Research On Collision Avoidance Strategy Of Active Safety Considering Characteristics Of Drivers And Road Adhesion Coefficient

Nowadays,automobile industry is moving in the direction of electrification,intelligence,interconnection and sharing.However,the rapid development of the automobile industry has also brought about problems such as air pollution,traffic congestion and traffic safety accidents,which seriously reduces the traffic efficiency and causes a large number of casualties and property losses to the society.At present,the vehicle rear-end collision has become the main cause of traffic accidents.The cause of collision traffic accidents is mainly related to human,vehicle and road.Therefore,it is particularly important to develop active safety collision avoidance system that can adapt to different road conditions and driving characteristics of drivers.This paper establishes an adaptive cruise strategy considering characteristics of drivers and road conditions.A longitudinal and lateral adaptive multi-modal collision warning strategy are also be established.Active safety collision avoidance system can be achieved through the double insurance of adaptive cruise strategy and multi-modal collision warning strategy,which will improve the safety of vehicles and the traffic efficiency.The main contents of the full text are as follows:(1)In view of the working conditions of acceleration driving,uniform driving and deceleration driving of the front vehicle,a safety distance model based on the vehicle braking process is established.A longitudinal adaptive collision avoidance safety distance model is established by introducing reaction time of drivers,braking factor,road adhesion coefficient and safety distance threshold updated in real time with the road adhesion coefficient.The lateral collision avoidance adaptive safety distance model is established based on the impact fact of reaction time,road condition and the minimum lateral safety distance,which makes the safety distance model realize adaptation of human and road.(2)Based on the nonlinear vehicle dynamics model with seven degrees of freedom and Dugoff tire model,the adaptive cascaded strong tracking unscented Kalman filter is used to estimate the vehicle state parameters and road adhesion coefficient.Based on strong tracking filtering,the proposed algorithm introduces multiple fading factors to adjust the predicted covariance matrix and the gain matrix in real time,which will reduce the weight of the old data.The two strong tracking Kalman filters are connected in series with each other,with the first filter estimating the motion state of the vehicle and the second estimating the road adhesion coefficient.Based on the joint simulation platform of Carsim and Simulink,the high attachment coefficient pavement and the low attachment coefficient pavement are selected for the simulation experiment.Simulation results show that the Dugoff tire model has a good fit to the longitudinal and lateral forces of the tire.The adaptive cascaded strong tracking unscented Kalman filter has higher estimation accuracy compared to extended Kalman filtering and unscented Kalman filtering,which efficiently solves the problem of poor estimation accuracy of vehicle motion state and road adhesion coefficient under the condition of highly nonlinear systems caused by the same weight of the old data.(3)Based on the fuzzy control algorithm,the acceleration and the speed of the front vehicle and the speed of the self-vehicle are selected as the input of fuzzy control algorithm to obtain the braking factor in different vehicle motion states.Weather condition,driving experience,the age of the driver and fatigue degree are also selected as the input of the fuzzy control algorithm to obtain the reaction time of different drivers.Based on the if-then fuzzy rule,both the braking factor and reaction time of the driver are inferred through Mamdani and reverse blurred by the method of area center of gravity method.The fuzzy surface diagram of braking factor and reaction time can be obtained.Finally,driving simulator is used to carry out the simulation test,which verifies the effectiveness of the fuzzy control algorithm on brake factor and reaction time of the driver.(4)An adaptive vehicle-following distance model is established considering characteristics of drivers and road conditions.Headways of different characteristics of drivers and minimum safety distance updated in real time with road adhesion coefficient are introduced.The expected acceleration is obtained by using the LQR controller based on vehicle spacing error and relative speed.A PID controller is used to track the expected acceleration.The throttle opening and brake pressure can be obtained based on the reverse engine model and the reverse brake model combined with the drive brake switching strategy.The joint simulation platform of Carsim and Simulink is used to verify the effectiveness and accuracy of the proposed adaptive cruise strategy.Finally,driving simulator is used to carry out the simulation test.Results show that the vehicle reverse dynamics model has a strong tracking effect on step and sinusoidal signals of the expected acceleration.The adaptive cruise strategy considering characteristics of drivers and road conditions has a good tracking effect on the speed of the front vehicle and the desired spacing.The strategy can adapt to different characteristics of drivers and complex road conditions,which makes the adaptive cruise strategy realize adaptation of human and road.(5)The longitudinal and lateral adaptive multi-modal collision warning strategy are established based on the collision avoidance safety distance model.The longitudinal adaptive multi-modal collision warning phase is established based on TTC model and safety state level.The lateral adaptive multi-modal collision warning phase is established based on self-vehicle speed and the two-vehicle lateral distance.The Simulink and Carsim joint simulation platform are used to simulate the working conditions of uniform driving,acceleration driving and deceleration driving to study the influence of road adhesion coefficient,braking factor and reaction time of drivers on collision avoidance safety distance and multi-modal collision warning strategy.The results show that the adaptive collision avoidance safety distance has a high fitting accuracy.The multi-modal collision warning strategy is consistent with the actual situation,which realizes adaptation of human and road.