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2014 | 2 | 145--153
Tytuł artykułu

MITC: An Intention-Based Model for Cooperative Resolution of Traffic Conflicts

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Urban traffic problems have become a quotidian problem that affects many cities in the world. This problem, caused by the exponential increase of vehicles, leads to the appearance of different complications such as environmental pollution, accidents and slow mobility. This work formulates MITC, a model of cooperation focused to conflict resolution for the traffic agents, considering explicit communication of their intentions, allowing them to adjust their decisions intelligently, so as to reduce the conflicts and mitigate traffic congestion.(original abstract)
Rocznik
Tom
2
Strony
145--153
Opis fizyczny
Twórcy
  • Pontifical Javeriana University
  • Pontifical Javeriana University
Bibliografia
  • Adler J. L. and Blue V. J. A cooperative multi-agent transportation management and route guidance system. Transportation Research Part C-emerging Technologies, 10(5-6):433-454, October 2002.
  • Adler J. L., Satapathy G., Manikonda V., Bowles B., and Blue V. J.. A multi-agent approach to cooperative traffic management and route guidance. Transportation Research Part B-methodological, 39(4):297-318, May 2005.
  • Akiyama T. and Okushima M.. Advanced fuzzy traffic controller for urban expressways. International Journal of Innovative Computing Information and Control, 2(2):339-355, April 2006.
  • Balaji P. G., German X., and Srinivasan D.. Urban traffic signal control using reinforcement learning agents. Iet Intelligent Transport Systems, 4(3):177-188, September 2010.
  • Bielli M., Ambrosino G., and Boero M.. Artificial intelligence applications to traffic engineering. Vsp, 1994.
  • Burguillo-Rial J. C., Rodriguez-Hernandez P. S., CostaMontenegro E., and Gil-Castineira F. History-based selforganizing traffic lights. Computing and Informatics, 28(2):157-168, 2009.
  • Chen B. and Cheng H. H.. A review of the applications of agent technology in traffic and transportation systems. Ieee Transactions On Intelligent Transportation Systems, 11(2):485-497, June 2010.
  • Chen R. S., Chen D. K., and Lin S. Y.. Actam: Cooperative multi-agent system architecture for urban traffic signal control. Ieice Transactions On Information and Systems, E88D(1):119-126, January 2005.
  • Choy M. C., Srinivasan D., and Cheu R. L.. Cooperative, hybrid agent architecture for real-time traffic signal control. Ieee Transactions On Systems Man and Cybernetics Part A-systems and Humans, 33(5):597-607, September 2003.
  • Fernandes R. A BDI-based approach for assessment of drivers decision-making in commuter. PhD thesis, Universidade Federal Do Rio Grande Do Sul, nov 2002.
  • Gonzales E. and Bustacara C. Desarrollo de Aplicaciones Basadas en Sistemas Multiagentes. 2007.
  • Hernandez J. Z., Ossowski S., and Garcia-Serrano A. Multiagent architectures for intelligent traffic management systems. Transportation Research Part C-emerging Technologies, 10(5-6):473-506, October 2002.
  • Hillenbrand J., Spieker A. M., and Kroschel K. A multilevel collision mitigation approach - its situation as sessment, decision making, and performance tradeoffs. Ieee Transactions On Intelligent Transportation Systems, 7(4):528-540, December 2006.
  • Ma T. and Abdulhai B. Genetic algorithm-based optimization approach and generic tool for calibrating traffic microscopic simulation parameters. Intelligent Transportation Systems and Vehicle-highway Automation 2002: Highway Operations, Capacity, and Traffic Control, (1800):6-15, 2002.
  • Srinivasan D., Choy M. C., and Cheu R.L. Neural networks for real-time traffic signal control. Ieee Transactions On Intelligent Transportation Systems, 7(3):261-272, September 2006.
  • Yin H. B., Wong S. C., Xu J. M., and Wong C. K.. Urban traffic flow prediction using a fuzzy-neural approach rid a-7258-2008. Transportation Research Part C-emerging Technologies, 10(2):85-98, April 2002.
  • Zhang N., Wang F. Y., Zhu F. H., Zhao D. B., and Tang S. M.. Dynacas: Computational experiments and decision support for its. Ieee Intelligent Systems, 23(6):19-23, November 2008.
  • Zhao D., Dai Y., and Zhang Z. Computational intelligence in urban traffic signal control: A survey. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, PP(99):1 -10, 2011
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171325043

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