Next-generation traffic management systems will make use of on-board intelligence and communication capabilities of vehicles and traffic infrastructure. In this paper, we investigate a multiagent approach allowing vehicle agents to form groups in order to co-ordinate their speed and lane choices. Our hypothesis is that a decentralized approach based on a co-operative driving method can contribute to higher and smoother traffic flow, leading to higher speeds and less delays. Our focus is on automated vehicle decision models. We develop a group-oriented driving method with vehicle agents that perceive their environment and exchange information. The paper proposes decentralized dynamic vehicle grouping algorithm, a conflict detection and global coordination method, and defines individual driving strategies for vehicles. For validation, we compare our method with a driving method implemented in the commercial traffic simulation platform AIMSUN. Experimental results indicate that group formation and group coordination methods can improveme traffic network throughput.
