Research On Vehicle Cooperative Lane Change Based On Virtual Mass-spring-damper Model

The proliferation of car ownership and limited road conditions have led to significant traffic congestion and frequent road accidents in today’s society.However,recent advances in vehicle infrastructure cooperation technology,with intelligent connected vehicles serving as a core component,provide a promising solution to address this problem.One of the most common behaviors in traffic is lane changing.Unsafe lanechanging behavior is a leading cause of traffic accidents and traffic congestion.Therefore,it is of paramount importance to study the collaborative lane change of intelligent connected vehicles based on vehicle infrastructure collaboration.To enhance the safety and efficiency of intelligent connected vehicles during the lane-changing process,this paper proposes a cooperative lane change merging model based on the virtual Mass-Spring-Damper(MSD)model.Additionally,a parameter calculation method for the lane change model is proposed based on the safe distance of the lane change and the motion response of the MSD model.The proposed model and associated parameter calculation method are expected to contribute significantly to the improvement of intelligent connected vehicle safety and efficiency during the lanechanging process.The main contents of this paper are as follows :(1)Firstly,this study analyzes the lane-changing behavior of vehicles in traffic and proposes a two-lane vehicle cooperative lane-changing scenario based on forced lanechanging situations where vehicle queues exist on the target lane.To ensure the safety of the lane-changing process and prevent collisions,we employ the rectangular contour model and calculate the minimum safe distance of the lane change,taking into account the potential collision forms that may occur during the process of vehicle lane change.(2)Then,this study focuses on the lane-changing behavior of vehicles and proposes a lane-changing trajectory planning method based on quintic polynomial theory.Subsequently,vehicle longitudinal and lateral controllers are established to ensure the vehicle tracks the lane-changing trajectory.For the longitudinal control,a vehicle inverse longitudinal dynamics model is established to convert the upper control’s expected acceleration into driving torque and braking pressure.Meanwhile,the LQR lateral controller is developed to control the vehicle along the reference trajectory.The control effect is verified through simulation.Additionally,to address the vehicle platoon on the target lane,a vehicle platoon model based on MSD model is established to ensure the stable driving of the vehicle platoon.The effectiveness of the model is confirmed through simulation.(3)Next,the vehicle virtual mapping theory is utilized to transform the cooperative lane change control problem into a vehicle longitudinal spacing control problem,by projecting the lane change vehicle onto the target lane.The MSD model is established between the projection of lane change vehicle and the target lane vehicle,and the corresponding acceleration control of the vehicle is calculated by utilizing the free vibration of the model to achieve the desired spacing.The motion response relationship of the MSD model is then analyzed under various damping conditions.Based on the motion response relationship of the MSD model under critical damping conditions,a parameter calculation method for the lane change model is proposed to safely control the vehicle to complete the lane change.(4)A co-simulation platform,utilizing Presan,Carsim,and Matlab/Simulink,has been constructed.Three distinct driving scenarios have been designed to test the effectiveness of the MSD cooperative lane change algorithm,while a two-stage cooperative lane change merge algorithm has been introduced for comparative analysis.The results have shown that the MSD cooperative lane change algorithm is capable of executing safe lane changes across various scenarios.Furthermore,it has demonstrated clear advantages in terms of lane change time and space requirements,ultimately leading to improved efficiency while maintaining safety.Finally,the cooperative lane change model has been validated through a hardware-in-the-loop experimental platform.Overall,these findings highlight the effectiveness of the MSD cooperative lane change algorithm and its potential for enhancing safety and efficiency in lane changing scenarios.