Highlights Smart card passengers are assigned to trains recorded in automated data. Passenger-to-train assignment leads to a train-level pattern of crowding. Crowding costs can be estimated in a revealed preference route choice setting. Standing costs 26.5% of travel time, the crowding multiplier does not exceed 1.981.

    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.


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    Title :

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


    Contributors:


    Publication date :

    2016-10-28


    Size :

    21 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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