Liu, Xuekai (Tongji University), Chen, Qian (Tongji University), Hang, Peng (Tongji University), Lu, Xiong (Tongji Unviersity), Sun, Jian (Tongji University)

A Self-Organizing Cooperative Control Framework for Connected Automated Vehicles at Unsignalized Roundabouts

Scheduled for presentation during the Invited Session "Cooperative Driving Technology for Connected Automated Vehicles" (WeAT10), Wednesday, September 25, 2024, 10:50−11:10, Salon 18

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on December 26, 2024

Abstract

Due to the huge traffic flow and complex weaving, unsignalized roundabout is one of the most challenging scenarios for autonomous driving. Though cooperative autonomous driving has the potential to address this challenge, solving the multi-vehicle cooperation problem usually can't meet the real-time requirement. To efficiently solve this problem, this paper proposes a self-organizing cooperative control framework considering both ``whom to cooperate with" and ``how to cooperate". At the high level, based on the self-organization theory and traffic safety theory, a finite state machine (FSM) is designed for connected automated vehicles (CAVs) to switch states, which reduce the size of the multi-vehicle cooperation problem by selecting allies and forming organizations real-time. At the low level, to solve the multi-vehicle cooperation problem, model predictive control (MPC) is used to minimize an objective function related to safety, efficiency and comfort of CAVs. Finally, simulations and micro-vehicle experiment are conducted to verify the effectiveness of the proposed method. The result demonstrates the superiority of the method in decreasing calculation time and enhancing traffic safety by comparing with an existing benchmark.