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

被引:128
作者
Hoercher, Daniel [1 ]
Graham, Daniel J. [1 ]
Anderson, Richard J. [1 ]
机构
[1] Imperial Coll London, Railway & Transport Strategy Ctr, Dept Civil & Environm Engn, London, England
关键词
Public transport; Crowding; Revealed preference; Smart card data; AVL data; PUBLIC TRANSPORT; TRAIN; RELIABILITY; ASSIGNMENT; CONGESTION; VALUATION; CHOICE; MODEL; TIME;
D O I
10.1016/j.trb.2016.10.015
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:105 / 125
页数:21
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