CN116373853A

CN116373853A - Auxiliary driving anti-collision control method based on fuzzy control

Info

Publication number: CN116373853A
Application number: CN202310071647.2A
Authority: CN
Inventors: 李诗桐; 许畅; 赵琦; 姬晨禹; 刘栋; 刘亮
Original assignee: Beijing Machinery Equipment Research Institute
Current assignee: Beijing Machinery Equipment Research Institute
Priority date: 2023-02-07
Filing date: 2023-02-07
Publication date: 2023-07-04

Abstract

The disclosure relates to a method, a system, a device, electronic equipment and a storage medium for controlling collision avoidance of auxiliary driving based on fuzzy control. Wherein the method comprises the following steps: based on the relative distance and relative speed of the sensor collection vehicle from the obstacle, judging a vehicle control mode according to preset logic, and based on an automatic vehicle emergency braking controller, a rear vehicle collision early warning controller and a transverse vehicle lane change controller, realizing anti-collision fuzzy control for auxiliary driving of the vehicle; and a fuzzy control is adopted in the transverse lane change control mode to realize stable lane change obstacle detouring.

Description

Auxiliary driving anti-collision control method based on fuzzy control

Technical Field

The present disclosure relates to the field of unmanned aerial vehicle, and more particularly, to a method, system, apparatus, electronic device, and computer-readable storage medium for controlling collision avoidance of an assisted driving based on fuzzy control.

Background

The control algorithm of the vehicle auxiliary driving system comprises a series of anti-collision control algorithms such as an automatic emergency brake AEB, a rear collision early warning RCW, a transverse obstacle detouring algorithm and the like, and switching logic between the anti-collision control modes is a key for ensuring the safe running of the intelligent driving vehicle under a complex driving environment. In the prior art, the anti-collision functions of AEB, RCW and the like are mainly judged according to a set threshold value and fixed accelerator opening or brake pressure signals are output, acceleration change is discontinuous, vehicle speed change is severe, and riding comfort of a vehicle is difficult to ensure.

Accordingly, there is a need for one or more approaches to address the above-described problems.

It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

It is an object of the present disclosure to provide a driving assistance collision prevention control method, apparatus, electronic device, and computer-readable storage medium based on fuzzy control, which overcome, at least in part, one or more of the problems due to the limitations and disadvantages of the related art.

According to one aspect of the present disclosure, there is provided a driving assistance collision prevention control method based on fuzzy control, including:

a vehicle self-checking step of detecting a vehicle power-on state, if the vehicle is in the power-on state, executing an environment detection step, and if the vehicle is not powered on, ending the control of the vehicle;

an environment detection step of acquiring vehicle-front obstacle relative speed, vehicle-rear obstacle relative speed, vehicle-left/right obstacle relative speed and vehicle position and posture information based on the relative distance between the vehicle and the front obstacle, the relative distance between the vehicle and the rear obstacle and the relative distance between the vehicle and the left/right obstacle;

an anti-collision control step of calculating a vehicle front collision time, a vehicle rear collision time and a vehicle side collision time respectively according to the relative distance between the vehicle and a front obstacle, the relative distance between the vehicle and a rear obstacle and the relative distance between the vehicle and a left/right obstacle, the relative speed between the vehicle and the front obstacle, the relative speed between the vehicle and the rear obstacle and the relative speed between the vehicle and the left/right obstacle, and judging the vehicle control according to the vehicle front collision time, the vehicle rear collision time and the vehicle side collision time as follows:

If the front collision time is smaller than the automatic emergency braking mode judgment threshold value of the vehicle, comparing the rear collision time of the vehicle with the rear collision early warning mode judgment threshold value of the vehicle, if the rear collision time of the vehicle is smaller than the rear collision early warning mode judgment threshold value of the vehicle, comparing the lateral collision time of the vehicle with the lateral lane change control mode judgment threshold value of the vehicle, and if the lateral collision time of the vehicle is smaller than the lateral lane change control mode judgment threshold value of the vehicle, starting the automatic emergency braking mode of the vehicle, enabling the automatic emergency braking mode of the vehicle to control the vehicle based on a preset automatic emergency braking algorithm of the vehicle, and returning to the vehicle self-checking step;

if the front collision time is smaller than the automatic emergency braking mode judgment threshold value of the vehicle, comparing the rear collision time of the vehicle with the rear collision early warning mode judgment threshold value of the vehicle, if the rear collision time of the vehicle is smaller than the rear collision early warning mode judgment threshold value of the vehicle, comparing the lateral collision time of the vehicle with the lateral lane change control mode judgment threshold value of the vehicle, and if the lateral collision time of the vehicle is larger than the lateral lane change control mode judgment threshold value of the vehicle, starting the lateral lane change control mode of the vehicle, controlling the vehicle by the lateral lane change control mode of the vehicle based on a preset lateral lane change control algorithm of the vehicle, and returning to the vehicle self-checking step;

If the front collision time is smaller than the automatic emergency braking mode judgment threshold value of the vehicle, comparing the rear collision time of the vehicle with the rear collision early warning mode judgment threshold value of the vehicle, and if the rear collision time of the vehicle is larger than the rear collision early warning mode judgment threshold value of the vehicle, starting the automatic emergency braking mode of the vehicle, enabling the automatic emergency braking mode of the vehicle to control the vehicle based on a preset automatic emergency braking algorithm of the vehicle, and returning to a vehicle self-checking step;

if the front collision time is greater than the automatic emergency braking mode judgment threshold value of the vehicle, comparing the vehicle rear collision time with the vehicle rear collision early warning mode judgment threshold value, and if the vehicle rear collision time is less than the vehicle rear collision early warning mode judgment threshold value, starting a vehicle rear collision early warning mode, enabling the vehicle rear collision early warning mode to control the vehicle based on a preset vehicle rear collision early warning algorithm, and returning to a vehicle self-checking step;

if the front collision time is greater than the automatic emergency braking mode judgment threshold value of the vehicle, comparing the rear collision time of the vehicle with the rear collision early warning mode judgment threshold value of the vehicle, and if the rear collision time of the vehicle is greater than the rear collision early warning mode judgment threshold value of the vehicle, returning to the vehicle self-checking step.

In an exemplary embodiment of the present disclosure, in the anti-collision control step of the method:

if the front collision time is smaller than the automatic emergency braking mode judgment threshold value of the vehicle, comparing the rear collision time of the vehicle with the rear collision early warning mode judgment threshold value of the vehicle, if the rear collision time of the vehicle is smaller than the rear collision early warning mode judgment threshold value of the vehicle, comparing the lateral collision time of the vehicle with the lateral lane change control mode judgment threshold value of the vehicle, and if the lateral collision time of the vehicle is smaller than the lateral lane change control mode judgment threshold value of the vehicle, starting the automatic emergency braking mode of the vehicle, enabling the automatic emergency braking mode of the vehicle to control the vehicle based on a preset automatic emergency braking algorithm of the vehicle, enabling the rear and lateral vehicle warning function of the vehicle, and returning to the vehicle self-checking step;

the vehicle rear and lateral vehicle warning function comprises the step of lighting a rear and lateral brake lamp.

In one exemplary embodiment of the present disclosure, the method wherein the vehicle automatic emergency braking mode controls the vehicle based on a preset vehicle automatic emergency braking algorithm comprises:

the automatic emergency braking controller of the vehicle takes the relative distance between the vehicle and the front obstacle and the relative speed between the vehicle and the front obstacle as input, and generates a forward control signal based on a preset automatic emergency braking fuzzy control rule table of the vehicle;

Generating a vehicle accelerator opening degree and brake pressure signal according to a vehicle inverse dynamics model based on the forward control signal;

and completing automatic emergency brake control of the vehicle based on the accelerator opening degree and the brake pressure signal of the vehicle.

In an exemplary embodiment of the present disclosure, the method wherein the vehicle rear collision warning mode controls the vehicle based on a preset vehicle rear collision warning algorithm includes:

the vehicle rear collision early warning controller takes the relative distance between the vehicle and the rear obstacle and the relative speed between the vehicle and the rear obstacle as input, and generates a forward control signal based on a preset vehicle rear collision early warning fuzzy control rule table;

and completing the vehicle rear collision early warning control of the vehicle based on the vehicle accelerator opening and brake pressure signals.

In one exemplary embodiment of the present disclosure, the method wherein the vehicle lateral lane change control mode controls the vehicle based on a preset vehicle lateral lane change control algorithm comprises:

the vehicle transverse lane changing controller takes the vehicle position and posture information, the relative distance between the vehicle and the left/right obstacle and the relative speed between the vehicle and the left/right obstacle as input, and generates a lane changing obstacle detour path through a local path planning algorithm, wherein the lane changing obstacle detour path comprises path point coordinates and speed information;

Generating a transverse deviation, a yaw angle deviation and a vehicle speed deviation of a vehicle relative lane-changing obstacle-detouring path based on the vehicle position and posture information and the lane-changing obstacle-detouring path, and generating a front wheel steering angle control signal, an accelerator opening control signal and a brake pressure control signal based on a preset vehicle transverse lane-changing fuzzy control rule table by using the transverse deviation, the yaw angle deviation and the vehicle speed deviation as inputs by a vehicle transverse lane-changing controller;

and finishing the transverse lane change control of the vehicle based on the front wheel steering angle control signal, the accelerator opening control signal and the brake pressure control signal of the vehicle.

In one aspect of the present disclosure, there is provided a driving assistance collision avoidance control system based on fuzzy control, including:

a sensor for acquiring relative distance between the vehicle and the front obstacle, relative distance between the vehicle and the rear obstacle, relative distance between the vehicle and the left/right obstacle, relative speed between the vehicle and the front obstacle, relative speed between the vehicle and the rear obstacle, relative speed between the vehicle and the left/right obstacle, and position and posture information of the vehicle;

the vehicle automatic emergency braking controller is used for taking the relative distance between the vehicle and a front obstacle and the relative speed between the vehicle and the front obstacle as inputs, generating a forward control signal based on a preset vehicle automatic emergency braking fuzzy control rule table, generating a vehicle accelerator opening and braking pressure signal based on the forward control signal according to a vehicle inverse dynamics model, and completing vehicle automatic emergency braking control of the vehicle based on the vehicle accelerator opening and the braking pressure signal;

The vehicle rear collision early warning controller is used for taking the relative distance between the vehicle and the rear obstacle and the relative speed between the vehicle and the rear obstacle as input, generating a forward control signal based on a preset vehicle rear collision early warning fuzzy control rule table, generating a vehicle accelerator opening and a brake pressure signal based on the forward control signal according to a vehicle inverse dynamics model, and completing vehicle rear collision early warning control of the vehicle based on the vehicle accelerator opening and the brake pressure signal;

the vehicle transverse lane changing controller takes the vehicle position and posture information, the relative distance between the vehicle and the left/right obstacle and the relative speed between the vehicle and the left/right obstacle as input, and generates a lane changing obstacle detour path through a local path planning algorithm, wherein the lane changing obstacle detour path comprises path point coordinates and speed information; generating a transverse deviation, a yaw angle deviation and a vehicle speed deviation of a vehicle relative lane-changing obstacle-detouring path based on the vehicle position and posture information and the lane-changing obstacle-detouring path, and generating a front wheel steering angle control signal, an accelerator opening control signal and a brake pressure control signal based on a preset vehicle transverse lane-changing fuzzy control rule table by using the transverse deviation, the yaw angle deviation and the vehicle speed deviation as inputs by a vehicle transverse lane-changing controller; and finishing the transverse lane change control of the vehicle based on the front wheel steering angle control signal, the accelerator opening control signal and the brake pressure control signal of the vehicle.

In one aspect of the present disclosure, there is provided a driving assistance collision prevention control apparatus based on fuzzy control, including:

the vehicle self-checking module is used for detecting the power-on state of the vehicle, executing an environment detection step if the vehicle is in the power-on state, and ending the control of the vehicle if the vehicle is not powered on;

the environment detection module is used for acquiring relative distance between the vehicle and a front obstacle, relative distance between the vehicle and a rear obstacle and relative distance between the vehicle and a left/right obstacle based on the sensor of the vehicle, and acquiring relative speed between the vehicle and the front obstacle, relative speed between the vehicle and the rear obstacle, relative speed between the vehicle and the left/right obstacle and position and posture information of the vehicle;

the anti-collision control module is used for respectively calculating the front collision time, the rear collision time and the lateral collision time of the vehicle according to the relative distance between the vehicle and the front obstacle, the relative distance between the vehicle and the rear obstacle and the relative distance between the vehicle and the left/right obstacle, the relative speed between the vehicle and the front obstacle, the relative speed between the vehicle and the rear obstacle and the relative speed between the vehicle and the left/right obstacle, and judging the control of the vehicle according to the front collision time, the rear collision time and the lateral collision time of the vehicle as follows:

In one aspect of the present disclosure, there is provided an electronic device comprising:

a processor; and

a memory having stored thereon computer readable instructions which, when executed by the processor, implement a method according to any of the above.

In one aspect of the present disclosure, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor, implements a method according to any of the above.

A driving assistance collision avoidance control method based on fuzzy control in an exemplary embodiment of the present disclosure, wherein the method includes: based on the relative distance and relative speed of the sensor collection vehicle from the obstacle, judging a vehicle control mode according to preset logic, and based on an automatic vehicle emergency braking controller, a rear vehicle collision early warning controller and a transverse vehicle lane change controller, realizing anti-collision fuzzy control for auxiliary driving of the vehicle; and a fuzzy control is adopted in the transverse lane change control mode to realize stable lane change obstacle detouring.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The above and other features and advantages of the present disclosure will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

FIG. 1 illustrates a flowchart of a method of assisted driving collision avoidance control based on fuzzy control in accordance with an exemplary embodiment of the present disclosure;

FIG. 2 illustrates a control logic diagram of a method of controlling collision avoidance for assisted driving based on fuzzy control in accordance with an exemplary embodiment of the present disclosure;

3A-3B illustrate a controller control logic diagram of a method of driving assistance collision avoidance control based on fuzzy control according to an exemplary embodiment of the present disclosure;

FIG. 4 illustrates a schematic block diagram of a driving assistance collision avoidance control device based on fuzzy control according to an exemplary embodiment of the present disclosure;

FIG. 5 schematically illustrates a block diagram of an electronic device according to an exemplary embodiment of the present disclosure; and

fig. 6 schematically illustrates a schematic diagram of a computer-readable storage medium according to an exemplary embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the disclosed aspects may be practiced without one or more of the specific details, or with other methods, components, materials, devices, steps, etc. In other instances, well-known structures, methods, devices, implementations, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.

The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, or in one or more software-hardened modules, or in different networks and/or processor devices and/or microcontroller devices.

In the present exemplary embodiment, there is first provided a driving assistance collision prevention control method based on fuzzy control; referring to fig. 1, the auxiliary driving anti-collision control method based on the fuzzy control may include the steps of:

A vehicle self-checking step S110, wherein the power-on state of the vehicle is detected, if the vehicle is in the power-on state, an environment detection step is executed, and if the vehicle is not powered on, the control of the vehicle is ended;

an environment detection step S120 of acquiring relative speed between the vehicle and the front obstacle, relative speed between the vehicle and the rear obstacle, relative speed between the vehicle and the left/right obstacle and relative position and posture information of the vehicle based on the relative distance between the vehicle and the front obstacle, the relative distance between the vehicle and the rear obstacle and the relative distance between the vehicle and the left/right obstacle;

the anti-collision control step S130, according to the relative distance between the vehicle and the front obstacle, the relative distance between the vehicle and the rear obstacle, and the relative distance between the vehicle and the left/right obstacle, the relative speed between the vehicle and the front obstacle, the relative speed between the vehicle and the rear obstacle, and the relative speed between the vehicle and the left/right obstacle, calculates the front collision time, the rear collision time, and the lateral collision time of the vehicle, and determines the control of the vehicle according to the front collision time, the rear collision time, and the lateral collision time of the vehicle as follows:

Next, a method of driving assistance collision prevention control based on fuzzy control in the present example embodiment will be further described.

Embodiment one:

in the vehicle self-checking step S110, a vehicle power-on state may be detected, and if the vehicle is in the power-on state, an environment detection step is executed, and if the vehicle is not powered on, control of the vehicle is terminated.

In the environment detection step S120, vehicle position and orientation information may be acquired based on the relative distance between the vehicle and the front obstacle, the relative distance between the vehicle and the rear obstacle, and the relative distance between the vehicle and the left/right obstacle, which are acquired by the sensors of the vehicle.

In the anti-collision control step S130, a vehicle front collision time, a vehicle rear collision time, and a vehicle side collision time may be calculated from the vehicle-to-front obstacle relative distance, the vehicle-to-rear obstacle relative distance, and the vehicle-to-left/right obstacle relative distance, the vehicle-to-front obstacle relative speed, the vehicle-to-rear obstacle relative speed, and the vehicle-to-left/right obstacle relative speed, respectively, and the vehicle control is determined from the vehicle-to-front collision time, the vehicle-to-rear collision time, and the vehicle side collision time as follows:

A driving assistance collision avoidance control method based on fuzzy control in an exemplary embodiment of the present disclosure, wherein the method includes: based on the relative distance and relative speed of the sensor collection vehicle from the obstacle, judging a vehicle control mode according to preset logic, and based on an automatic vehicle emergency braking controller, a rear vehicle collision early warning controller and a transverse vehicle lane change controller, realizing anti-collision fuzzy control of the auxiliary driving of the vehicle, wherein frequent and severe switching of an accelerator and a brake is reduced in the control process of the automatic vehicle emergency braking control mode or the rear vehicle collision early warning control mode, so that acceleration is continuously changed, and vehicle speed is changed more stably, so that a more stable and comfortable driving experience is obtained; and a fuzzy control is adopted in the transverse lane change control mode to realize stable lane change obstacle detouring.

In an embodiment of the present example, in the collision avoidance control step of the method:

In an embodiment of the present example, the method wherein the vehicle automatic emergency braking mode controls the vehicle based on a preset vehicle automatic emergency braking algorithm comprises:

In an embodiment of the present example, the controlling the vehicle in the method according to the vehicle rear collision pre-warning mode based on a preset vehicle rear collision pre-warning algorithm includes:

In an embodiment of the present example, the method in which the vehicle lateral lane change control mode controls the vehicle based on a preset vehicle lateral lane change control algorithm includes:

Embodiment two:

in the embodiment of the present example, in the control process of the AEB mode or the RCW mode, frequent and severe switching of the throttle and the brake is reduced, so that the acceleration is continuously changed, and the vehicle speed is changed more smoothly, thereby obtaining a smoother and more comfortable driving experience; and fuzzy control is adopted in the transverse lane change control mode to realize stable lane change obstacle detouring. The basic working steps are as follows:

step 1: judging whether the power-on self-test of the vehicle is finished or not;

step 2: sensors mounted on the vehicle body detect the relative positions of obstacles in front of, behind and on the left and right sides of the vehicle (S _f 、S _r S and S _l ) And relative velocity (v) _f 、v _r V _l ) Information;

step 3: the collision time (t) is calculated by dividing the relative distance by the relative velocity _f 、t _r T _l )；

Step 4: judging the front collision time t in the actual scene _f And an AEB mode judgment threshold T preset in a control system _AEB Size of the space;

step 5: judging the rear collision time t in the actual scene _r And a preset RCW mode judgment threshold T in a control system _RCW Size of the space;

step 6: judging the side collision time t in the actual scene _l And a transverse lane change control mode judgment threshold T preset in a control system _lateral Size of the space;

step 7: the vehicle enters an AEB mode and starts the rear and side vehicles to warn;

step 8: the vehicle enters a transverse lane change control mode;

step 9: the vehicle enters an AEB mode;

step 10: the vehicle enters an RCW mode;

step 11: the anti-collision control system does not act;

step 12: judging whether the vehicle is powered down;

in the present exemplary embodiment, as shown in fig. 2, according to the mode switching control logic, the control system workflow is:

firstly, executing the step 1, judging whether the power-on self-test of the vehicle is finished, if so, entering the step 2, and collecting the information of the vehicle and the obstacle; otherwise, step 1 is carried out again to judge whether the power-on self-test of the vehicle is finished;

When the program enters the step 2, the steps 2 to 4 are continued, and when the judgment result of the step 4 is t _f <T _AEB Step 5 is performed if the collision risk exists in front of the vehicle; when the judgment result in the step 5 is t _r <T _RCW If there is collision risk at the rear of the vehicle, step 6 is performed, and when the judgment result in step 6 is t _l <T _lateral If there is an obstacle in the side lane, the vehicle enters the AEB mode and starts the rear and side vehicles to warn, and lights the brake lamp and adopts other warning modes to prompt the rear and side vehicles to pay attention to the reductionThe vehicle is quickly avoided, then step 12 is carried out to judge whether the vehicle is electrified, if not, the program returns to step 2 to continuously detect the relative position and relative speed information of the vehicle and the obstacle at the next moment; if the power is turned off, the program is ended;

if the judgment result of the step 4 is t _f <T _AEB Step 5 is performed if the collision risk exists in front of the vehicle; when the judgment result in the step 5 is t _r <T _RCW If there is collision risk at the rear of the vehicle, step 6 is performed, and when the judgment result in step 6 is t _l >T _lateral If the lateral lane is not in collision risk, entering a step 8, enabling the vehicle to enter a transverse lane change control mode, then carrying out a step 12 to judge whether the vehicle is powered down, and if not, returning to the step 2 to continuously detect the relative position and the relative speed information of the vehicle and the obstacle at the next moment; if the power is turned off, the program is ended;

If the judgment result of the step 4 is t _f <T _AEB Step 5 is performed if the collision risk exists in front of the vehicle; when the judgment result in the step 5 is t _r >T _RCW If the collision risk does not exist behind the vehicle, the step 9 is entered, the vehicle enters an AEB mode, then the step 12 is carried out to judge whether the vehicle is powered down, if not, the program returns to the step 2 to continuously detect the relative position and the relative speed information of the vehicle and the obstacle at the next moment; if the power is turned off, the program is ended;

if the judgment result of the step 4 is t _f >T _AEB Step 5 is performed if no collision risk exists in front of the vehicle; when the judgment result in the step 5 is t _r <T _RCW If the collision risk exists behind the vehicle, the step 10 is entered, the vehicle enters the RCW mode, the step 12 is carried out to judge whether the vehicle is powered down, and if not, the program returns to the step 2 to continuously detect the relative position and the relative speed information of the vehicle and the obstacle at the next moment; if the power is turned off, the program is ended;

if the judgment result of the step 4 is t _f >T _AEB Step 5 is performed if no collision risk exists in front of the vehicle; when the judgment result in the step 5 is t _r >T _RCW There is no risk of collision behind the vehicle, thisStep 11 is carried out when the anti-collision control system of the vehicle does not act, step 12 is carried out to judge whether the vehicle is powered down, if not, the program returns to step 2 to continuously detect the relative position and relative speed information of the vehicle and the obstacle at the next moment; if power is down, the process ends.

In the embodiment of the present example, as shown in fig. 3A, in the AEB mode and the RCW mode, the collision avoidance system control method based on the fuzzy control is as follows:

the control mode of the AEB mode depends on fuzzy control to control and regulate the accelerator and the brake of the vehicle, and the control method principle is as follows: and inputting the relative distance and the relative speed of the vehicle acquired by the sensor into an AEB fuzzy controller, and outputting acceleration control signals corresponding to the input relative distance and relative speed according to a preset AEB fuzzy control rule table. The output acceleration control signal outputs an accelerator opening or brake pressure signal through a vehicle inverse dynamics model controller so as to control the longitudinal speed of the vehicle. The control mode of the RCW mode depends on fuzzy control to control and regulate the accelerator and the brake of the vehicle, and the control method principle is as follows: the relative distance and the relative speed of the vehicle, which are acquired by the sensor, are input into the RCW fuzzy controller, and acceleration control signals corresponding to the input relative distance and relative speed are output according to a preset RCW fuzzy control rule table. The output acceleration control signal outputs an accelerator opening or brake pressure signal through a vehicle inverse dynamics model controller so as to control the longitudinal speed of the vehicle. The longitudinal speed of the vehicle can be controlled to continuously and smoothly change through fuzzy control, and severe and frequent switching of accelerator braking in the control process of each mode is reduced, so that a smoother and comfortable driving experience is obtained.

In the embodiment of the present example, as shown in fig. 3B, the lateral lane change control mode control method is as follows:

in the transverse lane change control mode, a local path planning algorithm is adopted to plan a reasonable lane change path, and a fuzzy controller is adopted to control a vehicle to follow the planned path so as to ensure that the vehicle can effectively change lanes and turn the lane. According to the vehicle pose and speed information and the obstacle information acquired by the sensor, determining a lane-changing obstacle-detouring path through a local path planning algorithm, outputting planned path point coordinates and speed information, simultaneously calculating to obtain transverse deviation, yaw angle deviation and vehicle speed deviation information according to the vehicle pose and speed information acquired by the sensor, inputting the transverse deviation, yaw angle deviation and vehicle speed deviation information into a fuzzy controller, and calculating and outputting a front wheel corner and an accelerator opening/brake pressure control signal by the fuzzy controller according to the planned path and the vehicle state so as to control the vehicle to realize lane-changing obstacle detouring.

It should be noted that although the steps of the methods of the present disclosure are illustrated in the accompanying drawings in a particular order, this does not require or imply that the steps must be performed in that particular order or that all of the illustrated steps be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.

Further, in the present exemplary embodiment, there is also provided a driving assistance collision prevention control system based on fuzzy control, the system including:

In the embodiment of the example, the system is used for a vehicle auxiliary driving system, the anti-collision system integrates a series of functions of AEB, RCW, transverse lane changing obstacle detouring and the like, and intelligent driving vehicles are controlled through certain mode switching logic to automatically realize the anti-collision function, and the control is simple. The system can integrate the anti-collision systems AEB and RCW and a transverse obstacle detouring algorithm, has reasonable mode switching logic, can automatically judge the anti-collision system mode in an auxiliary driving scene, and ensures the driving safety of an auxiliary driving vehicle.

Further, in the present exemplary embodiment, there is also provided an assisted driving collision prevention control apparatus based on fuzzy control. Referring to fig. 4, the auxiliary driving collision avoidance control device 400 based on the fuzzy control may include: a vehicle self-test module 410, an environment detection module 420, and an anti-collision control module 430. Wherein:

the vehicle self-checking module 410 is configured to detect a power-on state of a vehicle, execute an environment detection step if the vehicle is in the power-on state, and end control of the vehicle if the vehicle is not powered on;

an environment detection module 420 for acquiring relative speed of the vehicle and the front obstacle, relative speed of the vehicle and the rear obstacle, relative speed of the vehicle and the left/right obstacle, and vehicle position and posture information based on the relative distance of the vehicle from the front obstacle, the relative distance of the vehicle from the rear obstacle, and the relative distance of the vehicle from the left/right obstacle;

the anti-collision control module 430 is configured to calculate a vehicle front collision time, a vehicle rear collision time, and a vehicle lateral collision time according to the vehicle front collision time, the vehicle rear collision time, and the vehicle lateral collision time, respectively, and determine the vehicle control according to the vehicle front collision time, the vehicle rear collision time, and the vehicle lateral collision time as follows:

The specific details of each of the above-mentioned auxiliary driving anti-collision control device modules based on the fuzzy control are described in detail in a corresponding auxiliary driving anti-collision control method based on the fuzzy control, so that the details are not repeated here.

It should be noted that although several modules or units of a driving assistance collision avoidance control device 400 based on fuzzy control are mentioned in the above detailed description, this division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.

In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

Those skilled in the art will appreciate that the various aspects of the invention may be implemented as a system, method, or program product. Accordingly, aspects of the invention may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" system.

An electronic device 500 according to such an embodiment of the invention is described below with reference to fig. 5. The electronic device 500 shown in fig. 5 is merely an example, and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.

As shown in fig. 5, the electronic device 500 is embodied in the form of a general purpose computing device. The components of electronic device 500 may include, but are not limited to: the at least one processing unit 510, the at least one memory unit 520, a bus 530 connecting the different system components (including the memory unit 520 and the processing unit 510), and a display unit 540.

Wherein the storage unit stores program code that is executable by the processing unit 510 such that the processing unit 510 performs steps according to various exemplary embodiments of the present invention described in the above-mentioned "exemplary methods" section of the present specification. For example, the processing unit 510 may perform steps S110 to S130 as shown in fig. 1.

The storage unit 520 may include readable media in the form of volatile storage units, such as Random Access Memory (RAM) 5201 and/or cache memory unit 5202, and may further include Read Only Memory (ROM) 5203.

The storage unit 520 may also include a program/utility 5204 having a set (at least one) of program modules 5203, such program modules 5205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.

Bus 550 may be a local bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or using any of a variety of bus architectures.

The electronic device 500 may also communicate with one or more external devices 570 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 500, and/or with any device (e.g., router, modem, etc.) that enables the electronic device 500 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 550. Also, electronic device 500 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 560. As shown, network adapter 560 communicates with other modules of electronic device 500 over bus 550. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 500, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, a computer-readable storage medium having stored thereon a program product capable of implementing the method described above in the present specification is also provided. In some possible embodiments, the various aspects of the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the invention as described in the "exemplary methods" section of this specification, when said program product is run on the terminal device.

Referring to fig. 6, a program product 600 for implementing the above-described method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).

Furthermore, the above-described drawings are only schematic illustrations of processes included in the method according to the exemplary embodiment of the present invention, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An auxiliary driving anti-collision control method based on fuzzy control is characterized by comprising the following steps:

2. The method according to claim 1, wherein in the collision prevention control step of the method:

3. The method of claim 1, wherein the vehicle automatic emergency braking mode in the method controlling the vehicle based on a preset vehicle automatic emergency braking algorithm comprises:

calculating and generating a vehicle accelerator opening degree and a brake pressure signal according to a vehicle inverse dynamics model based on the forward control signal;

4. The method of claim 1, wherein the vehicle rear collision warning mode in the method controls the vehicle based on a preset vehicle rear collision warning algorithm comprises:

5. The method of claim 1, wherein the method wherein the vehicle lateral lane change control mode controlling the vehicle based on a preset vehicle lateral lane change control algorithm comprises:

6. A drive-assisted collision avoidance control system based on fuzzy control, the system comprising:

7. An auxiliary driving anti-collision control device based on fuzzy control, characterized in that the device comprises:

8. An electronic device, comprising

A processor; and

a memory having stored thereon computer readable instructions which, when executed by the processor, implement the method according to any of claims 1 to 5.

9. A computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method according to any of claims 1 to 5.