Crowding cost estimation with large scale smart card and vehicle location data

Daniel Hörcher, Daniel J. Graham and Richard J. Anderson

Transportation Research Part B: Methodological, 2017, vol. 95, issue C, 105-125

Abstract: Crowding discomfort is an external cost of public transport trips imposed on fellow passengers that has to be measured in order to derive optimal supply-side decisions. This paper presents a comprehensive method to estimate the user cost of crowding in terms of the equivalent travel time loss, in a revealed preference route choice framework. Using automated demand and train location data we control for fluctuations in crowding conditions on the entire length of a metro journey, including variations in the density of standing passengers and the probability of finding a seat. The estimated standing penalty is 26.5% of the uncrowded value of in-vehicle travel time. An additional passenger per square metre on average adds 11.9% to the travel time multiplier. These results are in line with earlier revealed preference values, and suggest that stated choice methods may overestimate the user cost of crowding. As a side-product, and an important input of the route choice analysis, we derive a novel passenger-to-train assignment method to recover the daily crowding and standing probability pattern in the metro network.

Keywords: Public transport; Crowding; Revealed preference; Smart card data; AVL data (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (54)

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DOI: 10.1016/j.trb.2016.10.015

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