Research On Expressway Traffic Flow Model And Vehicle Carrying Efficiency Considering Driver Characteristics

With the aggravation of road congestion and the improvement of intelligent connected vehicle technology,the unified scheduling of vehicles in the expressway network to optimize road traffic flow has become the focus of current research.However,at the present stage,the driving of vehicles is still inseparable from driver,and the driver characteristics include many factors.How to quantify the influence of multiple driver factors on road traffic flow has become an urgent problem to be solved.Meanwhile,considering the passenger transport scenarios on expressway,in the microscopic traffic flow,there is a lack of corresponding vehicle carrying efficiency calculation and analysis for small passenger vehicles.Therefore,considering the impact of multiple-driver factors on road vehicle traffic,and establishing a corresponding evaluation index system of vehicle carrying efficiency in the microscopic traffic flow,has become an urgent problem to be solved.Focusing on the above problems,based on the intelligent connected highway environment,this thesis establishes a microscopic traffic flow model that considering driver characteristics,constructs a vehicle carrying efficiency evaluation index system in the microscopic traffic flow,and studies the change of road traffic flow and carrying efficiency of vehicles with driver characteristics and normal vehicles under the three maximum speed limits of highway.The specific research contents of this article are as follows:（1）Analyze the highway road environment,driver driving behavior and the influencing factors of vehicle lane changing,and constructs the hierarchical structure of the impact factors of vehicle lane changing process.Through the analytic hierarchy process,and the introduction of incentive values and vehicle expected speed,the influence of each driver factor is quantified as the speed difference during the vehicle changes lanes process.（2）Based on the intelligent connected environment,a microscopic traffic flow model of expressway considering driver characteristics is established.The process of lane changing is divided into three stages:lane changing desire judgment,traffic condition judgment,and lane changing condition judgment.Different lane changing rules are set for vehicles with driver characteristics and normal driving vehicles,the traffic of vehicles under the three types maximum speed limit of expressway are simulated.The simulation results show that,when the maximum road speed limit from v_max=4cells/s to v_max=5cells/s and then to v_max=6cells/s,compared to the normal driving vehicles,the average speed of vehicles on the road with driver characteristics increased by 13.0%,27.0%,and 49.6%,while the average vehicle density on the road decreased by 7.8%,17.9%,and 24.1%,and the average vehicle traffic flow on the road increased by 3.8%,4.8%,and 7.5%.The incentives brought by driver characteristics have a greater impact on the speed and density of road vehicles,while the impact on traffic flow is relatively small.（3）The evaluation index system of vehicle carrying efficiency in the microscopic traffic flow of expressway is constructed.We analyze the factors affecting the efficiency of vehicle on expressway,and define the relevant input and output indicators of driver and passenger respectively.According to the simulation results of the established cellular automata model,the carrying efficiency of participating vehicle under the maximum speed limit of three kinds of expressway is calculated by data envelopment analysis.The results show that the maximum speed limit on the road ranges from v_max=4cells/s to v_max=5cells/s and then to v_max=6cells/s,compared with normal vehicles,the cumulative vehicle carrying efficiency stimulated by the driver characteristic is increased by 1.6%,1.8%and 2.1%respectively.The driver characteristics have limited improvement on the overall vehicle carrying efficiency,and ensuring the smooth driving process is more conducive to improving the overall vehicle carrying efficiency.