@article{dresner08a,
  author =	 {Kurt Dresner and Peter Stone},
  title =	 {A multiagent approach to autonomous intersection
                  management},
  journal =	 {Journal of Artificial Intelligence Research},
  volume =	 31,
  number =	 1,
  year =	 2008,
  issn =	 {1076-9757},
  pages =	 {591--656},
  abstract =	 {Artificial intelligence research is ushering in a
                  new era of sophisticated, mass-market transportation
                  technology. While computers can already fly a
                  passenger jet better than a trained human pilot,
                  people are still faced with the dangerous yet
                  tedious task of driving automobiles. Intelligent
                  Transportation Systems (ITS) is the field that
                  focuses on integrating information technology with
                  vehicles and transportation infrastructure to make
                  transportation safer, cheaper, and more
                  efficient. Recent advances in ITS point to a future
                  in which vehicles themselves handle the vast
                  majority of the driving task. Once autonomous
                  vehicles become popular, autonomous interactions
                  amongst multiple vehicles will be possible. Current
                  methods of vehicle coordination, which are all
                  designed to work with human drivers, will be
                  outdated. The bottleneck for roadway efficiency will
                  no longer be the drivers, but rather the mechanism
                  by which those drivers’ actions are
                  coordinated. While open-road driving is a
                  well-studied and more-or-less-solved problem, urban
                  traffic scenarios, especially intersections, are
                  much more challenging. We believe current methods
                  for controlling traffic, specifically at
                  intersections, will not be able to take advantage of
                  the increased sensitivity and precision of
                  autonomous vehicles as compared to human drivers. In
                  this article, we suggest an alternative mechanism
                  for coordinating the movement of autonomous vehicles
                  through intersections. Drivers and intersections in
                  this mechanism are treated as autonomous agents in a
                  multiagent system. In this multiagent system,
                  intersections use a new reservation-based approach
                  built around a detailed communication protocol,
                  which we also present. We demonstrate in simulation
                  that our new mechanism has the potential to
                  significantly outperform current intersection
                  control technology—traffic lights and stop
                  signs. Because our mechanism can emulate a traffic
                  light or stop sign, it subsumes the most popular
                  current methods of intersection control. This
                  article also presents two extensions to the
                  mechanism. The first extension allows the system to
                  control human-driven vehicles in addition to
                  autonomous vehicles. The second gives priority to
                  emergency vehicles without significant cost to
                  civilian vehicles. The mechanism, including both
                  extensions, is implemented and tested in simulation,
                  and we present experimental results that strongly
                  attest to the efficacy of this
                  approach. 1. Introduction Few concepts, if any,
                  embody the goals and aspirations of artificial
                  intelligence as well as fully autonomous
                  robots. Countless films and stories have been made
                  that focus on a future filled with such humanoid
                  agents which, when not violently overthrowing their
                  human masters, run errands, complete menial tasks,
                  or perform duties that would be too difficult or
                  dangerous for humans. However, machines that sense,
                  think about, and take actions in the real world
                  around us are no longer just the stuff of science
                  fiction and fantasy.},
  cluster = 	 {7764924480122123386},
  url = 	 {http://jmvidal.cse.sc.edu/library/dresner08a.pdf},
}