Study On The Propagation Mechanism Of Traffic Flow Random Disturbance Involving Autonomous Vehicles

The study of highway traffic flow has always been a hot spot for researchers at home and abroad.With the development and maturity of autonomous driving technology,there will be more and more autonomous vehicles on highways,in order to ensure high-quality and fast traffic.Transportation development requires that how to efficiently and safely manage the mixed traffic flow of autonomous vehicles and manual vehicles has become one of the more difficult issues.From the perspective of manual driving vehicles,this paper divides manual drivers into aggressive drivers and conservative drivers based on the three-phase traffic flow framework,and explores the random disturbance caused by different types of drivers in mixed traffic with some autonomous vehicles.The characteristics of propagation and evolution in traffic flow.The research work is as follows:(1)Various factors such as road structure characteristics,driving environment conditions,and driver’s personality on the expressway will affect the speed and acceleration of the vehicle.Therefore,the change of the speed and acceleration of the vehicle is one of the most direct causes of random disturbance,which is also One of the most obvious signs used to distinguish between aggressive drivers and conservative drivers.The driving speed,acceleration,and deceleration of aggressive drivers are generally higher,while conservative drivers are the opposite.This article first adopts this feature Constructed a three-phase traffic flow model for different types of manual drivers.Secondly,by consulting the data to analyze the operation mode of the autonomous vehicle,it was learned that the autonomous vehicle uses sensors and other detection equipment to adapt its own speed to ensure the safety of the preceding vehicle.Distance,thereby establishing an autonomous vehicle model,combining the manual driver model with the autonomous vehicle model to obtain a manual-autonomous driving mixed three-phase traffic flow model,and finally verifying the effectiveness of the model through steady-state analysis of the basic graph and cross-correlation function analysis Sex.(2)The statistical data is obtained through Matlab simulation.First,the average speed and average flow of traffic flow under different densities are counted on a single lane.The change trend is basically consistent with the phase change of three-phase traffic flow F→S and S→J.The proportion of autonomous vehicles It has a certain positive impact on the density threshold of the phase change of the three-phase traffic flow,and then through statistics of the standard deviation of the speed and the standard deviation of the following distance of vehicles under different mixing ratios,it is found that the higher the proportion of autonomous vehicles,the better the stability of the traffic flow..Then from a microscopic point of view,take a value near the S→J phase transition density value to obtain the statistical data of the average speed change with time.The time point at which the speed is 0 means that there is traffic collapse on the road at this time.The speed of each vehicle is extracted,and the propagation and evolution process of the speed random disturbance between vehicles are analyzed.Through the trajectory graph and the time-speed graph,it is found that the self-driving vehicle can better prevent the speed random disturbance from moving backward vehicles through a good speed adaptation process.However,the aggressive acceleration and deceleration behavior of the aggressive driver makes the speed random disturbance spread to the rear vehicle.Finally,a two-lane manual-automatic mixed traffic flow model was established on the basis of the single-lane manual-automatic mixed traffic flow model.The traffic flow was measured through four combinations of different autonomous driving ratios,aggressive driver ratios and conservative driver ratios.According to statistics on speed and lane change times,autonomous vehicles still have an effect on improving the stability of traffic flow under two-lane conditions,but the stability of mixed traffic flow between autonomous vehicles and conservatively driven vehicles is poor under low-density conditions.