Researchers have attempted to compute a fuel-optimal vehicle trajectory by receiving traffic signal phasing and timing information. This problem, however, is complex when microscopic models are used to compute the objective function. This paper suggests use of a multi-stage dynamic programming tool that not only provides outputs that are closer to optimum, but are also computationally much faster. It uses a recursive trajectory generation that is similar to least-cost path-finding algorithms that optimizes the upstream profile while comparing discretized downstream cases. Since dynamic programming is faster than traditional computational methods, the algorithm can afford to use microscopic models and thereby be sensitive to a multitude of inputs such as grade, weather etc. Agent-based simulations suggest fuel savings in the range of 19 percent and travel-time savings of 32 percent in the vicinity of intersections. This research also showed potential benefits to vehicles following a vehicle that uses the proposed logic.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Multi-stage dynamic programming algorithm for eco-speed control at traffic signalized intersections


    Contributors:


    Publication date :

    2013-10-01


    Size :

    499912 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Traffic State Estimation near Signalized Intersections

    Maripini, Himabindu / Khadhir, Abdhul / Vanajakshi, Lelitha | ASCE | 2023


    Traffic capacity reduction at signalized intersections

    Lu, J. J. / Pernia, J. C. / Canadian Society for Civil Engineering | British Library Conference Proceedings | 2000



    Delay at Signalized Intersections under Mixed Traffic Conditions

    Saha, Arpita / Chandra, Satish / Ghosh, Indrajit | ASCE | 2017