Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Knowledge-Based System for Controlling Automobile Traffic


    Contributors:
    A. Maravas (author) / R. F. Stengel (author)

    Publication date :

    1994


    Size :

    9 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




    A knowledge-based system for controlling automobile traffic

    Maravas, Alexander / Stengel, Robert F. | NTRS | 1994


    A Knowledge-Based System for Controlling Automobile Traffic

    United States / National Aeronautics and Space Administration | British Library Conference Proceedings | 1995


    Intelligent system for reliable monitoring and controlling of automobile traffic

    Denis, Yurchenko / Ruslan, Zarovsky / Andrey, Radchenko et al. | IEEE | 2018


    Intelligent automobile traffic system

    ZHAN KESHAN | European Patent Office | 2020

    Free access

    METHOD FOR CONTROLLING AUTOMOBILE AND AUTOMOBILE SYSTEM

    HAMADA TAKASHI / NISHIJO YUMA / KOJIMA KOUICHI et al. | European Patent Office | 2022

    Free access