Measuring, Predicting and Controlling Disruption Impacts for Urban Public Transport

Doctoral Thesis (2020)
Author(s)

M.D. Yap (TU Delft - Transport and Planning)

Contributor(s)

Serge Paul Hoogendoorn – Promotor (TU Delft - Transport and Planning)

O. Cats – Promotor (TU Delft - Transport and Planning)

N. van Oort – Copromotor (TU Delft - Transport and Planning)

Transport and Planning
Copyright
© 2020 M.D. Yap
More Info
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Publication Year
2020
Language
English
Copyright
© 2020 M.D. Yap
Transport and Planning
Bibliographical Note
TRAIL Thesis Series no. T2020/3, the Netherlands Research School TRAIL@en
ISBN (print)
978-90-5584-261-2
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Public transport systems can be subject to disruptions, which have negative impacts on passengers. Disruptions can result in additional in-vehicle time, waiting time, transfer time and extra transfers for passengers. In addition, perceived journey times might increase due to higher crowding levels on public transport services. Public transport disruptions can also result in revenue losses, rescheduling costs, reimbursement costs and fines for the public transport service provider. Although it is thus important to reduce the impact of public transport disruptions, it is particularly challenging to foresee and study disruptions due to their uncertainty and variety. They occur in an environment with complex interactions between decisions made by both passengers and public transport service provider in response to these disruptions, surrounded by various sources of uncertainty in relation to disruption type, location and duration. In this research, we propose a generic, stepwise approach to reduce the passenger impacts of disruptions:
Step 1: Measure current disruption impacts.
Step 2: Predict future disruptions frequencies and impacts.
Step 3: Develop and evaluate measures aimed to control these disruption impacts.

Files

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