Research On Traffic Flow Control Method In Expressway Diversion Area Under Connected And Autonomous Environment

The lane changing behavior of diverted vehicles driving out of the main line in the expressway diversion area will conflict with through vehicles,resulting in disordered traffic flow in the diversion area,affecting the traffic capacity of the road section,and in severe cases,traffic congestion will occur,resulting in reduced traffic efficiency,decreased safety levels,increased fuel consumption,etc.Therefore,it is crucial to improve the traffic operation efficiency and alleviate traffic congestion in the expressway diversion area.The development of intelligent transportation systems has provided new ideas for expressway management and control.This thesis focuses on the study of expressway diversion areas,analyzes the causes of traffic congestion,and proposes traffic flow control method under connected and autonomous environment.Firstly,based on the analysis of the characteristics of connected and autonomous vehicles,this article summarizes the characteristics of traffic flow under connected and autonomous environment.On the basis of theoretical research on expressway diversion areas,the causes of congestion in the diversion area are summarized.And the causes and control methods of variable speed limit control and lane change control are analyzed.Secondly,this article establishes a car following model of connected and autonomous vehicles to study the laws of traffic flow movement.Based on the classic optimized velocity model,an improved car following model(CIPF)considering the comprehensive information of the preceding and following vehicles is proposed.Linear stability analysis and nonlinear analysis are performed on the CIPF model,and numerical simulation is conducted to verify that the CIPF model can alleviate traffic disturbances and improve the stability of traffic flow.Then,based on the causes of congestion in the expressway diversion area,the collaborative control method combining variable speed limit control and lane change control is proposed.The variable speed limit control method based on the model predictive control uses an improved METANET model to predict traffic flow,comprehensively considers the total travel time of vehicles and the total traffic capacity of the lane to establish the objective function,and considers actual factors to constrain the variable speed limit value.The lane-changing control method for decentralized vehicles’ changing lanes is proposed,an objective function is established considering the total travel time of vehicles,the lane change probability of the lane change sections is constrained,and genetic algorithm is used to solve the collaborative control optimization problem.Finally,the cellular automata method is used for simulation analysis.Based on the CIPF model,improvements were made to the traditional Na Sch model and STCA model,and a connected and autonomous vehicles driving model was established.A simulation scenario for the expressway diversion area was constructed,and four control schemes were designed: no control,variable speed limit control,lane change control,and collaborative control.Simulation analysis was conducted on different control schemes under different traffic conditions with different densities on the main road.The simulation results showed that,under low density traffic conditions,vehicles can pass through the diversion area at free flow speed without the need for traffic flow control.In medium density and high density traffic conditions,the collaborative control method can increase lane traffic flow and reduce the average travel time of vehicles,which is beneficial for alleviating congestion in expressway diversion areas.