Optimising Bridge Maintenance Planning Considering Hindrance to Road Users

An improved method combining optimisation and simulation applied to the city of Amsterdam

Master thesis (2024)

Authors

M. Sagasser Civil Engineering & Geosciences

Contributors

Gonçalo Correia Transport, Mobility and Logistics (mentor)
S.P. Hoogendoorn Traffic Systems Engineering (graduation committee member)
M. Snelder Transport, Mobility and Logistics (graduation committee member)
N. Mouter Transport and Logistics - TPM (graduation committee member)
Laura Hakvoort Gemeente Amsterdam (graduation committee member)
Marjolein van der Meer TNO (graduation committee member)
Faculty
Civil Engineering & Geosciences
More Info
expand_more

Published Date

01-10-2024

Language

English

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.

Faculty

Civil Engineering & Geosciences

Abstract

Amsterdam's extensive network of bridges and quay walls is facing a critical maintenance backlog due to structural underfunded infrastructure maintenance. The many upcoming bridge maintenance projects to ensure safety are expected to cause significant more hindrance to road users. However, complex road networks with high traffic density in urban areas like Amsterdam make it difficult to foresee how the effects of different maintenance projects interact and how the projects can be planned efficiently to reduce hindrance.
This study aims to optimise the planning of a given set of bridge maintenance projects to reduce hindrance to road users, combining a genetic algorithm with traffic simulations using a new estimation method to improve the assessment of simultaneous closures. The genetic algorithm selects the optimal starting time and execution duration for each bridge while minimising maintenance cost and additional travel times for the modalities car, freight and bicycle. Using the fast static traffic simulation of the Urban Strategy Tool of TNO, a new estimation method for evaluating simultaneous closures is proposed, accounting for interdependencies between bridges. Results of a case study on four urban bridges in Amsterdam show that the new method provides more accurate estimates of additional travel time compared to previous methods and generates better solutions. Moreover, the fast proposed optimisation framework makes it possible to evaluate multiple scenarios in reasonable time to assist in decision making of maintenance planning.