Research On Cooperative Adaptive Cruise Control Strategy With The Influence Of Traffic Flow

Autonomous vehicles are an important part of smart transportation and smart cities.However,due to unstable sensor reliability and control system vulnerabilities,it is too early to commercialize self-driving technology,which has catalyzed the development of assisted driving systems,especially cacc system.This dissertation will build a ring road simulation platform in view of acc system and cacc system to investigate the impact on traffic flow operating conditions,and then improve cacc system in detail from the perspective of multi-vehicle and multi-state information,and finally the software-in-the-loop test and analysis of the improved cacc strategy.Firstly,an acc system was designed based on the speed mode and distance mode,and its effectiveness was verified by the changes in the speed and distance between the leading vehicle and the following vehicle;And built an intelligent driver model that imitates human driving behavior;Using the established ring road simulation platform,two vehicle control type vectors are introduced,based on the investigate of100% IDM,50% IDM and 50% ACC,100% ACC proportion of traffic flow average speed and distance change trend,We found that the increase in the number of acc vehicles has significantly reduced the oscillations of speed and inter-vehicle distance,proving that the acc system can effectively improve the traffic flow operating conditions.Secondly,based on the vehicle kinematics model and the vehicle dynamics model,a cacc system for speed characterization and engine force characterization was designed,and the stability of the control system was verified with the help of Lyapunov’s second method;Then also introduce two vectors representing the control type on the ring road simulation platform to investigate the operation status of traffic flow at the ratio of 0% CACC-100% CACC.Based on the analysis of the fundamental diagram model of traffic flow,it is found that the increase in the proportion of cacc vehicles contributes to the significant increase in the average speed of the traffic flow,the maximum traffic flow and the critical traffic flow density,proving that cacc system can effectively improve the traffic flow capacity and road occupancy rate.Finally,an improved cacc system of linear quadratic optimal control is designed based on the status information of the distance between the leading vehicle and following vehicle of the target vehicle,relative speed and acceleration.The improved constant time headway strategy of the upper-level controller and The vehicle reverse dynamics system model of the lower-level controller makes a detailed design of the improved cacc strategy.With the Carsim and Simulink co-simulation platform,software-in-the-loop testing and verification were carried out on constant-speed cruise conditions,stable following conditions,stop-and-go conditions,lane-change cut-out conditions and lane-change cut-in conditions,and it was proved that the improved cacc strategy enabled the formation to adapt to the changes of various conditions and satisfactorily guarantee the tracking performance and comfort performance.