{"title":"Journey-Based Transit Equity Analysis: A Case Study in the Greater Boston Area","authors":"Daniela Shuman, Xiaotong Guo, Nicholas S. Caros","doi":"arxiv-2408.01888","DOIUrl":null,"url":null,"abstract":"In this paper, a new methodology, journey-based equity analysis, is presented\nfor measuring the equity of transit convenience between income groups. Two data\nsources are combined in the proposed transit equity analysis: on-board\nridership surveys and passenger origin-destination data. The spatial unit of\nour proposed transit equity analysis is census blocks, which are relatively\nstable over time and allows an exploration of the data that is granular enough\nto make conclusions about the service convenience various communities are\nfacing. A case study in the Greater Boston area using real data from the\nMassachusetts Bay Transportation Authority (MBTA) bus network demonstrates a\nsignificant difference in transit service convenience, measured by number of\ntransfers per unit distance, transfer wait time and travel time per unit\ndistance, between low-income riders and high income riders. Implications of\nanalysis results to transit agencies are also discussed.","PeriodicalId":501172,"journal":{"name":"arXiv - STAT - Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.01888","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a new methodology, journey-based equity analysis, is presented
for measuring the equity of transit convenience between income groups. Two data
sources are combined in the proposed transit equity analysis: on-board
ridership surveys and passenger origin-destination data. The spatial unit of
our proposed transit equity analysis is census blocks, which are relatively
stable over time and allows an exploration of the data that is granular enough
to make conclusions about the service convenience various communities are
facing. A case study in the Greater Boston area using real data from the
Massachusetts Bay Transportation Authority (MBTA) bus network demonstrates a
significant difference in transit service convenience, measured by number of
transfers per unit distance, transfer wait time and travel time per unit
distance, between low-income riders and high income riders. Implications of
analysis results to transit agencies are also discussed.