Transportation systems are becoming increasingly complex with the evolution of emerging technologies, including deeper connectivity and automation, which will require more advanced control mechanisms for efficient operation (in terms of energy, mobility, and productivity). Stakeholders, including government agencies, industry, and local populations, all have an interest in efficient outcomes, yet there are few tools for developing a holistic understanding of urban dynamics. Simulating large-scale, high-fidelity transportation systems can help, but remains a challenging task, due to the computational demand of processing massive numbers of events and the nonlinear interactions between system components and traveling agents. In this paper, we introduce Mobiliti, a proof-of-concept, scalable transportation system simulator that implements parallel discrete event simulation on high-performance computers. We instantiated millions of nodes, links, and agents to simulate the movement of the population through the San Francisco Bay Area road network and provide estimates of the associated congestion, energy usage, and productivity loss. Our preliminary results show excellent scalability on multiple compute nodes for statically-routed agents, simulating 9.5 million trip legs over a road network with 1.1 million nodes and 2.2 million links, processing 2.4 billion events in less than 30 seconds using 1,024 cores on NERSC's Cori computer.


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    Title :

    Mobiliti: Scalable Transportation Simulation Using High-Performance Parallel Computing


    Contributors:
    Chan, Cy (author) / Wang, Bin (author) / Bachan, John (author) / Macfarlane, Jane (author)


    Publication date :

    2018-11-01


    Size :

    1536315 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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