Research On The Model Of Motion State For Mixed Traffic Flow Based On The Safety Potential Field

Connected and automated vehicles(CAVs)environment is a new intelligent transportation environment integrating automobile,electronics,information communication,road transportation and other industries.At present,connected and automated transportation,which focuses on the coordinated development of people,vehicles,roads,and clouds,has ushered in a golden age of development under the guidance of the ‘building China's strength in transportation' strategy.Before the full deployment of the CAVs,the road traffic flow will be composed of CAVs and human-driving vehicles(HVs).How to analyze the impact of this mixed traffic group on road traffic,explore the construction of a new traffic flow model,and analyze the evolution of the movement of the mixed traffic group has become a key issue that needs to be resolved at this stage.To this end,based on the background of connected and automated vehicles environment,relevant research work has been carried out on the movement situation model of the mixed traffic flow composed of new mixed traffic groups in this thesis,which was supported by the National Key R&D Program in China(Grant No.2018YFB1600600).The research results are of great significance for improving the theory of mixed traffic flow and promoting the rapid development of technologies such as vehicle-road coordination,autonomous driving,and intelligent networking.The main research content and conclusions of the thesis can be summarized into the following parts:(1)For the movement behavior characteristics of mixed traffic groups,this thesis reviews the development of connected and automated transportation systems and analyzes the architecture of connected and automated transportation systems.Starting from the characteristics of the movement behavior of the mixed traffic group,the definition of the composition of the mixed traffic group is proposed,and the movement characteristics of different types of vehicles in the mixed traffic group are summarized.(2)For the road traffic safety movement state representation method,this paper constructs a dynamic safety potential field model that can characterize the vehicle movement state based on the movement characteristics of the mixed traffic group.The model integrates vehicle microscopic motion parameters such as speed,acceleration,and steering angle,and can dynamically represent the safety risk distribution of the vehicle in different motion states.Based on this model,a new quantitative index PFI for vehicle safety risks in complex traffic environments is proposed,and a road traffic safety characterization method based on safety potential field theory is proposed,and then the vehicle movement situation in the connected and automated environment is dynamically described from the perspective of safety.Compared with the traditional TTC and other indicators,the constructed new road safety risk index PFI can more accurately assess the road traffic safety risk in the connected and automated environment.(3)For the micro-behavior characterization model of mixed traffic flow in the connected and automated environment,this paper combines the degree of information received by different types of vehicles and their respective safety potential field distributions to construct a micro car-following model SPFM of vehicle motion in the connected and automated environment,and a calibration method of model parameters is proposed.The model can accurately describe the car-following behavior of vehicles in a connected and automated environment.In addition,the changing laws of various motion characteristics in the mixed traffic flow during the transition of the motion state are studied,and the microscopic traffic flow lane changing model is established according to the spatial distribution of the safety potential field in the complex traffic environment.The model can dynamically express the change of the critical safety distance between vehicles during the lane change process according to the different motion states of the vehicles.(4)For the macroscopic evolution model of mixed traffic flow in the connected and automated environment,the macro traffic flow model conforming to the characteristics of the mixed traffic group is derived from the correlation between the macro and micro models of traffic flow.This model realizes a unified representation of the movement situation of different types of vehicles.Based on simulation experiments,the potential of different connected and automated vehicle penetration rates to improve road traffic capacity is analyzed.It is found that when the market penetration rate of connected and automated vehicles is low,it is necessary to combine some effective active control measures to improve road traffic flow.(5)For the optimal control method of the vehicle platoon in the connected and automated environment,this paper uses the proposed safe potential field model and the mixed traffic flow model based on the safe potential field theory to study the control method of the intermediate vehicle platoon in the connected and automated environment.Combining the theory of safe potential field and graph theory,constructing different information topological structures between connected and automated vehicles,and combining different types of safe potential fields to construct a vehicle platoon formation control strategy.This strategy can make vehicles distributed in different lanes continuously adjust their positions and quickly complete the task of vehicle platoon formation.At the same time,combining the safety potential field theory with the MPC control framework,an optimized control strategy for the maintenance of connected and automated platoon is proposed,which realizes the optimization of multiple traffic performance indicators(safety,efficiency,energy saving)of the connected and automated platoon.