Driver’s Lane Selection Model Based on Phase-Field Coupling and Multiplayer Dynamic Game with Incomplete Information

Xiaoyuan Wang,Yaqi Liu,Fang Wang,Chen Chen,Dong Kong,Liping Liu

doi:10.1155/2018/2145207

Abstract

Intelligent driving is an effective means to achieve the active safety of automobile, and the accurate prediction of vehicle group situation is the premise to achieve the intelligent driving of vehicle. Lane selection and lane changing are not only the most fundamental reasons for the transformation of vehicle group situation, but also the basic contents for the research on driver behavior of traffic flow theory. In this paper, with a view to the background of Internet of Things, the vehicle group situation was given a comprehensive consideration on the basis of the factors which influence driver’s behavior. The driver’s lane selection behavior was analyzed under the condition of incomplete information, and lane selection model based on phase-field coupling and multiplayer dynamic game with incomplete information was constructed considering the time-varying character of driving propensity. The means of actual driving experiment, virtual driving experiment, and microscopic simulation of traffic flow were used to verify the model. The verification results showed that the model built in this paper can objectively reflect the actual operation characteristic of traffic flow on road section and the process of lane selection. The theoretical basis of the research on lane selection can be provided for intelligent driving especially anthropomorphic driving under the condition of Internet of Things.

Highlights

With the rapid development of the transportation industry, the car ownership has increased rapidly
Lane changing is one of the main factors affecting traffic safety, and lane selection which need drivers to analyze all kinds of information and consider a variety of factors in an instant is an important premise for lane changing, and the rationality of lane selection is directly related to driving safety
Vehicle group situation in which driver can perceive in the interest-sensitive area, including the characteristics of traffic entity and vehicle group relationship and considering the macroscopic characteristics of density and speed, was taken as an example to research the driver’s lane selection behavior

Summary

Introduction

With the rapid development of the transportation industry, the car ownership has increased rapidly. The contradiction among people, vehicle, and environment has become increasingly conspicuous, and the traffic safety is becoming more and more serious. Lane changing is one of the main factors affecting traffic safety, and lane selection which need drivers to analyze all kinds of information and consider a variety of factors in an instant is an important premise for lane changing, and the rationality of lane selection is directly related to driving safety. The multisource information of peoplevehicle-environment can be collected and shared through Internet of Things, which can provide decision-making basis for driver’s lane selection process and improve the active safety of driver and vehicle. It is of great practical significance to deeply study the lane selection behavior under the condition of Internet of Things. The theoretical basis of the research on lane selection can be provided for intelligent driving, especially the anthropopathic driving

Methods

Results

Discussion

Conclusion