Research On Multi-objective Cooperative Adaptive Cruise Control System

With the growing transportation system,it is difficult to solve the problems of traffic congestion,frequent accidents and environmental pollution that are gradually highlighted by relying on traditional solutions.Driver misuse and capacity limitations of the transportation infrastructure are considered to be one of the main causes of these problems.As an extension of the adaptive cruise control(ACC)system,the Cooperative Adaptive Cruise Control(CACC)system can realize the information interaction between vehicles through vehicle-to-vehicle communication technology and realize the coordinated control of vehicles and vehicles by using communication information combined with automation technology.The CACC system has been highly concerned by academic and industrial circles to improve the efficiency and safety of existing transportation system capacity and reduce traffic energy consumption.Due to the uncertainty of the model of the CACC system vehicle during driving and limited by the environment and other constraints,the traditional cruise control method is often difficult to meet the control requirements of the CACC system,and it is difficult to balance the coordination of multiple performance indexes.Therefore,this paper studies the multi-objective cooperative adaptive cruise control system.After introducing the domestic and international research overview of CACC system,the theoretical basis of adaptive dynamic programming(ADP)algorithm is introduced.The principle and basic structure of ADP algorithm are expounded,and the derivation process of multi-objective ADP method is further given.This paper expounds the vehicle-mounted structure of the CACC system,clarifies the hierarchical structure of the vehicle longitudinal motion control,and analyzes the performance indicators of the CACC system to clarify the system's control objectives.Then the overall framework of multi-objective CACC system is established.The longitudinal kinematics modeling of CACC vehicles is carried out,and the discrete state space equation of CACC system is derived.The reference driver model is selected as the basis for the design of subsequent multi-objective coordination controller.A multi-objective CACC system based on adaptive dynamic programming algorithm was proposed to solve the problem of conflicting performance indexes in the process of vehicle driving,so as to realize the optimal control of multiple control objectives including safety performance,tracking performance,driver acceptance performance and fuel economy performance.The multi-objective performance index function and utility function are designed according to the multi-objective adaptive dynamic programming method.Based on this,the core network of guided actiondependent heuristic dynamic programming structure is designed,and the multiobjective coordination optimization controller is established.Finally,the modeling and simulation of the designed multi-objective coordination controller is carried out in the Matlab/Simulink software environment.The simulation analyzes the effectiveness and adaptability of the algorithm.The simulation results show that the multi-objective CACC algorithm can better coordinate the relationship between multiple performance indexes during driving,and achieve system performance optimization and stability.