A Review on Simulation Platforms for Agent-Based Modeling in Electrified Transportation

Journal Article · 02 October 2023 · IEEE Transactions on Intelligent Transportation Systems

DOI: https://doi.org/10.1109/tits.2023.3318928 · OSTI ID:2212855

Harris, Donté  ^[1]; Silva, Felipe Da  ^[2]; Su, Wencong  ^[1]; Glatt, Ruben  ^[2]

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1. University of Michigan, Dearborn, MI (United States)
2. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

As the use of combustion engine vehicles plays a deciding role in global warming, we can observe a trend to replace them with electric vehicles (EV) driven by new environmentally conscious policies and increasing technological capabilities. With improvements in driving range and reduction in prices come new challenges that may hamper the progress towards complete battery driven transportation. A major challenge for the increasing EV adoption is the planning of extensions to existing infrastructure or the inclusion of new infrastructure components in the planning process. This demands increasingly complex planning tools that can simulate the interplay between different stakeholders in modern transportation scenarios such as EVs, charging stations, energy providers, and general transportation participants. Simulation platforms for agent-based modeling in transportation have been developed as effective interactive tools that allow planners to explore different trade-offs across different scenarios with the ability to simulate the impact of policy or infrastructure decisions on the different stakeholders in the simulation. This article surveys several of the major simulation platforms that include modern EV-based forms of transportation and allow the simulation of relevant infrastructure components alongside the well established transportation simulations. These tools allow researchers to analyze expected traffic flow, identify possible charging station locations based on area demand, predict electrical grid demand, and more. Here this survey intends to make it easier for researchers to identify and apply a simulation platform in the context of supporting the increasing electrification of the transportation sector, enabling more efficient simulation and planning capabilities in this domain.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: AC52-07NA27344
• OSTI ID: 2212855
• Report Number(s): LLNL-JRNL-837344; 1056276
• Journal Information: IEEE Transactions on Intelligent Transportation Systems, Vol. 25, Issue 2; ISSN 1524-9050
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English