A vehicle control method, device, electronic equipment and vehicle

Abstract

The application relates to a vehicle control method, device, electronic equipment and vehicle, comprising the following steps: acquiring road data and real-time weather data in a current driving path of a target vehicle; judging whether a road in front of the target vehicle is a crosswind area based on the road data and the real-time weather data; determining influence intensity data of the crosswind area when it is judged that the road in front of the target vehicle is the crosswind area; adjusting 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; and acquiring vehicle state data of the target vehicle affected by crosswind in the crosswind area and adjusting the vehicle parameters of the target vehicle according to the vehicle state data when it is detected that the target vehicle enters the crosswind area. Through the embodiment of the application, the crosswind area is accurately judged, and the vehicle parameters are adjusted without entering the crosswind area, so that vehicle control delay is avoided.

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:

[0006] A method for vehicle control, the method comprising:

[0007] Acquire road data and real-time weather data along the target vehicle's current driving path;

[0008] Based on the road data and the real-time weather data, determine whether the road ahead of the target vehicle is a crosswind area;

[0009] 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;

[0010] 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;

[0011] 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.

[0012] 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:

[0013] 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.

[0014] 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.

[0015] Optionally, 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:

[0016] Obtain the historical weather database corresponding to the current driving route;

[0017] 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.

[0018] Optionally, 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:

[0019] The road data, the real-time meteorological data, and the historical meteorological database are preprocessed respectively to obtain the target data;

[0020] Determine the weight data corresponding to the road data, the real-time meteorological data, and the historical meteorological database, respectively;

[0021] 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.

[0022] Optionally, the preprocessing of the road data, the real-time meteorological data, and the historical meteorological database to obtain the target data includes:

[0023] The road data is preprocessed to determine the first matching degree information between the road data and the preset high-wind area characteristics;

[0024] 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;

[0025] 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.

[0026] Optionally, determining the wind zone risk value along the target vehicle's travel path by weighted summation according to the weighted data includes:

[0027] Each weighted data point is weighted by its corresponding target data to obtain multiple weighted data points.

[0028] The wind zone risk value on the target vehicle's travel path is determined based on the weighted data.

[0029] Optionally, when determining that the road ahead of the target vehicle is a crosswind area, determining the influence intensity data of the crosswind area includes:

[0030] 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;

[0031] The impact intensity data of the crosswind area is determined based on the driving data, the road data, and the real-time meteorological data.

[0032] Optionally, determining the influence intensity data of the crosswind area based on the driving data, the road data, and the real-time meteorological data includes:

[0033] 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.

[0034] 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.

[0035] 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.

[0036] The impact intensity data is determined based on the comprehensive risk value.

[0037] Optionally, 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 includes:

[0038] 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.

[0039] Adjust the vehicle parameters of the target vehicle according to the second mode.

[0040] Optionally, the vehicle status data includes lateral offset distance, lateral wind force, and vehicle torque information, and adjusting the vehicle parameters of the target vehicle according to the vehicle status data includes:

[0041] 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.

[0042] 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.

[0043] Optionally, the dynamic parameter adjustment according to the vehicle parameters of the third mode includes:

[0044] 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;

[0045] Based on the lateral offset distance, the damping coefficient of the electronic shock absorber of the target vehicle in the third mode is adjusted.

[0046] Optionally, adjusting 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:

[0047] Based on the magnitude of the crosswind force and the lateral offset distance, the wind speed change value within the crosswind area is determined;

[0048] The height change rate of the air spring height in the target vehicle is determined based on the wind speed change value.

[0049] The height of the air spring is determined according to the stated rate of change in height.

[0050] The target vehicle is adjusted according to the air spring height.

[0051] Optionally, adjusting the damping coefficient of the electronic shock absorber of the target vehicle in the third mode based on the lateral offset distance includes:

[0052] The rate of change of the offset distance of the target vehicle is determined based on the lateral offset distance;

[0053] Obtain the basic damping coefficient of the target vehicle;

[0054] The damping adjustment amount is determined based on the basic damping coefficient and the rate of change of the offset distance;

[0055] Adjust the damping coefficient of the electronic shock absorber of the target vehicle in the third mode according to the damping adjustment amount.

[0056] Optionally, the method further includes:

[0057] 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.

[0058] Optionally, the exit event includes any of the following:

[0059] 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.

[0060] A vehicle control device, the device comprising:

[0061] The data acquisition module is used to acquire road data and real-time weather data along the current driving path of the target vehicle;

[0062] 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.

[0063] 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;

[0064] 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.

[0065] 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 enter the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle status data.

[0066] An electronic device includes: a processor; and a memory for storing processor-executable instructions.

[0067] The processor is configured to execute the instructions to implement the vehicle control method described above.

[0068] A computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a mobile terminal, enables the mobile terminal to perform the vehicle control method described above.

[0069] A vehicle comprising the aforementioned electronic equipment.

[0070] The beneficial effects of this invention are:

[0071] In this embodiment of the invention, road data and real-time meteorological data of the target vehicle's current driving path are acquired; based on the road data and real-time meteorological data, it is determined whether the road ahead of the target vehicle is a crosswind area; when it is determined that the road ahead 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 has entered the crosswind area, the vehicle status 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 status data. On the one hand, crosswind areas can be accurately determined based on road data and real-time meteorological data; on the other hand, after determining that there is a crosswind area ahead, vehicle parameters are adjusted even if the vehicle has not entered the crosswind area, thereby avoiding vehicle control delay. Attached Figure Description

[0072] Figure 1 This is a flowchart illustrating the steps of a vehicle control method provided in an embodiment of the present invention;

[0073] Figure 2 This is a flowchart of another vehicle control method provided in an embodiment of the present invention;

[0074] Figure 3 This is a flowchart of another vehicle control method provided in an embodiment of the present invention;

[0075] Figure 4 This is a flowchart of another vehicle control method provided in an embodiment of the present invention;

[0076] Figure 5 This is a schematic diagram of the structure of a vehicle control device provided in an embodiment of the present invention;

[0077] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0078] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0079] It should be noted that the embodiments of the present invention may involve the use of user data. In practical applications, user-specific personal data may be used in the scheme described herein within the scope permitted by applicable laws and regulations, provided that it complies with the applicable laws and regulations of the country (e.g., with the user's explicit consent, with the user being properly notified, etc.).

[0080] Reference Figure 1 The diagram illustrates a flowchart of a vehicle control method provided in an embodiment of the present invention, which specifically includes the following steps:

[0081] Step 101: Obtain road data and real-time weather data along the target vehicle's current driving path;

[0082] In this embodiment of the invention, in order to enable the vehicle to drive safely and smoothly in the crosswind area, road data in the current driving path can be collected during the vehicle's driving process, and real-time meteorological data of the road ahead of the target vehicle in the driving segment can also be obtained by connecting to the network.

[0083] The road information may include GPS positioning data, navigation route data, and terrain feature data; the real-time meteorological data may specifically include real-time wind, wind direction data, and weather warnings.

[0084] In practical applications, the target vehicle can obtain its current location (latitude and longitude information) and driving path (including the current road segment and the coordinates of the path ahead) through the GPS module; the target vehicle can also connect to the meteorological server through the vehicle communication module (such as 4G / 5G, Wi-Fi) to obtain real-time meteorological data of the vehicle's current location and the path ahead, including wind speed, wind direction, wind duration, temperature, humidity, etc.

[0085] Step 102: Determine whether the road ahead of the target vehicle is a crosswind area based on road data and real-time weather data;

[0086] After obtaining road data and real-time weather data, we can combine the road data and real-time weather data to comprehensively analyze whether the road ahead of the target vehicle is a crosswind area. For example, road data can determine the vehicle's current location, driving path, terrain features, etc., and then determine the location of the road segment ahead of the target vehicle. By combining real-time weather data, we can determine the recent weather changes at the road segment ahead, and thus infer whether the vehicle is in a crosswind area when it arrives at that location.

[0087] Step 103: 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;

[0088] When it is determined that the road ahead is a crosswind area, the intensity of the crosswind effect can be further determined. This intensity data indicates the strength of the crosswind's impact. The stronger the crosswind effect, the more difficult it is to guarantee vehicle safety.

[0089] Step 104: When the target vehicle is detected to be about to enter the crosswind area, adjust the vehicle parameters of the target vehicle according to the impact intensity data;

[0090] When a crosswind zone is confirmed ahead, to avoid control delays when the vehicle enters the crosswind zone, the vehicle parameters of the target vehicle can be adjusted in advance according to the impact intensity data. This allows for proactive vehicle control to prepare for the upcoming crosswind zone and ensure the target vehicle can safely pass through it. These vehicle parameters may include suspension parameters, such as air spring height.

[0091] Specifically, when the distance between the target vehicle and the crosswind area is detected to be 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 impact intensity data.

[0092] Step 105: When the target vehicle is detected to have entered the crosswind area, obtain the vehicle status data of the target vehicle affected by the crosswind in the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle status data.

[0093] Once the target vehicle has entered the crosswind area according to the adjusted vehicle parameters, the vehicle status data under the actual influence of the crosswind area can be obtained. The vehicle status data can include data such as lateral offset distance, crosswind force, and vehicle torque information.

[0094] After obtaining the vehicle status data of the target vehicle under the influence of crosswinds, the vehicle parameters of the target vehicle can be adjusted according to the vehicle status data to cope with the actual crosswind impact and ensure the safe driving of the target vehicle.

[0095] In this embodiment of the invention, on the one hand, the target vehicle can accurately determine the crosswind area based on road data and real-time meteorological data; on the other hand, after determining that there is a crosswind area ahead, the vehicle parameters are adjusted when it is about to enter the crosswind area, thereby avoiding vehicle control delay.

[0096] Reference Figure 2 The diagram illustrates a flowchart of a vehicle control method provided in an embodiment of the present invention, which specifically includes the following steps:

[0097] Step 201: Obtain road data and real-time weather data along the target vehicle's current driving path;

[0098] Step 202: Determine the wind zone risk value on the target vehicle's driving path, based on road data and real-time meteorological data, to represent the probability that the road ahead of the target vehicle is a crosswind area;

[0099] In practical applications, after obtaining road data and real-time meteorological data, in order to accurately determine whether the area in front of the target vehicle is a crosswind area, the road data and real-time meteorological data can be used as reference data to calculate the wind zone risk value, which represents the probability that the road in front of the target vehicle is a crosswind area. Thus, the crosswind area can be determined through quantitative calculation.

[0100] In one embodiment of the present invention, step 202 may include the following sub-steps: obtaining the historical meteorological database corresponding to the current driving path; and determining the wind zone risk value on the target vehicle's driving path based on the road data, the real-time meteorological data, and the historical meteorological database.

[0101] In practical applications, historical meteorological databases can be used to determine wind zone risk values. These databases can be accessed locally on the vehicle or via the cloud. The data in these databases can include historical records of geographical location, season, and time period. Stored on local or cloud servers, these databases can be used to further confirm the likelihood of crosswind impact areas by comparing the driving route with historical crosswind impact data.

[0102] After obtaining road data and real-time weather data, we can combine the road data and real-time weather data to comprehensively analyze whether the road ahead of the target vehicle is a crosswind area. For example, road data can determine the vehicle's current location, driving path, terrain features, etc., and then determine the location of the road segment ahead of the target vehicle. Then, combined with real-time weather data, we can determine the recent weather changes at the road segment ahead, and thus infer whether the vehicle is in a crosswind area when it arrives at that location.

[0103] To further accurately determine the crosswind area, information such as meteorological patterns of the road section can be analyzed by combining records from historical meteorological databases. This allows for the determination of the crosswind area by combining road data, real-time meteorological data, and historical meteorological databases.

[0104] In one embodiment of the present invention, 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 following sub-steps:

[0105] Sub-step 11 involves preprocessing the road data, the real-time meteorological data, and the historical meteorological database to obtain the target data.

[0106] In practical applications, the preprocessing process can include the following steps:

[0107] (1) Preprocess the road data to determine the first matching degree information between the road data and the preset high wind zone characteristics;

[0108] In practical applications, road data can be compared with preset high-wind zone features to determine the first degree of matching between the two. The higher the degree of matching, the closer the road data is to the features of the high-wind zone.

[0109] (2) Preprocess the real-time meteorological data to determine the degree information of the real-time meteorological data exceeding the benchmark threshold corresponding to the crosswind area;

[0110] Based on real-time meteorological data, the real-time meteorological data can be compared with the benchmark threshold corresponding to the crosswind area. When the real-time meteorological data exceeds the high benchmark threshold, it indicates that there is a crosswind area more likely to exist in the road section ahead. Thus, the degree information of the real-time meteorological data exceeding the benchmark threshold corresponding to the crosswind area can be determined, and the possibility of the crosswind area can be assessed based on the degree information.

[0111] (3) Preprocess the historical meteorological data to determine the second matching degree information of the crosswind area in front of the target vehicle in the historical meteorological database.

[0112] Sub-step 12: Determine the weight data corresponding to the road data, the real-time meteorological data, and the historical meteorological database respectively;

[0113] Different types of data can be assigned weights, with weight values ​​ranging from 0 to 1 (excluding 0 and 1), which can be set according to the actual scenario. The sum of multiple weights is 1.

[0114] For example, the first weighted data + the second weighted data + the third weighted data = 1.

[0115] Sub-step 13: The target data is weighted and summed according to the weighted data to determine the wind zone risk value on the target vehicle's driving path.

[0116] That is, the risk value of the wind zone = weighted data 1 * target data 1 + ... weighted data n * weighted data n.

[0117] In one embodiment of the present invention, the target vehicle can be weighted by each weighted data and the corresponding target data to obtain multiple weighted data; the wind zone risk value on the driving path of the target vehicle is determined based on the multiple weighted data.

[0118] Based on the foregoing analysis, the wind zone risk value = α × (the degree of matching between road data and high-wind zone characteristics) + β × (the degree to which meteorological data exceeds the baseline threshold) + γ × (the degree of matching between historical meteorological databases).

[0119] Wherein, α is the road data weighting factor (i.e., the first weighting data), β is the real-time meteorological data weighting factor (i.e., the second weighting data), and γ is the historical meteorological data weighting factor (i.e., the third weighting data).

[0120] Step 203: When the risk value of the wind zone is greater than the preset risk threshold, determine whether the road in front of the target vehicle is a crosswind zone.

[0121] The preset risk threshold is a critical value for judging crosswind areas, which can be set according to the actual scenario, and is not limited in this embodiment of the invention.

[0122] Step 204: 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;

[0123] Step 205: When the target vehicle is detected to be about to enter the crosswind area, adjust the vehicle parameters of the target vehicle according to the impact intensity data;

[0124] Step 206: When the target vehicle is detected to have entered the crosswind area, obtain the vehicle status data of the target vehicle affected by the crosswind in the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle status data.

[0125] In this embodiment of the invention, the risk value of the wind zone can be quantitatively calculated based on road data and real-time meteorological data, thereby accurately determining whether there is a crosswind area in front of the target vehicle, and thus ensuring the safety of the vehicle when driving in a crosswind area.

[0126] Reference Figure 3 The diagram illustrates a flowchart of a vehicle control method provided in an embodiment of the present invention, which specifically includes the following steps:

[0127] Step 301: Obtain road data and real-time weather data along the target vehicle's current driving path;

[0128] Step 302: Determine whether the road ahead of the target vehicle is a crosswind area based on road data and real-time meteorological data;

[0129] Step 303: When it is determined that the road ahead of the target vehicle is a crosswind area, obtain the driving data of the target vehicle;

[0130] In this embodiment of the invention, the driving data of the target vehicle may include real-time vehicle speed data, real-time vehicle load data, and a reference value for the upper limit of stable driving speed.

[0131] Step 304: Determine the intensity of the crosswind area's impact based on driving data, road data, and real-time meteorological data;

[0132] In practical applications, the impact intensity of crosswind areas can be quantitatively calculated by combining driving data, road data, and real-time meteorological data to better characterize the impact of crosswind areas.

[0133] In one embodiment of the present invention, determining the influence intensity data of the crosswind area based on driving data, road data, and real-time meteorological data includes:

[0134] Step 21: Obtain the wind direction angle from real-time meteorological data, and calculate the wind direction influence coefficient based on the wind direction angle;

[0135] In practical applications, real-time meteorological data can include crosswind direction, and the wind direction angle within the current crosswind area can be determined based on the crosswind direction. The wind direction angle is the angle between the vehicle's direction of travel and the wind direction.

[0136] The calculation process for the wind direction influence coefficient is as follows:

[0137] Wind direction influence coefficient = |90° - wind direction angle| / 90°.

[0138] Step 22: Determine the basic risk value 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;

[0139] Specifically, the wind speed data in real-time meteorological data can include the current wind speed / wind speed upper limit benchmark value, and the basic risk value can be calculated according to the following formula:

[0140] Basic risk value = (current wind speed / wind speed upper limit benchmark value) × wind direction influence coefficient × terrain coefficient;

[0141] The terrain coefficient can be set according to the terrain type.

[0142] Step 23: Determine the vehicle speed coefficient and load coefficient based on the driving data, and determine the comprehensive risk value based on the vehicle speed coefficient, load coefficient and basic risk value;

[0143] Overall risk value = Basic risk value × (1 + Speed ​​coefficient) × (1 + Load coefficient)

[0144] Among them, the speed coefficient = current speed / upper limit of stable driving speed, and the load coefficient = actual load / maximum load.

[0145] Step 24: Determine the impact intensity data based on the comprehensive risk value.

[0146] In practical applications, the impact intensity data can be divided into three levels: low-risk impact, medium-risk impact, and high-risk impact, with each level corresponding to a risk threshold.

[0147] When the overall risk value is less than the low-risk threshold, the impact intensity data is determined to be at the low-risk impact level; when the low-risk threshold is less than or equal to the overall risk value and less than the medium-risk threshold, the impact intensity data is determined to be at the medium-risk impact level; when the medium-risk threshold is less than or equal to the overall risk value and less than the high-risk threshold, the impact intensity data is determined to be at the high-risk impact level.

[0148] Step 305: When the target vehicle is detected to be about to enter the crosswind area, adjust the vehicle parameters of the target vehicle according to the impact intensity data;

[0149] Step 306: When the target vehicle is detected to have entered the crosswind area, obtain the vehicle status data of the target vehicle affected by the crosswind in the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle status data.

[0150] In this embodiment of the invention, driving data, road data, and real-time meteorological data are used to quantitatively assess the impact intensity of crosswind areas, so as to more accurately determine the impact within the crosswind area and thus effectively ensure the safe driving of vehicles within the crosswind area.

[0151] Reference Figure 4 The diagram illustrates a flowchart of a vehicle control method provided in an embodiment of the present invention, which specifically includes the following steps:

[0152] Step 401: Obtain road data and real-time weather data along the target vehicle's current driving path;

[0153] Step 402: Determine whether the road ahead of the target vehicle is a crosswind area based on road data and real-time meteorological data;

[0154] 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;

[0155] Step 404: When the target vehicle is detected to be about to enter the crosswind area, if the impact intensity data is medium or high risk, switch the vehicle mode of the target vehicle from the first mode to the second mode.

[0156] In the second mode, the height of the second air spring of the target vehicle is lower than that 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 that of the first damping coefficient of the electronic shock absorber of the target vehicle in the first mode.

[0157] In practical applications, the vehicle operation modes in the target vehicle can include a first mode, a second mode, and a third mode. The first mode is used for daily driving, while the second and third modes are safety driving modes set for crosswind scenarios.

[0158] During vehicle operation, the system defaults to Mode 1. However, if a crosswind area is detected ahead, and the impact intensity data indicates a medium or high risk, Mode 1 can be switched to Mode 2 to adapt to the crosswind area and ensure safe passage. When the impact intensity data indicates a low risk, meaning the crosswind has minimal impact, the vehicle can continue to enter the crosswind area in Mode 1.

[0159] Step 405: Adjust the vehicle parameters of the target vehicle according to the second mode;

[0160] 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, this can include adjusting the vehicle suspension parameters.

[0161] For example, if the crosswind area is predicted to be of medium or high risk, the system will enter crosswind control mode (i.e., mode 2) and the suspension system will be adjusted in advance.

[0162] (1) Based on the crosswind intensity prediction of medium risk, reduce the height of the air spring (e.g., reduce the standard height by 10%-20%), optimize the load distribution under crosswind action, and reduce the vehicle's roll angle; increase the damping force of the electronic shock absorber (e.g., increase the damping coefficient by 10%-20%), enhance the suspension system's ability to control the vehicle's attitude, and improve crosswind stability.

[0163] (2) Based on the prediction that the crosswind intensity is high risk, reduce the height of the air spring (e.g., reduce the standard height by 20%-40%); increase the damping force of the electronic shock absorber (e.g., increase the damping coefficient by 20%-40%).

[0164] Step 406: When the target vehicle is detected to have entered the crosswind area, acquire vehicle status data of the target vehicle affected by the crosswind in the crosswind area.

[0165] The vehicle status data includes lateral offset distance, lateral wind force, and vehicle torque information;

[0166] In practical applications, the steps for real-time monitoring of vehicle status include:

[0167] a) Measure the lateral deviation distance between the vehicle and the lane lines using cameras and radar;

[0168] b) The magnitude and direction of the lateral wind force acting on the vehicle are measured in real time using wind sensors;

[0169] c) The steering wheel angle and operating torque of the driver are measured in real time by a steering wheel angle sensor and a steering wheel torque sensor.

[0170] Step 407: When the lateral offset distance or lateral wind force is greater than the first preset threshold and the vehicle torque information is less than the torque threshold, control the target vehicle to continue driving according to the vehicle parameters of the first mode.

[0171] The first preset threshold and the torque threshold can be preset by the vehicle system, for example, lateral offset distance ≥ 0.5 meters, lateral wind force ≥ 300 Newtons, turning angle ≤ 5 degrees, and torque ≤ 10 Newtons.

[0172] Step 408: When the lateral offset distance or lateral wind force is greater than the second preset threshold and the vehicle torque information is less than the torque threshold, control the target vehicle to switch the vehicle mode to the third mode and make dynamic parameter adjustments according to the vehicle parameters of the third mode, wherein the first preset threshold is less than the second preset threshold.

[0173] The first preset threshold and the torque threshold can be preset by the vehicle system. For example, the second preset threshold is: lateral offset distance ≥ 1.0 meter, lateral wind force ≥ 500 Newtons, turning angle ≤ 5 degrees, and torque ≤ 10 Newtons.

[0174] In practical applications, once a vehicle enters a crosswind area, dynamic control of the target vehicle can be achieved by monitoring its actual changes within the crosswind area.

[0175] In one embodiment of the present invention, dynamic parameter adjustment according to the vehicle parameters of the third mode includes:

[0176] Sub-step 31: 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;

[0177] In practical applications, the air spring height of the target vehicle in the third mode can be dynamically adjusted based on the real-time lateral wind force and lateral offset distance.

[0178] In one embodiment of the present invention, the process of determining the air spring height in the third mode is as follows: based on the magnitude of 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 in 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.

[0179] In this embodiment of the invention, the air spring height can be gradually reduced based on the magnitude of 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 should be adjusted according to the relationship between the wind speed change rate and the height change rate, thereby optimizing the vehicle load distribution and crosswind resistance. For example, the height can be reduced by 5% for every 10 m / s increase in wind speed.

[0180] Sub-step 32: Based on the lateral offset distance, adjust the damping coefficient of the electronic shock absorber of the target vehicle in the third mode.

[0181] Within the crosswind zone, the damping coefficient of the electronic shock absorber in the third mode of the target vehicle can also be dynamically adjusted by the lateral offset distance.

[0182] In one embodiment of the present invention, the damping coefficient of the electronic shock absorber of the target vehicle in the third mode is adjusted based on the lateral offset distance. The method includes: determining the rate of change of the offset distance 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 rate of change of the offset distance; and adjusting the damping coefficient of the electronic shock absorber of the target vehicle in the third mode according to the damping adjustment amount.

[0183] The stability of the suspension system is enhanced by increasing the tensile and compressive damping forces of the shock absorber according to the rate of change of offset distance. The damping coefficient is calculated as follows:

[0184] Damping adjustment amount = base damping value × (1 + rate of change of offset distance);

[0185] Wherein, the rate of change of offset distance = (lateral offset distance 1 - lateral offset distance 2) / sampling time interval.

[0186] The damping coefficient can be determined based on the damping adjustment amount.

[0187] In one embodiment of the present invention, vehicle attitude optimization can also be performed. 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 impact of crosswinds on the lateral stability of the vehicle. At the same time, a fuzzy control algorithm is implemented to comprehensively adjust the suspension parameters based on multiple vehicle state parameters, thereby achieving multi-objective optimization of vehicle attitude (such as minimum offset distance and minimum body attitude change).

[0188] For example, a fuzzy inference system can be established with lateral offset, offset change rate, wind force level, and roll angle as input variables, and four-wheel independent height adjustment and damping control as output variables to achieve the goals of vehicle dynamic balance stability and comfort.

[0189] In one embodiment of the present invention, when the target vehicle is in the second mode or the third mode, if a preset exit event is detected, the target vehicle is controlled to switch from the second mode or the third mode to the first mode.

[0190] In one example, the exit event includes any of the following:

[0191] 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.

[0192] The following describes the process of exiting the second mode (i.e., crosswind control mode) or the third mode (i.e., high-precision adjustment mode) in detail with reference to the exit event in the embodiments of the present invention:

[0193] (1) Driver active control detection: If the steering wheel angle exceeds the predetermined threshold (e.g., >10 degrees) or the operating torque exceeds the predetermined threshold (e.g., >30 Nm), the system determines that the driver is actively controlling the vehicle, shuts down the crosswind correction module, and exits the high-precision adjustment mode or crosswind control mode.

[0194] (2) Crosswind impact reduction detection: If the real-time measured lateral offset distance and lateral wind force are both lower than the first predetermined threshold (e.g., offset distance < 0.5 meters, wind force < 300 Newtons), the system determines that the crosswind impact is reduced and gradually reduces the intensity of the crosswind correction module until it completely exits the high-precision adjustment mode.

[0195] (3) Abnormal state detection and exit: If the system detects that the vehicle's ABS function or other functions are triggered (indicating that the vehicle has lost control or there are other abnormal states), or if real-time monitoring data indicates that the vehicle's deviation distance exceeds the safe range (e.g., >1.5 meters), the system will immediately exit the high-precision adjustment mode or crosswind control mode and issue an alarm to prompt the driver to take over control.

[0196] Once the target vehicle exits the high-precision adjustment mode, the system gradually restores the air spring height and electronic shock absorber damping characteristics to normal driving parameters (e.g., the air spring height is restored to the standard value, and the shock absorber damping is restored to the comfort mode).

[0197] In this embodiment of the invention, the target vehicle can adjust different vehicle parameters depending on whether the vehicle is in a crosswind area. When it is not in a crosswind area, static parameter adjustments can be made in advance. After entering a crosswind area, the vehicle parameters can be dynamically adjusted based on real-time vehicle status data, thereby effectively ensuring the safe driving of the vehicle in the crosswind area.

[0198] Reference Figure 5 The diagram shows a structural schematic of a vehicle control device provided in an embodiment of the present invention, which specifically includes the following modules:

[0199] Data acquisition module 501 is used to acquire road data and real-time weather data in the current driving path of the target vehicle;

[0200] The crosswind area determination module 502 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.

[0201] The influence intensity data determination module 503 is used 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;

[0202] Crosswind control module 504 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.

[0203] The crosswind control module 505 is used to acquire vehicle status data of the target vehicle affected by the crosswind in the crosswind area when the target is detected to enter the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle status data.

[0204] In one embodiment of the present invention, the crosswind area determination module 502 may include:

[0205] The wind zone risk value determination submodule is used to determine the wind zone risk value on the target vehicle's driving path by using the road data and the real-time meteorological data. The wind zone risk value is used to represent the probability that the road in front of the target vehicle is a crosswind area.

[0206] The crosswind area determination submodule is used to determine the road in front of the target vehicle as a crosswind area when the risk value of the wind area is greater than a preset risk threshold.

[0207] In one embodiment of the present invention, the wind zone risk value determination submodule may include:

[0208] The historical meteorological database acquisition unit is used to acquire the historical meteorological database corresponding to the current driving path;

[0209] The wind zone risk value determination unit is used to determine the wind zone risk value on the target vehicle's travel path based on the road data, the real-time meteorological data, and the historical meteorological database.

[0210] In one embodiment of the present invention, the wind zone risk value determination unit includes:

[0211] The target data determination subunit is used to preprocess the road data, the real-time meteorological data, and the historical meteorological database respectively to obtain the target data.

[0212] The weight data determination subunit is used to determine the weight data corresponding to the road data, the real-time meteorological data, and the historical meteorological database, respectively.

[0213] The wind zone risk value determination subunit is used to perform weighted summation on the target data according to the weighted data to determine the wind zone risk value on the target vehicle's driving path.

[0214] In one embodiment of the present invention, the target data determination subunit may include:

[0215] The first matching degree information determination block is used to preprocess the road data and determine the first matching degree information between the road data and the preset high wind area features;

[0216] The degree information determination block is used to preprocess the real-time meteorological data and determine the degree information of the real-time meteorological data exceeding the benchmark threshold corresponding to the crosswind area;

[0217] The second matching degree information determination block is used to preprocess the historical meteorological data and determine the second matching degree information of the crosswind area in front of the target vehicle in the historical meteorological database.

[0218] In one embodiment of the present invention, the wind zone risk value determination subunit may include:

[0219] The weighted data determination block is used to weight each weighted data point with the corresponding target data to obtain multiple weighted data points.

[0220] The wind zone risk value determination block is used to determine the wind zone risk value on the target vehicle's driving path based on the multiple weighted data.

[0221] In one embodiment of the present invention, the influence intensity data determination module 503 may include:

[0222] The driving data determination submodule is used to acquire the driving data of the target vehicle when it is determined that the road ahead of the target vehicle is a crosswind area;

[0223] The impact intensity determination submodule is used to determine the impact intensity data of the crosswind area based on the driving data, the road data, and the real-time meteorological data.

[0224] In one embodiment of the present invention, the submodule for determining the intensity of influence may include:

[0225] The wind direction influence coefficient calculation unit is used to obtain the wind direction angle from the real-time meteorological data and calculate the wind direction influence coefficient based on the wind direction angle.

[0226] The basic risk value determination unit is used to determine the basic risk value 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.

[0227] The comprehensive risk value determination unit is used to determine the vehicle speed coefficient and load coefficient based on the driving data, and to determine the comprehensive risk value based on the vehicle speed coefficient, the load coefficient and the basic risk value;

[0228] The impact intensity data determination unit is used to determine the impact intensity data based on the comprehensive risk value.

[0229] In one embodiment of the present invention, the crosswind control module 504 may include:

[0230] The mode switching submodule is used to switch the vehicle mode of the target vehicle from the first mode to the second mode when it is detected that the target vehicle has not entered the crosswind area and the influence intensity data is medium risk or high risk. 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.

[0231] The vehicle parameter adjustment submodule is used to adjust the vehicle parameters of the target vehicle according to the second mode.

[0232] In one embodiment of the present invention, the vehicle status data includes lateral offset distance, lateral wind force, and vehicle torque information, and the crosswind control module 505 may include:

[0233] The first mode maintenance submodule is used to control 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 first preset threshold and the vehicle torque information is less than the torque threshold.

[0234] The third mode switching submodule is used to control the vehicle mode of the target vehicle to switch to the third 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, and to make dynamic parameter adjustments according to the vehicle parameters of the third mode, wherein the first preset threshold is less than the second preset threshold.

[0235] In one embodiment of the present invention, the third mode switching submodule may include:

[0236] An air spring height adjustment unit is used to adjust the air spring height of the target vehicle in the third mode based on the magnitude of the lateral wind force and the lateral offset distance.

[0237] A damping coefficient adjustment unit is used to adjust the damping coefficient of the electronic shock absorber of the target vehicle in the third mode based on the lateral offset distance.

[0238] In one embodiment of the present invention, the damping coefficient adjustment unit may include:

[0239] The wind speed change value determination subunit is used to determine the wind speed change value in the crosswind area based on the crosswind force magnitude and the crosswind offset distance;

[0240] The height change rate determination subunit is used to determine the height change rate of the air spring height in the target vehicle based on the wind speed change value.

[0241] An air spring height subunit is used to determine the air spring height according to the height change rate.

[0242] The vehicle adjustment subunit is used to adjust the target vehicle according to the height of the air spring.

[0243] In one embodiment of the present invention, the damping coefficient adjustment unit may include:

[0244] Offset distance change rate determination subunit, used to determine the offset distance change rate of the target vehicle based on the lateral offset distance;

[0245] The basic damping coefficient acquisition subunit is used to acquire the basic damping coefficient of the target vehicle;

[0246] The damping adjustment determination subunit is used to determine the damping adjustment amount based on the basic damping coefficient and the rate of change of the offset distance.

[0247] The damping coefficient determination subunit is used to adjust the damping coefficient of the electronic shock absorber of the target vehicle in the third mode according to the damping adjustment amount.

[0248] In one embodiment of the present invention, the device further includes:

[0249] The exit event response module is used 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.

[0250] In one embodiment of the present invention, the exit event includes any one of the following:

[0251] 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.

[0252] In this embodiment of the invention, road data and real-time meteorological data in the current driving path of the target vehicle are acquired; based on the road data and the real-time meteorological data, it is determined whether the road ahead of the target vehicle is a crosswind area; when it is determined that the road ahead 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 has entered the crosswind area, the vehicle status 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 status data. On the one hand, crosswind areas can be accurately determined based on road data, real-time meteorological data, and historical meteorological databases; on the other hand, after determining that the road ahead is a crosswind area, vehicle parameters are adjusted even if the vehicle has not entered the crosswind area, thereby avoiding vehicle control delay.

[0253] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0254] This invention also provides an electronic device, such as... Figure 6 As shown, it includes a processor 601, a device interface 602, a memory 603, and a bus 604;

[0255] Memory 603 is used to store computer programs;

[0256] The processor 601 performs the above steps when executing the program stored in the memory 603.

[0257] The bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0258] The memory may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0259] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0260] The present invention also provides a storage medium that, when the instructions in the storage medium are executed by the processor of an electronic device, enables the electronic device to perform the vehicle control method of the foregoing embodiments.

[0261] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0262] The algorithms and displays provided herein are not inherently related to any particular computer, virtual device, or other equipment. The structure required to construct such a device is readily apparent from the above description. Furthermore, this invention is not directed to any particular programming language. It should be understood that the contents of the invention described herein can be implemented using various programming languages, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the invention.

[0263] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0264] Similarly, it should be understood that, in order to simplify the invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this method of disclosure should not be construed as reflecting an intention that the claimed invention requires more features than expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0265] Those skilled in the art will understand that modules in the device of the embodiments can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components. Except where at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or device so disclosed. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0266] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the sorting device according to the present invention. The present invention can also be implemented as a device or apparatus program for performing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0267] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0268] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0269] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0270] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0271] It should be noted that the various data-related processes in the embodiments of this application are carried out in compliance with the relevant data protection laws and policies of the country where the location is located, and with the authorization granted by the owner of the corresponding device.

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, the 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. 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 meteorological 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.

2. The method according to claim 1, characterized in that, 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.

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, 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.

4. The method according to claim 3, 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.

5. The method according to claim 3, characterized in that, The step of weighting and summing the target data according to the weighted data to determine the wind zone risk value along 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.

6. 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.

7. The method according to claim 6, 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.

8. 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.

9. The method according to claim 8, 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.

10. The method according to claim 9, 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.

11. The method according to claim 10, 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.

12. The method according to claim 10, 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.

13. 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.

14. The method according to claim 13, 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.

15. 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 enter the crosswind area, and adjust the vehicle parameters of the target vehicle according to the vehicle status data. The crosswind area determination module includes: The wind zone risk value determination submodule is used to determine the wind zone risk value on the target vehicle's driving path by using the road data and the real-time meteorological data. The wind zone risk value is used to represent the probability that the road in front of the target vehicle is a crosswind area. The crosswind area determination submodule is used to determine the road in front of the target vehicle as a crosswind area when the risk value of the wind area is greater than a preset risk threshold.

16. 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 14.

17. 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 14.

18. A vehicle, characterized in that, The vehicle includes the electronic equipment as described in claim 16.

Images