Integrated simulation of activity-based demand and multi-modal dynamic supply for energy assessment

Siyu Chen, Isabel Hemerly Viegas de Lima, Zach Needell, Andrea Araldo, Arun Akkinepally, Jessica Trancik, Moshe Ben-Akiva, Nicholas Fournier, Aikaterini Deliali, Eleni Christofa, Carlos M. Lima Azevedo

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    The development of a large scale agent-based simulation model for the Greater Boston Area is presented, closing the gap between state-of-the art integrated demandsupply modeling techniques (SimMobility) with advanced energy estimation models (TripEnergy) and shedding light on its practical application to large urban areas. This paper describes the technical details of its three key components (activity-based demand, multi-modal dynamic supply, and trajectory-based energy models), the used data, the model estimation, integration and calibration processes. The proposed model can simulate any day with and without congestion in order to capture changes in energy use across all dimensions of a mobility system, namely temporal, spatial, modal or functional. For an average 24h in the Greater Boston Area the simulated travel of 4.5-million people resulted in 15-million trips and a total vehicle energy consumption of 548 thousand equivalent gallons of gasoline. Our proposed platform allows for the comprehensive and consistent assessment of energy related policies, technologies and services affecting traveler behavior, the transportation system’s and vehicle energy performances
    Original languageEnglish
    Title of host publicationProceedings of the 21st IEEE International Conference on Intelligent Transportation Systems
    Number of pages6
    Publication date2018
    Publication statusPublished - 2018
    Event21st International IEEE Conference on Intelligent Transportation Systems - Maui, Maui, United States
    Duration: 4 Nov 20187 Nov 2018
    Conference number: 21


    Conference21st International IEEE Conference on Intelligent Transportation Systems
    Country/TerritoryUnited States
    Internet address


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