Open AccessFormation control for connected and automated vehicles on multi‐lane roads: Relative motion planning and conflict resolution
Author(s) -
Cai Mengchi,
Xu Qing,
Chen Chaoyi,
Wang Jiawei,
Li Keqiang,
Wang Jianqiang,
Zhu Qianying
Publication year - 2023
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/itr2.12249
Subject(s) - bottleneck , process (computing) , collision , control (management) , trajectory , computer science , motion planning , simulation , real time computing , control theory (sociology) , artificial intelligence , robot , physics , computer security , astronomy , embedded system , operating system
Abstract Existing research has revealed that multi‐vehicle coordinated decision making and control can achieve an improvement in both traffic efficiency and driving safety. In the multi‐lane scenarios, a typical coordination method is multi‐vehicle formation control. The existing formation control methods predefine the formation switching process and have not considered or explained the collision‐free behaviour of vehicles in detail. In this paper, a multi‐lane formation control strategy for connected and automated vehicles (CAVs) is proposed. The planning framework is bi‐level, which can switch the structure of multi‐vehicle formation in different scenarios smoothly and effectively. In the upper‐level, the relative coordinate system is built to plan the collision‐free relative paths for vehicles. In the lower‐level, multi‐stage trajectory planning and tracking are modelled as an optimal control problem with path constraints. The case study verifies the function of the formation control method in three lane‐number‐changing scenarios. Large‐scale simulations in the lane‐drop bottleneck scenario are conducted under different input traffic volumes, and the numerical results indicate that the proposed formation control method reduces congestion and improves both traffic efficiency and fuel economy at high traffic volumes.