United States Department of Transportation
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Tracking the Energy and Emissions of MBTA Rapid Transit Vehicles
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2021-08-01
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[PDF-4.36 MB]
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Edition:Final Report - August 2021 [May 2020-August 2021]
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Abstract:Rapid transit systems are critical components of public transportation networks in urban areas, in terms of their impact on person mobility and on monetary, energy, and environmental costs associated with their operations. To facilitate effective planning for current and future needs, a framework is required that provides important consumption metrics and explains the various contributors to energy consumption and their interactions. This study presents a model that utilizes operational and ridership data for the Massachusetts Bay Transportation Authority's rapid transit system, as well as ambient temperature, to accurately predict system-wide electricity consumption. Linear regression and random forests were used to estimate energy consumption, which could explain a 0.93 and 0.95 variance in the data set, respectively. The model was trained with data from 2019 and tested with data from 2020. The linear regression model provided predictions with RMSE of 2.7 MWh and MAPE of 4.68%, and the random forest model resulted in a RMSE of 2.94 MWh and MAPE of 5.01%. These models are robust and perform well, even with the significant impacts to transit operations associated with the COVID-19 pandemic. This project also investigated COVID-19 impact on the whole system by exploring effects on ridership, energy consumption, cost, and train movement metrics, before and during the pandemic.
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