Stop-Free Strategies for Traffic Networks: Decentralized On-line Optimization

Traffic management in large networks remains an important chal-lenge 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 con-trol. In this paper, we propose a two-level decentralized multi-agent system which allows autonomous vehicles crossing the network in-tersections 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 consump-tion), showing the advantages and disadvantages of each approach.