A Decentralized Approach for Anticipatory Vehicle Routing Using Delegate Multiagent Systems
摘要:
Advanced vehicle guidance systems use real-time traffic information to route traffic and to avoid congestion. Unfortunately, these systems can only react upon the presence of traffic jams and not to prevent the creation of unnecessary congestion. Anticipatory vehicle routing is promising in that respect, because this approach allows directing vehicle routing by accounting for traffic forecast information. This paper presents a decentralized approach for anticipatory vehicle routing that is particularly useful in large-scale dynamic environments. The approach is based on delegate multiagent systems, i.e., an environment-centric coordination mechanism that is, in part, inspired by ant behavior. Antlike agents explore the environment on behalf of vehicles and detect a congestion forecast, allowing vehicles to reroute. The approach is explained in depth and is evaluated by comparison with three alternative routing strategies. The experiments are done in simulation of a real-world traffic environment. The experiments indicate a considerable performance gain compared with the most advanced strategy under test, i.e., a traffic-message-channel-based routing strategy.
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关键词:
Practical/ automated highways mobile agents multi-agent systems real-time systems road traffic road vehicles traffic engineering computing/ delegate multiagent system advanced vehicle guidance system real-time traffic information traffic routing traffic congestion traffic jam traffic forecast information decentralized approach anticipatory vehicle routing large-scale dynamic environment environment-centric coordination mechanism ant behavior antlike agent congestion forecast real-world traffic environment traffic-message-channel-based routing strategy intelligent vehicle mobile agent/ C7445 Traffic engineering computing C6190 Distributed systems software C6170 Expert systems and other AI software and techniques
DOI:
10.1109/TITS.2011.2105867
被引量:
年份:
2011







































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