lateral offset distance.

[0082] In the crosswind area, the damping coefficient of the electronic shock absorber of the target vehicle in the third mode can also be dynamically adjusted based on the lateral offset distance. In an embodiment of the present application, the damping coefficient of the electronic shock absorber of the target vehicle in the third mode is adjusted based on the lateral offset distance, and the method comprises: determining the offset distance change rate of the target vehicle based on the lateral offset distance; obtaining the basic damping coefficient of the target vehicle; determining the damping adjustment amount according to the basic damping coefficient and the offset distance change rate; and adjusting the damping coefficient of the electronic shock absorber of the target vehicle in the third mode according to the damping adjustment amount.

[0083] The extension damping force and the compression damping force of the shock absorber are increased according to the offset distance change rate, so as to enhance the stability of the suspension system. The damping coefficient is calculated as follows: Damping adjustment amount = basic damping value × (1 + offset distance change rate); Wherein, offset distance change rate = (lateral offset distance 1 - lateral offset distance 2) / sampling time interval.

[0084] The damping coefficient can be determined based on the damping adjustment amount.

[0085] In an embodiment of the present application, the vehicle posture can also be optimized. Specifically, the aerodynamic performance of the vehicle can be optimized by adjusting the height difference of the air springs of each wheel, further reducing the influence of crosswind on the lateral stability of the vehicle, and at the same time, a fuzzy control algorithm is implemented to comprehensively adjust the suspension parameters according to various vehicle state parameters, so as to realize multi-objective optimization of the vehicle posture (such as minimum offset distance and minimum vehicle body posture change amplitude).

[0086] For example, a fuzzy reasoning system is established with lateral offset, offset change rate, wind grade, and roll angle as input variables, and four-wheel independent height adjustment and damping control as output variables, so as to achieve the goals of vehicle dynamic balance stability and comfort.

[0087] In an embodiment of the present application, when the target vehicle is in the second mode or the third mode, if a preset exit event is detected, the target vehicle is switched from the second mode or the third mode to the first mode.

[0088] In an example, the exit event comprises any one of the following: Driver active control exit event, crosswind influence weakening exit event, and vehicle abnormal state exit event.

[0089] The process of exiting the second mode (i.e. crosswind control mode) or the third mode (i.e. high-precision adjustment mode) is specifically described as follows in an embodiment of the present application: (1) Driver active control detection: if the steering wheel angle exceeds a predetermined threshold (for example, > 10 degrees) or the operation torque exceeds a predetermined threshold (for example, > 30 Nm), the system determines that the driver actively controls, the crosswind correction module is closed, and the high-precision adjustment mode or the crosswind control mode is exited. (2) Crosswind influence weakening detection: if the real-time measured lateral offset distance and lateral wind force are both lower than a first predetermined threshold (e.g. offset distance < 0.5 meters, wind force < 300 Newtons), the system determines that the crosswind influence is weakening, gradually reduces the action strength of the crosswind correction module, and exits the high-precision adjustment mode completely. (3) Abnormal state detection and exit: if the system detects that the ABS function or other functions of the vehicle are triggered (indicating that the vehicle loses control or other abnormal states exist), or the real-time monitoring data indicates that the vehicle offset distance exceeds the safe range (e.g. > 1.5 meters), the system will immediately exit the high-precision adjustment mode or the crosswind control mode, and issue a warning to prompt the driver to take over control.

[0090] When the target vehicle exits the high-precision adjustment mode, the system gradually restores the height of the air spring and the damping characteristics of the electronic shock absorber to the normal driving state parameters (e.g. air spring height is restored to the standard value, and shock absorber damping is restored to the comfort mode).

[0091] In the embodiment of the application, the target vehicle can achieve different vehicle parameter adjustments according to whether the vehicle is in the crosswind area. When not entering the crosswind area, static parameter adjustment can be performed in advance, and when entering the crosswind area, dynamic adjustment of vehicle parameters based on real-time vehicle state data can be realized, thereby effectively ensuring the safe driving of the vehicle in the crosswind area.

[0092] Referring to Figure 5 , a structure schematic diagram of a vehicle control device provided in an embodiment of the application is shown, which specifically includes the following modules: The data acquisition module 501 is configured to acquire road data and real-time weather data in the current driving path of the target vehicle. The crosswind area judgment module 502 is configured to judge whether the road in front of the target vehicle is a crosswind area based on the road data and the real-time weather data. The influence intensity data determination module 503 is configured to determine the influence intensity data of the crosswind area when it is determined that the road in front of the target vehicle is a crosswind area. The crosswind pre-control module 504 is configured to adjust the vehicle parameters of the target vehicle according to the influence intensity data when it is detected that the target vehicle is about to enter the crosswind area. The crosswind control module 505 is configured to acquire vehicle state data of the target vehicle affected by the crosswind in the crosswind area when it is detected that the target vehicle enters the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle state data.

[0093] In an embodiment of the application, the crosswind area judgment module 502 can include: The wind area risk value determination submodule is configured to determine a wind area risk value on the driving path of the target vehicle based on the road data and the real-time meteorological data, where the wind area risk value is used to represent a probability that the road in front of the target vehicle is a crosswind area. The crosswind area determination submodule is configured to determine that the road in front of the target vehicle is a crosswind area when the wind area risk value is greater than a preset risk threshold.

[0094] In an embodiment of the present application, the wind area risk value determination submodule can include: The historical meteorological database acquisition unit is configured to acquire a historical meteorological database corresponding to the current driving path. The wind area risk value determination unit is configured to determine a wind area risk value on the driving path of the target vehicle based on the road data, the real-time meteorological data and the historical meteorological database.

[0095] In an embodiment of the present application, the wind area risk value determination unit includes: The target data determination subunit is configured to pre-process the road data, the real-time meteorological data and the historical meteorological database respectively to obtain target data. The weight data determination subunit is configured to determine weight data corresponding to the road data, the real-time meteorological data and the historical meteorological database respectively. The wind area risk value determination subunit is configured to perform weighted summation on the target data according to the weight data respectively to determine a wind area risk value on the driving path of the target vehicle.

[0096] In an embodiment of the present application, the target data determination subunit can include: The first matching degree information determination block is configured to pre-process the road data to determine first matching degree information of the road data with preset high wind area characteristics. The degree information determination block is configured to pre-process the real-time meteorological data to determine degree information of the real-time meteorological data exceeding a reference threshold corresponding to a crosswind area. The second matching degree information determination block is configured to pre-process the historical meteorological data to determine second matching degree information of the target vehicle in front of a crosswind area in the historical meteorological database.

[0097] In an embodiment of the present application, the wind area risk value determination subunit can include: The weight data determination block is configured to perform weighting on each weight data and corresponding target data to obtain a plurality of weighted data. The wind area risk value determination block is configured to determine a wind area risk value on the driving path of the target vehicle based on the plurality of weighted data.

[0098] In an embodiment of the present application, the influence intensity data determining module 503 can comprise: a driving data determining sub-module, configured to acquire driving data of the target vehicle when determining that the road ahead of the target vehicle is a crosswind area; an influence intensity determining sub-module, configured to determine influence intensity data of the crosswind area according to the driving data, the road data and the real-time weather data.

[0099] In an embodiment of the present application, the influence intensity determining sub-module can comprise: a wind direction influence coefficient calculating unit, configured to acquire a wind direction included angle from the real-time weather data, and calculate a wind direction influence coefficient according to the wind direction included angle; a basic risk value determining unit, configured to determine a basic risk value according to the wind direction influence coefficient, a terrain coefficient in the road data and wind speed data in the real-time weather data; a comprehensive risk value determining unit, configured to determine a vehicle speed coefficient and a load coefficient according to the driving data, and determine a comprehensive risk value based on the vehicle speed coefficient, the load coefficient and the basic risk value; an influence intensity data determining unit, configured to determine influence intensity data according to the comprehensive risk value.

[0100] In an embodiment of the present application, the crosswind control module 504 can comprise: a mode switching sub-module, configured to switch a vehicle mode of the target vehicle from a first mode to a second mode if the influence intensity data is medium risk or high risk when detecting that the target vehicle has not entered the crosswind area, the second air spring height of the target vehicle in the second mode being lower than the first air spring height of the target vehicle in the first mode, and the second damping coefficient of the electronic shock absorber of the target vehicle in the second mode being greater than the first damping coefficient of the electronic shock absorber of the target vehicle in the first mode; a vehicle parameter adjusting sub-module, configured to adjust vehicle parameters of the target vehicle according to the second mode.

[0101] In an embodiment of the present application, the vehicle state data comprises lateral offset distance, lateral wind force and vehicle torque information, and the crosswind control module 505 can comprise: a first mode maintaining sub-module, configured to control the target vehicle to continue driving according to vehicle parameters in a first mode when the lateral offset distance or the lateral wind force is greater than a first preset threshold value, and the vehicle torque information is less than a torque threshold value. a third mode switching sub-module, configured to control the vehicle mode of the target vehicle to switch to a third mode and perform dynamic parameter adjustment according to vehicle parameters of the third mode when the lateral offset distance or the lateral wind force is greater than a second preset threshold and the vehicle torque information is less than a torque threshold, wherein the first preset threshold is less than the second preset threshold.

[0102] In an embodiment of the present application, the third mode switching sub-module can include: an air spring height adjustment unit, configured to adjust an air spring height of the target vehicle in the third mode based on the lateral wind force and the lateral offset distance; a damping coefficient adjustment unit, configured to adjust a damping coefficient of an electronic shock absorber of the target vehicle in the third mode based on the lateral offset distance.

[0103] In an embodiment of the present application, the damping coefficient adjustment unit can include: a wind speed change value determination sub-unit, configured to determine a wind speed change value in the crosswind region based on the lateral wind force and the lateral offset distance; a height change rate determination sub-unit, configured to determine a height change rate of the air spring height of the target vehicle according to the wind speed change value; an air spring height sub-unit, configured to determine the air spring height according to the height change rate; a vehicle adjustment sub-unit, configured to adjust the target vehicle according to the air spring height.

[0104] In an embodiment of the present application, the damping coefficient adjustment unit can include: an offset distance change rate determination sub-unit, configured to determine an offset distance change rate of the target vehicle based on the lateral offset distance; a basic damping coefficient acquisition sub-unit, configured to acquire a basic damping coefficient of the target vehicle; a damping adjustment amount determination sub-unit, configured to determine a damping adjustment amount according to the basic damping coefficient and the offset distance change rate; a damping coefficient determination sub-unit, configured to adjust the damping coefficient of the electronic shock absorber of the target vehicle in the third mode according to the damping adjustment amount.

[0105] In an embodiment of the present application, the device further includes: an exit event response module, configured to control the target vehicle to switch from the second mode or the third mode to the first mode if a preset exit event is detected when the target vehicle is in the second mode or the third mode.

[0106] In an embodiment of the present application, the exit event includes any one of the following: The exit event is actively controlled by the driver, the exit event is affected by the crosswind, and the exit event is caused by an abnormal state of the vehicle.

[0107] In an embodiment of the present application, the road data in the current driving path of the target vehicle and real-time weather data are acquired; whether the road in front of the target vehicle is a crosswind area is determined based on the road data and the real-time weather data; when it is determined that the road in front of the target vehicle is a crosswind area, the influence intensity data of the crosswind area is determined; when it is detected that the target vehicle is about to enter the crosswind area, the vehicle parameters of the target vehicle are adjusted according to the influence intensity data; when it is detected that the target vehicle enters the crosswind area, the vehicle state data of the target vehicle affected by the crosswind in the crosswind area is acquired, and the vehicle parameters of the target vehicle are adjusted according to the vehicle state data. On the one hand, the crosswind area can be accurately determined according to the road data, the real-time weather data and the historical weather database, and on the other hand, the vehicle parameters are adjusted when it is determined that the road in front is a crosswind area without entering the crosswind area, so as to avoid vehicle control delay.

[0108] For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the related parts refer to the part of the method embodiment. The embodiment of the present application also provides an electronic device, such as Figure 6 As shown in the figure, the electronic device includes a processor 601, a device interface 602, a memory 603 and a bus 604. The memory 603 is used to store a computer program. The processor 601 is used to execute the program stored in the memory 603, so as to realize the above steps.

[0109] The bus mentioned above can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus can be divided into an address bus, a data bus and a control bus. For the convenience of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0110] The memory can include a Random Access Memory (RAM) and can also include a non-volatile memory, such as at least one disk storage. Optionally, the memory can also be at least one storage device remotely located from the aforementioned processor.

[0111] The processor described above can be a general processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc. It can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other programmable logic device, a discrete gate or transistor logic, a discrete hardware component.

[0112] The application further provides a storage medium, which enables an electronic device to execute the vehicle control method of the foregoing embodiments when an instruction in the storage medium is executed by a processor of the electronic device.

[0113] For the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the description of the method embodiments.

[0114] The algorithms and displays presented herein are not inherently related to any particular computer, virtual apparatus, or other apparatus. Structural requirements of such apparatus required to be constructed in accordance with the description above are explicitly set forth in this section. Moreover, the application is not intended to be related to any particular programming language. It should be understood that the application described herein can be implemented using a variety of programming languages, and the description of a specific language above is intended to disclose the best mode of the application.

[0115] In the specification provided herein, a large number of specific details are described. However, it can be understood that the embodiments of the application can be practiced without these specific details. In some examples, well-known methods, structures and techniques are not shown in detail in order not to obscure the understanding of the specification.

[0116] Similarly, it is to be understood that the embodiments of the present application can be positioned and described in a number of different orientations, and the terminology or description can be chosen for purposes of convenience only. It is therefore intended that the application include all such modifications and alterations in the depiction of the essential aspects of the preferred embodiments of the application that were required over and above the normal variations inherent in any significant, modular, reusable hardware or software components. Additionally, the term "data bus" as used throughout this detailed description shall be interpreted to include any type of bus structure or bus system, including a memory bus, address bus, peripheral bus, or other busses that are known to those skilled in the art.

[0117] Those skilled in the art will appreciate that the modules in the apparatuses in the embodiments can be adapted and placed in one or more apparatuses other than the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and further can be divided into more sub-modules or sub-units or sub-components. Any combination of all the features disclosed in the specification (including the accompanying claims, abstract and drawings), and any method or steps of any method so disclosed can be made unless specifically stated otherwise. Each feature disclosed in the specification (including the accompanying claims, abstract and drawings) can be replaced by alternative features serving the same, equivalent or similar purpose unless specifically stated otherwise.

[0118] Embodiments of the various components of the application can be implemented in hardware, or as software modules running in one or more processors, or some combination of both. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functionality of some or all of the components in the sequencing apparatus according to the present application. The present application can also be implemented as a program for executing the part or all of the methods described herein on a device or apparatus. Such a program can be stored on a computer readable medium or can have one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier medium, or in any other form.

[0119] It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of both hardware and software, and any combination thereof. In a unit claim, several devices can be listed with a comma. The use of the term 'about' followed by a value and / or a term 'approximately' preceding a value means that the value can vary from the stated value by 10%. The use of any of the following terms in the claims is neither meant to limit the scope nor to introduce a non-combination limitation. The terms 'comprise', 'include', and 'contain' are not used in their exclusive sense. The use of the term 'first','second', and 'third' does not connote any order, quantity, creation or importance, but rather are used to denote one element from another. The use of these terms is interchangeable under appropriate circumstances.

[0120] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the devices, apparatuses and units described above can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0121] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0122] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0123] It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of both hardware and software, and any combination thereof. In a unit claim, several devices can be listed with a comma. The use of the term 'about' followed by a value and / or a term 'approximately' preceding a value means that the value can vary from the stated value by 10%. The use of any of the following terms in the claims is neither meant to limit the scope nor to introduce a non-combination limitation. The terms 'comprise', 'include', and 'contain' are not used in their exclusive sense. The use of the term 'first','second', and 'third' does not connote any order, quantity, creation or importance, but rather are used to denote one element from another. The use of these terms is interchangeable under appropriate circumstances.

Claims

1. A method for vehicle control, characterized in that, The method includes: Acquire road data and real-time weather data along the target vehicle's current driving path; Based on the road data and the real-time weather data, determine whether the road ahead of the target vehicle is a crosswind area; When it is determined that the road in front of the target vehicle is a crosswind area, the influence intensity data of the crosswind area is determined; When the target vehicle is detected to be about to enter the crosswind area, the vehicle parameters of the target vehicle are adjusted according to the influence intensity data; When the target vehicle is detected to have entered the crosswind area, vehicle status data of the target vehicle affected by the crosswind in the crosswind area is obtained, and the vehicle parameters of the target vehicle are adjusted according to the vehicle status data.

2. The method according to claim 1, characterized in that, The step of determining whether the road ahead of the target vehicle is a crosswind area based on the road data and the real-time weather data includes: Based on the road data and the real-time meteorological data, the wind zone risk value on the target vehicle's driving path is determined, and the wind zone risk value is used to represent the probability that the road in front of the target vehicle is a crosswind area. When the risk value of the wind zone is greater than a preset risk threshold, the road in front of the target vehicle is determined to be a crosswind zone.

3. The method according to claim 2, characterized in that, The step of determining the wind zone risk value along the target vehicle's travel path based on the road data and the real-time meteorological data includes: Obtain the historical weather database corresponding to the current driving route; The wind zone risk value on the target vehicle's travel path is determined based on the road data, the real-time meteorological data, and the historical meteorological database.

4. The method according to claim 3, characterized in that, The step of determining the wind zone risk value along the target vehicle's travel path based on the road data, the real-time meteorological data, and the historical meteorological database includes: The road data, the real-time meteorological data, and the historical meteorological database are preprocessed respectively to obtain the target data; Determine the weight data corresponding to the road data, the real-time meteorological data, and the historical meteorological database, respectively; The target data is weighted and summed according to the weighted data to determine the wind zone risk value on the target vehicle's travel path.

5. The method according to claim 4, characterized in that, The process of preprocessing the road data, the real-time weather data, and the historical weather database to obtain target data includes: The road data is preprocessed to determine the first matching degree information between the road data and the preset high-wind area characteristics; The real-time meteorological data is preprocessed to determine the degree to which the real-time meteorological data exceeds the baseline threshold corresponding to the crosswind area; The historical meteorological data is preprocessed to determine the second matching degree information of the crosswind area in front of the target vehicle in the historical meteorological database.

6. The method according to claim 4, characterized in that, The step of weighting and summing the target data according to the weighted data to determine the wind zone risk value on the target vehicle's travel path includes: Each weighted data point is weighted by its corresponding target data to obtain multiple weighted data points. The wind zone risk value on the target vehicle's travel path is determined based on the weighted data.

7. The method according to claim 1, characterized in that, When determining that the road ahead of the target vehicle is a crosswind area, the determination of the influence intensity data of the crosswind area includes: When it is determined that the road ahead of the target vehicle is a crosswind area, the driving data of the target vehicle is acquired; The impact intensity data of the crosswind area is determined based on the driving data, the road data, and the real-time meteorological data.

8. The method according to claim 7, characterized in that, The step of determining the influence intensity data of the crosswind area based on the driving data, the road data, and the real-time meteorological data includes: The wind direction angle is obtained from the real-time meteorological data, and the wind direction influence coefficient is calculated based on the wind direction angle. The basic risk value is determined based on the wind direction influence coefficient, the terrain coefficient in the road data, and the wind speed data in the real-time meteorological data. The vehicle speed coefficient and load coefficient are determined based on the driving data, and the comprehensive risk value is determined based on the vehicle speed coefficient, the load coefficient, and the basic risk value. The impact intensity data is determined based on the comprehensive risk value.

9. The method according to claim 1, characterized in that, The step of adjusting the vehicle parameters of the target vehicle according to the influence intensity data when the target vehicle is detected to be about to enter the crosswind area includes: When the target vehicle is detected to be about to enter the crosswind area, if the impact intensity data is medium risk or high risk, the vehicle mode of the target vehicle is switched from the first mode to the second mode. In the second mode, the height of the second air spring of the target vehicle is lower than the height of the first air spring of the target vehicle in the first mode, and the second damping coefficient of the electronic shock absorber of the target vehicle in the second mode is greater than the first damping coefficient of the electronic shock absorber of the target vehicle in the first mode. Adjust the vehicle parameters of the target vehicle according to the second mode.

10. The method according to claim 9, characterized in that, The vehicle status data includes lateral offset distance, lateral wind force, and vehicle torque information. Adjusting the vehicle parameters of the target vehicle according to the vehicle status data includes: When the lateral offset distance or the lateral wind force is greater than a first preset threshold and the vehicle torque information is less than a torque threshold, the target vehicle is controlled to continue driving according to the vehicle parameters of the first mode. When the lateral offset distance or the lateral wind force is greater than the second preset threshold and the vehicle torque information is less than the torque threshold, the vehicle mode of the target vehicle is switched to the third mode, and the vehicle parameters are dynamically adjusted according to the vehicle parameters of the third mode, wherein the first preset threshold is less than the second preset threshold.

11. The method according to claim 10, characterized in that, The dynamic parameter adjustment according to the vehicle parameters of the third mode includes: Based on the magnitude of the lateral wind force and the lateral offset distance, adjust the air spring height of the target vehicle in the third mode; Based on the lateral offset distance, the damping coefficient of the electronic shock absorber of the target vehicle in the third mode is adjusted.

12. The method according to claim 11, characterized in that, The adjustment of the air spring height of the target vehicle in the third mode based on the lateral wind force magnitude and the lateral offset distance includes: Based on the magnitude of the crosswind force and the lateral offset distance, the wind speed change value within the crosswind area is determined; The height change rate of the air spring height in the target vehicle is determined based on the wind speed change value. The height of the air spring is determined according to the stated rate of change in height. The target vehicle is adjusted according to the air spring height.

13. The method according to claim 11, characterized in that, The adjustment of the damping coefficient of the electronic shock absorber of the target vehicle in the third mode based on the lateral offset distance includes: The rate of change of the offset distance of the target vehicle is determined based on the lateral offset distance; Obtain the basic damping coefficient of the target vehicle; The damping adjustment amount is determined based on the basic damping coefficient and the rate of change of the offset distance; Adjust the damping coefficient of the electronic shock absorber of the target vehicle in the third mode according to the damping adjustment amount.

14. The method according to claim 1, characterized in that, The method further includes: When the target vehicle is in the second or third mode, if a preset exit event is detected, the target vehicle is controlled to switch from the second or third mode to the first mode.

15. The method according to claim 14, characterized in that, The exit event includes any of the following: Exit events that are actively controlled by the driver, exit events that are affected by reduced crosswinds, and exit events that are due to abnormal vehicle conditions.

16. A vehicle control device, characterized in that, The device includes: The data acquisition module is used to acquire road data and real-time weather data along the current driving path of the target vehicle; The crosswind area determination module is used to determine whether the road ahead of the target vehicle is a crosswind area based on the road data and the real-time meteorological data. The impact intensity data determination module is used to determine the impact intensity data of the crosswind area when it is determined that the road in front of the target vehicle is a crosswind area; A crosswind control module is used to adjust the vehicle parameters of the target vehicle according to the influence intensity data when it is detected that the target vehicle is about to enter the crosswind area. The crosswind control module is used to acquire vehicle status data of the target vehicle affected by the crosswind in the crosswind area when the target vehicle is detected to have entered the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle status data.

17. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to execute the instructions to implement the vehicle control method as described in any one of claims 1 to 15.

18. A computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor of the mobile terminal, the mobile terminal is able to perform the vehicle control method as described in any one of claims 1 to 15.

19. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 17.

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