String Stability and Platoon Safety Analysis of a New Car-Following Model Considering a Stabilization Strategy

Mingfei Mu,Changmiao Wang,Can Yang,Junjie Zhang,Jun Zhang

doi:10.1109/access.2021.3102655

Abstract

Adaptive cruise control (ACC) systems can reduce collision risk and make traffic flow more smoothly; nevertheless, improving the string stability and car-following safety in ACC systems has remained an important research topic. Based on the desired safety margin (DSM) model adopted as an ACC velocity control method, a sliding mode controller is proposed to investigate string stability and car-following safety using the time headway policy (THP), and its stability is verified by the Lyapunov stability theory. Furthermore, numerical simulations are conducted to verify the effectiveness of the proposed stabilization strategy for the stability of the DSM model. Analyzing the risk assessment indexes (time-to-collision, TTC, and time headway, TH) of the DSM model reveals that the proposed stabilization strategy can improve the traffic flow stability and avoid rear-end collision risks when the leading car exhibits a small disturbance. Therefore, the proposed stabilization strategy is valuable for designing ACC controllers to enhance traffic flow stability and car-following safety in automotive platoon driving.

Highlights

Traffic congestion and safety problems have been increasingly threatening environmental and economic development in modern society
Swaroop et al [40] presented a comparative study of time headway policy and spacing for automatic control vehicles, and the results show that spacing control is a very attractive method without requiring intervehicle communication for autonomous intelligent cruise control systems
In this study, the desired safety margin (DSM) model was used as an adaptive cruise control (ACC) control strategy for a rear-end avoidance system

Summary

Introduction

Traffic congestion and safety problems have been increasingly threatening environmental and economic development in modern society. Humans play a key role in transportation systems because they are the participants, handlers, controllers, and decision makers of all driving behaviors that significantly influence roadway performance and traffic safety [1, 2]. Traffic flow stability and the reduction in collision risk should be improved. Intelligent transportation systems (ITSs) and vehicle-to-vehicle (V2V) communication can detect potential risk situations, thereby avoiding collisions and improving vehicle control performance [3]. ACC systems have been widely installed in vehicles to improve string stability and platoon (carfollowing) safety [4,5,6], and the system mainly comprises information collection equipment, vehicle longitudinal dynamic models (one of the core parts), and human machine interactive systems. The nonlinear longitudinal dynamic model was proposed by Lu et al [10], and includes road resistance, gravity, aerodynamic drag, and other influencing factors

Methods

Discussion

Conclusion