Simon J. Berrebi, Sanskruti Joshi, Kari E. Watkins
{"title":"Cross-checking automated passenger counts for ridership analysis","authors":"Simon J. Berrebi, Sanskruti Joshi, Kari E. Watkins","doi":"10.5038/2375-0901.23.2.5","DOIUrl":null,"url":null,"abstract":"<div><p>Due to concerns about data quality, Automated Passenger Counting technology has rarely been used to analyze local ridership trends. This paper presents a novel framework to test the consistency and completeness of automated passenger count (APC) data in four cities. Weekday APC data are aggregated at the system level and compared with the National Transit Database between 2012 and 2018. In all four agencies, passenger counts closely follow the fluctuations observed in the national transit database. There is, however, a slight drift in two of the four agencies, possibly due to the diverging trends between weekday and weekend ridership. At the stop-level, missing and duplicate vehicle-trips are identified using schedule data from the General Transit Feed Specification. Missing and duplicate trips only concern a small proportion of stops, which can be eliminated using the proposed method. Overall, this research leads the way towards the analysis of factors affecting ridership on a tight spatial and temporal scale.</p></div>","PeriodicalId":47173,"journal":{"name":"Journal of Public Transportation","volume":"24 ","pages":"Article 100008"},"PeriodicalIF":2.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1077291X2200008X/pdfft?md5=3982cf9e15db5f9c813e0a4cc146e576&pid=1-s2.0-S1077291X2200008X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Public Transportation","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1077291X2200008X","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Due to concerns about data quality, Automated Passenger Counting technology has rarely been used to analyze local ridership trends. This paper presents a novel framework to test the consistency and completeness of automated passenger count (APC) data in four cities. Weekday APC data are aggregated at the system level and compared with the National Transit Database between 2012 and 2018. In all four agencies, passenger counts closely follow the fluctuations observed in the national transit database. There is, however, a slight drift in two of the four agencies, possibly due to the diverging trends between weekday and weekend ridership. At the stop-level, missing and duplicate vehicle-trips are identified using schedule data from the General Transit Feed Specification. Missing and duplicate trips only concern a small proportion of stops, which can be eliminated using the proposed method. Overall, this research leads the way towards the analysis of factors affecting ridership on a tight spatial and temporal scale.
期刊介绍:
The Journal of Public Transportation, affiliated with the Center for Urban Transportation Research, is an international peer-reviewed open access journal focused on various forms of public transportation. It publishes original research from diverse academic disciplines, including engineering, economics, planning, and policy, emphasizing innovative solutions to transportation challenges. Content covers mobility services available to the general public, such as line-based services and shared fleets, offering insights beneficial to passengers, agencies, service providers, and communities.