CN116476807A - Auxiliary driving control method and device for vehicle tire burst and vehicle - Google Patents

Abstract

The invention discloses an auxiliary driving control method and device for a vehicle when a tire burst occurs, and the vehicle, wherein the method comprises the following steps: acquiring road condition information around a vehicle, position information of the vehicle, body posture information of the vehicle and tire burst position information of a tire of the vehicle; determining a motion track of the vehicle according to road condition information around the vehicle, position information of the vehicle and body posture information of the vehicle, and determining a tire burst suppression bias according to the body posture information of the vehicle and tire burst position information of a tire of the vehicle; and correcting the motion trail of the vehicle according to the tire burst suppression bias to determine the target motion trail of the vehicle, and controlling the vehicle according to the target motion trail. According to the control method, when the tire burst occurs in the running process of the vehicle, the motion track of the vehicle can be corrected according to the tire burst restraining bias so as to control the vehicle to run according to the safe track, the occurrence probability of accidents is reduced, and the safety of passengers is ensured.

Description

Assisted driving control method and control device when vehicle tire blows out, and vehicle

technical field

The present invention relates to the technical field of vehicles, in particular to an auxiliary driving control method when a vehicle tire blows out, an auxiliary driving control device when a vehicle tire blows out, a vehicle and a computer-readable storage medium.

Background technique

When a vehicle tire blows out, the driver is in a state of panic or confusion and cannot control the vehicle well. He often takes some dangerous driving behaviors, such as slamming on the brakes, slamming the steering wheel, etc., which leads to accidents.

In the related art, when a tire blows out, the steering angle is adjusted so that the tire blown vehicle returns to the original track. However, in this way, the system controller calculates the steering wheel angle for deviation correction according to the cone angle formed by the reduction of the effective rolling radius of the wheel after the tire blowout and the wheelbase and the forward vector before the tire blowout, and corrects the deviation of the vehicle body through the steering system. In this method, it is difficult to accurately know the effective rolling radius of the wheel after the tire blowout. At the same time, the calculated cone angle is also inaccurate. The error of the steering wheel angle that needs to be corrected based on the forward vector calculation is too large, so it is impossible to safely control the vehicle to follow the trajectory.

Contents of the invention

The present invention aims to solve one of the technical problems in the related art at least to a certain extent. For this reason, the first object of the present invention is to propose an auxiliary driving control method when a vehicle tire blows out. When a tire blows out while the vehicle is running, the motion track of the vehicle can be corrected according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe track, reduce the probability of accidents, and ensure the safety of passengers.

The second object of the present invention is to provide an auxiliary driving control device when a vehicle tire blows out.

A third object of the invention is to propose a vehicle.

A fourth object of the present invention is to provide a computer-readable storage medium.

In order to achieve the above object, the embodiment of the first aspect of the present invention proposes an assisted driving control method when a vehicle tire blows out, including: acquiring road condition information around the vehicle, vehicle position information, vehicle body attitude information, and tire blowout position information of the vehicle; determining a vehicle trajectory according to the road condition information around the vehicle, vehicle position information, and vehicle body attitude information; The trajectory of the vehicle is corrected to determine the target trajectory of the vehicle; the vehicle is controlled according to the target trajectory.

According to the assisted driving control method when a vehicle tire blows out according to an embodiment of the present invention, the road condition information around the vehicle, the position information of the vehicle, the body attitude information of the vehicle, and the tire blowout position information of the vehicle are obtained, and the motion trajectory of the vehicle is determined according to the road condition information around the vehicle, the position information of the vehicle, and the body attitude information of the vehicle, and then the tire blowout suppression bias is determined according to the body posture information of the vehicle and the tire blowout position information of the vehicle, and finally the motion trajectory of the vehicle is corrected according to the tire blowout suppression bias, and the vehicle is controlled to drive according to the target motion trajectory. Therefore, when a tire blows out while the vehicle is running, the method can correct the trajectory of the vehicle according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe trajectory, reduce the probability of accidents, and ensure the safety of passengers.

In addition, the assisted driving control method when the vehicle tire blows out according to the above-mentioned embodiments of the present invention may also have the following additional technical features:

According to an embodiment of the present invention, the body attitude information of the vehicle includes the yaw rate of the vehicle and the lateral acceleration of the vehicle, wherein the determination of the tire blowout suppression bias according to the body posture information of the vehicle and the tire blowout position information of the vehicle includes: determining the tire blowout suppression bias coefficient according to the tire blowout position information of the vehicle tire; determining the tire blowout suppression bias according to the tire blowout suppression bias coefficient, the yaw rate of the vehicle, and the lateral acceleration of the vehicle.

According to an embodiment of the present invention, the tire blowout suppression bias is calculated by the following formula:

e _blowout ＝A _i *ω(t)+B _i *da _l (t)/dt

Among them, e _puncture represents the puncture suppression bias, A _i and _Bi represent the puncture suppression bias coefficients, ω(t) represents the yaw rate of the vehicle at time t, and a _l (t) represents the lateral acceleration of the vehicle at time t.

According to an embodiment of the present invention, correcting the motion track of the vehicle according to the tire burst suppression bias includes: inverting the tire burst suppression bias to obtain a correction value of the vehicle motion track; and correcting the vehicle motion track according to the correction value of the vehicle motion track.

According to an embodiment of the present invention, the body posture information of the vehicle includes the longitudinal acceleration of the vehicle, wherein, according to the road condition information around the vehicle, the position information of the vehicle and the body posture information of the vehicle, determining the trajectory of the vehicle includes: determining the safe driving area of the vehicle according to the road condition information; determining the horizontal planning path of the vehicle according to the position information of the vehicle and the safe driving area of the vehicle; determining the longitudinal planning path of the vehicle according to the longitudinal acceleration of the vehicle; determining the moving trajectory of the vehicle according to the horizontal planning path and the longitudinal planning path.

According to an embodiment of the present invention, the position information of the vehicle includes the initial position of the vehicle, wherein, determining the lateral planned path of the vehicle according to the positional information of the vehicle and the safe driving area of the vehicle includes: determining the target position of the vehicle according to the safe driving area of the vehicle; determining a plurality of intermediate positions according to the lateral distance between the initial position of the vehicle and the target position of the vehicle; using an N-order polynomial to fit the initial position of the vehicle, the target position of the vehicle, and a plurality of intermediate positions to obtain the lateral planning path of the vehicle, wherein the number of the multiple intermediate positions is determined by an N-order polynomial, and N is a positive integer.

According to an embodiment of the present invention, determining the longitudinal planned path of the vehicle according to the longitudinal acceleration of the vehicle includes: acquiring the target longitudinal acceleration of the vehicle; determining the planned longitudinal path of the vehicle according to the curve from the initial acceleration of the vehicle to the target longitudinal acceleration.

According to an embodiment of the present invention, determining the trajectory of the vehicle according to the horizontal planning path and the longitudinal planning path includes: performing secondary integration processing on the longitudinal planning path to obtain the curve of the longitudinal position of the vehicle over time; obtaining the position combination of the lateral position and the longitudinal position of the vehicle at the same time according to the horizontal planning path and the curve of the longitudinal position of the vehicle changing over time; determining the two-dimensional trajectory of the vehicle according to the combination of positions;

According to an embodiment of the present invention, using the cost function to screen the two-dimensional motion track of the vehicle to determine the motion track of the vehicle includes: obtaining a plurality of different types of cost functions corresponding to the expected results of the cost function; screening the two-dimensional motion track of the vehicle according to each cost function to obtain the corresponding minimum value; performing weighted summation on the multiple minimum values to determine the motion track of the vehicle.

In order to achieve the above object, the embodiment of the second aspect of the present invention proposes a driving assistance control device when a vehicle tire blows out, including: a first acquisition module, used to acquire road condition information around the vehicle; a second acquisition module, used to acquire vehicle body position information; a third acquisition module, used to acquire vehicle body posture information; a fourth acquisition module, used to obtain vehicle tire burst position information; The tire blowout position information determines the tire blowout suppression bias, wherein the tire blowout suppression bias is the offset generated when the tire blows out; the trajectory correction module is used to correct the vehicle's motion trajectory according to the tire blowout suppression bias to determine the vehicle's target motion trajectory; the control module is used to control the vehicle according to the target motion trajectory.

According to the auxiliary driving control device for a vehicle tire blowout according to an embodiment of the present invention, the motion track determination module determines the motion track of the vehicle according to the road condition information around the vehicle, the position information of the vehicle, and the body attitude information of the vehicle, the first determination module determines the tire blowout suppression bias according to the vehicle body posture information and the tire blowout position information of the vehicle tires, the trajectory correction module corrects the motion track of the vehicle according to the tire blowout suppression bias, and the control module controls the vehicle to drive according to the target motion track. Thus, when a tire blows out while the vehicle is running, the device can correct the motion track of the vehicle according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe track, reduce the probability of accidents, and ensure the safety of passengers.

In order to achieve the above-mentioned purpose, the embodiment of the third aspect of the present invention proposes a vehicle, including a memory, a processor, and an assisted driving control program when the vehicle tire blows out, which is stored on the memory and can run on the processor.

According to the vehicle of the embodiment of the present invention, by implementing the above-mentioned assisted driving control method when the vehicle tire blows out, when a tire blows out while the vehicle is running, the motion track of the vehicle can be corrected according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe track, reduce the probability of accidents, and ensure the safety of passengers.

In order to achieve the above-mentioned purpose, the embodiment of the fourth aspect of the present invention proposes a computer-readable storage medium, on which is stored an assisted driving control program when a vehicle tire blows out, and when the vehicle assisted driving control program is executed by a processor, the above-mentioned assisted driving control method when a vehicle tire blows out is realized.

According to the computer-readable storage medium of the embodiment of the present invention, by executing the above-mentioned assisted driving control method when a vehicle tire blows out, when a tire blows out while the vehicle is running, the motion track of the vehicle can be corrected according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe track, reduce the probability of accidents, and ensure the safety of passengers.

Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Description of drawings

FIG. 1 is a flow chart of a driving assistance control method when a vehicle tire blows out according to an embodiment of the present invention;

Fig. 2 is a force analysis diagram of a vehicle according to an embodiment of the present invention;

FIG. 3 is an analysis diagram of a vehicle control model according to an embodiment of the present invention;

FIG. 4 is a flow chart of a driving assistance control method when a vehicle tire blows out according to an embodiment of the present invention;

Fig. 5 is a visual schematic diagram of grid map attribute assignment of the assisted driving control method when the vehicle tire blows out according to an embodiment of the present invention;

Fig. 6 is a schematic diagram of a grid map safe driving area of the assisted driving control method when the vehicle tire blows out according to an embodiment of the present invention;

Fig. 7 is a schematic diagram of a safe driving area according to an embodiment of the present invention;

Fig. 8 is a schematic diagram of a vehicle's lateral planning path according to an assisted driving control method when a vehicle tire blows out according to an embodiment of the present invention;

FIG. 9 is a schematic diagram of a longitudinally planned path of a vehicle according to an assisted driving control method when a vehicle tire blows out according to an embodiment of the present invention;

Fig. 10 is a schematic diagram of the visualization result of the two-dimensional trajectory beam of the vehicle motion trajectory in the assisted driving control method when the vehicle tire blows out according to an embodiment of the present invention;

Fig. 11 is a schematic diagram of the path planning results of the own lane in the assisted driving control method when the vehicle tire blows out according to an embodiment of the present invention;

Fig. 12 is a schematic diagram of the cross-lane path planning results of the assisted driving control method when the vehicle tire blows out according to an embodiment of the present invention;

Fig. 13 is a schematic block diagram of an auxiliary driving control device when a vehicle tire blows out according to an embodiment of the present invention;

14 is a block schematic diagram of a vehicle according to an embodiment of the present invention.

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

The assisted driving control method and device, vehicle, and computer-readable storage medium proposed by the embodiments of the present invention when a tire blows out are described below with reference to the accompanying drawings.

FIG. 1 is a flow chart of a method for controlling driving assistance when a vehicle tire blows out according to an embodiment of the present invention.

As shown in FIG. 1, the assisted driving control method when the vehicle tire blows out according to the embodiment of the present invention may include the following steps:

S1. Obtain road condition information around the vehicle, vehicle location information, vehicle body posture information, and vehicle tire burst location information.

In an embodiment of the present invention, the vehicle has an ADAS (Advanced Driving Assistance System) system and a sensor platform, wherein the sensor platform is a fusion of various sensors, such as: front-view camera, forward-facing radar, front-angle radar, rear-angle radar, surround-view camera, side camera, laser radar and other sensors. The road condition information around the vehicle and the location information of the vehicle can be obtained through the sensors in the sensor platform (such as: camera, radar, etc.). The ADAS system can monitor the vehicle's wheel speed information, lateral and longitudinal acceleration, yaw rate, accelerator opening, brake pedal information and other information in real time, so as to obtain the vehicle's body posture information, and transmit it to the ADAS system through the body bus signal. The tire burst location information can be obtained through the tire burst sensor equipped on the vehicle or the system monitoring the rate of change of tire pressure or the chassis domain controller signal notification, etc., and output to the ADAS system through the vehicle bus signal.

It should be noted that ADAS systems usually include navigation and real-time traffic systems, electronic police systems, Internet of Vehicles, adaptive cruise control, lane departure warning systems, lane keeping systems, collision avoidance or pre-collision systems, night vision systems, adaptive lighting control, pedestrian protection systems, automatic parking systems, traffic sign recognition, blind spot detection, driver fatigue detection, downhill control systems, and electric vehicle alarm systems.

S2. Determine the movement track of the vehicle according to the road condition information around the vehicle, the position information of the vehicle and the body posture information of the vehicle.

S3. Determine a tire blowout suppression offset according to the body posture information of the vehicle and the tire blowout location information of the vehicle, wherein the tire blowout suppression offset is an offset generated when a tire blows out.

According to an embodiment of the present invention, the body attitude information of the vehicle includes the yaw rate of the vehicle and the lateral acceleration of the vehicle, wherein the determination of the tire blowout suppression bias according to the body posture information of the vehicle and the tire blowout position information of the vehicle includes: determining the tire blowout suppression bias coefficient according to the tire blowout position information of the vehicle tire; determining the tire blowout suppression bias according to the tire blowout suppression bias coefficient, the yaw rate of the vehicle, and the lateral acceleration of the vehicle.

According to an embodiment of the present invention, the tire blowout suppression bias is calculated by the following formula:

e _blowout ＝A _i *ω(t)+B _i *da _l (t)/dt

Among them, e _puncture represents the puncture suppression bias, A _i and _Bi represent the puncture suppression bias coefficients, ω(t) represents the yaw rate of the vehicle at time t, and a _l (t) represents the lateral acceleration of the vehicle at time t.

Specifically, when the vehicle is running normally, the forces acting on the vehicle are distributed along three different axes. As shown in Figures 2 and 3, the forces on the vertical axis include: driving force, braking force, rolling resistance, and drag resistance, and the vehicle makes a rolling motion around the vertical axis; the forces on the horizontal axis include: steering force, centrifugal force, and side wind force, and the vehicle makes a pitching motion around the horizontal axis; the forces on the vertical axis include: the force exerted by the vehicle's up and down oscillation, and the vehicle yaws or turns around the vertical axis. However, the current vehicle dynamic model only considers the characteristics of pure lateral tires, ignores the longitudinal and lateral coupling relationship of tire forces, does not consider the left and right transfer of loads, and ignores the lateral and longitudinal aerodynamics. When a vehicle has a puncture, due to the reduction of the effective rolling radius of the punctured tire, the vehicle tilts and deflects to the side of the punctured tire, and the vehicle undergoes significant changes due to friction/lateral force/thrust. In the case of a tire blowout, the functions of the ADAS system can no longer control the normal driving of the vehicle, such as: adaptive cruise control, lane keeping assist function. At this time, the ADAS system determines the trajectory of the vehicle according to the road condition information around the vehicle, the position information of the vehicle, and the vehicle body attitude information, and determines the tire blowout suppression bias according to the vehicle body attitude information and the tire blowout location information of the vehicle.

Specifically, the body attitude information of the vehicle includes the vehicle's yaw rate ω and the vehicle's lateral acceleration a _l , which can be obtained by real-time monitoring of acceleration and angular velocity feedback signals from the accelerometer and gyroscope. The tire blowout position information of the vehicle tire is obtained from the tire blowout position feedback of the vehicle tire, and the tire blowout suppression bias coefficients A _i and B _i can be determined according to the tire blowout position information of the vehicle tire. Among them, the tire blowout suppression bias coefficient can be a set of parameter values obtained by calibrating the control performance of the vehicle through simulation and debugging of a large amount of data. There are four pairs of different coefficients in this set of parameters Represent the tire blowout suppression bias coefficients corresponding to wheel blowouts at different positions, for example, A1 and B1 represent the bias coefficients of the left wheel among the front wheels, A2 and B2 represent the bias coefficients of the right wheel among the front wheels, A3 and B3 represent the bias coefficients of the left wheel among the rear wheels, and A4 and B4 represent the bias coefficients of the right wheel among the rear wheels.

After determining the position information of the tire blowout, the yaw rate and lateral acceleration of the vehicle at the current moment, and the position information of the wheel blowout are brought into the above formula to obtain the tire blowout suppression bias.

In one embodiment of the present invention, if two tires are blown out, after the tire blowout suppression biases of the corresponding tire blowout wheels are respectively obtained through the above method, the final tire blowout suppression bias can be obtained by weighted summation. In order to prevent the tire blowout from seriously affecting driving safety, it is also possible to control the vehicle to travel to the emergency position and then stop when multiple tire blowouts are determined.

S4, correcting the motion trajectory of the vehicle according to the tire blowout suppression bias, so as to determine the target motion trajectory of the vehicle.

S5, controlling the vehicle according to the target trajectory.

According to an embodiment of the present invention, correcting the motion track of the vehicle according to the tire burst suppression bias includes: inverting the tire burst suppression bias to obtain a correction value of the vehicle motion track; and correcting the vehicle motion track according to the correction value of the vehicle motion track.

Specifically, when a tire blows out while the vehicle is running at high speed, the ADAS system of the vehicle determines the trajectory of the vehicle based on the road condition information around the vehicle, the position information of the vehicle, and the body attitude information of the vehicle, and determines the tire blowout suppression bias based on the body attitude information of the vehicle and the tire blowout location information of the vehicle. After the tire blowout suppression bias is determined, the tire blowout suppression bias is reversed, so that the correction value of the vehicle's motion trajectory can be obtained. Correcting the vehicle's motion trajectory according to the correction value can determine the vehicle's target motion trajectory. For example, if the left wheel of the front wheel of the vehicle blows out, the vehicle will deviate to the left. At this time, a control force to the right is applied to correct the original driving track of the vehicle so that the vehicle can return to the originally planned driving path. The ADAS system controls the vehicle according to the target trajectory, and controls the vehicle to drive according to the target trajectory, so that the vehicle can drive in the safe driving area. When the vehicle control tends to be stable, that is, the yaw angle and the lateral acceleration tend to zero, the puncture suppression bias value tends to zero.

How to determine the motion track of the vehicle according to the road condition information around the vehicle, the position information of the vehicle and the posture information of the vehicle body will be specifically described below in conjunction with specific embodiments.

Fig. 4 is a flow chart of a driving assistance control method when a vehicle tire blows out according to an embodiment of the present invention. As shown in Fig. 4, according to an embodiment of the present invention, the body attitude information of the vehicle includes the longitudinal acceleration of the vehicle, wherein, determining the trajectory of the vehicle according to the road condition information around the vehicle, the position information of the vehicle and the body attitude information of the vehicle may include the following steps:

S201. Determine a safe driving area of the vehicle according to road condition information.

Specifically, the road condition information around the vehicle includes: the distance between the lane line and the vehicle, the position information of obstacles (vehicles in adjacent lanes, etc.), the safety distance from obstacles, and the like. During the driving process of the vehicle, the road condition information around the vehicle changes in real time. When the vehicle blows out, the vehicle's trajectory deviates. In order to ensure the driving safety of the vehicle, it is necessary to determine the safe driving area of the vehicle.

Specifically, when the ADAS system plans the lateral behavior and vertical behavior of the vehicle, it first needs to unify the coordinate system, that is, the vehicle coordinate system, the sensor platform perception coordinate system, and the world coordinate system into a new planning coordinate system, and divide the planning coordinate system into grids to form a grid map, and then assign attribute values to each grid. The attribute values are constraints and boundaries. As shown in Figure 5, the constraints and boundaries include: the distance between the lane line and the vehicle, the position information of the obstacle, the position prediction of the obstacle in the future, and the safe distance from the obstacle. The above constraints are assigned values in the grid map. The assignment principle is from small to large corresponding to the degree of threat from light to heavy. For example, as the distance between the lane line and the vehicle gradually decreases, the greater the value assigned; Constraints and boundaries are the result of assignments made within the time interval and within the current task. Through the threshold value, the grid map after the attribute assignment is performed to remove the grid whose threshold value is too large, and the area that the vehicle can pass through can be obtained. Therefore, through the screening of constraints and boundaries, a safe area without collision risk in time and space can be obtained, that is, the safe driving area of the vehicle. As shown in Figure 6, the safe driving area of the vehicle is the area limited by the boundary. The visualization result of the safe driving area in the unified planning coordinate system is shown in Figure 7. The safe driving area, obstacles, lane lines and road boundaries are all composed of many point clouds.

S202. Determine a laterally planned path of the vehicle according to the position information of the vehicle and the safe driving area of the vehicle.

According to an embodiment of the present invention, the position information of the vehicle includes the initial position of the vehicle, wherein, determining the lateral planned path of the vehicle according to the positional information of the vehicle and the safe driving area of the vehicle includes: determining the target position of the vehicle according to the safe driving area of the vehicle; determining a plurality of intermediate positions according to the lateral distance between the initial position of the vehicle and the target position of the vehicle; using an N-order polynomial to fit the initial position of the vehicle, the target position of the vehicle, and a plurality of intermediate positions to obtain the lateral planning path of the vehicle, wherein the number of the multiple intermediate positions is determined by an N-order polynomial, and N is a positive integer.

Specifically, when the vehicle has a tire blowout and the vehicle has deviated laterally, the ADAS system needs to plan the vehicle to drive in the safe driving area. For example, a point in the safe driving area can be selected as the target position of the vehicle. There is a lateral distance D ₀ between the position where the vehicle starts to deviate (the starting position) and the target position. Horizontal path planning can be simplified as the relationship between horizontal distance and time, so that a one-dimensional spatial relationship DT (distance-time) can be established, as shown in Figure 8, where the abscissa represents time and the ordinate represents the lateral distance. There are countless possibilities for the lateral distance and the change of the lateral distance over time. Multiple intermediate positions can be determined according to the lateral distance between the initial position of the vehicle and the target position of the vehicle, and one possibility can be determined by the initial position of the vehicle, the target position of the vehicle and multiple intermediate positions. Thus, an N-order polynomial can be used to fit the starting position of the vehicle, the target position of the vehicle and multiple intermediate positions, so as to obtain the laterally planned path of the vehicle. In the following, an example is used to illustrate by selecting three intermediate positions and obtaining the horizontal planning path of the vehicle by using a fifth-order polynomial.

Specifically, when using a fifth-order polynomial to fit the lateral planning path, six boundary conditions are considered: initial position, target position, initial velocity, target velocity, initial acceleration, and target acceleration, so the fifth-order polynomial of the lateral planning path is: D(t)=D ₀ +a ₁ (tt ₀ )+a ₂ (tt ₀ ) ² +a ₃ (tt ₀ ) ³ +a ₄ (tt ₀ ) ⁴ +a ₅ (tt ₀ ) ⁵ . D ₀ refers to the lateral distance between the initial position and the target position, t is the current moment, t ₀ is the initial moment, and D(t) is the relationship of the lateral distance in this one-dimensional space with time. The coefficients a ₁ , a ₂ , a ₃ , a ₄ , and a ₅ are unknown, and a set of coefficient values can be obtained through the five nodes that have been sampled (starting position, three intermediate positions and the target position). From this, the lateral planned path of the vehicle can be obtained.

S203. Determine the longitudinal planned path of the vehicle according to the longitudinal acceleration of the vehicle.

According to an embodiment of the present invention, determining the longitudinal planned path of the vehicle according to the longitudinal acceleration of the vehicle includes: acquiring the target longitudinal acceleration of the vehicle; determining the planned longitudinal path of the vehicle according to the curve from the initial acceleration of the vehicle to the target longitudinal acceleration.

Specifically, the longitudinal planning path can be simplified as analyzing the relationship between longitudinal acceleration and time, so that a one-dimensional spatial relationship a-T (acceleration-time) can be established, as shown in Figure 9, where the abscissa represents time and the ordinate represents longitudinal acceleration. The target longitudinal acceleration always goes from large to small to zero.

S204. Determine the movement track of the vehicle according to the horizontal planning path and the longitudinal planning path.

According to an embodiment of the present invention, determining the trajectory of the vehicle according to the horizontal planning path and the longitudinal planning path includes: performing secondary integration processing on the longitudinal planning path to obtain the curve of the longitudinal position of the vehicle over time; obtaining the position combination of the lateral position and the longitudinal position of the vehicle at the same time according to the horizontal planning path and the curve of the longitudinal position of the vehicle changing over time; determining the two-dimensional trajectory of the vehicle according to the combination of positions;

Further, according to an embodiment of the present invention, using a cost function to screen the two-dimensional trajectory of the vehicle to determine the trajectory of the vehicle includes: obtaining a plurality of different types of cost functions corresponding to the expected results of the cost function; filtering the two-dimensional trajectory of the vehicle according to each cost function to obtain the corresponding minimum value; performing weighted summation on the multiple minimum values to determine the trajectory of the vehicle.

Specifically, both the horizontal planning path and the vertical planning path are carried out in the safe passage area, so the separate planning results of the horizontal planning path and the vertical planning path are potential results, and the horizontal planning path and the vertical planning path need to be fused and screened to obtain an optimal control planning path. Since the longitudinal planning path is the relationship of the change of acceleration with time, the curve of the longitudinal position of the vehicle with time can be obtained by performing quadratic integral processing on the longitudinal planning path. According to the time-varying curve of the horizontal planning path and the longitudinal position of the vehicle, there are countless lateral positions and longitudinal positions at each moment. The lateral position and longitudinal position of the vehicle at the same time can be combined into countless arrangements. The arrangement is a group of two-dimensional motion trajectories. The trajectory at this time is a two-dimensional discrete trajectory bundle, as shown in Figure 10. Therefore, it is necessary to use the cost function to screen the two-dimensional trajectory of the vehicle to determine the trajectory of the vehicle.

In one embodiment of the present invention, the expected results of the cost function include: reaching the goal, avoiding collisions, and being stable and comfortable. Therefore, five different types of cost functions are designed correspondingly. The higher the value of the cost function, the less satisfied the requirements are. The weighted sum of the values of these five cost functions is the result of the total cost function cost(). The five cost functions are specifically expressed as:

The cost function cost1 of the first cost function reaching the destination. The value of the cost function cost1 refers to the mileage of the trajectory from the starting position to the target position. The larger the mileage, the greater the value of the cost function cost1 of the trajectory.

The second cost function is the lateral offset cost function cost2. The cost function cost2 is to make the lateral change of the vehicle conform to the vehicle dynamics as much as possible. For example, the trajectory of the vibration, the trajectory of the vector direction changes sharply, and the value of the cost function cost2 is relatively high.

The third cost function is the collision risk cost function cost3. Even the horizontal and vertical behavior relationship results planned in the safe driving area still have the risk of collision. When the relative distance between the trajectory and the obstacle is closer, the value of the collision cost function cost3 will be relatively higher.

The fourth cost function is the cost function cost4 of longitudinal jerk. Jerk is the derivative of acceleration with respect to time and represents the rate of change of acceleration. When the jerk is larger, the vehicle brakes are more unstable, and the value of the cost function cost4 is larger.

The fifth cost function is the cost function cost5 for lateral acceleration. The cost function cost5 is for the vehicle to change lanes smoothly. For example, according to the lane keeping or lane change planned in the scene analysis, if the lane is kept, the value of the lateral acceleration cost5 will be relatively large; if the lane is changed, the value of the lateral acceleration cost5 will be relatively small.

Thus, a cost value can be calculated for each set of permutation results, a combination of the smallest cost values is selected, and the weighted sum of multiple smallest cost values in the combination can be determined to determine the trajectory of the vehicle. Then, the trajectory of the vehicle is corrected according to the tire blowout suppression bias, so that the target trajectory of the vehicle can be determined, and the vehicle is controlled according to the target trajectory.

When the current deviation degree of the punctured vehicle is small, the position of the punctured tire has little influence on the vehicle control, and the ADAS system plans the vehicle to drive in this lane, as shown in Figure 11. When the current deviation of the punctured vehicle is large, the puncture position of the vehicle tire has a great influence on the vehicle control, and the vehicle cannot be planned to return to the lane, and the corner radar sensor does not detect the vehicle approaching the lane or there is no risk of collision. The planned vehicle is to drive in the direction of the punctured side of the lane, as shown in Figure 12. Planning results.

In one embodiment of the present invention, the algorithm used for lateral control of the vehicle is an MPC (Model Predictive Control, model predictive control) algorithm. The process of MPC model predictive control can be summed up in three steps: forecasting model - predicting the output in a certain period of time in the future; rolling optimization - scrolling for limited time domain online optimization (optimal control); feedback correction - correcting the forecasting model through forecasting error feedback to improve forecasting accuracy.

The trajectory of the vehicle determined according to the horizontal planning path and the longitudinal planning path is the target trajectory that the ADAS system needs to control the vehicle. At the same time, the tire blowout suppression bias is used to weight the lateral planning path in the prediction model of the MPC algorithm. During the feedback correction process, the prediction model will be corrected according to the control state of the vehicle, and the tire blowout suppression bias will be adjusted. The weighted value is a calibration value, which can be calibrated according to the actual situation of the vehicle. At the next moment, the ADAS system will determine the vehicle’s trajectory and tire blowout suppression bias results based on the horizontal planning path and the longitudinal planning path at that moment, and continue to execute the three steps of the MPC algorithm model to correct the vehicle’s control state again. In the following moments, this rolling optimization and feedback correction process is repeated. Therefore, the determination of the vehicle's trajectory and vehicle control are well combined. In order to eliminate this error in the control of the MPC model, the calculated results can be understood as increasing the reverse steering wheel angle that is out of balance with the tire blowout vehicle, which is associated with the correct driving behavior when the tire blows out.

In one embodiment of the present invention, the algorithm used for longitudinal control of the vehicle is a PID (Proportion Integral Differential, proportional integral differential) adjustment algorithm.

In some embodiments of the present invention, when a tire blowout accident occurs while the vehicle is running at high speed, there will be conspicuous text or pictures on the instrument panel to inform the driver that the tire blowout driving assistance function is activated at the current moment, and the ADAS system will output the torque value to the electric power steering system EPS (Electric Power Steering, Electronic Power Steering System) for lateral control, and a relatively large torque output will be maintained at this time. If the driver intervenes with a force greater than the set value (eg> 5Nm), the ADAS system will exit the tire blowout driving assistance function. When the control reaches the preset time (assuming that after 5s), the vehicle is already in a relatively stable state, the ADAS system will control the EPS to output a small torque, and when the ADAS system judges that the longitudinal speed of the vehicle is already in a safe driving area, it will remind the driver to take over, so that the control of the lateral state of the vehicle can be well realized.

In summary, according to the assisted driving control method when a vehicle tire blows out according to the embodiment of the present invention, the vehicle’s motion track is determined according to the road condition information around the vehicle, the vehicle’s position information, and the vehicle’s body posture information, and the tire blowout suppression bias is determined according to the vehicle’s body posture information and the tire burst position information of the vehicle, and then the vehicle’s motion track is corrected according to the tire blowout suppression bias, and the vehicle is controlled to drive according to the target motion track. Therefore, this method can determine the trajectory of the vehicle and the tire burst suppression bias when the tire blows out while the vehicle is running, and correct the motion trajectory of the vehicle according to the tire burst suppression bias, so that the vehicle can be controlled to drive on a safe trajectory, reducing the probability of accidents and ensuring the safety of passengers.

Corresponding to the above-mentioned embodiments, the present invention also proposes an auxiliary driving control device when the tire of the vehicle is blown out.

FIG. 13 is a schematic block diagram of a driving assistance control device when a vehicle tire blows out according to an embodiment of the present invention.

As shown in FIG. 13 , the auxiliary driving control device for vehicle tire blowout according to the embodiment of the present invention includes: a first acquisition module 10 , a second acquisition module 20 , a third acquisition module 30 , a fourth acquisition module 40 , a movement trajectory determination module 50 , a first determination module 60 , a trajectory correction module 70 and a control module 80 .

Wherein, the first obtaining module 10 is used for obtaining road condition information around the vehicle. The second obtaining module 20 is used for obtaining the location information of the vehicle. The third acquiring module 30 is used for acquiring body attitude information of the vehicle. The fourth obtaining module 40 is used for obtaining the tire burst location information of the vehicle tire. The motion track determining module 50 is used to determine the motion track of the vehicle according to the road condition information around the vehicle, the position information of the vehicle and the body posture information of the vehicle. The first determination module 60 is used for determining the tire blowout suppression offset according to the body posture information of the vehicle and the tire blowout position information of the vehicle, wherein the tire blowout suppression offset is an offset generated when a tire blows out. The trajectory correction module 70 is used to correct the movement trajectory of the vehicle according to the tire blowout suppression bias, so as to determine the target movement trajectory of the vehicle. The control module 80 is used to control the vehicle according to the target trajectory.

According to an embodiment of the present invention, the body posture information of the vehicle includes the yaw rate of the vehicle and the lateral acceleration of the vehicle, wherein the first determination module 60 determines the tire blowout suppression bias according to the body posture information of the vehicle and the tire blowout position information of the vehicle tires, and is specifically used to determine the tire blowout suppression bias coefficient according to the tire blowout position information of the vehicle tires; determine the tire blowout suppression bias according to the tire blowout suppression bias coefficient, the yaw rate of the vehicle, and the lateral acceleration of the vehicle.

According to an embodiment of the present invention, the first determination module 60 calculates and obtains the tire blowout suppression bias through the following formula:

e _blowout ＝A _i *ω(t)+B _i *da _l (t)/dt

Among them, e _puncture represents the puncture suppression bias, A _i and _Bi represent the puncture suppression bias coefficients, ω(t) represents the yaw rate of the vehicle at time t, and a _l (t) represents the lateral acceleration of the vehicle at time t.

According to an embodiment of the present invention, the track correction module 70 corrects the motion track of the vehicle according to the tire blowout suppression bias, and is specifically used to invert the tire blowout suppression bias to obtain a correction value of the vehicle motion track; and correct the vehicle motion track according to the correction value of the vehicle motion track.

According to an embodiment of the present invention, the body posture information of the vehicle includes the longitudinal acceleration of the vehicle, wherein the motion trajectory determination module 50 determines the motion trajectory of the vehicle according to the road condition information around the vehicle, the position information of the vehicle and the body posture information of the vehicle, and is specifically used to determine the safe driving area of the vehicle according to the road condition information; determine the horizontal planning path of the vehicle according to the position information of the vehicle and the safe driving area of the vehicle; determine the longitudinal planning path of the vehicle according to the longitudinal acceleration of the vehicle; determine the motion trajectory of the vehicle according to the horizontal planning path and the longitudinal planning path.

According to an embodiment of the present invention, the position information of the vehicle includes the starting position of the vehicle, wherein the motion track determination module 50 determines the lateral planning path of the vehicle according to the position information of the vehicle and the safe driving area of the vehicle, specifically for determining the target position of the vehicle according to the safe driving area of the vehicle; determining a plurality of intermediate positions according to the lateral distance between the initial position of the vehicle and the target position of the vehicle; adopting an N-order polynomial to fit the initial position of the vehicle, the target position of the vehicle and a plurality of intermediate positions to obtain the lateral planning path of the vehicle, wherein the number of the plurality of intermediate positions is determined by an N-order polynomial, N is a positive integer.

According to an embodiment of the present invention, the motion trajectory determination module 50 determines the longitudinal planning path of the vehicle according to the longitudinal acceleration of the vehicle, specifically for obtaining the target longitudinal acceleration of the vehicle; and determines the longitudinal planning path of the vehicle according to the curve from the initial acceleration of the vehicle to the target longitudinal acceleration.

According to an embodiment of the present invention, the motion track determination module 50 determines the motion track of the vehicle according to the horizontal planning path and the longitudinal planning path, and is specifically used to perform secondary integration processing on the longitudinal planning path to obtain the curve of the vehicle's longitudinal position changing with time; obtain the position combination of the vehicle's lateral position and longitudinal position at the same time according to the horizontal planning path and the vehicle's longitudinal position changing with time curve; determine the two-dimensional motion track of the vehicle according to the position combination; use a cost function to filter the two-dimensional motion track of the vehicle to determine the vehicle's motion track.

According to an embodiment of the present invention, the motion track determining module 50 uses a cost function to screen the two-dimensional motion track of the vehicle to determine the vehicle's motion track, and is specifically used to obtain a plurality of different types of cost functions corresponding to the expected results of the cost function; respectively filter the two-dimensional motion track of the vehicle according to each cost function to obtain a corresponding minimum value; perform weighted summation on the multiple minimum values to determine the vehicle's motion track.

It should be noted that, for the details not disclosed in the driving assistance control device for vehicle tire blowout in the embodiment of the present invention, please refer to the details disclosed in the driving assistance control method for vehicle tire blowout in the embodiment of the present invention, which will not be repeated here.

According to the auxiliary driving control device when a vehicle tire blows out according to an embodiment of the present invention, the motion track determination module determines the vehicle's motion track according to the road condition information around the vehicle, the vehicle's position information and the vehicle's body attitude information, and the first determination module determines the tire blowout suppression bias according to the vehicle's body posture information and the vehicle tire's tire blowout position information, and then uses the track correction module to correct the vehicle's motion track according to the tire blowout suppression bias, and finally the control module controls the vehicle to drive according to the target motion track. Thus, when a tire blows out while the vehicle is running, the device can correct the motion track of the vehicle according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe track, reduce the probability of accidents, and ensure the safety of passengers.

Corresponding to the above embodiments, the present invention also provides a vehicle.

14 is a block schematic diagram of a vehicle according to an embodiment of the present invention.

As shown in FIG. 14 , the vehicle 200 according to the embodiment of the present invention includes a memory 210, a processor 220, and an assisted driving control program stored on the memory 210 and operable on the processor. When the processor 220 executes the assisted driving control program when the vehicle is blown out, the above-mentioned assisted driving control method when the vehicle is blown out is realized.

According to the vehicle according to the embodiment of the present invention, by implementing the above-mentioned assisted driving control method when the vehicle tire blows out, when a tire blows out while the vehicle is running, the motion track of the vehicle can be corrected according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe track, reduce the probability of accidents, and ensure the safety of passengers.

Corresponding to the foregoing embodiments, the present invention further provides a computer-readable storage medium.

The computer-readable storage medium of the embodiment of the present invention stores thereon the assisted driving control program when the vehicle tire blows out. When the vehicle punctured assisted driving control program is executed by the processor, the above-mentioned assisted driving control method when the vehicle tire blows out is realized.

According to the computer-readable storage medium of the embodiment of the present invention, by executing the above-mentioned assisted driving control method when a vehicle tire blows out, when a tire blows out while the vehicle is running, the motion track of the vehicle can be corrected according to the tire blowout suppression bias, so as to control the vehicle to drive on a safe track, reduce the probability of accidents, and ensure the safety of passengers.

It should be noted that the logic and/or steps shown in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from an instruction execution system, device or device and execute instructions), or use in combination with these instruction execution systems, devices or devices. For the purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use in or in conjunction with an instruction execution system, device or device. More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connections with one or more wires (electronic device), portable computer disk case (magnetic device), random access memory (RAM), read-only memory (ROM), erasable-editable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program can be printed, since the program can be obtained electronically, for example, by optical scanning of the paper or other medium, followed by editing, interpretation, or other suitable processing as necessary, and then stored in the computer memory.

It should be understood that various parts of the present invention can be realized by hardware, software, firmware or their combination. In the embodiments described above, various steps or methods may be implemented by software or firmware stored in memory and executed by a suitable instruction execution system. For example, if it is implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit with logic gates for implementing logic functions on data signals, an application specific integrated circuit with suitable combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

In the description of this specification, descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific examples", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with this embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

In addition, the terms "first" and "second" are used for descriptive purposes only, and cannot be interpreted as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of these features. In the description of the present invention, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

In the present invention, unless otherwise clearly specified and limited, the terms "installation", "connection", "connection", "fixation" and other terms should be understood in a broad sense, for example, it may be a fixed connection or a detachable connection, or integrated; it may be a mechanical connection or an electrical connection; it may be a direct connection or an indirect connection through an intermediate medium, and it may be the internal communication of two elements or the interaction relationship between two elements, unless otherwise clearly defined. Those of ordinary skill in the art can understand the specific meanings of the above terms in the present invention according to specific situations.

Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and those skilled in the art can change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims (12)

1. A method for controlling assisted driving when a tire of a vehicle is punctured, comprising:

acquiring road condition information around the vehicle, position information of the vehicle, body posture information of the vehicle and tire burst position information of the vehicle tire;

determining a motion trail of the vehicle according to road condition information around the vehicle, position information of the vehicle and body posture information of the vehicle;

determining a blowout suppressing bias according to the body posture information of the vehicle and the blowout position information of the vehicle tire, wherein the blowout suppressing bias is a bias generated when the tire is blown out;

correcting the motion trail of the vehicle according to the tire burst suppression bias to determine a target motion trail of the vehicle;

and controlling the vehicle according to the target motion trail.

2. The driving assist control method at the time of tire burst of the vehicle according to claim 1, characterized in that the vehicle body posture information includes a yaw rate of the vehicle and a lateral acceleration of the vehicle, wherein determining a tire burst suppression bias from the vehicle body posture information and the tire burst position information of the vehicle tire includes:

Determining a blowout inhibition bias coefficient according to the blowout position information of the vehicle tire;

and determining the tire burst suppression bias according to the tire burst suppression bias coefficient, the yaw rate of the vehicle and the lateral acceleration of the vehicle.

3. The driving assist control method at the time of a tire burst of a vehicle according to claim 2, wherein the tire burst suppression bias is obtained by calculation by the following formula:

e _{tire burst} ＝A _i *ω(t)+B _i *da _l (t)/dt

Wherein e _{Tire burst} Representing the puncture inhibiting bias, A _i And B _i Represents the runflat suppression bias coefficient, ω (t) represents the yaw rate of the vehicle at time t, a _l (t) represents the lateral acceleration of the vehicle at time t.

4. A driving assist control method at the time of tire burst of a vehicle according to any one of claims 1 to 3, characterized in that correcting a movement locus of the vehicle according to the tire burst suppression bias includes:

inverting the tire burst suppression bias to obtain a correction value of the motion trail of the vehicle;

and correcting the motion trail of the vehicle according to the correction value of the motion trail of the vehicle.

5. The driving support control method at the time of tire burst of the vehicle according to claim 1, wherein the body posture information of the vehicle includes a longitudinal acceleration of the vehicle, wherein determining a movement locus of the vehicle based on road condition information around the vehicle, position information of the vehicle, and body posture information of the vehicle includes:

Determining a safe driving area of the vehicle according to the road condition information;

determining a transverse planning path of the vehicle according to the position information of the vehicle and the safe driving area of the vehicle;

determining a longitudinal planned path of the vehicle according to the longitudinal acceleration of the vehicle;

and determining the movement track of the vehicle according to the transverse planning path and the longitudinal planning path.

6. The driving support control method at the time of tire burst of the vehicle according to claim 5, wherein the position information of the vehicle includes a start position of the vehicle, wherein determining the lateral planned path of the vehicle based on the position information of the vehicle and the safe running area of the vehicle includes:

determining a target position of the vehicle according to a safe driving area of the vehicle;

determining a plurality of intermediate positions according to a lateral distance between a starting position of the vehicle and a target position of the vehicle;

and fitting the starting position of the vehicle, the target position of the vehicle and the plurality of intermediate positions by using an N-order polynomial to obtain a transverse planning path of the vehicle, wherein the number of the plurality of intermediate positions is determined by the N-order polynomial, and N is a positive integer.

7. The driving assist control method for a tire burst of a vehicle according to claim 5, wherein determining a longitudinal planned path of the vehicle from a longitudinal acceleration of the vehicle comprises:

acquiring a target longitudinal acceleration of the vehicle;

and determining a longitudinal planning path of the vehicle according to a curve from the initial acceleration of the vehicle to the target longitudinal acceleration.

8. The driving assist control method for a tire burst of a vehicle according to claim 5, wherein determining a movement locus of the vehicle from the lateral planned path and the longitudinal planned path comprises:

performing secondary integration processing on the longitudinal planning path to obtain a curve of the longitudinal position of the vehicle changing along with time;

obtaining a position combination of the transverse position and the longitudinal position of the vehicle at the same moment according to the transverse planning path and the curve of the longitudinal position of the vehicle changing along with time;

determining a two-dimensional motion trail of the vehicle according to the position combination;

and screening the two-dimensional motion trail of the vehicle by using a cost function to determine the motion trail of the vehicle.

9. The driving support control method for a tire burst of a vehicle according to claim 8, wherein screening the two-dimensional motion trajectory of the vehicle with a cost function to determine the motion trajectory of the vehicle, comprises:

Acquiring a plurality of different types of cost functions corresponding to expected results of the cost functions;

screening the two-dimensional motion trail of the vehicle according to each cost function to obtain a corresponding minimum value;

a weighted sum of the plurality of minima is performed to determine a trajectory of movement of the vehicle.

10. An assisted driving control device for a vehicle when a tire burst occurs, comprising:

the first acquisition module is used for acquiring road condition information around the vehicle;

the second acquisition module is used for acquiring the position information of the vehicle;

a third acquisition module for acquiring body posture information of the vehicle;

a fourth obtaining module, configured to obtain puncture location information of the vehicle tire;

the motion trail determining module is used for determining the motion trail of the vehicle according to the road condition information around the vehicle, the position information of the vehicle and the body posture information of the vehicle;

a first determining module, configured to determine a blowout suppressing bias according to body posture information of the vehicle and blowout position information of the vehicle tire, where the blowout suppressing bias is a bias generated when the tire is blown out;

the track correction module is used for correcting the motion track of the vehicle according to the tire burst suppression bias so as to determine the target motion track of the vehicle;

And the control module is used for controlling the vehicle according to the target motion trail.

11. A vehicle characterized by comprising a memory, a processor and a driving assistance control program stored on the memory and operable on the processor when the vehicle is flat, wherein the processor implements the driving assistance control method when the vehicle is flat according to any one of claims 1-9 when executing the driving assistance control program when the vehicle is flat.

12. A computer-readable storage medium, characterized in that an assisted driving control program at the time of a tire burst of a vehicle is stored thereon, which when executed by a processor, implements the assisted driving control method at the time of a tire burst of a vehicle according to any one of claims 1 to 9.