Research On Vehicle Anti-Collision Control Strategy Based On V2X For Discontinuous Ice-Snow Roads

In recent years,with the continuous development of the national economy,the domestic vehicle ownership has reached a new high.The increase in the number of motor vehicles and drivers has brought convenience to people,but also posed severe challenges to traffic safety.In order to enhance the safety of road traffic,vehicles are continuously developing towards intelligence and networking,and more and more vehicles are equipped with automatic emergency braking systems.However,the sensors mounted on vehicles have the disadvantage of imprecise measurement in harsh weather conditions,obstacle obstructions,driving on sharp curves,etc.And there is currently little research on collision avoidance control for vehicles traveling on discontinuous ice-snow roads.The size of the road adhesion coefficient is one of the main factors affecting the vehicle braking distance.Based on V2 X technology,this thesis builds a vehicle collision avoidance control model that considers the road adhesion coefficient to avoid accidents when vehicles travel on discontinuous ice-snow roads.Based on the vehicle’s dynamic response,the Unscented Kalman Filter algorithm is used to estimate the road adhesion coefficient in real-time.Firstly,this thesis builds a seven-degree-of-freedom vehicle dynamic model and the Dugoff tire model.Then,after normalizing the tire force,it is brought back to the whole vehicle model to obtain the relationship between the state variables and observed variables.Finally,the road adhesion coefficient is estimated based on the Unscented Kalman Filter algorithm.The joint simulation of MATLAB/Simulink and Car Sim software is used to verify the accuracy of the road adhesion coefficient estimator in estimating the adhesion conditions of discontinuous ice and snow roads(three types of uniform roads,joint road,and split road).Research on vehicle anti-collision control strategy based on V2 X.The strategy mainly includes three modules: information collection module,decision-making module,and execution module.The information collection module mainly uses V2 X technology to obtain surrounding environmental information and surrounding vehicle motion state parameters,providing data for the decision-making module.The decisionmaking module is mainly used to give different control strategies based on the different motion states of the host vehicle and the front vehicle as well as the road conditions.This module includes three sub-models,respectively: the vehicle’s surrounding environmental state detection model for detecting the target vehicle,the variable TTC safety time model based on environment,and the multi-level braking model based on the road adhesion coefficient.The execution module is mainly used to respond to the braking deceleration request output by the decision-making module,and ABS is added to the module to prevent the loss of steering ability due to wheel lock during vehicle braking.The joint simulation is used to verify the effectiveness of the vehicle anti-collision control strategy.Using the Pre Scan,MATLAB/Simulink and Car Sim software for joint simulation,Euro-NCAP is used as the standard test scenario to simulate and verify whether the vehicle can effectively avoid collisions when driving on uniform road,joint road,and split road under different test scenarios.The results show that the collision avoidance strategy proposed in this thesis can effectively prevent collision when vehicles travel on discontinuous ice-snow roads.