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Bi-Objective Optimization for Battery Electric Bus Deployment Considering Cost and Environmental Equity

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Sustainable development of the transport system has been the consensus around the world for the past decades. Encouraged by the urgent need for cleaner alternatives to fossil fuels, vehicle electrification… Click to show full abstract

Sustainable development of the transport system has been the consensus around the world for the past decades. Encouraged by the urgent need for cleaner alternatives to fossil fuels, vehicle electrification has been advancing at an unprecedented pace. As a major component of the multimodal transportation system, public transit is at the forefront of adopting battery technology into its operation. Battery Electric Bus (BEB), with superior features such as zero-emission and reduced noise, is made ready for commercial deployment in the past several years. However, it is still a grand challenge to successfully deploy BEB system given the nature of the public transit system and the unique spatio-temporal characteristics of BEB. This research presents a bi-objective optimization model for BEB deployment to consider constraints unique to the BEB system and to address the trade-off between environmental equity for the disadvantaged population and capital investment. The model is further demonstrated using the transit system operated by the Utah Transit Authority (UTA) to offer insights on the benefits gained as a result of BEB deployment. Optimal deployment plans under different budgets are provided to illustrate the effectiveness of the model. The trade-offs in each of the plans are further discussed and compared. This research set the foundation for transit agencies to develop optimal deployment strategies for BEB systems when multiple goals need to be considered, allowing planners and decision-makers to create a transportation ecosystem that better serves livable and sustainable communities.

Keywords: system; battery electric; deployment; electric bus; transit

Journal Title: IEEE Transactions on Intelligent Transportation Systems
Year Published: 2021

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