Cross-checking automated passenger counts for ridership analysis

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2022-01-01 DOI:10.5038/2375-0901.23.2.5
Simon J. Berrebi, Sanskruti Joshi, Kari E. Watkins
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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.

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交叉核对自动统计的客流量分析
由于对数据质量的担忧,自动乘客计数技术很少被用于分析当地的乘客趋势。本文提出了一个新的框架来检验四个城市的自动乘客计数(APC)数据的一致性和完整性。工作日APC数据在系统层面汇总,并与2012年至2018年的国家交通数据库进行比较。在所有四个机构中,乘客人数与国家过境数据库中观察到的波动密切相关。然而,四家旅行社中有两家的客流量略有波动,这可能是由于工作日和周末客流量的趋势不同。在停车级别,使用通用运输馈送规范中的时间表数据来识别缺失和重复的车辆行程。遗漏和重复行程只涉及一小部分站点,可以使用所提出的方法消除。总的来说,本研究为在严格的时空尺度上分析影响客流量的因素开辟了道路。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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