The macroscopic fundamental diagram (MFD) is a graphical method used to characterize the traffic state in a road network and to monitor and evaluate the effect of traffic management. For the determination of an MFD, both traffic volumes and traffic densities are needed. This study introduces a methodology to determine an MFD using combined data from probe vehicles and loop detector counts. The probe vehicles in this study were taxis with GPS. The ratio of taxis in the total traffic was determined and used to convert taxi density to the density of all vehicles. This ratio changes over the day and between different links. We found evidence that the MFD was rather similar for days in the same year based on real data collected in Changsha, China. The difference between MFDs made of data from 2013 and 2015 reveals that the modification of traffic control can influence the MFD significantly. A macroscopic fundamental diagram could also be drawn for an area with incomplete data gained from a sample of loop detectors. An MFD based on incomplete data can also be used to monitor the emergence and disappearance of congestion, just as an MFD based on complete traffic data.
Daganzo C.F., Urban gridlock: Macroscopic modeling and mitigation approaches. Transportation Research Part B-Methodological. 2007, 41(1):49-62.
Daganzo C. F., Geroliminis N., An analytical approximation for the macroscopic fundamental diagram of urban traffic. Transportation Research Part B-Methodological. 2008, 42(9):771-781.
Geroliminis N, Daganzo C., Existence of urban-scale macroscopic fundamental diagrams: some experimental findings. Transportation Research B. 2008 42(9): 759-770.
Mühlich N., Gayah V.V., Menendes M., 2015. An examination of MFD hysteresis patterns for hierarchical Urban street networks using micro-simulation. Transportation Research Records. 2015. 2491:117-126.
Yuxuan J., Geroliminis N., Luo J. Empirical observations of congestion propagation and dynamic partitioning with probe data for large scale systems, Transportation Research Board Annual Meeting paper 2014, 14-0816, Washington D.C.
Gayah V.V., Daganzo C.F., Clockwise hysteresis loops in the Macroscopic Fundamental Diagram: an effect of network instability.Transportation Research Part B-Methodological 2011 45:643-655.
Ortigosa J., Menendez M., Tapia H., Study on the number and location of measurement points for an MFD perimeter control scheme: a case study of Zurich. EURO Journal on Transportation and Logistics 2014 3(3):245-266.
Buisson C., Ladier C., Exploring the Impact of the Homogeneity of Traffic Measurements on the Existence of the Macroscopic Fundamental Diagram. Transportation Research Records, Journal of the Transportation Research Board, 2009 2124:127-136.
GEROLIMINIS N, SUN J., HYSTERESIS PHENOMENA OF A MACROSCOPIC FUNDAMENTAL DIAGRAM IN FREEWAY NETWORKS. TRANSPORTATION RESEARCH PART A: POLICY AND PRACTICE 2011 45(9): 966-979.
Geroliminis N, Sun J., Properties of a well-defined Macroscopic Fundamental Diagram for urban traffic. Transportation Research Part B Methodological 2011 45(3):605-617.
Knoop V.L., Hoogendoorn S.P., Van Lint J.W.C., The Impact of Traffic Dynamics on the Macroscopic Fundamental Diagram.Physica A-statistical mechanics and its applications 2013 438:36-250.
Leclercq L, Chiabaut N, Trinquier B., Macroscopic Fundamental Diagrams: A Cross-comparison of estimation methods, Transportation Research Part B-Methodological 2014 (62):1–12.
Laval J.A., F Castrillón, Stochastic approximations for the Macroscopic Fundamental Diagram of urban networks, Transportation Research B-Methodological 2015 81(3):904-906.
Herrera J.C., Work D.B., Herring R., Ban X., Jacobson Q, Bayen A.M., Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment. Transportation Research Part C: Emerging Technologies, 2010 18(4):568-583.
Li J., van Zuylen H.J. Wei G., Loop detector data error diagnosing and interpolating with probe vehicle data, Transportation Research Records 2014:61 – 67.
DU J., RAKHA H., GAYAH V.V., DERIVING MACROSCOPIC FUNDAMENTAL DIAGRAMS FROM PROBE DATA: ISSUES AND PROPOSED SOLUTIONS.TRANSPORTATION RESEARCH PART C 2016 5(66):136-149.
COURBON T, LECLERCQ L., CROSS-COMPARISON OF MACROSCOPIC FUNDAMENTAL DIAGRAM ESTIMATION METHODS. PROCEDIA-SOCIAL BEHAVIORAL 2011 20:417-426.
Nagle A.S., Gayah V.V., A method to estimate the macroscopic fundamental diagram using limited mobile probe data. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC 2013(6728521):1987-1992.
Nagle, A.S., and Gayah, V.V., 2014. The accuracy of network-wide traffic state estimations using mobile probe data, Transportation Research Record: Journal of the Transportation Research Board Dec 2014(2421):1-11.
Ji Y., Geroliminis N., On the spatial partitioning of urban transportation network. Transportation Research Part B 2012 46(10):1639-1656.
Ambuhl Lukas, Menendez Monica. Data fusion algorithm for macroscopic fundamental diagram estimation. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES. 2016 10(71):184-197.
Lu S., Wang J., van Zuylen H.J., Liu X., Deriving the Macroscopic Fundamental Diagram for an Urban Area using Counted Flows and Taxi GPS. Proceedings of the 16th International IEEE annual conference on Intelligent Transportation Systems 2013.
Saeedmanesh M., Geroliminis N., Empirical observation of MFDs and hysteresis loops for multi-region urban networks with stop-line detectors. Transportation Research Board Annual Meeting paper 2015 15-2071, Washington D.C.
Zhang L., Garoni T.M., de Gier, J. A comparative study of Macroscopic Fundamental Diagrams of arterial road networks governed by adaptive traffic signal systems. Transportation Research Part B-Methodological 2013 (49):1–23.
Gayah V.V., Gao X., Nagle A.S., On the impacts of locally adaptive signal control on urban network stability and the Macroscopic Fundamental Diagram. Transportation Research Part B-Methodological 2014(70): 255–268.
Keyvan-Ekbatani M., Papageorgiou M., Papamichail I., Urban congestion gating control based on reduced operational network fundamental diagrams. Transportation Research Part C: Emerging Technologies 2013(33): 74–87.
Guest Editor: Eleonora Papadimitriou, PhD
Editors: Dario Babić, PhD; Marko Matulin, PhD; Marko Ševrović, PhD.
The mission of our journal is to provide high quality communication of research results, which is crucial for the effectiveness of scientific research, the promotion of scientific information, new ideas, and original research in the field of traffic and transportation engineering.
1848-4069
0353-5320
Proud publisher
Accelerating Discoveries in Traffic Science |
2024 © Promet - Traffic&Transportation journal
