@inproceedings{vasirani09a,
  author =	 {Vasirani, Matteo and Ossowski, Sascha},
  title =	 {A market-inspired approach to reservation-based
                  urban road traffic management},
  booktitle =	 {Proceedings of The 8th International Conference on
                  Autonomous Agents and Multiagent Systems},
  year =	 2009,
  isbn =	 {978-0-9817381-6-1},
  pages =	 {617--624},
  location =	 {Budapest, Hungary},
  publisher =	 {International Foundation for Autonomous Agents and
                  Multiagent Systems},
  address =	 {Richland, SC},
  abstract =	 {Urban road traffic management is an example of a
                  socially relevant problem that can be modelled as a
                  large-scale, open, distributed system, composed of
                  many autonomous interacting agents, which need to be
                  controlled in a decentralized manner. Most models
                  for urban road traffic management rely on control
                  elements that act on traffic flows. Dresner and
                  Stone have put forward the idea of an advanced urban
                  road traffic infrastructure that allows for cars to
                  individually reserve space and time at an
                  intersection so as to be able to safely cross it. In
                  this paper we extend Dresner and Stone's approach to
                  networks of intersections. For this purpose, we draw
                  upon market-inspired control methods as a paradigm
                  for urban road traffic management. We conceive the
                  system as a computational economy, where driver
                  agents trade with infrastructure agents in a virtual
                  marketplace, purchasing reservations to cross
                  intersections when commuting through the city. We
                  show that in situations of similar traffic load, an
                  increase of the infrastructure's monetary benefit
                  usually implies a decrease of the drivers' average
                  travel times.},
  cluster = 	 {10874315322717558310},
  url = 	 {http://jmvidal.cse.sc.edu/library/vasirani09a.pdf},
}