Vehicle control method and related equipment

Abstract

The present invention provides a vehicle control method and related equipment, belonging to the field of vehicle driving technology. The method includes: obtaining the road surface material, road surface characteristics, and slippery state of the road currently located by the vehicle, and obtaining the total weight of the vehicle; determining the road surface type of the road based on the road surface material and road surface characteristics, and determining the center of mass position of the vehicle based on the total weight; determining the target control parameters of the vehicle based on the center of mass position, the total weight, the road surface type, and the slippery state; and driving according to the target control parameters. In the present invention, by obtaining the total weight, road surface material, road surface characteristics, and slippery state of the vehicle during driving, the control parameters of the vehicle are determined in real time, so that the vehicle driving according to the control parameters matches the current driving state of the vehicle, improving the configuration accuracy of the vehicle control parameters and ensuring the safety of people in the vehicle.

Description

Technical Field

[0001] The present invention relates to the field of vehicle driving technology, and in particular to a vehicle control method and related equipment. Background Art

[0002] In order to improve the competitiveness of vehicles, vehicle intelligence has become the current development trend.

[0003] The level of intelligence of a vehicle is reflected in its intelligent driving system. The intelligent driving system can configure control parameters for the vehicle and control the vehicle's driving through these control parameters.

[0004] Currently, intelligent driving systems configure control parameters based on vehicle parameters, such as weight and center of mass. However, these parameters vary during actual driving. For example, the center of mass position varies depending on the position of the occupants. Control parameters configured by intelligent driving systems based on fixed vehicle parameters may not be consistent with the vehicle's current state, compromising safety for both the occupants and the vehicle's passengers. Summary of the Invention

[0005] The present invention provides a vehicle control method and related equipment to solve the problem of low safety of vehicle occupants.

[0006] In one aspect, the present invention provides a vehicle control method, comprising:

[0007] Obtaining the road surface material, road surface characteristics, and slippery conditions of the road the vehicle is currently on, and obtaining the total weight of the vehicle;

[0008] Determining a road surface type of the road according to the road surface material and the road surface characteristics, and determining a center of mass position of the vehicle according to the total weight;

[0009] determining a target control parameter of the vehicle according to the center of mass position, the total weight, the road surface type, and the slippery state;

[0010] Drive according to the target control parameters.

[0011] In one embodiment, determining the target control parameter of the vehicle based on the center of mass position, the total weight, the road surface type, and the slippery state includes:

[0012] determining a friction force of the road on the vehicle according to the road surface type and the slippery state, and determining a ground adhesion force of the road on the vehicle according to the friction force;

[0013] Acquiring a lateral acceleration of the vehicle, and determining a target lateral force of the vehicle according to the lateral acceleration;

[0014] determining a longitudinal traction force of the vehicle according to the target lateral force and the ground adhesion;

[0015] The center of mass position, the total weight, the road surface type, the slippery state, and the longitudinal traction are input into a vehicle dynamics model to obtain target control parameters of the vehicle.

[0016] In one embodiment, determining the target lateral force of the vehicle according to the lateral acceleration includes:

[0017] Calculating a first lateral force of the vehicle according to the lateral acceleration, and obtaining wind force information at a current position of the vehicle;

[0018] A second lateral force generated by wind on the vehicle is determined according to the wind force information, and a target lateral force of the vehicle is determined according to the first lateral force and the second lateral force.

[0019] In one embodiment, determining the target lateral force of the vehicle according to the lateral acceleration includes:

[0020] calculating a first lateral acceleration of the vehicle according to the lateral acceleration, and obtaining a change in air pressure of an environment in which the vehicle is located;

[0021] When the air pressure change is greater than a preset change, a third lateral force generated by the air pressure on the vehicle is determined according to the air pressure change, and a target lateral force of the vehicle is determined according to the first lateral force and the third lateral force.

[0022] In one embodiment, obtaining the lateral acceleration of the vehicle includes:

[0023] Obtaining a change in air pressure in the environment in which the vehicle is located;

[0024] When the air pressure change is greater than a preset change, the lateral acceleration of the vehicle is obtained.

[0025] In one embodiment, obtaining the air pressure change in the environment in which the vehicle is located includes:

[0026] Obtaining the location of the vehicle;

[0027] When the vehicle is located at a preset position, the air pressure change of the environment in which the vehicle is located is obtained, and the preset position is a tunnel or a mountain road.

[0028] In one embodiment, inputting the center of mass position, the total weight, the road surface type, the slippery state, and the total lateral force into a vehicle dynamics model to obtain target control parameters of the vehicle includes:

[0029] Inputting the center of mass position, the total weight, the road surface type, the slippery state, and the total lateral force into a vehicle dynamics model to obtain control parameters to be determined;

[0030] Acquiring road condition information of the road and environmental condition information of the vehicle;

[0031] The control parameter to be determined is corrected according to the road condition information and the environmental vehicle condition information to obtain the target control parameter.

[0032] In one embodiment, the vehicle is provided with a first sensor for collecting the weight of a seat, a second sensor for collecting the weight of items in the vehicle, and a third sensor for collecting the weight of fuel in a fuel tank, and the vehicle is provided with a built-in image acquisition module; obtaining the total weight of the vehicle includes:

[0033] Obtaining the initial weight of the vehicle, the load-bearing weight collected by the first sensor, the weight of the item collected by the second sensor, and the weight of the fuel collected by the third sensor;

[0034] Determining the posture and seating position of each person in the vehicle based on the images captured by the image acquisition module;

[0035] Determining the weight of the person according to the person's posture and the corresponding load-bearing weight of the seat where the person is seated;

[0036] The total weight of the vehicle is determined according to the weight of the person, the initial weight, the weight of the object, and the weight of the fuel.

[0037] In another aspect, the present invention further provides a vehicle comprising:

[0038] An acquisition module is used to obtain the road surface material, road surface characteristics, and slippery state of the road on which the vehicle is currently located, and to obtain the total weight of the vehicle;

[0039] a determination module, configured to determine a pavement type of the road according to the pavement material and the pavement characteristics, and to determine a center of mass position of the vehicle according to the total weight;

[0040] The determination module is further configured to determine a target control parameter of the vehicle based on the center of mass position, the total weight, the road surface type, and the slippery state;

[0041] A control module is used for driving according to the target control parameters.

[0042] In another aspect, the present invention further provides a vehicle, comprising: a memory and a processor;

[0043] The memory is used to store program instructions;

[0044] The processor is used to call the program instructions in the memory to execute the vehicle control method as described above.

[0045] On the other hand, the present invention further provides a computer-readable storage medium having a computer program stored thereon; when the computer program is executed, the vehicle control method described above is implemented.

[0046] The vehicle control method and related equipment provided by the present invention instantly determine the vehicle control parameters by obtaining the total weight, road material, road characteristics and slippery conditions of the vehicle during driving, so that the vehicle traveling according to the control parameters matches the current driving state of the vehicle, thereby improving the configuration accuracy of the vehicle control parameters and ensuring the safety of people in the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0048] Figure 1 This is an application scenario diagram for implementing the vehicle control method of the present invention;

[0049] Figure 2 This is a flow chart of a first embodiment of a vehicle control method according to the present invention;

[0050] Figure 3 This is a detailed flowchart of step S203 in the second embodiment of the vehicle control method of the present invention;

[0051] Figure 4 This is a detailed flowchart of step S302 in the third embodiment of the vehicle control method of the present invention;

[0052] Figure 5 This is a detailed flowchart of step S302 in the fourth embodiment of the vehicle control method of the present invention;

[0053] Figure 6 This is a detailed flowchart of step S304 in the fifth embodiment of the vehicle control method of the present invention;

[0054] Figure 7 A schematic diagram of a module of the vehicle of the present invention;

[0055] Figure 8 Schematic diagram of the hardware structure of the vehicle of the present invention.

[0056] The above drawings illustrate specific embodiments of the present disclosure, which will be described in more detail below. These drawings and textual descriptions are not intended to limit the scope of the present disclosure in any way, but rather to illustrate the concepts of the present disclosure to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0057] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0058] Reference Figure 1 , Figure 1 In order to realize the application scenario diagram of the vehicle control method provided by the present invention, the vehicle 100 is provided with an external image acquisition module (not shown), through which the road surface material, road surface characteristics and slippery state of the road on which the vehicle 100 is located can be obtained. In addition, a weight sensor or a pressure sensor (not shown) is provided on the vehicle 100, which can be used to detect the total weight of the vehicle. The vehicle 100 determines the road surface type of the road by the road surface material and road surface characteristics, and determines the center of mass position of the vehicle based on the total weight, thereby determining the target control parameters of the vehicle 100 by the center of mass position, total weight, road surface type and slippery state, and then causing the vehicle 100 to travel according to the target control parameters. The target control parameters include control parameters such as steering angle and acceleration.

[0059] The following specific embodiments describe in detail the technical solutions of the present invention and how the technical solutions of this application solve the above-mentioned technical problems. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. The following embodiments of the present invention are described in conjunction with the accompanying drawings.

[0060] Reference Figure 2 , Figure 2 In a first embodiment of the vehicle control method of the present invention, the vehicle control method includes the following steps:

[0061] Step S201, obtaining the road surface material, road surface characteristics and slippery state of the road the vehicle is currently on, and obtaining the total weight of the vehicle.

[0062] In this embodiment, the vehicle is equipped with an external camera and a built-in weight sensor or pressure sensor. While the vehicle is driving, the camera is controlled to capture images of the road on which the vehicle is traveling and identify the road in the image, thereby determining the road's pavement material, pavement characteristics, and slippery condition. Examples of pavement materials include asphalt concrete or cement, and examples of pavement characteristics include whether the road surface is smooth or not. The slippery condition refers to whether there is a significant amount of water, ice, or snow on the road. If there is a significant amount of water, ice, or snow on the road, the road's slippery condition is considered slippery. If there is no water, ice, or snow on the road, the road's slippery condition is considered non-slippery.

[0063] While the vehicle is in motion, it can use built-in weight sensors or pressure sensors to determine the weight of people, objects, and fuel inside the vehicle. The vehicle itself has an initial weight, which refers to the weight of the vehicle without people, objects, or fuel. The total vehicle weight can be calculated by combining the weight detected by the weight sensors or pressure sensors with the initial weight.

[0064] Step S202 , determining the road type according to the road material and road characteristics, and determining the center of mass position of the vehicle according to the total weight.

[0065] The vehicle determines the road surface type based on the road surface material and road surface characteristics. For example, if the road surface material is asphalt concrete and the road surface characteristics are rough, the road surface type can be determined to be asphalt.

[0066] The vehicle's center of mass is determined by its gross weight. Specifically, if the vehicle has a regular shape, its initial center of mass is its center of gravity. However, the weight of the occupants, fuel, and other items in the vehicle can cause the center of mass to shift. The vehicle determines the center of mass shift based on these weights, and then uses this shift to correct the initial center of mass, ultimately determining the vehicle's current center of mass.

[0067] Step S203 : determining target control parameters of the vehicle according to the center of mass position, total weight, road surface type, and slippery condition.

[0068] Step S204: driving according to target control parameters.

[0069] After determining the vehicle's center of mass and road surface type, the vehicle's center of mass, gross weight, road surface type, and slippery conditions are input into the vehicle dynamics model within the vehicle's chassis dynamics system. This output generates target control parameters, including steering angle and acceleration. Once these target control parameters are determined, the vehicle can then drive according to them.

[0070] In this embodiment, by obtaining the total weight of the vehicle, road material, road characteristics and slippery conditions during driving, the vehicle control parameters are determined in real time, so that the vehicle traveling according to the control parameters matches the current driving state of the vehicle, thereby improving the configuration accuracy of the vehicle control parameters and ensuring the safety of people in the vehicle.

[0071] Reference Figure 3 , Figure 3 This is the second embodiment of the vehicle control method of the present invention. Based on the first embodiment, step S203 includes:

[0072] Step S301 : determining the friction of the road to the vehicle based on the road surface type and the wet state, and determining the ground adhesion of the road to the vehicle based on the friction.

[0073] In this embodiment, the vehicle can adjust its longitudinal control in real time based on the magnitude of the lateral force to prevent vehicle slip. Lateral force refers to a force perpendicular to the vehicle body, while longitudinal control refers to traction control. Longitudinal refers to a direction parallel to the vehicle's direction of travel.

[0074] After determining the road surface type, the vehicle can search the database for the friction coefficient associated with that road surface type. The vehicle's gross weight and friction coefficient are then used to determine the road's frictional force. Furthermore, the slippery condition of the road can affect the road's frictional force. Therefore, the vehicle uses the slippery condition to modify the friction coefficient determined by the road surface type. For example, if the road surface is slippery, the friction coefficient determined by the road surface type needs to be reduced. The greater the slipperiness, the greater the reduction in friction. The vehicle then calculates the road's frictional force using the modified friction coefficient and the vehicle's gross weight. This frictional force can be used to calculate the road's adhesion to the ground.

[0075] Step S302: Acquire the lateral acceleration of the vehicle, and determine the target lateral force of the vehicle according to the lateral acceleration.

[0076] The vehicle is equipped with an IMU (Inertial Measurement Unit). The IMU measures the vehicle's lateral acceleration and then calculates the vehicle's lateral force from the lateral acceleration. In this embodiment, the lateral force calculated from the lateral acceleration is defined as the target lateral force.

[0077] Step S303 : determining the longitudinal traction of the vehicle according to the ground adhesion and the target lateral force.

[0078] Ground adhesion can be the combined force in the vehicle's lateral and longitudinal directions. The force in the vehicle's longitudinal direction is the longitudinal lateral stress. To address this, ground adhesion is decomposed into lateral and longitudinal forces, and the total lateral force between these lateral forces and the target lateral force is calculated. A greater total lateral force results in a smaller total longitudinal force, which determines the vehicle's longitudinal acceleration. Therefore, the total longitudinal force can be determined based on the total lateral force. The total longitudinal force is the sum of the longitudinal force decomposed from ground adhesion and the vehicle's required longitudinal traction. Therefore, the vehicle's longitudinal traction can be determined from the total longitudinal force and the longitudinal force decomposed from ground adhesion.

[0079] In step S304 , the center of mass position, total weight, road surface type, slippery state, and longitudinal traction are input into the vehicle dynamics model to obtain target control parameters of the vehicle.

[0080] After determining the vehicle's longitudinal lateral force, the vehicle's center of mass position, gross weight, road surface type, wet conditions, and longitudinal traction are input into the vehicle dynamics model to derive target control parameters. The target control parameters include longitudinal acceleration, meaning the vehicle's acceleration in the direction of travel. This acceleration is combined with a correction for the total lateral force. For example, when a vehicle is subjected to a large lateral force, there is a risk of lateral slip. Since maximum ground adhesion is fixed, the longitudinal traction should be reduced to reduce the longitudinal force while increasing the lateral force, thus preventing outward slip.

[0081] In this embodiment, the vehicle accurately determines the control parameters of the vehicle by combining the longitudinal traction with the center of mass position, total weight, road type, and slippery conditions, thereby avoiding vehicle slippage.

[0082] Reference Figure 4 , Figure 4 This is the third embodiment of the vehicle control method of the present invention. Based on the second embodiment, step S302 includes:

[0083] Step S401 : Calculate the first lateral force of the vehicle according to the lateral acceleration, and obtain wind force information at the current position of the vehicle.

[0084] Step S402 : determining a second lateral force generated by the wind on the vehicle according to the wind information, and determining a target lateral force of the vehicle according to the first lateral force and the second lateral force.

[0085] In this embodiment, a vehicle in strong winds may be affected by the wind, causing it to deflect. For example, when a vehicle is traveling on a bridge, the wind is strong due to the lack of obstructions. This means that the vehicle itself generates a lateral force (for example, when turning), and the wind also generates a lateral force on the vehicle. To address this, the vehicle calculates its own first lateral force based on the lateral acceleration.

[0086] The vehicle then obtains the wind force information of its current location. Specifically, the vehicle determines its current location through positioning, and then sends the current location to the server to request the server to send the wind force information of the current location. The wind force information includes the second lateral force generated by the wind on the vehicle. The second lateral force is determined by the server based on the wind direction and wind speed on the bridge. The vehicle calculates the sum of the second lateral force and the first lateral force to obtain the target lateral force. Furthermore, after obtaining the second lateral force generated on the vehicle, the vehicle determines whether the second lateral force is greater than a preset threshold. If it is greater than the preset threshold, it can be determined that the wind will cause the vehicle to deviate. The vehicle then calculates the sum of the second lateral force and the first lateral force to obtain the target lateral force.

[0087] Furthermore, the vehicle can detect wind direction and speed at its current location in real time, or obtain wind force and speed information from a weather forecast. The vehicle calculates the lateral force exerted on the vehicle based on the wind direction and speed, and then sends this lateral force and current location to a cloud server. This allows other vehicles at their current location to directly obtain the lateral force from the server.

[0088] In this embodiment, the vehicle obtains wind information at its current location, determines the second lateral force generated by the wind on the vehicle based on the wind information, and determines the target lateral force through the first lateral force and the second lateral force determined by acceleration, that is, taking into account the impact of wind on the vehicle to avoid vehicle deviation.

[0089] Reference Figure 5 , Figure 5 This is the fourth embodiment of the vehicle control method of the present invention. Based on the second embodiment, step S302 includes:

[0090] Step S501 : Calculate a first lateral acceleration of the vehicle according to the lateral acceleration, and obtain a change in the air pressure of the environment in which the vehicle is located.

[0091] In this embodiment, a sudden change in air pressure will also generate a lateral force on the vehicle. To this end, the vehicle obtains the air pressure detected by the air pressure sensor in real time and calculates the air pressure difference between the current detected air pressure and the last detected air pressure.

[0092] Step S502 : When the air pressure variation is greater than a preset variation, a third lateral force generated by the air pressure on the vehicle is determined based on the air pressure variation, and a target lateral force of the vehicle is determined based on the first lateral force and the third lateral force.

[0093] The vehicle calculates its own first lateral force based on lateral acceleration. The vehicle detects whether the change in air pressure is greater than a preset change. If so, the vehicle determines that the air pressure in its environment has experienced a sudden change. At this point, the air pressure will exert an increased lateral force on the vehicle, causing the vehicle to deflect. To address this, the vehicle calculates a third lateral force generated by the air pressure based on the detected air pressure change. The vehicle then calculates the sum of the second lateral force and the first lateral force to obtain a target lateral force. If the air pressure change is less than or equal to the preset change, the first lateral force is determined as the target lateral force.

[0094] Furthermore, when the vehicle is traveling at a preset location, the air pressure will change significantly. The preset location is a tunnel or a mountain road. For example, when a vehicle exits or enters a tunnel entrance, the air pressure will change significantly. For another example, when a vehicle is traveling on a mountain road, the air becomes thinner as the altitude increases or decreases, which means that the air pressure will change significantly. To address this, the vehicle obtains its own location. If the vehicle is at the preset location, the air pressure sensor is activated to obtain the air pressure change in the vehicle's environment. This eliminates the need to obtain the air pressure change in real time, thereby avoiding wasting the vehicle's computing resources.

[0095] In this embodiment, the vehicle obtains the air pressure change of the current environment. If the air pressure change is greater than a preset change, the lateral acceleration of the vehicle is obtained, and the vehicle control parameters are calculated and optimized to avoid vehicle deviation.

[0096] Reference Figure 6 , Figure 6 This is a fifth embodiment of the vehicle control method of the present invention, based on any one of the second to fourth embodiments, step S304 includes:

[0097] Step S601 : inputting the center of mass position, total weight, road surface type, slippery state, and total lateral force into the vehicle dynamics model to obtain control parameters to be determined.

[0098] In this embodiment, the vehicle adjusts the control parameters based on the road condition information and the vehicle's environmental condition information so that the control parameters match the vehicle's environment.

[0099] The vehicle first inputs the center of mass position, total weight, road surface type, wet slip device and total lateral force into the vehicle dynamic model to obtain control parameters, which are defined as the control parameters to be determined.

[0100] Step S602: Acquire road condition information and vehicle environment condition information.

[0101] After obtaining the control parameters to be determined, the vehicle obtains road condition information and the vehicle's environmental condition information. Road condition information includes, for example, the status of traffic lights on the road the vehicle is on and road congestion. Road condition information can be obtained by analyzing images captured by a camera mounted outside the vehicle. Environmental condition information can include information such as the type of target located in front of the vehicle (such as a car, truck, bus, two-wheeled vehicle, pedestrian, etc.), the distance between the vehicle and the target, and the target's speed, acceleration, and azimuth.

[0102] Step S603: Correct the control parameter to be determined according to the road condition information and the environmental vehicle condition information to obtain the target control parameter.

[0103] The vehicle obtains the target control parameter by modifying the undetermined control parameter using road and ambient vehicle condition information. For example, if the target type is a passenger car and the distance between the passenger car and the vehicle is small, the undetermined acceleration (including the undetermined acceleration) needs to be reduced to obtain the target acceleration. For another example, if the road condition information indicates that the traffic light is red, the undetermined acceleration needs to be reduced to a negative number, causing the vehicle to stop at the intersection.

[0104] In this embodiment, the vehicle modifies the control parameters based on the road condition information and the vehicle's environmental condition information, thereby obtaining target environmental parameters that match the current environment of the vehicle.

[0105] In one embodiment, a vehicle is equipped with a first sensor for measuring the weight of a seat, a second sensor for measuring the weight of items in the vehicle, and a third sensor for measuring the weight of the fuel in the fuel tank. The vehicle also includes a built-in image acquisition module. The first, second, and third sensors may be weight sensors or pressure sensors.

[0106] The vehicle obtains the initial weight of the vehicle, the load-bearing weight collected by the first sensor, the weight of the items collected by the second sensor, and the weight of the fuel collected by the third sensor. Furthermore, the vehicle obtains images captured by the image acquisition module, thereby determining the posture and seating position of each person in the vehicle (including passengers and the driver) based on the images. The vehicle determines the weight of each person based on their posture and the load-bearing weight corresponding to the seat where they are seated. That is, the weight of the person is obtained by correcting the load-bearing weight corresponding to the seat where they are seated based on their posture. The vehicle calculates the sum of the weight of each person, the initial weight, the weight of the items, and the weight of the fuel to obtain the total weight of the vehicle.

[0107] In this embodiment, the vehicle corrects the weight of the person detected by the person's posture, thereby accurately determining the total weight of the vehicle and further accurately determining the control parameters of the vehicle.

[0108] The present invention also provides a vehicle, referring to Figure 7 , the vehicle 700 includes:

[0109] An acquisition module 710 is used to obtain the road surface material, road surface characteristics, and slippery conditions of the road on which the vehicle is currently located, and to obtain the total weight of the vehicle;

[0110] a determination module 720 for determining a road surface type based on the road surface material and road surface characteristics, and determining a center of mass position of the vehicle based on the total weight;

[0111] a determination module 720 for determining target control parameters of the vehicle based on the center of mass position, gross weight, road surface type, and slippery condition;

[0112] The control module 730 is configured to drive according to target control parameters.

[0113] In one embodiment, the vehicle 700 further includes:

[0114] a determination module 720 for determining the friction of the road on the vehicle based on the road surface type and the slippery state, and determining the ground adhesion of the road to the vehicle based on the friction;

[0115] an acquisition module 710 for acquiring the lateral acceleration of the vehicle and determining a target lateral force of the vehicle based on the lateral acceleration;

[0116] a determination module 720 for determining the longitudinal traction of the vehicle based on the target lateral force and the ground adhesion;

[0117] The input module is used to input the center of mass position, total weight, road surface type, slippery state and longitudinal traction into the vehicle dynamic model to obtain the target control parameters of the vehicle.

[0118] In one embodiment, the vehicle 700 further includes:

[0119] An acquisition module 710 is configured to calculate a first lateral force of the vehicle based on the lateral acceleration and obtain wind force information at the current location of the vehicle;

[0120] The acquisition module 710 is configured to determine a second lateral force generated by the wind on the vehicle based on the wind information, and determine a target lateral force of the vehicle based on the first lateral force and the second lateral force.

[0121] In one embodiment, the vehicle 700 further includes:

[0122] An acquisition module 710 is configured to calculate a first lateral acceleration of the vehicle based on the lateral acceleration and obtain a change in air pressure of an environment in which the vehicle is located;

[0123] The acquisition module 710 is used to determine the third lateral force generated by the air pressure on the vehicle according to the air pressure change when the air pressure change is greater than the preset change, and to determine the target lateral force of the vehicle according to the first lateral force and the third lateral force.

[0124] In one embodiment, the vehicle 700 further includes:

[0125] An acquisition module 710 is used to acquire the location of the vehicle;

[0126] The acquisition module 710 is used to acquire the air pressure change of the environment in which the vehicle is located when the vehicle is located at a preset location, where the preset location is a tunnel or a mountain road.

[0127] In one embodiment, the vehicle 700 further includes:

[0128] An input module is used to input the center of mass position, total weight, road surface type, slippery state and total lateral force into the vehicle dynamic model to obtain the control parameters to be determined;

[0129] An acquisition module 710 is used to acquire road condition information and vehicle environment condition information;

[0130] The correction module is used to correct the control parameters to be determined according to the road condition information and the environmental vehicle condition information to obtain the target control parameters.

[0131] In one embodiment, the vehicle 700 further includes:

[0132] An acquisition module 710 is configured to acquire the initial weight of the vehicle, the load-bearing weight acquired by the first sensor, the weight of the item acquired by the second sensor, and the weight of the fuel liquid acquired by the third sensor;

[0133] A determination module 720 is configured to determine the posture and seating position of each person in the vehicle based on the images captured by the image capture module;

[0134] Determination module 720, for determining the weight of the person based on the person's posture and the corresponding load-bearing weight of the seat where the person is sitting;

[0135] The determination module 720 is configured to determine the total weight of the vehicle according to the weight of the personnel, the initial weight, the weight of the items, and the weight of the fuel.

[0136] Figure 8 is a hardware structure diagram of a vehicle according to an exemplary embodiment.

[0137] The vehicle 800 may include a processor 801, such as a CPU, a memory 802, and a transceiver 803. As will be appreciated by those skilled in the art, Figure 8The structure shown in the figure does not limit the vehicle and may include more or fewer components than shown, or a combination of certain components, or a different arrangement of components. The memory 802 may be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0138] The processor 801 can call the computer program stored in the memory 802 to complete all or part of the steps of the above-mentioned vehicle control method.

[0139] The transceiver 803 is used to receive information sent by an external device and send information to the external device.

[0140] A non-transitory computer-readable storage medium, when the instructions in the storage medium are executed by a processor of a vehicle, enables the vehicle to execute the above-mentioned vehicle control method.

[0141] A computer program product includes a computer program, which, when executed by a processor of a vehicle, enables the vehicle to execute the above-mentioned vehicle control method.

[0142] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0143] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A vehicle control method, characterized in that: include: Obtaining the road surface material, road surface characteristics, and slippery conditions of the road the vehicle is currently on, and obtaining the total weight of the vehicle; Determining a road surface type of the road according to the road surface material and the road surface characteristics, and determining a center of mass position of the vehicle according to the total weight; determining a target control parameter of the vehicle based on the center of mass position, the gross weight, the road surface type, the slippery state, and longitudinal traction, wherein the longitudinal traction is determined based on a target lateral force and the road's ground adhesion to the vehicle, and the first lateral force of the vehicle is calculated based on a lateral acceleration of the vehicle; driving according to the target control parameters; Among them, the target lateral force is determined based on the first lateral direction and the third lateral force generated by the vehicle, and the third lateral force is determined based on the air pressure change when the air pressure change in the environment in which the vehicle is located is greater than a preset change.

2. The vehicle control method according to claim 1, characterized in that: The determining of the target control parameters of the vehicle according to the center of mass position, the total weight, the road surface type, the slippery state, and the longitudinal traction includes: determining a friction force of the road on the vehicle according to the road surface type and the slippery state, and determining a ground adhesion force of the road on the vehicle according to the friction force; The center of mass position, the total weight, the road surface type, the slippery state, and the longitudinal traction are input into a vehicle dynamics model to obtain target control parameters of the vehicle.

3. The vehicle control method according to claim 1, characterized in that: The obtaining of the air pressure change in the environment in which the vehicle is located includes: Obtaining the location of the vehicle; When the vehicle is located at a preset position, the air pressure change of the environment in which the vehicle is located is obtained, and the preset position is a tunnel or a mountain road.

4. The vehicle control method according to claim 2, wherein: The step of inputting the center of mass position, the total weight, the road surface type, the slippery state, and the lateral force into a vehicle dynamics model to obtain target control parameters of the vehicle includes: Inputting the center of mass position, the total weight, the road surface type, the slippery state, and the lateral force into a vehicle dynamics model to obtain control parameters to be determined; Acquiring road condition information of the road and environmental condition information of the vehicle; The control parameter to be determined is corrected according to the road condition information and the environmental vehicle condition information to obtain the target control parameter.

5. The vehicle control method according to any one of claims 1 to 4, characterized in that: The vehicle is provided with a first sensor for collecting the weight of a seat, a second sensor for collecting the weight of items in the vehicle, and a third sensor for collecting the weight of fuel in a fuel tank. The vehicle is also provided with an image acquisition module. The method of obtaining the total weight of the vehicle includes: Obtaining the initial weight of the vehicle, the load-bearing weight collected by the first sensor, the weight of the item collected by the second sensor, and the weight of the fuel collected by the third sensor; Determining the posture and seating position of each person in the vehicle based on the images captured by the image acquisition module; Determining the weight of the person according to the person's posture and the corresponding load-bearing weight of the seat where the person is seated; The total weight of the vehicle is determined according to the weight of the person, the initial weight, the weight of the object, and the weight of the fuel.

6. A vehicle, characterized in that: include: An acquisition module is used to obtain the road surface material, road surface characteristics, and slippery state of the road on which the vehicle is currently located, and to obtain the total weight of the vehicle; a determination module, configured to determine a pavement type of the road according to the pavement material and the pavement characteristics, and to determine a center of mass position of the vehicle according to the total weight; The determination module is further configured to determine a target control parameter of the vehicle based on the center of mass position, the total weight, the road surface type, the slippery state, and longitudinal traction, wherein the longitudinal traction is determined based on a target lateral force and a ground adhesion of the road to the vehicle, and the first lateral force of the vehicle is calculated based on a lateral acceleration of the vehicle; a control module, configured to drive according to the target control parameters; Among them, the target lateral force is determined based on the first lateral direction and the third lateral force generated by the vehicle, and the third lateral force is determined based on the air pressure change when the air pressure change in the environment in which the vehicle is located is greater than a preset change.

7. A vehicle, characterized in that: include: memory and processor; The memory is used to store program instructions; The processor is used to call the program instructions in the memory to execute the vehicle control method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program; when the computer program is executed, the vehicle control method according to any one of claims 1 to 5 is implemented.

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