In the research, the applicability of autonomous intelligent agents are investigated in Urban Traffic Control (UTC), and why these Artificial Intelligent strategies are useful. Designing, implementing, optimising and adjusting UTC systems involves quite some effort and knowledge. A system is proposed that autonomously can adapt to changing environments. The main advantages from the Artificial Intelligent Agents (ALA) are: (1) Self adjustability is an integral part of ALA based traffic control unit, (both long (road works) and short term (accidents) changes are covered); and (2) The more flexible, traffic control unit can be optimised while the unit is operating. For self-evaluation, -optimising and -adjusting UTC we need a fully pro-active, real-time traffic control system. Such a UTC system requires monitoring system of traffic, a rule or model base for evaluation and adjustment, a model of the surrounds and an efficient diagnostic routine for both traffic light operations as well as rule and parameter adjustments. A computer model is used to get insight into the technical and functional applicability of autonomous UTC. The UTC model system is based on several intersection traffic signalling agents (TSA) and some authority agents. Agents will sometimes be required to work autonomously, but will often be commanded or influenced by others. A TSA makes decisions based on goals, capability, knowledge, perception and traffic data. If necessary an agent can request for additional information or receive goals or orders from its authority agent. Our research shows that UTC systems based on agent technology can adapt and respond to traffic conditions in real-time and in the meantime making better use of the capacity of the intersection. In case of unsaturated intersections the strategy proves to be better than intersections with detectors. In saturated situations (degree of saturation >0.5) delays per vehicle on a single approach intersection could improve by 5% to 15%. For the covering abstract see ITRD E105068.

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  • Corporate Authors:

    PTRC Education and Research Services Limited

    Glenthorne House, Hammersmith Grove
    London W6OL9,   England 
  • Authors:
    • Roozemond, D A
  • Publication Date: 1999-9


  • English

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  • Accession Number: 00793723
  • Record Type: Publication
  • Source Agency: Transport Research Laboratory
  • ISBN: 0-86050-323-2
  • Files: ITRD
  • Created Date: Jun 15 2000 12:00AM