01623320

Component

https://doi.org/10.3141/2647-05

Data from automated vehicle location (AVL) systems, automatic passenger counter (APC) systems, and fare box payments have been heavily used to generate dwell time models with the goal of recommending improvements in efficiency and reliability of bus transit systems. However, automatic data collection methods may result in a loss of detail with regard to the dynamics of passenger activity, which may bias the estimates associated with dwell or passenger activity time. The purpose of this study is to understand better any biases that might exist from using data from AVL–APC systems or fare box payments when estimating dwell time. Manually collected data from Montreal, Quebec, Canada, are used to estimate detailed dwell time models. This study compared those estimates to models generated by using data similar to what was reported by AVL–APC systems and fare boxes. The results reveal an overestimation in the passenger activity component of dwell time, which is mainly attributed to excess dwell time that AVL–APC data and fare box payments generally do not capture. While AVL–APC and fare box technologies provide transit agencies with rich data for analysis, adjustments to such data collection methods are warranted to reduce the overestimation of dwell time and to provide a more accurate picture of what is happening on the ground to generate better interventions that can reduce dwell times.

01624542

17-01226

English

pp 33–40

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309442121

Digital/other

Figures (2) ; References (28) ; Tables (3)

Automatic data collection systems; Automatic vehicle location; Bus transit operations; Dwell time; Passenger counting

Montreal (Canada)

Operations and Traffic Management; Planning and Forecasting; Public Transportation

PRP, TRIS, TRB, ATRI

Dec 8 2016 10:22AM

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