Research On Adaptive Cruise Control Strategy Intergrating Human-Machine Co-Driving

With the continuous innovation and breakthrough of intelligent driving technology,today’s intelligent driving vehicles are gradually transitioning from L2～L3 level to L5 level.In the short term,intelligent vehicles will be in a mode where the intelligent driving system drives together with the driver.In order to organically combine the driver and the intelligent control system,cooperate with each other to complete the driving task,and make the car more intelligent and humanized,the human-machine co-driving mode is the key to the transition from the assisted driving system to the unmanned driving.Therefore,the adaptive cruise control strategy integrating human-machine co-driving is particularly important.Aiming to improve the driving safety,comfort and followability of vehicles,and taking an electric vehicle as the research object,this thesis mainly studies the adaptive cruise control strategy considering the driver’s characteristics and the human-machine co-driving control strategy based on real-time allocation of driving rights.The main research contents are as follows:First,using Car Sim and Matlab/Simulink,a vehicle dynamics model that conforms to the driving and braking characteristics of pure electric vehicles and a vehicle inverse dynamics model based on longitudinal dynamics equations are built.The accuracy of the dynamic model is verified by simulation,which lays the foundation for the following research.Secondly,the structure of the adaptive cruise system is analyzed,and the layered adaptive cruise control strategy is designed.By collecting the driver’s characteristic parameters,a personalized car-following safety distance model is designed.In the decision-making layer,the mode switching strategy of the adaptive cruise system is designed for the highway driving environment.For the cruise control mode,a PID-based vehicle speed control strategy is designed.For the following mode,by establishing the following kinematics state space equation,performance index function and constraints,a MPC-based following control strategy is designed and the rolling optimization solution is carried out.On the basis of the adaptive cruise control strategy,a human-machine co-pilot control strategy based on the dual-pilot dual-control theory is designed.In order to evaluate the control performance of the man-machine co-pilot system,a man-machine co-pilot performance evaluation system with safety,comfort,followability and driving load as the indicators is proposed.Combined with the evaluation index of human-machine co-driving,through the analysis of longitudinal car-following risk factors,taking speed and vehicle spacing risk as two-dimensional input terminals,a human-machine co-driving control strategy for real-time allocation of driving rights is designed.Finally,a co-simulation platform based on Matlab/Simulink,Car Sim and Pre Scan is established,and typical working conditions are selected for simulation.The results show that the adaptive cruise control strategy integrating human-machine co-driving designed in this thesis has good performance,ensures driving safety,comfort and followability,and meets the control requirements of modern intelligent vehicles.In the campus environment,based on the intelligent vehicle test platform,the actual vehicle control effect of the vehicle speed control strategy is verified.