Control method and device and intelligent driving equipment

Abstract

The invention discloses a control method and device and intelligent driving equipment, and the method comprises the steps: determining a second torque at least according to a first torque of a steering wheel when there is a collision risk between the intelligent driving equipment and an obstacle; wherein the first torque is the torque acting on the steering wheel by a user of the intelligent driving equipment, the direction of the second torque is opposite to that of the first torque, and the value obtained by subtracting the value of the first torque from the value of the second torque is larger than or equal to a first preset threshold value; controlling the steering wheel according to the first torque and the second torque. The technical scheme can be applied to intelligent driving equipment such as electric vehicles and new energy vehicles, when the collision risk is detected, the torque of the steering wheel can be controlled in combination with the action intention of a driver, the behaviors of the intelligent driving equipment in the obstacle avoidance process can be more similar to those of people, and the obstacle avoidance efficiency is improved. And large lateral acceleration caused by overlarge torque applied when the obstacle avoidance function is triggered can be avoided, so that the driving experience of a driver and passengers is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving, and more specifically, to a control method, device and intelligent driving equipment. Background Art

[0002] With the rapid development of the automotive industry, many assisted driving and autonomous driving technologies have emerged, which can reduce driving pressure, improve safety and traffic efficiency. Assisted driving functions include active safety functions, which can take active judgments and preventive safety measures in emergency situations before the driver's subjective reaction, thereby significantly reducing road traffic accidents and related casualties.

[0003] However, under the current technical background, the timing of triggering active safety functions is very close to the moment of collision, resulting in a large deceleration or lateral acceleration value of the vehicle designed when the function is triggered, affecting the driving experience of the driver and passengers, and even causing function failure, threatening driving safety. Summary of the invention

[0004] The present application provides a control method, device and intelligent driving equipment. When a collision risk is detected, the steering wheel torque can be controlled in combination with the driver's action intention, which can not only make the behavior of the intelligent driving equipment more human-like during the obstacle avoidance process, but also avoid applying excessive torque when the obstacle avoidance function is triggered to cause a large lateral acceleration, thereby improving the driving experience of the driver and passengers.

[0005] In a first aspect, a control method is provided, which can be executed by an intelligent driving device; or, it can also be executed by a computing platform of the intelligent driving device; or, it can also be executed by a chip or circuit used for the intelligent driving device, which is not limited in this application.

[0006] The method includes: when there is a risk of collision between the intelligent driving device and the first obstacle, determining a second torque at least based on a first torque of the steering wheel; wherein the first torque is a torque applied to the steering wheel by a user of the intelligent driving device, the direction of the second torque is opposite to the direction of the first torque, and the value of the second torque minus the value of the first torque is greater than or equal to a first preset threshold; and controlling the steering wheel based on the first torque and the second torque.

[0007] It should be noted that the value of the first torque refers to the torque value of the first torque, and the value of the second torque refers to the torque value of the second torque.

[0008] In some possible implementations, the first preset threshold may be a negative number, that is, the value of the second torque may be less than the value of the first torque. For example, the first preset threshold may be -0.5 Newton·meter (N·m), or the first preset threshold may be other values.

[0009] For example, under the action of the first torque, the intelligent driving device moves from the current driving direction toward the first side of the intelligent driving device, and the first obstacle is located on the first side of the intelligent driving device. The first side may be the left side or the right side of the intelligent driving device.

[0010] In the above technical solution, when a collision risk is detected, an opposite force can be applied to the steering wheel according to the torque applied by the driver to the steering wheel to remind the driver of the collision risk. In addition, the steering wheel can be controlled in combination with the driver's action intention, which can also make the behavior of the intelligent driving device more human-like during the obstacle avoidance process, and can also avoid applying excessive torque when the obstacle avoidance function is triggered to cause a large lateral acceleration, thereby improving the driving experience of the driver and passengers.

[0011] It should be noted that, in the present application, the transverse direction refers to a direction perpendicular to the longitudinal symmetry plane of the intelligent driving device, and the longitudinal direction refers to a direction parallel to the longitudinal symmetry plane of the intelligent driving device.

[0012] In combination with the first aspect, in certain implementations of the first aspect, the second torque is determined at least based on the first torque of the steering wheel, including: determining the value of the second torque based on a first collision risk between the intelligent driving device and the first obstacle and the value of the first torque; wherein, when the first collision risk is less than or equal to a first threshold, the value of the second torque minus the value of the first torque is greater than or equal to a first preset threshold and less than a second preset threshold; or, when the first collision risk is greater than the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the second preset threshold.

[0013] Exemplarily, the second preset threshold may be zero, or may be a positive number.

[0014] Exemplarily, the value of the second torque can be determined according to the magnitude of the first collision risk. The greater the first collision risk, the greater the difference between the value of the second torque and the value of the first torque. Furthermore, under the action of the second torque, the lateral acceleration of the intelligent driving device in the direction opposite to the first side is greater.

[0015] In some possible implementations, the first collision risk may be measured according to time to collision (TTC), and the first collision risk may be quantified into at least two levels according to the TTC.

[0016] In some possible implementations, the first collision risk may be measured according to the distance between the first obstacle and the intelligent driving device and the time to react (TTR), and the first collision risk may be quantified into at least two levels.

[0017] In some possible implementations, the first collision risk may be calculated in combination with the positions and speeds of other obstacles except the first obstacle, and the position and speed of each obstacle may quantify the first collision risk into at least two levels.

[0018] Exemplarily, the at least two levels may include level 1 and level 2. The collision risk corresponding to level 1 is smaller than the collision risk corresponding to level 2. The first threshold may be level 1.

[0019] In the above technical solution, before a collision occurs, the steering wheel torque is intervened in stages according to the collision risk. When the collision risk is small, an anti-torque is generated according to the torque applied by the driver to the steering wheel. The anti-torque can promptly remind the driver of the existence of the collision risk, which helps to prevent the intelligent driving device from entering a more dangerous driving scenario. When the collision risk is large, a corrective torque can be generated according to the torque applied by the driver to the steering wheel. The corrective torque can avoid the occurrence of a collision and help improve driving safety.

[0020] In combination with the first aspect, in certain implementations of the first aspect, the method also includes: when the second collision risk between the intelligent driving device and the first obstacle is less than or equal to a second threshold, determining a first longitudinal acceleration according to driving comfort, and controlling the intelligent driving device to decelerate according to the first longitudinal acceleration; or, when the second collision risk is greater than the second threshold, determining a second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and controlling the intelligent driving device to decelerate according to the second longitudinal acceleration; wherein the absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

[0021] It can be understood that both the first longitudinal acceleration and the second longitudinal acceleration are negative values.

[0022] In some possible implementations, the second collision risk is measured according to TTC, and the second collision risk is quantified into at least two levels according to TTC; or, the second collision risk is measured according to the distance between the first obstacle and the intelligent driving device and TTR, and the second collision risk is quantified into at least two levels.

[0023] In some possible implementations, a method for determining the second collision risk is the same as a method for determining the first collision risk.

[0024] Exemplarily, determining the second longitudinal acceleration at least based on the distance between the intelligent driving device and the first obstacle includes: determining TTC based on the distance between the intelligent driving device and the first obstacle, and the relative speed between the two, and determining the second longitudinal acceleration based on TTC and the current speed of the intelligent driving device.

[0025] In the above technical solution, the collision risk of the intelligent driving device is predicted in advance. When the collision risk is small, the intelligent driving device can be controlled to slow down at an acceleration that does not affect the driver's physical sensation, which can prevent the intelligent driving device from entering more dangerous scenes (such as scenes with greater collision risks). While ensuring driving safety, it helps to improve the experience of drivers and passengers. In the case of a large collision risk, it can still be decelerated at a faster acceleration to improve driving safety. In addition, when the collision risk is detected, through the joint lateral and longitudinal control, in more complex driving scenarios, it helps to reduce the probability of collision and improve driving safety.

[0026] In combination with the first aspect, in certain implementations of the first aspect, the method also includes: when the third collision risk between the intelligent driving device and the first obstacle is greater than or equal to a third threshold, determining a first motion trajectory based on control information input by a user of the intelligent driving device and an obstacle boundary, the control information including at least one of the following: opening information of an accelerator pedal of the intelligent driving device, opening information of a deceleration pedal of the intelligent driving device, and a first torque, and the obstacle boundary is determined by multiple obstacles including the first obstacle; the above-mentioned determining the second torque at least based on the first torque of the steering wheel includes: determining the second torque based on the first motion trajectory and the first torque, so that when the steering wheel is controlled according to the second torque, the intelligent driving device travels along the first motion trajectory.

[0027] In some possible implementations, the method for determining the third collision risk is the same as the method for determining the first and second collision risks. For example, the third collision risk is determined according to TTC, and the third threshold is smaller than the first and second thresholds.

[0028] In some possible implementations, the first collision risk and the second collision risk are determined by the first motion trajectory.

[0029] In the above technical solution, trajectory planning is performed according to the control information input by the user, which helps to generate an obstacle avoidance trajectory (such as the first motion trajectory) that conforms to the driver's driving behavior, and can improve the driver's driving experience. Furthermore, lateral control is performed based on the obstacle avoidance trajectory that conforms to the driver's driving behavior, which helps to improve the human-likeness of the lateral control of the intelligent driving device.

[0030] In combination with the first aspect, in certain implementations of the first aspect, the method also includes: determining multiple motion trajectories based on the driver's reaction time and a reachable set of control parameters, where the reachable set of control parameters is a set of motion parameters that can be achieved by the intelligent driving device under user control; determining a third collision risk based on the multiple motion trajectories and the position and speed of the first obstacle.

[0031] Exemplarily, determining a third collision risk based on multiple motion trajectories and the position and speed of the first obstacle includes: determining the collision risk of each of the multiple motion trajectories based on the position and speed of the first obstacle; assigning different weights to the collision risk of each motion trajectory and then adding them up to obtain the third collision risk.

[0032] Exemplarily, the weights may be determined according to the lateral offset of the motion trajectory, and the larger the lateral offset, the smaller the weight.

[0033] In the above technical solution, multiple motion trajectories are determined based on the driver's reaction time and the control parameter reachable set, which can detect potential collision risks in advance, and then control the intelligent driving device laterally and / or longitudinally according to the potential collision risks, which can prevent the intelligent driving device from entering a scene with a greater collision risk, and help improve the driving experience of the driver and passengers. Predicting the collision risk based on multiple motion trajectories helps reduce the probability of misjudging the collision risk, and can increase the detection rate of potential collision risks in complex scenes, thereby improving driving safety.

[0034] In combination with the first aspect, in certain implementations of the first aspect, the first obstacle includes at least one of the following: a motor vehicle, a non-motor vehicle, a general obstacle, and a pedestrian.

[0035] In the above technical solution, when performing collision risk detection, in addition to motor vehicles, the impact of other types of obstacles on intelligent driving equipment is also considered, which helps to improve driving safety.

[0036] In combination with the first aspect, in certain implementations of the first aspect, the second torque is determined at least based on the first torque of the steering wheel, including: determining the value of the second torque based on the TTC between the intelligent driving device and the first obstacle and the value of the first torque; wherein, when the TTC is greater than or equal to the first time length, the value of the second torque minus the value of the first torque is greater than or equal to the first preset threshold and less than the second preset threshold; or, when the TTC is less than the first time length, the value of the second torque minus the value of the first torque is greater than or equal to the second preset threshold.

[0037] Exemplarily, the first duration may be 1.5 seconds, or the first duration may be other values.

[0038] In combination with the first aspect, in certain implementations of the first aspect, the method further includes: when the remaining distance between the intelligent driving device and the first obstacle is greater than or equal to a preset distance, determining a first longitudinal acceleration according to driving comfort, and controlling the intelligent driving device to decelerate according to the first longitudinal acceleration; or, when the remaining distance is less than the preset distance, determining a second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and controlling the intelligent driving device to decelerate according to the second longitudinal acceleration; wherein the absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

[0039] Exemplarily, the remaining distance may be the actual longitudinal distance between the intelligent driving device and the first obstacle minus the product of the speed of the intelligent driving device and the driver's reaction time.

[0040] Exemplarily, the preset distance may be 2 meters, or the preset distance may be other values.

[0041] In a second aspect, a control method is provided, the method comprising: when a second collision risk between the intelligent driving device and the first obstacle is less than or equal to a second threshold, determining a first longitudinal acceleration according to driving comfort, and controlling the intelligent driving device to decelerate according to the first longitudinal acceleration; or, when the second collision risk is greater than the second threshold, determining a second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and controlling the intelligent driving device to decelerate according to the second longitudinal acceleration; wherein the absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

[0042] In combination with the second aspect, in certain implementations of the second aspect, the method also includes: determining a value of a second torque based on a first collision risk between the intelligent driving device and the first obstacle and a value of a first torque of the steering wheel; wherein the first torque is a torque applied to the steering wheel by a user of the intelligent driving device, and a direction of the second torque is opposite to that of the first torque; when the first collision risk is less than or equal to a first threshold, the value of the second torque minus the value of the first torque is greater than or equal to a first preset threshold and less than a second preset threshold; or, when the first collision risk is greater than the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to a second preset threshold; and controlling the steering wheel based on the first torque and the second torque.

[0043] In combination with the second aspect, in certain implementations of the second aspect, the method also includes: when the third collision risk between the intelligent driving device and the first obstacle is greater than or equal to a third threshold, determining a first motion trajectory based on control information input by a user of the intelligent driving device and an obstacle boundary, the control information including at least one of the following: opening information of an accelerator pedal of the intelligent driving device, opening information of a deceleration pedal of the intelligent driving device, and a first torque, and the obstacle boundary is determined by multiple obstacles including the first obstacle; the above-mentioned determining the second torque at least based on the first torque of the steering wheel includes: determining the second torque based on the first motion trajectory and the first torque, so that when the steering wheel is controlled based on the second torque, the intelligent driving device travels along the first motion trajectory.

[0044] In combination with the second aspect, in certain implementations of the second aspect, the method also includes: determining multiple motion trajectories based on the driver's reaction time and a reachable set of control parameters, where the reachable set of control parameters is a set of motion parameters that can be achieved by the intelligent driving device under user control; determining a third collision risk based on the multiple motion trajectories and the position and speed of the first obstacle.

[0045] In combination with the second aspect, in certain implementations of the second aspect, the first obstacle includes at least one of the following: a motor vehicle, a non-motor vehicle, a general obstacle, and a pedestrian.

[0046] In a third aspect, a control device is provided, which includes: a first determination unit, used to determine a second torque based on at least a first torque of a steering wheel when there is a risk of collision between an intelligent driving device and a first obstacle; wherein the first torque is a torque applied to the steering wheel by a user of the intelligent driving device, a direction of the second torque is opposite to a direction of the first torque, and a value of the second torque minus a value of the first torque is greater than or equal to a first set threshold; and a processing unit, used to control the steering wheel based on the first torque and the second torque.

[0047] In combination with the third aspect, in certain implementations of the third aspect, the first determination unit is used to: determine the value of the second torque based on the first collision risk between the intelligent driving device and the first obstacle and the value of the first torque; wherein, when the first collision risk is less than or equal to the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the first preset threshold and less than the second preset threshold; or, when the first collision risk is greater than the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the second preset threshold.

[0048] In combination with the third aspect, in certain implementations of the third aspect, the first determination unit is further used to: when the second collision risk between the intelligent driving device and the first obstacle is less than or equal to a second threshold, determine the first longitudinal acceleration according to the driving comfort, and control the intelligent driving device to decelerate according to the first longitudinal acceleration; or, when the second collision risk is greater than the second threshold, determine the second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and control the intelligent driving device to decelerate according to the second longitudinal acceleration; wherein the absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

[0049] In combination with the third aspect, in certain implementations of the third aspect, the device also includes a second determination unit, which is used to: when the third collision risk between the intelligent driving device and the first obstacle is greater than or equal to the third threshold, determine the first motion trajectory according to control information input by a user of the intelligent driving device and the obstacle boundary, the control information including at least one of the following: opening information of an accelerator pedal of the intelligent driving device, opening information of a deceleration pedal of the intelligent driving device, and a first torque, and the obstacle boundary is determined by multiple obstacles including the first obstacle; the first determination unit is used to: determine the second torque according to the first motion trajectory and the first torque, so that when the steering wheel is controlled according to the second torque, the intelligent driving device travels along the first motion trajectory.

[0050] In combination with the third aspect, in certain implementations of the third aspect, the device also includes a third determination unit, which is used to: determine multiple motion trajectories based on the driver's reaction time and a reachable set of control parameters, where the reachable set of control parameters is a set of motion parameters that can be achieved by the intelligent driving device under user control; determine a third collision risk based on the multiple motion trajectories and the position and speed of the first obstacle.

[0051] In combination with the third aspect, in certain implementations of the third aspect, the first obstacle includes at least one of the following: a motor vehicle, a non-motor vehicle, a general obstacle, and a pedestrian.

[0052] In a fourth aspect, a control device is provided, comprising a determination unit and a processing unit, for executing a method as in any possible implementation of the second aspect.

[0053] In a fifth aspect, a control device is provided, comprising: a memory for storing a computer program; and a processor for executing the computer program stored in the memory, so that the device performs a method in any possible implementation of the first aspect or the second aspect.

[0054] In a sixth aspect, an intelligent driving device is provided, which includes a device as in any possible implementation of the third to fifth aspects.

[0055] In combination with the sixth aspect, in certain implementations of the sixth aspect, the intelligent driving device is a vehicle.

[0056] In a seventh aspect, a computer program product is provided, the computer program product comprising: a computer program code, when the computer program code is run on a computer, the computer executes a method in any possible implementation of the first aspect or the second aspect.

[0057] It should be noted that the above-mentioned computer program code may be stored in whole or in part on a first storage medium, wherein the first storage medium may be packaged together with the processor or may be packaged separately from the processor.

[0058] In an eighth aspect, a computer-readable medium is provided, wherein the computer-readable medium stores instructions, and when the instructions are executed by a processor, the processor implements the method in any possible implementation of the first aspect or the second aspect.

[0059] In a ninth aspect, a chip is provided, the chip comprising a circuit, the circuit being used to execute the method in any possible implementation of the first aspect or the second aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a schematic diagram of a driving scenario;

[0061] Figure 2 is a functional schematic block diagram of an intelligent driving device provided in an embodiment of the present application;

[0062] Figure 3 is a schematic diagram of the system architecture required for implementing the control method provided in the embodiment of the present application;

[0063] Figure 4 is a schematic flow chart of a control method provided in an embodiment of the present application;

[0064] Figure 5 is a schematic diagram of a driving scenario provided in an embodiment of the present application;

[0065] Figure 6 is a schematic diagram of another driving scenario provided in an embodiment of the present application;

[0066] Figure 7 is another schematic flow chart of the control method provided in the embodiment of the present application;

[0067] Figure 8 is a schematic block diagram of a control device provided in an embodiment of the present application;

[0068] Fig. 9This is another schematic block diagram of the control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0069] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0070] As mentioned above, the timing of triggering active safety functions is very close to the moment of collision, resulting in a large deceleration or lateral acceleration value of the designed vehicle when the function is triggered, affecting the driving experience of the driver and passengers, and even causing function failure, threatening driving safety.

[0071] In addition, active safety functions have difficulty making reasonable decisions when road conditions are complex. Figure 1 In the scenario shown, the autonomous emergency braking (AEB) function usually triggers emergency braking for the nearest front vehicle (such as the other car in the picture), and the triggering time is generally between 0.8 seconds and 1.6 seconds before the collision. It can be seen that the actual triggering time of AEB is relatively close to the collision time, and the collision cannot be avoided in some scenarios. For example, if the front vehicle decelerates suddenly, the AEB function may not be able to avoid the collision. In the above situation, the evasive steering assist (ESA) function can also be used to assist the driver in emergency lateral collision avoidance. However, for Figure 1 In the scenario shown, when the vehicle takes the lane change path shown in the figure, it may not be able to avoid colliding with the obstacle on the right. In other words, the above-mentioned AEB function and ESA function can only perform longitudinal control and lateral control on the vehicle respectively, and single lateral or longitudinal control is not effective for Figure 1 The more complex scenario shown cannot avoid collisions.

[0072] In view of this, the embodiments of the present application provide a control method, device and intelligent driving equipment, which can plan the path in advance in combination with the driver's driving intention when a collision risk is detected, and control the vehicle to avoid obstacles through the joint planning of lateral and longitudinal control, thereby improving the driving safety of the vehicle. In addition, the control method provided in the embodiments of the present application can control the torque of the steering wheel in stages when performing lateral control, which can not only timely remind the driver through the steering wheel torque at the early stage of the collision risk, but also avoid the steering wheel torque from intervening too early in the opposite direction of the possible collision, affecting the driver's driving experience.

[0073] The technical solutions in the embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0074] Figure 2It is a functional block diagram of the intelligent driving device 100 provided in an embodiment of the present application. The intelligent driving device 100 may include a perception system 120, an interactive system 130 and a computing platform 150, wherein the perception system 120 may include one or more sensors for sensing information about the environment around the intelligent driving device 100. For example, the perception system 120 may include a positioning system, and the positioning system may be a global positioning system (GPS), or a Beidou system or other positioning systems, or an inertial measurement unit (IMU). For another example, the perception system 120 may also include one or more of a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera device.

[0075] The interactive system 130 may include a hand force interaction module, which may include a torque detection device for detecting the torque applied by the driver's hand to the steering wheel. The interactive system 130 may also include a human-machine interface (HMI) for providing the user with a triggering opportunity for adjusting the anti-collision function of the auxiliary driving system to adapt to different driver styles. Exemplarily, the interactive system 130 may also include a speaker, a sound device, etc., for broadcasting information to the user.

[0076] Some or all functions of the intelligent driving device 100 may be controlled by the computing platform 150. The computing platform 150 may include one or more processors, such as processors 151 to 15n (n is a positive integer). The processor is a circuit with the ability to process instructions. In one implementation, the processor may be a circuit with the ability to read and run instructions, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationship of the hardware circuit, and the logical relationship of the hardware circuit is fixed or reconfigurable, such as a hardware circuit implemented by a processor as an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as a field programmable gate array (FPGA). In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc. In addition, the computing platform 150 can also include a memory, the memory is used to store instructions, and some or all of the processors 151 to 15n can call the instructions in the memory and execute the instructions to achieve corresponding functions.

[0077] The intelligent driving device 100 may include an advanced driving assistant system (ADAS). ADAS uses a variety of sensors on the intelligent driving device (including but not limited to: lidar, millimeter wave radar, camera device, ultrasonic sensor, global positioning system, inertial measurement unit) to obtain information from the surroundings of the intelligent driving device, and analyzes and processes the obtained information to achieve functions such as obstacle perception, target recognition, intelligent driving device positioning, path planning, user monitoring / reminder, etc., thereby improving the safety, automation and comfort of driving the intelligent driving device.

[0078] In terms of logical functions, ADAS systems generally include three main functional modules: perception module, decision module and execution module. The perception module perceives the environment around the vehicle body through sensors and inputs corresponding real-time data to the decision-making layer processing center. The perception module mainly includes on-board cameras / ultrasonic radars / millimeter-wave radars / lidar, etc.; the decision module uses computing devices and algorithms to make corresponding decisions based on the information obtained by the perception module; the execution module takes corresponding actions after receiving the decision instructions from the decision module, such as driving, changing lanes, steering, braking, and warnings.

[0079] In an embodiment of the present application, the computing platform 150 can generate multiple predicted trajectories based on the driver's intention, and then evaluate the current collision risk based on the multiple predicted trajectories and the position, speed and other information of obstacles around the intelligent driving device collected by the perception system 120. When the collision risk is greater than or equal to a preset threshold, the anti-collision function is activated, and the intelligent driving device is laterally and longitudinally controlled based on the above-mentioned multiple predicted trajectories and relevant information of the obstacles, wherein the lateral control can be performed in combination with the hand torque applied to the steering wheel by the user collected by the interactive system 130.

[0080] The intelligent driving equipment involved in this application may include road vehicles, water vehicles, air vehicles, industrial equipment, agricultural equipment, or entertainment equipment, etc. For example, the intelligent driving equipment may be a vehicle, which is a vehicle in a broad sense, and may be a vehicle (such as a commercial vehicle, a passenger car, a motorcycle, a flying car, a train, etc.), an industrial vehicle (such as a forklift, a trailer, a tractor, etc.), an engineering vehicle (such as an excavator, a bulldozer, a crane, etc.), agricultural equipment (such as a lawn mower, a harvester, etc.), amusement equipment, a toy vehicle, etc. The embodiment of this application does not specifically limit the type of vehicle.

[0081] Figure 2 FIG. 1 is a schematic diagram showing the system architecture required for implementing the control method provided in the embodiment of the present application. Figure 2 As shown, the system includes a perception module 210, an activation decision module 220, a horizontal and vertical planning module 230 and an interaction module 240. The perception module 210 may include Figure 1 One or more sensors in the perception system 120 shown in the figure, the activation decision module 220, the lateral and longitudinal planning module 230 can respectively include Figure 1 In the illustrated computing platform 150, one or more processors, the interaction module 240 may include Figure 1 One or more modules in the interactive system 130 shown.

[0082] The perception module 210 is used to collect real-time operating parameters of the intelligent driving device (such as driving speed, power information, steering wheel angle), as well as the location and speed of obstacles around the intelligent driving device. The perception module 210 sends the relevant information it perceives to the activation decision module 220 and the lateral and longitudinal planning module 230.

[0083] The activation decision module 220 generates a plurality of predicted trajectory lines according to the real-time operating parameters of the driving device and the driver's reaction time; further, the activation decision module 220 evaluates the collision risk of the intelligent driving device according to the plurality of predicted trajectory lines and the position and speed information of obstacles around the intelligent driving device. When the collision risk is greater than or equal to the preset threshold, the activation decision module 220 activates the lateral and longitudinal planning module 230 to perform lateral and longitudinal control of the intelligent driving device to avoid collision. Among them, the lateral and longitudinal planning module 230 includes a path planning module 231, a speed planning module 232 and a trajectory selection module 233. The path planning module 231 generates a plurality of lateral paths based on the sampling of the state space. The speed planning module 232 plans the longitudinal speed of the lateral path based on the speed, acceleration and other information of the intelligent driving device to obtain a plurality of planned trajectories. The trajectory selection module 233 determines a planned trajectory from the plurality of trajectories output by the speed planning module 232 and inputs it to the interaction module 240. Exemplarily, the planned trajectory determined by the trajectory selection module 233 may be the trajectory that best meets the driver's intention.

[0084] The interaction module 240 includes a longitudinal control module 241, a torque calculation module 242 and a torque interaction module 243, wherein the longitudinal control module 241 determines the planned speed of the intelligent driving device according to the planned trajectory, and the torque calculation module 242 determines the preliminary planned torque of the steering wheel according to the planned trajectory, and inputs the preliminary planned torque to the torque interaction module 243. Further, the torque interaction module 243 determines the final planned torque according to the force applied by the user to the steering wheel and the collision risk. When the intelligent driving device executes the above-mentioned planned speed and final planned torque, it can drive according to the planned trajectory.

[0085] It should be understood that the above modules are only examples, and in actual applications, the above modules may be added or deleted according to actual needs. Figure 3 In the system architecture shown in , the path planning module 231 and the speed planning module 232 can be combined into one module.

[0086] Figure 4 The schematic flow chart of the control method provided in the embodiment of the present application is shown. The method can be applied to Figure 2 In the intelligent driving device shown, or the method can be performed by Figure 3For example, the following description is made by taking the intelligent driving device as a vehicle and the method being executed by a computing platform of the vehicle as an example, and the method 400 may include:

[0087] S401, when at least one obstacle is detected within a preset range of the vehicle, a plurality of predicted trajectory lines are generated according to control information input by the driver and a reachable set of control parameters.

[0088] The control parameter reachable set is a set of motion parameters that can be achieved by the vehicle under user control, for example, the longitudinal acceleration and lateral displacement that can be achieved by the vehicle under user control.

[0089] Exemplarily, the preset range may be a range of 100 meters from the outer contour of the vehicle, or a range that may affect the driving safety of the vehicle, or another range.

[0090] Exemplarily, at least one obstacle may be stationary or movable, and the at least one obstacle may include, but is not limited to: motor vehicles, non-motor vehicles, general obstacles, and pedestrians. Among them, general obstacles may include roadblocks such as cones and triangular warning signs, or may include temporary warning signs set up on the road, or may include obstacles such as guardrails, walls, and stone piers.

[0091] It should be noted that the at least one obstacle may include an obstacle in front of the vehicle, and may also include obstacles located behind and to the side of the vehicle within a preset range.

[0092] For example, the control information may include, but is not limited to: the opening information of the accelerator pedal of the vehicle, the opening information of the decelerator pedal of the vehicle, and the torque of the steering wheel. The opening information includes the opening size and the opening change rate.

[0093] In some possible implementations, in order to generate multiple predicted trajectory lines, lateral path deduction and longitudinal trajectory deduction may be performed separately. Further, multiple predicted trajectory lines with time information are generated according to the lateral path and the longitudinal trajectory.

[0094] For example, the lateral path of the vehicle can be deduced by the following formula:

[0095]

[0096] Among them, s e is the longitudinal position of the vehicle, l(s e ) is the vehicle longitudinal position s e The corresponding lateral offset. is a position at a first distance from the starting position in the longitudinal direction of the vehicle, the first distance being calculated based on the driver's reaction time and the current speed of the vehicle. The starting position in the longitudinal direction of the vehicle can be understood as the position of the vehicle in a direction parallel to the longitudinal symmetry plane of the vehicle at the current moment. For example, Can be Figure 5 The length of the TTR interval shown in , i.e., the distance from the vehicle head to point a; to Can be Figure 5 The reachable interval is shown in . Lateraloffset cur is the lateral offset of the vehicle at the current moment, lateraloffset re is the lateral offset at the end of the cubic curve connection, which can be determined based on the torque applied by the driver to the steering wheel and / or the lateral acceleration that the vehicle can reach under user control: is the longitudinal position where the cubic curve ends. This value can be preset by the system. In specific implementation, it can be dynamically adjusted according to the vehicle model and the degree of aggressiveness of the driver. For example, when the vehicle model is a large vehicle or the driver drives more aggressively, The value of is larger. arrive Use cubic curves to connect paths, and cubic curves are The tangent direction at is parallel to the driving direction of the vehicle, wherein a, b, c, and d are coefficients of a cubic polynomial, and their specific values ​​can be determined according to the control information input by the driver, and this application does not limit their specific values.

[0097] Exemplarily, the driver reaction time may be preset by the system, or may be set by the user of the vehicle. For example, the driver reaction time may be any value between 0.4 seconds and 1.0 seconds.

[0098] Further, the longitudinal trajectory of the vehicle is determined according to the opening information of the accelerator pedal, the opening information of the decelerator pedal, and the longitudinal acceleration that the vehicle can achieve in response to the driver's control in the current running state.

[0099] It is understood that the longitudinal trajectory includes the longitudinal position (s e ) changes with the time of simulation.

[0100] It should be noted that the lateral acceleration that the vehicle may achieve under the control of the user may be a lateral acceleration interval, and the longitudinal acceleration that the vehicle may achieve in response to the driver's control in the current operating state may be a longitudinal acceleration interval. Therefore, the deduced lateral path and longitudinal trajectory may have multiple sets of data respectively. In the specific implementation process, the user can adjust the number of predicted trajectory lines by adjusting the value step size of the lateral and longitudinal acceleration intervals.

[0101] S402, assessing collision risk 1 based on multiple predicted trajectory lines and information such as the position and speed of at least one obstacle.

[0102] For example, the collision risk 1 can be determined by the following formula (2):

[0103] S co =∑ i s i *cost i , (2)

[0104] Among them, S co is the collision risk 1, cost i is the collision risk of trajectory i among multiple predicted trajectories, s i is the weight of the collision risk of trajectory i. Where i is a positive integer, s i It can be a value between 0 and 1. i The specific value of can be determined according to the lateral offset of the predicted trajectory relative to the current position of the vehicle. The larger the lateral offset, the smaller the weight.

[0105] Among them, cost i Determined according to the following formula (3):

[0106]

[0107] in, Indicates whether the vehicle will collide with an obstacle when traveling along trajectory i. If a collision occurs, Take 1, no collision occurs, Take 0. Indicates the degree of consistency between trajectory line i and the driver's driving intention, It can be a value between 0 and 1. The more the trajectory line i matches the driver's driving intention, The smaller. It indicates the comfort of the driver in the vehicle when the vehicle is traveling along the trajectory i, which can be determined by formula (4). w1, w2, and w3 are respectively The weights w1, w2, and w3 take values ​​between 0 and 1, and the sum of w1, w2, and w3 is equal to 1.

[0108]

[0109] Wherein, jerk represents the acceleration change rate of the vehicle, jerkThresMin represents the lower threshold of the acceleration change rate of the vehicle, and jerkThresMax represents the upper threshold of the acceleration change rate of the vehicle. For example, when jerk is less than jerkThresMin, cost ve Take 0; when jerk is greater than jerkThresMax, cost ve Take 1.

[0110] It can be understood that the maximum cost of each trajectory line is 1 and the minimum cost is 0.

[0111] S403: When the collision risk 1 is greater than or equal to the trigger threshold, a lateral reference line is generated based on the sampling of the state space, and a plurality of planned trajectories are generated according to the obstacle boundary formed by at least one obstacle.

[0112] Exemplarily, the trigger threshold may be 1, or the trigger threshold may be other values.

[0113] Exemplarily, multiple trajectories may be generated according to the method of S401, and then, according to the obstacle boundary, trajectories that exceed the obstacle boundary among the multiple trajectories are removed to obtain multiple planned trajectories.

[0114] S404: determining an obstacle avoidance trajectory from a plurality of planned trajectories according to the control information input by the driver.

[0115] For example, a motion trajectory may be generated based on the control information input by the driver and the current operating parameters of the vehicle, wherein the current operating parameters of the vehicle may include the vehicle speed, the vehicle attitude angle, and the like.

[0116] Furthermore, a matching degree between the motion trajectory and each of the multiple planned trajectories is determined, and a planned trajectory with the highest matching degree among the multiple planned trajectories is determined as the obstacle avoidance trajectory.

[0117] S405: Determine collision risk 2 according to the obstacle avoidance trajectory.

[0118] For example, the collision risk 2 may indicate at least one of the following: a risk of the vehicle colliding with a side obstacle, and a risk of the vehicle colliding with a front obstacle.

[0119] In some possible implementations, when a vehicle is traveling along an obstacle avoidance trajectory and may collide with an obstacle ahead, the risk of the vehicle colliding with the obstacle ahead can be determined based on the longitudinal distance between the vehicle and the obstacle ahead and the vehicle's current speed; alternatively, the risk of the vehicle colliding with the obstacle ahead can be determined based on TTC.

[0120] In some possible implementations, when a vehicle is traveling along an obstacle avoidance trajectory and may collide with a side obstacle, the risk of the vehicle colliding with the side obstacle may be determined based on the lateral distance between the vehicle and the side obstacle and the lateral speed of the vehicle; or, the risk of the vehicle colliding with the side obstacle may be determined based on TTC; or, the risk of the vehicle colliding with the side obstacle may be determined based on the position, speed and obstacle avoidance trajectory of the side obstacle.

[0121] In some possible implementations, the collision risk 2 may be determined based on the obstacle avoidance trajectory and the positions and speeds of multiple obstacles that exist while the vehicle is traveling along the obstacle avoidance trajectory. For example, the collision risk 2 may be determined using the above formula (3).

[0122] For example, the collision risk may be classified into levels, for example, divided into at least two levels, so that the vehicle performs lateral control and / or longitudinal control according to different levels of the collision risk.

[0123] The following takes the determination of the risk of collision between the vehicle and the nearest obstacle in front according to the longitudinal distance between the vehicle and the nearest obstacle in front and the current speed of the vehicle as an example to illustrate the classification of different levels of collision risk. For example, the remaining distance L is determined according to the longitudinal distance 1 between the vehicle and the nearest obstacle in front and the current speed v of the vehicle. Different remaining distances correspond to different levels of collision risk. The corresponding relationship between the remaining distance and the level of collision risk is shown in Table 1. Wherein, L = 1-v*T, T is the driver's reaction time.

[0124] Table 1

[0125] Level of collision risk Remaining distance L Level 3 L≤1m Level 2 1 meter<L≤2 meters Level 1 2 meters<L≤3 meters

[0126] The following takes the risk of collision between a vehicle and a side obstacle determined by TTC as an example to illustrate the classification of different levels of collision risk. For example, TTC is determined based on the lateral component of the vehicle's current speed v, the lateral distance between the side obstacle and the vehicle, and the speed of the side obstacle. Different TTCs correspond to different levels of collision risk. The corresponding relationship between TTC and the level of collision risk is shown in Table 2.

[0127] Table 2

[0128] Level of collision risk TTC Level 3 TTC≤1 second Level 2 1 second<TTC≤2.5 seconds Level 1 2.5<TTC≤4 seconds

[0129] S406: Determine a target torque according to the collision risk and the hand torque applied to the steering wheel by the driver, and control the steering wheel according to the target torque.

[0130] It is understandable that the hand torque applied by the driver to the steering wheel causes the vehicle to deflect in the first direction, thereby causing a risk of collision between the vehicle and at least one obstacle in the first direction, otherwise S403 to S405 will not be triggered. Therefore, in order to reduce the risk of collision between the vehicle and at least one obstacle, it is necessary to control the vehicle to have a tendency to travel in the opposite direction of the first direction. In other words, the direction of the target torque is opposite to the direction of the torque formed by the hand torque applied by the driver to the steering wheel. The first direction can be the left side of the vehicle, or it can also be the right side of the vehicle.

[0131] For example, the target torque may be determined based on the relationship between the collision risk 2 and the preset threshold and the hand torque applied by the driver to the steering wheel. Alternatively, the target torque may be determined based on the level of the risk of collision between the vehicle and the obstacle 1 and the hand torque applied by the driver to the steering wheel. Among them, the obstacle 1 may be the obstacle with the highest probability of collision with the vehicle among the at least one obstacle in the first direction.

[0132] Exemplarily, when the level of collision risk is less than or equal to the preset level threshold 1, the electric power steering (EPS) power-assistance characteristic curve is queried according to the hand torque applied by the driver to the steering wheel and the current speed of the vehicle, the counter torque is preliminarily determined according to the EPS power-assistance characteristic curve, and the target torque is obtained after the slope is limited and filtered. Among them, the slope limit refers to limiting the rate of change of the torque output according to the torque change slope control. The value of the target torque minus the torque formed by the hand torque applied by the driver to the steering wheel is greater than or equal to the preset threshold 1, and less than or equal to the preset threshold 2, so that the driver can feel the impedance in the process of continuing to turn the steering wheel in the first direction, so as to prompt the driver that the vehicle has a collision risk, so that the driver has enough time to control the vehicle to avoid collision. Exemplarily, the preset threshold 1 can be -0.5N·m, the preset threshold 2 can be 0N·m, or the preset threshold 1 and the preset threshold 2 can also be other values.

[0133] Exemplarily, when the level of collision risk is greater than a preset level threshold 1, the EPS power assist characteristic curve is queried according to the torque applied by the driver to the steering wheel and the current speed of the vehicle, and a preliminary target torque is determined. The value of the preliminary target torque may be the same as the value of the torque formed by the hand torque applied by the driver to the steering wheel. Further, an additional torque is determined according to the speed of the vehicle, the lateral distance between the vehicle and the obstacle, and the longitudinal distance. The additional torque is used to correct the lateral position of the vehicle so that the vehicle does not collide with the obstacle. The value of the additional torque superimposed on the preliminary target torque is the target torque. The value of the target torque minus the value of the torque formed by the hand torque applied by the driver to the steering wheel is greater than the preset threshold 2, so as to control the vehicle to turn in the direction opposite to the first direction to avoid collision with the obstacle in the first direction.

[0134] Exemplarily, the preset level threshold 1 may be level one or level two.

[0135] In some possible implementations, when the level of collision risk is less than or equal to the preset level threshold 1, in addition to controlling the steering wheel through the target torque to remind the driver of the collision risk, the driver may also be reminded of the collision risk in combination with HMI, speakers, etc. For example, the speaker may announce "Please pay attention to the obstacle in the first direction" for reminder.

[0136] S407: Determine the longitudinal acceleration according to the collision risk and the driving comfort or the longitudinal distance, and control the vehicle to decelerate according to the longitudinal acceleration.

[0137] For example, the longitudinal acceleration may be determined based on the relationship between the collision risk 2 and a preset threshold value, and the driving comfort level or the longitudinal distance between the vehicle and the nearest obstacle ahead. Alternatively, the longitudinal acceleration may be determined based on the level of the collision risk between the vehicle and the nearest obstacle ahead, and the driving comfort level or the longitudinal distance between the vehicle and the nearest obstacle ahead.

[0138] For example, when the level of collision risk is less than or equal to the preset level threshold 2, the longitudinal acceleration 1 is determined according to the driving comfort, so that the vehicle decelerates slowly before entering a state with a higher collision risk, thereby improving driving safety and the comfort of the driver and passengers. When the collision risk levels are different, different longitudinal accelerations can be used to control vehicle deceleration while ensuring driving comfort. For example, when the level of collision risk is less than or equal to the preset level threshold 2, when the collision risk level is low, a smaller longitudinal acceleration is used to control vehicle deceleration; when the collision risk level is high, a larger longitudinal acceleration is used to control vehicle deceleration.

[0139] Exemplarily, when the level of the collision risk is greater than or equal to a preset level threshold 2, the longitudinal acceleration 2 is determined according to the longitudinal distance between the vehicle and the nearest obstacle in front and the speed of the vehicle.

[0140] For example, the absolute value of the longitudinal acceleration 1 may be less than or equal to 4 m / s 2 , the absolute value of the longitudinal acceleration 2 can be greater than 4m / s 2 .

[0141] Exemplarily, the preset level threshold 2 may be level one, or level two.

[0142] In the specific implementation process, it is not necessary to execute Figure 4 All operations in, for example, S406 or S407 may be executed. For example, when there is no risk of lateral collision, only S407 may be executed, and when there is no risk of longitudinal collision, only S406 may be executed. In addition, Figure 4 The operations shown may also not be executed in the order shown in the figure, for example, S406 and S407 may be executed at the same time, or S407 may be executed before S406.

[0143] Figure 6 An application scenario of an embodiment of the present application is shown. Figure 6 As shown in (a) of FIG. 4 , when the vehicle 601 is in the human driving mode and is driving in lane 2, the driver applies torque to the steering wheel, causing the vehicle 601 to drive to the right of the lane center line. This may cause a collision with the obstacle 603. Then, the steering wheel of the vehicle 601 may be controlled according to the above method 400 to avoid the collision. Figure 6 As shown in (b), when vehicle 601 is in human driving mode and driving in lane 2, the front vehicle 604 suddenly decelerates, causing a collision risk between vehicle 601 and front vehicle 604. When vehicle 601 cannot avoid the collision by decelerating at the maximum deceleration, the target torque can be determined based on the torque applied by the driver to the steering wheel to make vehicle 601 drive to the right to avoid collision between vehicle 601 and front vehicle 604. In the process of determining the target torque, the speed and position of obstacle 605 are considered to avoid collision between vehicle 601 and obstacle 605 during obstacle avoidance. Figure 6 As shown in (c), vehicle 601 is in human driving mode and driving in lane 2. The driver applies torque to the steering wheel, causing vehicle 601 to drive to the right of the center line of the lane. At this time, vehicle 601 may collide with vehicle 607 on the right rear side. The collision risk level can be determined based on the position and speed of vehicle 601 and the position and speed of vehicle 607. The target torque can be determined based on the collision risk level and the torque applied by the driver to the steering wheel, and then the steering wheel of vehicle 601 can be controlled based on the target torque to avoid a collision. Alternatively, vehicle 601 is in a state as shown in FIG. Figure 6 When the vehicle 601 is in the posture shown in (c) in the figure, the driver applies torque to the steering wheel to make the vehicle 601 deviate from the current posture to the left side relative to the center line of the lane line. At this time, the vehicle 601 may collide with the front vehicle 606. The collision risk level can be determined according to the position and speed of the vehicle 601 and the position and speed of the vehicle 606, and the target torque can be determined according to the collision risk level and the torque applied to the steering wheel by the driver, and then the steering wheel of the vehicle 601 can be controlled according to the target torque. At the same time, the longitudinal acceleration can be determined according to the collision risk level, and the vehicle 601 can be controlled to decelerate according to the longitudinal acceleration to avoid a collision.

[0144] Figure 7 A control method provided by an embodiment of the present application is shown, which can be applied to Figure 2 In the intelligent driving device shown, or the method can be performed by Figure 3 The system shown is executed. The method includes:

[0145] S701, when there is a risk of collision between the intelligent driving device and the first obstacle, determine a second torque based on at least a first torque of the steering wheel, wherein the first torque is a torque applied to the steering wheel by a user of the intelligent driving device, a direction of the second torque is opposite to a direction of the first torque, and a value of the second torque minus a value of the first torque is greater than or equal to a first preset threshold.

[0146] Exemplarily, the intelligent driving device may be the intelligent driving device 100, for example, may include the above-mentioned vehicle.

[0147] Exemplarily, the first obstacle may include the nearest obstacle in front of the intelligent driving device; or, it may also include an obstacle on the first side of the intelligent driving device, for example, the above-mentioned obstacle 1. The first side is the side to which the intelligent driving device is biased under the action of the first torque, for example, Figure 6 The right side of the vehicle 601 shown in (a).

[0148] Exemplarily, the method for determining whether there is a collision risk between the intelligent driving device and the first obstacle can refer to the description in S401 and S402, which will not be repeated here.

[0149] Optionally, determining the second torque at least according to the first torque of the steering wheel includes: determining the second torque according to the relationship between the first collision risk between the intelligent driving device and the first obstacle and the first threshold. For example, determining the value of the second torque according to the value of the first torque; wherein, when the first collision risk between the intelligent driving device and the first obstacle is less than or equal to the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the first preset threshold and less than the second preset threshold; or, when the first collision risk is greater than the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the second preset threshold.

[0150] For example, the first collision risk may include the above-mentioned collision risk 2, or the first collision risk may include the collision risk between the intelligent driving device and the lateral obstacle. The method for determining the first collision risk may refer to the description in S405, which will not be repeated here.

[0151] S702: Control the steering wheel according to the first torque and the second torque.

[0152] Optionally, the method also includes: when the second collision risk between the intelligent driving device and the first obstacle is less than or equal to a second threshold, determining a first longitudinal acceleration according to driving comfort, and controlling the intelligent driving device to decelerate according to the first longitudinal acceleration; or, when the second collision risk is greater than the second threshold, determining a second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and controlling the intelligent driving device to decelerate according to the second longitudinal acceleration; wherein the absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

[0153] For example, the second collision risk may include the above-mentioned collision risk 2, or the second collision risk may include the collision risk between the intelligent driving device and the nearest obstacle in front. The method for determining the second collision risk may refer to the description in S405, which will not be repeated here.

[0154] Exemplarily, the first collision risk and the second collision risk are determined based on the first motion trajectory, and the first motion trajectory may include the obstacle avoidance trajectory in the above embodiment. The specific method of determining the first motion trajectory can refer to the description in the above embodiment, which will not be repeated here.

[0155] The control method provided in the embodiment of the present application can apply an opposite force to the steering wheel according to the torque applied by the driver to the steering wheel when the intelligent driving device detects a collision risk in the human driving mode, so as to remind the driver of the risk of collision. In addition, by controlling the steering wheel in combination with the driver's action intention, the behavior of the intelligent driving device during obstacle avoidance can be made more human-like, and excessive torque can be avoided when the function is triggered to cause a large lateral acceleration, thereby improving the driving experience of the driver and passengers. In addition, through the joint control of lateral and longitudinal directions, in more complex driving scenarios, it helps to reduce the probability of collision and improve driving safety.

[0156] Combined with the above Figures 1 to 7 The method provided in the embodiment of the present application is described in detail. Figure 8 and Fig. 9 The device provided in the embodiment of the present application is described in detail. It should be understood that the description of the device embodiment corresponds to the description of the method embodiment, so the contents not described in detail can be referred to the method embodiment above, and for the sake of brevity, they will not be repeated here.

[0157] Figure 8 A schematic block diagram of a control device 2000 provided in an embodiment of the present application is shown. The device 2000 includes a first determining unit 2010 and a processing unit 2020.

[0158] The apparatus 2000 may include a Figure 4 or Figure 7 Furthermore, each unit in the device 2000 is respectively for implementing Figure 4 or Figure 7 The corresponding process of the method embodiment in FIG.

[0159] Exemplarily, when the device 2000 is used to execute method 700, the first determination unit 2010 is used to determine the second torque based on at least the first torque of the steering wheel when there is a risk of collision between the intelligent driving device and the first obstacle; wherein the first torque is the torque applied to the steering wheel by a user of the intelligent driving device, the direction of the second torque is opposite to the direction of the first torque, and the value of the second torque minus the value of the first torque is greater than or equal to a first set threshold; and the processing unit 2020 is used to control the steering wheel based on the first torque and the second torque.

[0160] Optionally, the first determination unit 2010 is used to: determine the value of the second torque based on the first collision risk between the intelligent driving device and the first obstacle and the value of the first torque; wherein, when the first collision risk is less than or equal to a first threshold, the value of the second torque minus the value of the first torque is greater than or equal to a first preset threshold and less than a second preset threshold; or, when the first collision risk is greater than the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the second preset threshold.

[0161] Optionally, the first determination unit 2010 is further used to: when the second collision risk between the intelligent driving device and the first obstacle is less than or equal to a second threshold, determine the first longitudinal acceleration according to the driving comfort, and control the intelligent driving device to decelerate according to the first longitudinal acceleration; or, when the second collision risk is greater than the second threshold, determine the second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and control the intelligent driving device to decelerate according to the second longitudinal acceleration; wherein the absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

[0162] Optionally, the device 2000 also includes a second determination unit, which is used to: when the third collision risk between the intelligent driving device and the first obstacle is greater than or equal to a third threshold, determine the first motion trajectory according to control information input by a user of the intelligent driving device and the obstacle boundary, the control information including at least one of the following: opening information of an accelerator pedal of the intelligent driving device, opening information of a deceleration pedal of the intelligent driving device, and a first torque, and the obstacle boundary is determined by multiple obstacles including the first obstacle; the first determination unit 2010 is used to: determine the second torque according to the first motion trajectory and the first torque, so that when the steering wheel is controlled according to the second torque, the intelligent driving device travels along the first motion trajectory.

[0163] Exemplarily, the third collision risk may include the collision risk 1 described above.

[0164] Optionally, the device also includes a third determination unit, which is used to: determine multiple motion trajectories based on the driver's reaction time and a reachable set of control parameters, where the reachable set of control parameters is a set of motion parameters that can be achieved by the intelligent driving device under user control; determine a third collision risk based on the multiple motion trajectories and the position and speed of the first obstacle.

[0165] Exemplarily, the multiple motion trajectories may include the multiple predicted trajectory lines mentioned above. The method for determining the multiple motion trajectories may refer to the description in S401 above, which will not be described in detail here.

[0166] Optionally, the first obstacle includes at least one of the following: a motor vehicle, a non-motor vehicle, a general obstacle, and a pedestrian.

[0167] Exemplarily, the first determining unit 2010 and the processing unit 2020 may be arranged in an intelligent driving device. More specifically, the first determining unit 2010 and the processing unit 2020 may be arranged in Figure 3 In the interactive module 240 shown in FIG. 4 , the second determining unit may be arranged in Figure 3 In the horizontal and vertical planning module 230 shown in FIG. 1 , the third determining unit can be set Figure 3In the activation decision module 220 shown.

[0168] Exemplarily, the operations performed by the first determining unit 2010 and the processing unit 2020 may be performed by one processor, or may be performed by different processors. Figure 2 The processor in the intelligent driving device 100 shown in the figure; or, the above-mentioned device 2000 can be a chip set in the intelligent driving device 100.

[0169] In the specific implementation process, all or part of the units in the above device can be integrated together, or can be implemented independently. In one implementation, these units are integrated together and implemented in the form of a system-on-a-chip (SoC).

[0170] Fig. 9 It is a schematic block diagram of a control device provided in an embodiment of the present application. Fig. 9 The device 2100 shown may include: a processor 2110, a transceiver 2120, and a memory 2130. The processor 2110, the transceiver 2120, and the memory 2130 are connected via an internal connection path, the memory 2130 is used to store instructions, and the processor 2110 is used to execute the instructions stored in the memory 2130 to implement the methods in the above embodiments. Optionally, the memory 2130 may be coupled to the processor 2110 via an interface, or may be integrated with the processor 2110.

[0171] It should be noted that the transceiver 2120 may include but is not limited to a transceiver device such as an input / output interface to achieve communication between the device 2100 and other devices or a communication network.

[0172] The memory 2130 may be a read only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM).

[0173] The transceiver 2120 uses a transceiver device such as but not limited to a transceiver to implement communication between the device 2100 and other devices or a communication network to receive / send data / information used to implement the methods in the above embodiments.

[0174] In the specific implementation process, the device 2100 can be set at Figure 2 In the computing platform 150 of the intelligent driving device 100 shown.

[0175] An embodiment of the present application also provides an intelligent driving device, which includes the above-mentioned device 2000 or the above-mentioned device 2100.

[0176] In some possible implementations, the intelligent driving device may be a vehicle.

[0177] An embodiment of the present application further provides a computer program product, which includes a computer program code. When the computer program code runs on a computer, the computer implements the methods in the above embodiments of the present application.

[0178] An embodiment of the present application further provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed on a computer, the computer implements the methods in the above embodiments of the present application.

[0179] An embodiment of the present application also provides a chip, including a circuit, for executing the methods in the above embodiments of the present application.

[0180] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or a power-on erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0181] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0182] In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is a kind of association relationship that describes associated objects, indicating that three relationships can exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In this application, "at least one" means one or more, and "multiple" means two or more. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0183] The prefixes such as "first" and "second" used in the embodiments of the present application are only used to distinguish different description objects, and have no limiting effect on the position, order, priority, quantity or content of the described objects. The use of prefixes such as ordinal numbers used to distinguish description objects in the embodiments of the present application does not constitute a limitation on the described objects. For the statement of the described objects, please refer to the description in the context of the claims or embodiments, and the use of such prefixes should not constitute an unnecessary limitation.

[0184] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0185] In the various embodiments of the present application, unless otherwise specified or logically conflicting, the terms and / or descriptions between the various embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0186] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0187] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0188] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A control method, characterized in that: include: When there is a risk of collision between the intelligent driving device and the first obstacle, determining the second torque at least according to the first torque of the steering wheel; The first torque is a torque applied to the steering wheel by a user of the intelligent driving device, the direction of the second torque is opposite to the direction of the first torque, and the value of the second torque minus the value of the first torque is greater than or equal to a first preset threshold; The steering wheel is controlled according to the first torque and the second torque.

2. The method according to claim 1, characterized in that The determining the second torque at least according to the first torque of the steering wheel comprises: determining a value of the second torque according to a first collision risk between the intelligent driving device and the first obstacle and a value of the first torque; Wherein, when the first collision risk is less than or equal to a first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the first preset threshold and less than a second preset threshold; or, When the first collision risk is greater than the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the second preset threshold.

3. The method according to claim 1 or 2, characterized in that: The method further comprises: When the second collision risk between the intelligent driving device and the first obstacle is less than or equal to a second threshold, determining a first longitudinal acceleration according to driving comfort, and controlling the intelligent driving device to decelerate according to the first longitudinal acceleration; or When the second collision risk is greater than the second threshold, determining a second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and controlling the intelligent driving device to decelerate according to the second longitudinal acceleration; The absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

4. The method according to any one of claims 1 to 3, characterized in that The method further comprises: When a third collision risk between the intelligent driving device and the first obstacle is greater than or equal to a third threshold, determining a first motion trajectory according to control information input by a user of the intelligent driving device and an obstacle boundary, the control information comprising at least one of the following: opening information of an accelerator pedal of the intelligent driving device, opening information of a decelerator pedal of the intelligent driving device, and the first torque, and the obstacle boundary is determined by a plurality of obstacles including the first obstacle; The determining the second torque at least according to the first torque of the steering wheel comprises: The second torque is determined according to the first motion trajectory and the first torque, so that when the steering wheel is controlled according to the second torque, the intelligent driving device travels according to the first motion trajectory.

5. The method according to claim 4, characterized in that The method further comprises: Determining a plurality of motion trajectories according to the driver reaction time and a control parameter reachable set, wherein the control parameter reachable set is a set of motion parameters that can be achieved by the intelligent driving device under the control of the user; The third collision risk is determined according to the multiple motion trajectories and the position and speed of the first obstacle.

6. The method according to any one of claims 1 to 5, characterized in that The first obstacle includes at least one of the following: a motor vehicle, a non-motor vehicle, a general obstacle, and a pedestrian.

7. A control device, characterized in that: include: a first determining unit, configured to determine a second torque at least according to a first torque of a steering wheel when there is a risk of collision between the intelligent driving device and the first obstacle; The first torque is the torque applied to the steering wheel by the user of the intelligent driving device, the direction of the second torque is opposite to the direction of the first torque, and the value of the second torque minus the value of the first torque is greater than or equal to a first set threshold; A processing unit is used to control the steering wheel according to the first torque and the second torque.

8. The device according to claim 7, characterized in that The first determining unit is used for: determining a value of the second torque according to a first collision risk between the intelligent driving device and the first obstacle and a value of the first torque; Wherein, when the first collision risk is less than or equal to a first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the first preset threshold and less than a second preset threshold; or, When the first collision risk is greater than the first threshold, the value of the second torque minus the value of the first torque is greater than or equal to the second preset threshold.

9. The device according to claim 7 or 8, characterized in that The first determining unit is further configured to: When the second collision risk between the intelligent driving device and the first obstacle is less than or equal to a second threshold, determining a first longitudinal acceleration according to driving comfort, and controlling the intelligent driving device to decelerate according to the first longitudinal acceleration; or When the second collision risk is greater than the second threshold, determining a second longitudinal acceleration at least according to the distance between the intelligent driving device and the first obstacle, and controlling the intelligent driving device to decelerate according to the second longitudinal acceleration; The absolute value of the second longitudinal acceleration is greater than the absolute value of the first longitudinal acceleration.

10. The device according to any one of claims 7 to 9, characterized in that The device further includes a second determining unit, wherein the second determining unit is configured to: When a third collision risk between the intelligent driving device and the first obstacle is greater than or equal to a third threshold, determining a first motion trajectory according to control information input by a user of the intelligent driving device and an obstacle boundary, the control information comprising at least one of the following: opening information of an accelerator pedal of the intelligent driving device, opening information of a decelerator pedal of the intelligent driving device, and the first torque, and the obstacle boundary is determined by a plurality of obstacles including the first obstacle; The first determining unit is used for: The second torque is determined according to the first motion trajectory and the first torque, so that when the steering wheel is controlled according to the second torque, the intelligent driving device travels according to the first motion trajectory.

11. The device according to claim 10, characterized in that The device further includes a third determining unit, wherein the third determining unit is configured to: Determining a plurality of motion trajectories according to the driver reaction time and a control parameter reachable set, wherein the control parameter reachable set is a set of motion parameters that can be achieved by the intelligent driving device under the control of the user; The third collision risk is determined according to the multiple motion trajectories and the position and speed of the first obstacle.

12. The device according to any one of claims 7 to 11, characterized in that The first obstacle includes at least one of the following: a motor vehicle, a non-motor vehicle, a general obstacle, and a pedestrian.

13. A control device, characterized in that: include: Memory for storing computer programs; A processor, configured to execute the computer program stored in the memory, so that the apparatus performs the method according to any one of claims 1 to 6.

14. An intelligent driving device, characterized in that: Comprising a device as claimed in any one of claims 7 to 13.

15. A computer-readable storage medium, characterized in that: Instructions are stored thereon, and when the instructions are executed by a processor, the processor implements the method according to any one of claims 1 to 6.

16. A chip, characterized in that: The chip comprises a circuit for executing the method according to any one of claims 1 to 6.

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