CN113928284A - Self-adaptive multistage braking control method for automatic emergency braking system - Google Patents
Self-adaptive multistage braking control method for automatic emergency braking system Download PDFInfo
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- CN113928284A CN113928284A CN202110997407.6A CN202110997407A CN113928284A CN 113928284 A CN113928284 A CN 113928284A CN 202110997407 A CN202110997407 A CN 202110997407A CN 113928284 A CN113928284 A CN 113928284A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/17—Using electrical or electronic regulation means to control braking
- B60T8/171—Detecting parameters used in the regulation; Measuring values used in the regulation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T7/00—Brake-action initiating means
- B60T7/12—Brake-action initiating means for automatic initiation; for initiation not subject to will of driver or passenger
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T8/00—Arrangements for adjusting wheel-braking force to meet varying vehicular or ground-surface conditions, e.g. limiting or varying distribution of braking force
- B60T8/17—Using electrical or electronic regulation means to control braking
- B60T8/172—Determining control parameters used in the regulation, e.g. by calculations involving measured or detected parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T2210/00—Detection or estimation of road or environment conditions; Detection or estimation of road shapes
- B60T2210/10—Detection or estimation of road conditions
- B60T2210/12—Friction
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- Engineering & Computer Science (AREA)
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- Mechanical Engineering (AREA)
- Regulating Braking Force (AREA)
Abstract
An adaptive multistage braking control algorithm of an automatic emergency braking system belongs to the technical field of traffic safety. In order to improve the performance of an Automatic Emergency Braking (AEB) system of an automobile and give consideration to safety and comfort in the emergency braking process, the application provides an adaptive AEB control algorithm considering a road adhesion coefficient and a vehicle running state, wherein the AEB control algorithm determines a safety time threshold and braking pressure of two-stage braking by acquiring vehicle state information, front obstacle information and an estimated road adhesion coefficient; and when the brake triggering condition is met, the brake pressure control signal is sent to the brake actuating mechanism, so that automatic emergency braking of the vehicle is realized. The control algorithm can adaptively adjust the AEB control strategy according to the braking emergency degree, guarantees the safety and meanwhile gives consideration to the braking comfort, and avoids emergency braking.
Description
Technical Field
The invention relates to the technical field of automobile active safety, in particular to an adaptive multistage braking control algorithm of an automatic emergency braking system.
Background
As one of typical active safety technologies, an AEB system can identify dangerous targets in front of a road through sensing equipment such as a radar/camera and the like, and when a driver fails to timely operate a vehicle to avoid collision, active braking measures are taken to avoid collision, so that the accident rate can be effectively reduced or casualties caused by accidents can be reduced. The current AEB control strategy is mainly divided into a safe distance model and a safe time model. The safe distance model takes the relative distance between the front vehicle and the rear vehicle as a braking triggering condition and mainly comprises an NHSTA model, a Jaguar model, a Honda model and the like; the safe time model is a collision avoidance model using a Time To Collision (TTC) as a brake triggering condition, and may be classified into a safe time model considering comfort of a person, a safe event model considering characteristics of a driver, and the like according to different influence factors. The existing control algorithm of automatic emergency braking can realize the emergency collision avoidance of the vehicle to a certain extent, avoid the occurrence of forward collision and reduce the damage when the collision occurs.
The road adhesion coefficient determines the maximum vehicle deceleration that the ground can provide, and is an important factor that must be considered when formulating an AEB control strategy, and the control algorithm described above does not take into account changes in the road adhesion coefficient and does not enable adaptive control of the brake deceleration and the timing of brake intervention. The braking effect is poor when the road surface is attached to a rainy or snowy place.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an automatic emergency braking system self-adaptive multistage braking control algorithm, which aims to solve the problem that the prior art does not consider the road surface adhesion coefficient, so that the good collision avoidance effect can not be realized on the road surfaces with different road surface adhesion coefficients.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
the self-adaptive multi-stage brake control algorithm of the automatic emergency brake system comprises the following steps:
(1) according to vehicle state information acquired by a vehicle body sensor, estimating a road adhesion coefficient of a current vehicle running road in real time through a road adhesion coefficient observer;
(2) according to the estimated value of the current road adhesion coefficient, the information of obstacles in front of the vehicle and the information of the vehicle state, a multi-stage brake distribution coefficient related to the collision emergency degree is obtained through a fuzzy controller;
(3) according to the multi-stage brake distribution coefficient, calculating trigger conditions of AEB partial braking (primary braking) and full braking (secondary braking) at the current moment;
(4) according to the estimated value of the current road adhesion coefficient, determining the expected deceleration of AEB when partial braking and full braking are triggered;
(5) when the AEB trigger condition is met, the required brake deceleration rate of the vehicle is provided by the brake actuator.
In conjunction with step (1), the embodiment of the present invention provides one possible implementation manner of step (1). Wherein, the step of estimating the road adhesion coefficient of the road on which the vehicle is currently traveling in real time by the road adhesion coefficient observer based on the vehicle state information acquired by the vehicle body sensor includes: obtaining parameters such as the speed, the acceleration, the yaw angular velocity, the front wheel turning angle and the wheel speed of the vehicle through a vehicle body sensor; and estimating the road adhesion coefficient of the current running road of the vehicle in real time through a road adhesion coefficient observer according to the parameters.
In conjunction with step (2), the embodiment of the present invention provides a possible implementation manner of step (2). Wherein, the step of obtaining a multistage braking distribution coefficient related to the degree of collision emergency through a fuzzy controller according to the current road adhesion coefficient estimated value, the information of the obstacle ahead of the vehicle and the information of the vehicle state comprises: acquiring parameters such as speed, acceleration, relative distance between the vehicle and the front obstacle through one or more of a forward camera and a millimeter wave radar; and obtaining a multistage braking distribution coefficient related to the collision emergency degree through a fuzzy controller according to the current road adhesion coefficient estimated value, the information of the obstacle in front of the vehicle and the vehicle state information.
In conjunction with step (5), the present invention provides one possible implementation manner of step (5). Wherein, the step of providing the braking deceleration degree required by the vehicle by the braking executing mechanism when the AEB triggering condition is satisfied comprises the following steps: comparing the TTC threshold value of the two-stage braking at the current moment with the TTC calculated according to the front obstacle information and the vehicle state information: when the TTC is larger than a first-stage braking TTC threshold value, no action is performed; when the TTC is smaller than a first-stage braking TTC threshold value, the first-stage braking expected deceleration is sent to a braking executing mechanism through a CAN bus; when the TTC is smaller than a TTC threshold value of the secondary braking, the expected deceleration of the secondary braking is sent to a braking executing mechanism through a CAN bus; the brake actuator establishes a desired brake pressure based on the received desired brake deceleration.
An automated emergency brake adaptive multi-level brake control algorithm is presented herein. Through reasonably distributing TTC trigger thresholds of two-stage braking and adjusting target braking deceleration according to different road adhesion coefficients, the collision avoidance control effect can be effectively realized, and the safety and comfort of the vehicle are ensured in the braking process.
Drawings
FIG. 1 is a flow chart of an automatic emergency brake adaptive multi-level brake control algorithm provided by the present invention;
FIG. 2 is a schematic diagram of an automatic emergency brake adaptive multi-level brake control algorithm provided by the present invention;
FIG. 3 is a schematic diagram of front and rear vehicle speed membership functions of a multi-stage brake distribution coefficient fuzzy controller.
FIG. 4 is a schematic diagram of a preceding vehicle acceleration membership function of a multi-stage brake distribution coefficient fuzzy controller.
FIG. 5 is a schematic diagram of a multi-level brake distribution coefficient membership function of a multi-level brake distribution coefficient fuzzy controller.
FIG. 6 is a graph of the AEB test of the real vehicle at a vehicle speed of 20km/h ahead under the CCRs condition of C-NCAP.
FIG. 7 is a graph showing the AEB test of an actual vehicle at a front vehicle speed of 30km/h under the CCRs of C-NCAP.
FIG. 8 is a graph of the AEB test of the real vehicle at the preceding vehicle speed of 40km/h under the CCRs condition of C-NCAP.
Detailed Description
In order to further enhance the understanding of the present invention, the following detailed description of the present invention is given with reference to the following examples and the accompanying drawings, which are only used for explaining the present invention and are not to be construed as limiting the scope of the present invention.
The control algorithm does not consider the change of the road surface adhesion coefficient, can not realize the self-adaptive control of the braking deceleration and the braking intervention time, and has poor braking effect on the road surface adhesion in rainy and snowy days. Based on the above, the adaptive multistage brake control algorithm for the automatic emergency brake system provided by the embodiment of the invention can be applied to the fields of active braking and other related braking of vehicles.
Referring to fig. 1, a flow chart of an automatic emergency braking system adaptive multi-level brake control algorithm for automatic emergency braking system control of a vehicle is shown, comprising the steps of:
step 101, according to vehicle state information acquired by a vehicle body sensor, estimating a road adhesion coefficient of a current vehicle driving road in real time through a road adhesion coefficient observer. Firstly, parameters such as the speed, the acceleration, the yaw velocity, the front wheel turning angle and the wheel speed of the vehicle are obtained through a vehicle body sensor, and a road surface adhesion coefficient observer is established based on a UKF algorithm. The observer was designed as follows:
the system nonlinear state equation and the measurement equation are as follows:
in the formula xk，uk，ykSequentially an output vector, a state vector and an input vector; w is akIs process noise, vkTo observe the noise.
The equation of state is
The measurement equation is
Wherein:
state vector x (t) of unscented kalman observer [ μ [ ]f1,μfr,μrl,μrr]TInput vector
Observation vector
The covariance of the process and observation noise w (t), v (t) of the state estimate is Q and R. Wherein, axAnd ayIs the lateral longitudinal acceleration of the vehicle; fxijAnd FyijIs the longitudinal and lateral forces on each tire; delta is the front wheel angle, m is the vehicle mass, IzIs the moment of inertia of the vehicle about the z-axis. Subscript i includes f and r, representing front and back, respectively, and subscript j includes l and r, representing left and right, respectively. The system noise covariance matrix, the measurement noise covariance matrix, the initial value of the state vector and the initial value of the state vector variance of the observer are selected in sequence as follows: q is 10-6*I4*4，R＝10-4*I3*3，x(0)＝[1,1,1,1]T，P(0)＝0.1*I3*3。
102, according to the estimated value of the current road adhesion coefficient, the information of obstacles in front of the vehicle and the state information of the vehicle, obtaining a multistage braking distribution coefficient related to the collision emergency degree through a fuzzy controller. Firstly, acquiring parameters such as speed, acceleration, relative distance with a vehicle and the like of a front obstacle through one or more of a front camera and a millimeter wave radar; and obtaining a multistage braking distribution coefficient related to the collision emergency degree through a fuzzy controller according to the current road adhesion coefficient estimated value, the information of the obstacle in front of the vehicle and the vehicle state information. The multi-stage brake distribution coefficient fuzzy controller comprises the following steps:
the designed multi-stage brake distribution coefficient fuzzy controller is used for controlling the speed (km/h) of a front vehicle, the speed (km/h) of a self vehicle and the acceleration (m/s) of the front vehicle2) And outputting a multi-stage brake distribution coefficient according to the brake emergency degree for input. Wherein the multi-stage brake distribution coefficient alpha is the difference delta v between the speed of the vehicle and the target speed when the full brake is triggeredf(i.e., (v)2-v1) And the difference Δ v between the vehicle speed and the target speed at the time of partial brake activationp(i.e., (v)0-v1) A ratio of v0For the speed of the vehicle in partial braking triggering, v1V is a target speed, v is an actual target vehicle speed equal to the speed of the preceding vehicle so that the vehicle is kept stationary relative to the preceding vehicle after braking is completed2To trigger the speed of the vehicle when fully braking. Fuzzy controller input and output linguistic variables are divided according to M (slow), Z (medium), K (fast), TK (very fast), J0 (slow), J1 (speed up), H (slow), C (normal), R (fast), SR (emergency). The detailed linguistic variable description is shown in table 1.
TABLE 1 input-output linguistic variables
The fuzzy controller adopts an IF-THEN rule, a defuzzification mode of an area gravity center method and an inference method of a Mamdani method to estimate the numerical value of the multistage brake distribution coefficient. Fig. 1 to 4 show the relevant membership function and the variable surface of the fuzzy controller, which define the boundary condition of the fuzzy rule.
The driving crowds with different driving habits are tested, the braking habits of the driver at different front and rear vehicle speeds are analyzed, and different fuzzy rules corresponding to the motion states of the own vehicle and the front vehicle are summarized as shown in tables 1 and 2.
TABLE 1 fuzzy rule for deceleration of preceding vehicle
TABLE 2 fuzzy rules for uniform or accelerated speed of front vehicle
Step 103 calculates triggering conditions of AEB partial braking (primary braking) and full braking (secondary braking) at the current moment according to the multi-stage braking distribution coefficient. The instant time of impact TTC is taken as the trigger condition of AEB, and the TTC threshold values of partial braking and full braking departure are respectively set as TTC1And TTC2The calculation method is as follows:
considering the influence of the relative acceleration of the front and the rear vehicles on the collision avoidance process, an improved 2-order TTC calculation method is adopted, namely
Where Δ v represents the difference between the speeds of the own vehicle and the preceding vehicle; d represents the distance between two vehicles; Δ a represents the difference between the acceleration of the host vehicle and the acceleration of the preceding vehicle.
Setting k as a braking demand coefficient, the value of which is equal to
v0Is the speed of the bicycle, v1The vehicle speed is the vehicle speed of the front vehicle.
Wherein, TTC1For one-stage braking (partial braking) TTC threshold, TTC2TTC threshold for two-stage braking (full braking), d1Total braking distance, d2Braking distance, Δ v, required for secondary brakingpRelative speed of two vehicles, Deltav, at first-stage brakingfRelative speed of two vehicles during two-stage braking, a1To a first degree of braking deceleration, a2Is the secondary braking deceleration. According to relevant regulation regulations and safety considerations, the TTC threshold range for limiting the primary braking is required to meet the condition that the TTC is more than or equal to 1.9s and less than or equal to 3s, so that the TTC threshold of the primary braking calculated according to the calculation method is 1.9s when the TTC threshold is less than 1.9s and is 3s when the TTC threshold is more than 3 s.
Step 104 determines the desired deceleration at the triggering of the AEB partial braking and full braking based on the current road adhesion coefficient estimate. The rules for the desired deceleration determination are as follows:
is influenced by the adhesion factor mu between the tire and the road surface,
amax＝gμ. (9)
wherein alpha ismaxThe maximum braking deceleration of the automobile.
If the maximum braking deceleration is greater than-7.1 m/s2Time of flight
If the maximum braking deceleration is greater than-4 m/s2 but less than-7.1 m/s2
If the maximum braking deceleration can not reach-4 m/s2, the braking is single-stage braking, and the braking deceleration degree is
a＝-gμm/s2. (13)
Step 105 provides the brake deceleration required by the vehicle by the brake actuator when the AEB trigger condition is met. Comparing the TTC threshold value of the two-stage braking at the current moment with the TTC calculated according to the front obstacle information and the vehicle state information: when the TTC is larger than a first-stage braking TTC threshold value, no action is performed; when the TTC is smaller than a first-stage braking TTC threshold value, sending the first-stage braking expected deceleration to a braking executing mechanism through a CAN bus; when the TTC is less than a secondary braking TTC threshold, a secondary braking desired deceleration is sent to the brake actuator over the CAN bus. The brake actuator is a brake-by-wire system that establishes a desired brake pressure based on a received desired brake deceleration.
As shown in fig. 2, the process of the control algorithm of the present invention is illustrated schematically.
Finally, the self-adaptive multi-stage brake control method of the automatic emergency brake system is verified through an example, and the vehicle verification result is shown in the figure.
And (3) carrying out test run test on the collision avoidance control strategy in a closed field, and selecting a CCRs (front vehicle static) working condition with the vehicle speed of the vehicle being 20-40 km/h. The AEB function triggering effect within the range of 20-40 km/h of the speed of the vehicle is tested and counted, when the speed of the vehicle is 20km/h, the TTC triggering threshold value of primary braking is 1.9s, and because the speed of the vehicle is very small at the moment, secondary braking is not triggered; the threshold value of two-stage braking is as follows when the speed of the bicycle is 30 km/h: TTC1＝1.9s，TTC20.77s, it can be seen from fig. 7 that the primary braking lasts for about 1.3s, and occupies the main body in the whole braking process, so that the braking is more gradual on the premise of ensuring collision avoidance; the threshold value of two-stage braking is as follows when the speed of the bicycle is 40 km/h: TTC1＝1.9s，TTC2Compared with fig. 7, the second-stage brake occupancy is obviously increased at this time when the vehicle is 0.9s, so as to ensure that collision avoidance can be successfully achieved, and a safe vehicle distance of about 2m is kept between the vehicle and the front vehicle after the vehicle is stationary. Therefore, the self-adaptive multi-stage brake control strategy can provide two-stage brake requests in real time according to the speeds of the front vehicle and the self vehicle and calculate and output corresponding TTC trigger thresholds so as to give consideration to the safety and comfort of the whole vehicle when the AEB function is triggered, and the test result is consistent with the expectation.
Claims (6)
1. An adaptive multistage brake control algorithm of an automatic emergency brake system is characterized by comprising the following steps:
according to vehicle state information acquired by a vehicle body sensor, estimating a road adhesion coefficient of a current vehicle running road in real time by a road adhesion coefficient observer;
according to the estimated value of the current road adhesion coefficient, the information of obstacles in front of the vehicle and the vehicle state information, a multi-stage brake distribution coefficient related to the collision emergency degree is obtained through a fuzzy controller;
according to the multistage brake distribution coefficient, calculating trigger conditions of AEB partial braking, namely primary braking, and complete braking, namely secondary braking at the current moment;
according to the estimated value of the current road adhesion coefficient, determining the expected deceleration when AEB partial braking and full braking are triggered;
when the AEB trigger condition is satisfied, the required braking deceleration of the vehicle is provided by the brake actuator.
2. The adaptive multi-stage brake control algorithm for an automatic emergency brake system according to claim 1, wherein the estimating of the road adhesion coefficient of the road on which the current vehicle is traveling in real time by a road adhesion coefficient observer based on the vehicle state information acquired by the vehicle body sensor comprises: and the road adhesion coefficient is obtained by real-time estimation through a road adhesion coefficient observer.
3. The adaptive multi-stage brake control algorithm for an automatic emergency brake system according to claim 1, wherein the obtaining of the multi-stage brake distribution coefficient related to the crash emergency degree through the fuzzy controller based on the current road adhesion coefficient estimation value, the obstacle information in front of the vehicle, and the vehicle state information comprises:
the information of the obstacle in front of the vehicle is acquired through one or more of a front-view camera and a millimeter wave radar; the fuzzy controller is used for controlling the speed (km/h) of the front vehicle, the speed (km/h) of the self vehicle and the acceleration (m/s) of the front vehicle2) Outputting a multi-stage brake distribution coefficient according to the brake emergency degree for input; the multistage brake distribution coefficient alpha is the difference delta v between the speed of the vehicle and the target speed when the full brake is triggeredfI.e. (v)2-v1) And the difference Deltav between the speed of the vehicle and the target speed when the partial braking is triggeredpI.e. (v)0-v1) Ratio of (v)0For speed of vehicle triggered by partial braking，v1V is a target speed, v is an actual target vehicle speed equal to the speed of the preceding vehicle so that the vehicle is kept stationary relative to the preceding vehicle after braking is completed2The speed of the bicycle is triggered when the brake is completely braked; the input and output linguistic variables of the fuzzy controller are divided according to M (slow), Z (medium), K (fast), TK (extra fast), J0 (slow), J1 (acceleration), H (slow), C (normal), R (fast) and SR (emergency); the fuzzy controller estimates the numerical value of the multistage brake distribution coefficient by adopting an IF-THEN rule, a defuzzification mode of an area gravity center method and an inference method of a Mamdani method; the driving crowds with different driving habits are tested, the braking habits of the driver at different front and rear vehicle speeds are analyzed, and different fuzzy rules corresponding to the self vehicle motion state and the front vehicle motion state are summarized.
4. The automated emergency braking system adaptive multi-level brake control algorithm of claim 1, wherein the calculating trigger conditions for partial braking, primary braking, and full braking, secondary braking, AEB at the current time based on the multi-level brake distribution coefficient α comprises:
setting k as a braking demand coefficient, the value of which is equal to
v0Is the speed of the bicycle, v1The speed of the front vehicle;
since the vehicle braking time includes: 1) time t required for driver reaction1I.e. the time at which the driver identifies a hazard and makes a decision; 2) time t required for response of brake system2I.e. the time of response of the mechanical structure of the braking system; 3) time t required to reach target brake pressure3(ii) a 4) Brake pressure hold time t4 [11]；
Wherein, the active braking process does not need the intervention of the driver, and is performed on t1Do not consider; t is t2Take 0.1s, t3Taking for 0.2 s; setting the headway tpTaking the value of 0.15 s;
the two-stage braking TTC threshold value calculation method comprises the following steps:
wherein, TTC1For first-order braking TTC threshold, TTC2For two-stage braking TTC threshold, d1Total braking distance, d2Braking distance, Δ v, required for secondary brakingpRelative speed of two vehicles, Deltav, during primary brakingfRelative speed of two vehicles during two-stage braking, a1For a first braking deceleration, a2Is the secondary braking deceleration; the TTC threshold range for limiting the first-level braking is required to meet the condition that the TTC is more than or equal to 1.9s and less than or equal to 3 s.
5. The automated emergency braking system adaptive multi-level brake control algorithm of claim 1, wherein determining the desired deceleration at AEB partial braking and full braking triggers based on the current road adhesion coefficient estimate comprises:
is influenced by the adhesion factor mu between the tire and the road surface,
amax＝gμ. (9)
wherein alpha ismaxThe deceleration is the maximum braking deceleration of the automobile, and g is the gravity acceleration;
if the maximum braking deceleration is greater than-7.1 m/s2Time of flight
If the maximum braking deceleration is greater than-4 m/s2But less than-7.1 m/s2Time of flight
If the maximum braking deceleration can not reach-4 m/s2When the braking is single-stage braking, the braking deceleration is
a＝-gμm/s2 (13)。
6. The automated emergency braking system adaptive multi-level brake control algorithm of claim 1, wherein the providing by the brake actuator the brake deceleration required by the vehicle when the AEB trigger condition is met comprises:
the brake actuating mechanism is controlled by wire, and receives target brake pressure or target brake deceleration through the CAN bus to realize the automatic emergency brake requirement.
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| CN114802133A (en) * | 2022-05-31 | 2022-07-29 | 重庆理工大学 | Automatic emergency braking self-adaptive control method considering comfort |
| CN115071696A (en) * | 2022-06-20 | 2022-09-20 | 重庆理工大学 | Automatic emergency collision avoidance control method for intelligent automobile intersection based on V2X |
| CN114987412A (en) * | 2022-06-30 | 2022-09-02 | 东风汽车有限公司东风日产乘用车公司 | Automatic emergency braking control method, device, equipment and storage medium |
| CN116279341A (en) * | 2023-05-19 | 2023-06-23 | 北京宏景智驾科技有限公司 | Safety braking method and device, electronic equipment and storage medium |
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