Traffic congestion is one of the leading causes of lost productivity and decreased standard of living in urban settings. Recent advances in artificial intelligence suggest vehicle navigation by autonomous agents will be possible in the near future. In this paper, we propose a reservation-based system for alleviating traffic congestion, specifically at intersections, and under the assumption that the cars are controlled by agents. First, we describe a custom simulator that we have created to measure the different delays associated with conducting traffic through an intersection. Second, we specify a precise metric for evaluating the quality of traffic control at an intersection. Using this simulator and this metric, we show that our reservation-based system can perform two to three hundred times better than traffic lights. As a result, it can smoothly handle much heavier traffic conditions. We show that our system very closely approximates an overpass, which is the optimal solution for the problem with which we are dealing.

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In The Third International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 530-537, July 2004.

@InProceedings{AAMAS04, title={Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism}, author={Kurt Dresner and Peter Stone}, booktitle={The Third International Joint Conference on Autonomous Agents and Multiagent Systems}, month={July}, pages={530-537}, url="http://www.cs.utexas.edu/users/ai-lab?AAMAS04", year={2004} }