Study On CACC Vehicle Following Model Considering The Influence Of Multiple Leading Vehicles And The Characteristics Of Mixed Traffic Flow

Thanks to the continuous development of China’s economy,people’s economic level has also been improved,more and more families choose to buy cars for travel,and the per capita vehicle ownership keeps rising,which is also an important factor leading to the constant occurrence of traffic congestion and traffic accidents.In the past,new roads and road reconstruction were considered to be the core methods to solve traffic problems.Due to the limitation of land area and construction cost,it is difficult to solve the more and more serious traffic problems by relying only on new transportation facilities.Since the beginning of the 21 st century,automatic driving technology has been continuously developed and popularized,some theories have been realized and commercialized,and intelligent network technology has also emerged,making automatic driving vehicles equipped with ACC system and intelligent network vehicles using CACC system gradually enter people’s attention.Intelligent networked vehicles remove the impact of "human" factors on traffic,avoid traffic incidents caused by drivers’ personality and physiological problems,and can respond more accurately and quickly to traffic environment changes,which is an effective way to solve traffic congestion,traffic accidents and other problems.First of all,this paper introduces the development and research status of autonomous driving technology and intelligent network technology in detail,analyzes the working principle and following behavior of ACC vehicles and CACC vehicles that already exist in real cars.Meanwhile,it analyzes the working logic of manually driven vehicles operated by drivers,and finds that the following behavior of vehicles is greatly affected by uncontrollable factors such as driver characteristics.Cannot be directly used to accurately describe the following behavior of an autonomous vehicle.Then,this paper analyzes the following behavior of CACC vehicles in mixed traffic flow,and points out the degradation phenomenon of CACC vehicles.Based on GM linear following model,intelligent driver model,ACC vehicle and CACC vehicle following model calibrated by PATH Laboratory of University of California,Berkeley using real vehicle data,and considering the influence of multiple vehicles on CACC vehicles,an improved CACC vehicle following model considering the influence of multiple vehicles is proposed.Then,using the NGSIM data set,this paper uses the least square method and genetic algorithm to calibrate the parameters of the model after cleaning and filtering the data.By using SUMO software for simulation,it is found that the improved vehicle following model can ensure the stability of the traffic system,and compared with the CACC vehicle following model of PATH laboratory,the improved CACC vehicle following model avoids the situation of increasing speed fluctuations and gradually dissipates the traffic disturbance.Therefore,it is considered that the improved CACC vehicle following model is more stable than the CACC vehicle following model of PATH laboratory.Finally,this paper sets a simulation scenario for mixed traffic flow,and compares the performance of HDV,ACC vehicles and CACC vehicles using the improved CACC vehicle following model in mixed traffic flow.The results show that CACC vehicles perform slightly better than HDV and ACC vehicles under the two conditions of acceleration at start and deceleration at brake.This advantage can be reflected back to mixed traffic flow.However,when CACC vehicles form a team,CACC vehicles show a better response effect,and can make mixed traffic flow reach a stable operation state in a shorter time,and effectively inhibit the transmission of traffic disturbance in the face of accidents.It is believed that the mixture of CACC vehicles can improve traffic flow capacity and increase traffic stability.Ensure traffic safety.