Multiagent traffic management: a reservation-based intersection control mechanism

By Kurt M. Dresner, Peter Stone. Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004., 2004

706 citations recorded by the source corpus.

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.

Subfields: Building and Construction, Control and Systems Engineering, Transportation

View Paper: https://www.semanticscholar.org/paper/e1a13d19fbe42e72979f486d7dcc0f2aeeb19872

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Franziska Klügl-Frohnmeyer
2. Ana Lúcia Cetertich Bazzan
3. Trevor Scott Standley

In Control and Systems Engineering

1. Franziska Klügl-Frohnmeyer
2. Liviu Panait
3. Sean Luke
4. Ana Lúcia Cetertich Bazzan
5. Trevor Scott Standley

In Transportation

1. Franziska Klügl-Frohnmeyer
2. Liviu Panait
3. Sean Luke
4. Ana Lúcia Cetertich Bazzan
5. Trevor Scott Standley

Citations in the corpus

• Finding Optimal Solutions to Cooperative Pathfinding Problems (2010, background): “This seems to be the intuition behind most inadmissible algorithms developed up to this point (Silver 2005; Jansen and Sturtevant 2008b; Dresner and Stone 2004; Wang and Botea 2008).”
• A review on agent-based technology for traffic and transportation (2013, background): “That seminal approach by Dresner and Stone (2004) plus its extensions have inspired other authors (see next section); major challenges are to address the low-level issues related to both fine grained activities of the driving task, and how to cope with mixed traffic (human and autonomous vehicles).”
• Cooperative Multi-Agent Learning: The State of the Art (2005, background): “Stone and Veloso [255] argue that unrestricted communication reduces a multi-agent system to something isomorphic to a single-agent system.”
• Opportunities for multiagent systems and multiagent reinforcement learning in traffic control (2009, background): “The research presented in [26] has left as open questions: what happens if the driver has to make sudden changes; whether the AGV is really committed to the deceleration; what happens if conventional vehicles participate in the system as well; and what happens outside the look of the intersection ma”