How many cars in the city are too many?

Towards finding the optimal modal split for a multi-modal urban road network

Journal Article (2021)
Author(s)

Allister Loder (ETH Zürich, Technische Universität München)

Lea Bressan (ETH Zürich)

Maria J. Wierbos (Transport and Planning)

Henrik Becker (ETH Zürich)

Andy Emmonds (Transport for London)

Martin Obee (Transport for London)

Victor L. Knoop (Transport and Planning)

Monica Menendez (New York University Abu Dhabi)

Kay W. Axhausen (ETH Zürich)

Transport and Planning
DOI related publication
https://doi.org/10.3389/ffutr.2021.665006 Final published version
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Publication Year
2021
Language
English
Transport and Planning
Journal title
Frontiers in Future Transportation
Volume number
2
Article number
665006
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Abstract

Interactions among different modes or vehicle classes in urban road networks affect the network performance in different and complex ways. Thus, an answer to the question of “how many cars are too many for a city?” is not trivial. However, multi-modal macroscopic fundamental diagrams (MFD) offer a novel opportunity to answer this question. So far, no methodology exists to estimate multi-modal MFDs resulting from arbitrary multi-modal interactions. In this paper, we propose a methodology to capture additional delays in the shape of the MFD and derive an approach for estimating multi-modal MFDs thereof. The influence on the MFD shape is established using the two-fluid theory of urban traffic by defining pairwise copula functions between travel times of each mode. In contrast to many existing approaches, the presented approach retains individual mode's speed information. We show the applicability of the approach with a tri-modal case of bicycles, buses, and cars with empirical data from Amsterdam (The Netherlands) and London (United Kingdom). Although the approach is not limited to this specific tri-modal case, we use the example to discuss the initial policy question by deriving optimal modal splits for a given accumulation of travelers. Last, we compare the new approach to existing estimation methods for bi-modal MFDs describing car and bus traffic.