Most of the existing traffic simulation packages require significant calibration work to be able to reflect reality. To evaluate special operations including emerging technologies, a microscopic simulation that tracks detailed interactions of all the elements of the traffic systems is usually needed. This type of simulation is usually computationally demanding. This work developed an Airport Shuttle Planning and Improved Routing Event-driven Simulation (ASPIRES) package to simulate and evaluate current, potential, and future airport shuttle operations. The simulation was driven by data and thus did not require much calibration effort. The discrete-event simulation nature of ASPIRES makes the simulation computationally efficient. Simulating 1 day of shuttle operations takes less than 2 s. The study site of this work is the Dallas/Fort Worth International Airport in the U.S. The shuttle service that connects the five terminals of the airport and the rental car center was studied. Travel times, dwell times, and passenger arrivals were simulated using empirical distributions derived mainly from real data to capture the stochastic nature of the rental car center shuttle bus operations. Data on bus miles traveled, bus energy consumption, passenger wait times, and passengers left behind at stops were collected to study the trade-off between energy use and passenger experience. Electric bus and on-demand bus operations were also included. The simulation outputs can show passengers statistics at terminals, shuttles statistics, and charging station statistics. ASPIRES cannot be used to model a generic traffic system but is well-suited for fleet systems.


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    Title :

    ASPIRES: Airport Shuttle Planning and Improved Routing Event-driven Simulation


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2022-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English