Study On Variable Speed Limit Control Method Of Highway Mainline In Intelligent Network Environment

With the characteristics of high speed,high safety and high transportation capacity,highways are one of the most important components in modern transportation system.However,highways often cause traffic bottleneck area due to local road construction,emergencies and other factors,resulting in reduced driving safety level and traffic efficiency.Intelligent connected vehicle technology provides a new method in the field of highway control by virtue of the real-time interactive information and strong vehicle sensing ability.It is of great significance to study the variable speed limit control in the intelligent network environment to ameliorate traffic operation status in the bottleneck area and improve the traffic efficiency.Firstly,the bottleneck area of the highway is taken as the research object,and the definition and characteristics of the traffic bottleneck are elaborated.Based on this,the mechanism of congestion spreading and dissipation of the bottleneck area is analyzed by examples.By analyzing the characteristics of the intelligent network environment,the intelligent connected vehicle following model and congestion alleviation theory are mentioned.Moreover,the variable speed limit control theory is put forward and the control principle and structure are analyzed under the framework of variable speed limit control theory.Secondly,METANET was selected as the basic traffic flow model of variable speed limit control through comparative analysis.The characteristics of variable speed limit control and intelligent network environment were analyzed to improve the METANET model,and the model was calibrated using simulation data.Thirdly,with reference to the idea of model predictive control,a variable speed limit control system is constructed.Total travel capacity,total travel time,and total speed difference are used as control targets.Using the 1-9 scale method,the weight coefficients of the three control targets are determined according to importance.Based on the characteristics of the driver and the highway,the speed limit value is constrained toa reasonable interval,and the genetic algorithm is used as a solving tool to achieve rolling optimization.Finally,SUMO is used as the basic simulation platform,and the intelligent connected vehicle is added by modifying its built-in files.The SUMO Tra CI interface and the python programming language are used for secondary development of SUMO to build a variable speed limit control system in an intelligent network environment.The simulation results show that compared with the uncontrolled state,the variable speed limit control can effectively alleviate congestion and improve traffic efficiency;the improved speed limit control system under the intelligent networked environment is better than the unimproved state.In addition,as the penetration rate of intelligent connected vehicles increases,traffic operation status will be further improved.