Title
Stop-Free Strategies for Traffic Networks: Decentralized On-line Optimization.
Abstract
Traffic management in large networks remains an important challenge in transportation systems. The best approach would be to use existing infrastructure and find a solution to manage the increasing flows of vehicles. Multi-agent systems and autonomous vehicles are today considered as a promising approach to deal with traffic control. In this paper, we propose a two-level decentralized multi-agent system which allows autonomous vehicles crossing the network intersections without stopping. At the first level, we use a control agent at each intersection which (1) lets the vehicles from each road pass alternately, and (2) allows them to optimally regulate their speed in its vicinity. At the second level, each agent coordinates with its neighboring agents in order to optimize the flows inside the network. We evaluate this approach empirically, with a comparison with a more opportunistic First-Come First-Served strategy. Experimental results (in simulation) are presented (measuring energy consumption), showing the advantages and disadvantages of each approach.
Year
DOI
Venue
2014
10.3233/978-1-61499-419-0-1191
Frontiers in Artificial Intelligence and Applications
Field
DocType
Volume
Mathematical optimization,Large networks,Computer science,Simulation,Energy consumption,Distributed computing
Conference
263
ISSN
Citations 
PageRank 
0922-6389
3
0.41
References 
Authors
6
3
Name
Order
Citations
PageRank
Mohamed Tlig130.75
Olivier Buffet225826.77
Olivier Simonin 0001372.20