Analysis And Optimization Of Highway Moving Bottleneck Operation Under Intelligent Network Environment

During the operation of the expressway,especially during major holidays,it is often found that the expressway is already overcrowded before it reaches its capacity.The relevant parties recognize that this is due to the large amount of overload,full load,and performance of the expressway in China.Poor trucks are mixed with other vehicles,resulting in a large number of "mobile bottlenecks" along the road.Due to the randomness and mobility of mobile bottlenecks,it is more difficult to optimize management.However,in the existing research,there are few studies on mobile bottlenecks,and there are still studies that fail to analyze the mobile bottleneck optimization mechanism from the perspective of mobile bottleneck influencing factors and operating characteristics.This article is based on the theory of intelligent networked environment,The mechanism,the model and the application of four aspects to carry out the operation and optimization of the freeway mobile bottleneck.This paper first analyzes the formation mechanism of the mobile bottleneck of the expressway,and then studies its impact on the capacity of the expressway through simulation,and analyzes the traffic operation status,traffic characteristics and traffic flow at the mobile bottleneck of the expressway.,Optimization structure and optimization method to study the optimization mechanism of intelligent network mobile bottleneck.Because the vehicle has the technical characteristics of "intelligence + network connection" in the environment of intelligent network connection,the driving characteristics of the vehicle under the condition of intelligent network connection are analyzed and the driving behavior of the vehicle is described.Then,the The way of obtaining vehicle traffic data mainly includes the source of basic data and the way of obtaining data by building an intelligent network connection scenario.Due to the difficulty of obtaining road traffic density in an intelligent networked environment,the Kalman filter algorithm is considered to estimate the road traffic density and make a corresponding error analysis with the actual road traffic density.Due to the characteristics of vehicle acceleration and deceleration,car insertion,parking,and starting at the junction of the highway moving bottleneck change,the IDM model is selected as the optimization method for the lane change and junction of the mobile bottleneck.This model has certain complexity and accuracy to To meet the requirements of the networked vehicle control strategy,after the IDM model is calibrated,combined with the obtained vehicle traffic data,it will provide different lane-changing opinions for different vehicle lane-changing behaviors at the mobile bottleneck.In order to overcome the modeling difficulties caused by the randomness and mobility of freeway mobile bottlenecks,MPC was selected to optimize the traffic flow of mobile bottlenecks,and the average speed and traffic density estimates of road sections under the intelligent network environment were used to predict the future traffic flow State and establish the corresponding model,through the establishment of constraints to dynamically optimize the control of its traffic flow.Finally,after the establishment of the theoretical model,the validity of the model and the value of the research are verified by simulation.The simulation results show that the optimization model based on MPC proposed for the mobile bottleneck in this study can better improve the traffic congestion of the road section and effectively improve the passengers.The comfort of the road improves the efficiency of road traffic and has good practical value.