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The Macroscopic Fundamental Diagram (MFD) describes the relation between accumulation and speed in a zone. While theoretically expected, empirical validations have been done with limited numbers of floating car (e.g., taxi) data, and loop detectors. This paper will verify existence, shape and crispness of the MFD using Floating Car Data (FCD) from Google. Due to the large amount of users (i.e., high penetration rate), this unique data-set contains traffic information with a high spatial resolution, a high spatial scope and high reliability. We use the data for 3 purposes. First, an MFD for the city of Amsterdam is constructed, revealing a strong relationship between the average density and the average flow. It also shows that the urban road network never reaches its capacity. Secondly, inhomogeneity is analysed. Traffic is well spread over the network, hence inhomogeneity is low. Moreover, if present, the inhomogeneity has only a minor effect on the flow. Also traffic in different directions is homogeneous. Thirdly, for the first time, an MFD is created for a whole country, which turned out to be very crisp as well. This suggests that small areas or a directional split are not needed to create crisp MFDs. That, in turn, implies that a crisp MFD is not a sufficient condition to apply control without considering internal dynamics.
Original languageEnglish
Title of host publication2018 IEEE Intelligent Transportation Systems Conference, ITSC 2018
Subtitle of host publicationNovember 4-7, 2018, Maui, Hawaii, USA
Number of pages8
ISBN (Electronic)9781728103235
Publication statusPublished - 2019
Event21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018 - Maui, United States
Duration: 4 Nov 20187 Nov 2018
Conference number: 21


Conference21st IEEE International Conference on Intelligent Transportation Systems, ITSC 2018
Abbreviated titleITSC 2018
CountryUnited States
Internet address

    Research areas

  • macroscopic fundamental diagram, traffic congestion, traffic dynamics, Traffic flow, urban traffic

ID: 47689559