Analysis Of Mixed Traffic Flow Characteristics And Energy Consumption Research In Intelligent And Connected Environment

With the rapid development of intelligent transportation system,the future road will be a mixture of traditional Human-driven vehicle and Connected and Autonomous vehicle(CAV).The existing research results showed that Connected and Autonomous vehicle can effectively reduce traffic congestion and provide new ideas for energy conservation and emission reduction.Therefore,this thesis studies the mixed traffic flow theory and discusses the influence of the addition of intelligent networked vehicles on the energy consumption of the fleet on the basis of analyzing the characteristics of the mixed traffic flow.The main contents of this thesis are as follows:Firstly,the following model of mixed traffic flow is established.Mixed traffic flow is composed of Connected and Autonomous vehicles and Human-driven vehicles.Based on the Intelligent Driver Model,Considering the different reaction times of four following modes(Connected and Autonomous vehicle following Human-driven vehicle,Connected and Autonomous vehicle following Connected and Autonomous vehicle,Human-driven vehicle following Human-driven vehicle,Human-driven vehicle following Connected and Autonomous vehicle)and the trust of Human-driven vehicle following Connected and Autonomous vehicle,the IDM model was improved and an IDM model based on reaction time and trust was established.And the basic diagram of mixed traffic flow is derived.Secondly,the characteristics of mixed traffic flow are analyzed.Based on the basic diagram model of mixed traffic flow established above,the mixed traffic flow is simulated and analyzed by Matlab.Based on the relationship diagram and space-time diagram among flow,velocity and density,the influence of the ratio of connected vehicles on the capacity of mixed traffic was analyzed.Through the analysis of congestion degree and stability,the influence of the proportion of intelligent networked vehicles on the congestion,stability,capacity and other aspects of mixed traffic flow is obtained.Then,the influence factors of energy consumption and acceleration characteristics of mixed traffic flow are analyzed.Based on the characteristic analysis of mixed traffic flow,it is concluded that intelligent networked vehicles can effectively relieve congestion under high density,which provides a solution to the problem of energy consumption.Since the acceleration fluctuations of vehicles directly affect the energy consumption of the fleet,based on the analysis of the influencing factors of energy consumption,the acceleration characteristics of mixed traffic flow with different proportions of Connected and Autonomous vehicle and different positions of Connected and Autonomous vehicle in the fleet were analyzed through SUMO.The relationship between the average deceleration of the fleet and the proportion of Connected and Autonomous vehicle is obtained from the acceleration fluctuation curve.The final braking time of the fleet under different conditions is analyzed to get the influence of the position distribution of Connected and Autonomous vehicle in the fleet on the stability of the fleet.The analysis results of this part lay a foundation for the subsequent research on the influence of intelligent connected car distribution on energy consumption.Finally,CarSim software is used to analyze the fuel consumption of mixed traffic flow.The vehicle speed and acceleration at every moment obtained in SUMO software are taken as input,and the vehicle fuel consumption results are output in Car Sim.According to the analysis of the fuel consumption results of the fleet,when the Connected and Autonomous vehicle are evenly distributed in the fleet,the fuel consumption of the vehicles will decrease with the increase of the proportion of Connected and Autonomous vehicle.In addition,under the same proportion of Connected and Autonomous vehicle,The fuel consumption of intelligent Internet-connected vehicles in uniform distribution is 0.3% higher than that of those in the front,the fuel consumption of intelligent Internet-connected vehicles in uniform distribution is 2.0% higher than that in the rear,and the fuel consumption of intelligent Internet-connected vehicles in uniform distribution is 1.7% higher than that in the front.Therefore,in the actual traffic,setting the Connected and Autonomous vehicle evenly distributed in the fleet and increasing the proportion of Connected and Autonomous vehicle can effectively alleviate the problem of high energy consumption.The research results provide ideas for the problem of high energy consumption,and have certain theoretical guiding significance and practical application value.