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Evaluation of Analytical Approximation Methods for the Macroscopic Fundamental Diagram

The Macroscopic Fundamental Diagram (MFD) describes the relation of average network flow, density and
speed in urban networks. It can be estimated based on empirical or simulation data, or approximated
analytically. Two main analytical approximation methods to derive the MFD for arterial roads and urban
networks exist at the moment. These are the method of cuts (MoC) and related approaches, as well as
the stochastic approximation (SA). This paper systematically evaluates these methods including their most
recent advancements for the case of an urban arterial MFD. Both approaches are evaluated based on a
traffic data set for a segment of an arterial in the city of Munich, Germany. This data set includes loop
detector and signal data for a typical working day. It is found that the deterministic MoC finds a more
accurate upper bound for the MFD for the studied case. The estimation error of the stochastic method is
about three times higher than the one of the deterministic method. However, the SA outperforms the MoC
in approximating the free-flow branch of the MFD. The analysis of the discrepancies between the empirical
and the analytical MFDs includes an investigation of the measurement bias and an in-depth sensitivity
study of signal control and public transport operation related input parameters. This study is conducted
as a Monte-Carlo-Simulation based on a Latin Hypercube sampling. Interestingly, it is found that applying
the MoC for a high number of feasible green-to-cycle ratios predicts the empirical MFD well. Overall, it is
concluded that the availability of signal data can improve the analytical approximation of the MFD even
for a highly inhomogeneous arterial.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:78688
Date02 May 2022
CreatorsTilg, Gabriel, Mühl, Susan Amini, Busch, Fritz
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageGerman
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/acceptedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess
Relation10.1016/j.trc.2020.02.003

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