Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach

While public transportation has seen improvement over time with advancements in vehicle technology and urban planning, low-income populations do not see the full benefit of these advancements. The common approach to transportation planning is to distribute benefits in the most cost-efficient manner,...

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Main Author: Rajagopal, Kirsi K.
Other Authors: Botterud, Audun
Format: Thesis
Published: Massachusetts Institute of Technology 2024
Online Access:https://hdl.handle.net/1721.1/156770
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author Rajagopal, Kirsi K.
author2 Botterud, Audun
author_facet Botterud, Audun
Rajagopal, Kirsi K.
author_sort Rajagopal, Kirsi K.
collection MIT
description While public transportation has seen improvement over time with advancements in vehicle technology and urban planning, low-income populations do not see the full benefit of these advancements. The common approach to transportation planning is to distribute benefits in the most cost-efficient manner, meaning neighborhoods with the best existing infrastructure are likely to receive more timely benefits than low-income areas that require more costly updates. This disparity can be thought of as a lack of equity in transportation planning, where equity means that the population that needs a public service the most should benefit the most from improvement of that service. This work focuses on improving equity within the proposed electrification of the Massachusetts Bay Transportation Authority (MBTA) bus network in Boston. We are interested in which routes should receive updates first to maximize equity, while understanding that focusing on equity poses an inherent cost trade-off. To solve this problem, an optimal subset of routes must be selected for electrification using an objective function that prioritizes routes with the lowest income riders and the highest levels of pollution from diesel buses. Assuming an optimal cost structure for the full transition to battery-electric buses, and also assuming that not all depots and routes will be electrified on the same time scale, we use Mixed Integer Linear Programming (MILP) methods and a quantification of transportation equity in various objective functions to decide which bus routes originating from the Cabot depot should be prioritized for electrification benefits from an equity standpoint. We then analyze the sensitivity of our results to changes in the cost constraint and conclude the degree to which equity factors correspond to higher energy transition costs. The results show that high-pollution routes are less attractive from a cost standpoint than low-income ridership routes. It is also shown that a given percentage of total electrification costs can electrify a subset of routes with even larger percentages of total pollution and low-income ridership, meaning that the benefits of including equity factors are high for given cost levels in our problem scope.
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spelling mit-1721.1/1567702024-09-17T04:08:26Z Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach Rajagopal, Kirsi K. Botterud, Audun Veeramachaneni, Kalyan Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science While public transportation has seen improvement over time with advancements in vehicle technology and urban planning, low-income populations do not see the full benefit of these advancements. The common approach to transportation planning is to distribute benefits in the most cost-efficient manner, meaning neighborhoods with the best existing infrastructure are likely to receive more timely benefits than low-income areas that require more costly updates. This disparity can be thought of as a lack of equity in transportation planning, where equity means that the population that needs a public service the most should benefit the most from improvement of that service. This work focuses on improving equity within the proposed electrification of the Massachusetts Bay Transportation Authority (MBTA) bus network in Boston. We are interested in which routes should receive updates first to maximize equity, while understanding that focusing on equity poses an inherent cost trade-off. To solve this problem, an optimal subset of routes must be selected for electrification using an objective function that prioritizes routes with the lowest income riders and the highest levels of pollution from diesel buses. Assuming an optimal cost structure for the full transition to battery-electric buses, and also assuming that not all depots and routes will be electrified on the same time scale, we use Mixed Integer Linear Programming (MILP) methods and a quantification of transportation equity in various objective functions to decide which bus routes originating from the Cabot depot should be prioritized for electrification benefits from an equity standpoint. We then analyze the sensitivity of our results to changes in the cost constraint and conclude the degree to which equity factors correspond to higher energy transition costs. The results show that high-pollution routes are less attractive from a cost standpoint than low-income ridership routes. It is also shown that a given percentage of total electrification costs can electrify a subset of routes with even larger percentages of total pollution and low-income ridership, meaning that the benefits of including equity factors are high for given cost levels in our problem scope. MNG 2024-09-16T13:48:06Z 2024-09-16T13:48:06Z 2024-05 2024-07-11T14:37:04.428Z Thesis https://hdl.handle.net/1721.1/156770 Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) Copyright retained by author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Massachusetts Institute of Technology
spellingShingle Rajagopal, Kirsi K.
Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach
title Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach
title_full Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach
title_fullStr Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach
title_full_unstemmed Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach
title_short Equitable Bus Route Electrification Based on a Mixed Integer Linear Programming Approach
title_sort equitable bus route electrification based on a mixed integer linear programming approach
url https://hdl.handle.net/1721.1/156770
work_keys_str_mv AT rajagopalkirsik equitablebusrouteelectrificationbasedonamixedintegerlinearprogrammingapproach