Introducing a re-sampling methodology for the estimation of empirical macroscopic fundamental diagrams
Bliemer, Michiel C.J.
Axhausen, Kay W.
- Working Paper
Rights / licenseIn Copyright - Non-Commercial Use Permitted
The uncertainty in the estimation of the macroscopic fundamental diagram (MFD) under real- world traffic conditions and urban dynamics, might result in an inaccurate estimation of the MFD parameters - especially if congestion is rarely observed network-wide. For example, if the observed data does not exhibit a distinct congested branch, it is hard to determine the network capacity and critical density. Similarly, as the data normally comes from punctual observations out of the whole network, it is unclear how representative these observations might be (i.e. how much is the observed capacity affected by the network’s inhomogeneity). This, in turn, also leads to uncertainties and errors in the parametrization of the MFD for applications, e.g. traffic control. In this paper we introduce a novel methodology to estimate (i) the critical density of the MFD, even when no congested branch is observed, and (ii) the level of inhomogeneity in the network. The methodology is based on the idea of re-sampling the empirical data set. Using an extensive data set from Lucerne, Switzerland, and London, UK, we provide insights on the performance and the application of the proposed methodology. We show that, for the network of Lucerne, the proposed methodology allows us to accurately estimate the critical density up to 16 times more often than it would be possible otherwise. This simple and robust estimation of the critical density is crucial for the application of many traffic control algorithms. Additionally, we also use the proposed methodology to illustrate how the level of inhomogeneity is lower in Lucerne than in the three areas of the network of London that we investigate. The proposed measure of the level of inhomogeneity gives city planners the possibility to analyze and investigate how efficiently their road network is utilized Show more
External linksSearch via SFX
Journal / seriesArbeitsberichte Verkehrs- und Raumplanung
PublisherIVT ETH Zurich
Organisational unit08686 - Gruppe Strassenverkehrstechnik
03521 - Axhausen, Kay W.
02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
Related publications and datasets
Is previous version of: http://hdl.handle.net/20.500.11850/204589
MoreShow all metadata