Leading Cruise Control in Mixed Traffic Flow: System Modeling, Controllability, and String Stability

• Published in: IEEE transactions on intelligent transportation systems Vol. 23; no. 8; pp. 12861 - 12876
• Main Authors: Wang, Jiawei, Zheng, Yang, Chen, Chaoyi, Xu, Qing, Li, Keqiang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Car following; Connected and autonomous vehicle; Control stability; Controllability; Cruise control; Driving conditions; Dynamic models; Flow stability; Longitudinal control; mixed traffic flow; Numerical stability; Observability; Observability (systems); Perturbation; Perturbation methods; Road transportation; Stability analysis; string stability; Strings; Topology; Traffic control; Traffic flow; Traffic models; Transportation systems; Upstream; Vehicle dynamics
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2021.3118021

Connected and autonomous vehicles (CAVs) have great potential to improve road transportation systems. Most existing strategies for CAVs' longitudinal control focus on downstream traffic conditions, but neglect the impact of CAVs' behaviors on upstream traffic flow. In this paper, we introduce a notion of Leading Cruise Control (LCC), in which the CAV maintains car-following operations adapting to the states of its preceding vehicles, and also aims to lead the motion of its following vehicles. Specifically, by controlling the CAV, LCC aims to attenuate downstream traffic perturbations and smooth upstream traffic flow actively. We first present the dynamical modeling of LCC, with a focus on three fundamental scenarios: car-following, free-driving, and Connected Cruise Control. Then, the analysis of controllability, observability, and head-to-tail string stability reveals the feasibility and potential of LCC in improving mixed traffic flow performance. Extensive numerical studies validate that the capability of CAVs in dissipating traffic perturbations is further strengthened when incorporating the information of the vehicles behind into the CAVs' control.