Validation of Macroscopic Fundamental Diagrams-Based Models with Microscopic Simulations on Real Networks: Importance of Production Hysteresis and Trip Lengths Estimation
Restricted accessResearch articleFirst published online May, 2019
Validation of Macroscopic Fundamental Diagrams-Based Models with Microscopic Simulations on Real Networks: Importance of Production Hysteresis and Trip Lengths Estimation
This work focuses on the application of accumulation-based and trip-based macroscopic fundamental diagrams (MFD) approaches to real transportation networks and discusses the calibration of the MFD shape and trip lengths estimation using a thorough validation of the network dynamics with microsimulation data. This work not only investigates a classical unimodal approach to fit the production MFD, but also a bimodal MFD curve. Different methods of calibrating trip lengths in the reservoir are introduced to study the influence of trip lengths estimation on the accuracy of MFD models. MFD models are validated against microsimulations that are carried out using real origin–destination (OD) matrix and demand estimated from the data of Lyon city in France. The proposed bimodal production MFD curve captures the hysteresis in the production MFD to a good extent. Subsequently, it is shown that the refined description of trip lengths gives more accurate estimates of accumulation evolution for the trip-based approach. Finally, a case is presented with a modified OD matrix to study the effect of OD matrix changes on accuracy of MFD simulations.
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References
1.
GodfreyJ.The Mechanism of a Road Network. Traffic Engineering and Control, Vol. 11, No. 7, 1969, pp. 323–327.
2.
DaganzoC. F.Urban Gridlock: Macroscopic Modeling and Mitigation Approaches. Transportation Research Part B: Methodological, Vol. 41, No. 1, 2007, pp. 49–62.
3.
GeroliminisN.DaganzoC. F.Existence of Urban-Scale Macroscopic Fundamental Diagrams: Some Experimental Findings. Transportation Research Part B: Methodological, Vol. 42, No. 9, 2008, pp. 759–770.
4.
KnoopV. L.HoogendoornS. P., Network Transmission Model: A Dynamic Traffic Model at Network Level. Presented at 93rd Annual Meeting of the Transportation Research Board, Presented at 93rd Annual Meeting of the Transportation Research Board, Washington, D.C., 2014.
5.
YildirimogluM.GeroliminisN.Approximating Dynamic Equilibrium Conditions with Macroscopic Fundamental Diagrams. Transportation Research Part B: Methodological, Vol. 70, 2014, pp. 186–200.
6.
Keyvan-EkbataniM.KouvelasA.PapamichailI.PapageorgiouM.Exploiting the Fundamental Diagram of Urban Networks for Feedback-Based Gating. Transportation Research Part B: Methodological, Vol. 46, No. 10, 2012, pp. 1393–1403.
7.
HaddadJ.MirkinB.Coordinated Distributed Adaptive Perimeter Control for Large-Scale Urban Road Networks. Transportation Research Part C: Emerging Technologies, Vol. 77, 2017, pp. 495–515.
8.
AmpountolasK.ZhengN.GeroliminisN.Macroscopic Modelling and Robust Control of Bi-Modal Multi-Region Urban Road Networks. Transportation Research Part B: Methodological, Vol. 104, 2017, pp. 616–637.
9.
CaoJ.MenendezM.System Dynamics of Urban Traffic Based on its Parking-Related-States. Transportation Research Part B: Methodological, Vol. 81, 2015, pp. 718–736.
10.
LeclercqL.SénécatA.MariotteG.Dynamic Macroscopic Simulation of On-Street Parking Search: A Trip-Based Approach. Transportation Research Part B: Methodological, Vol. 101, 2017, pp. 268–282.
11.
DaganzoC. F.GeroliminisN.An Analytical Approximation for The Macroscopic Fundamental Diagram of Urban Traffic. Transportation Research Part B: Methodological, Vol. 42, No. 9, 2008, pp. 771–781.
12.
BuissonC.LadierC.Exploring the Impact of Homogeneity of Traffic Measurements on the Existence of Macroscopic Fundamental Diagrams. Transportation Research Record: Journal of the Transportation Research Board, 2009. 2124: 127–136.
13.
GayahV. V.DaganzoC. F.Clockwise Hysteresis Loops in the Macroscopic Fundamental Diagram: An Effect of Network Instability. Transportation Research Part B: Methodological, Vol. 45, No. 4, 2011, pp. 643–655.
14.
GeroliminisN.SunJ.Hysteresis Phenomena of a Macroscopic Fundamental Diagram in Freeway Networks. Transportation Research Part A: Policy and Practice, Vol. 45, No. 9, 2011, pp. 966–979.
15.
RamezaniM.HaddadJ.GeroliminisN.Dynamics of Heterogeneity in Urban Networks: Aggregated Traffic Modeling and Hierarchical Control. Transportation Research Part B: Methodological, Vol. 74, 2015, pp. 1–19.
16.
LeclercqL.ParzaniC.KnoopV. L.AmouretteJ.HoogendoornS. P.Macroscopic Traffic Dynamics with Heterogeneous Route Patterns. Transportation Research Part C: Emerging Technologies, Vol. 59, 2015, pp. 292–307.
17.
MahmassaniH. S.SaberiM.ZockaieA.Urban Network Gridlock: Theory, Characteristics, and Dynamics. Transportation Research Part C: Emerging Technologies, Vol. 36, 2013, pp. 480–497.
18.
LeclercqL.PaipuriM.Macroscopic Traffic Dynamics in Reservoirs under Fast-Varying Demand Profiles. Transportation Science, 2018, in press.
19.
KouvelasA.SaeedmaneshM.GeroliminisN.Enhancing Model-Based Feedback Perimeter Control with Data-Driven Online Adaptive Optimization. Transportation Research Part B: Methodological, Vol. 96, 2017, pp. 26–45.
20.
GeroliminisN.Dynamics of Peak Hour and Effect of Parking for Congested Cities. Presented at 88th Annual Meeting of the Transportation Research Board, Washington, D.C., 2009.
21.
YildirimogluM.RamezaniM.GeroliminisN.Equilibrium Analysis and Route Guidance in Large-Scale Networks with MFD Dynamics. Transportation Research Part C: Emerging Technologies, Vol. 59, 2015, pp. 404–420.
22.
ArnottR.A Bathtub Model of Downtown Traffic Congestion. Journal of Urban Economics, Vol. 76, 2013, pp. 110–121.
23.
DaganzoC. F.LeheL. J.Distance-dependent Congestion Pricing for Downtown Zones. Transportation Research Part B: Methodological, Vol. 75, 2015, pp. 89–99.
24.
LamotteR.GeroliminisN.The Morning Commute in Urban Areas: Insights from Theory and Simulation. Presented at 95th Annual Meeting of the Transportation Research Board, Washington, D.C., 2016.
25.
MariotteG.LeclercqL.LavalJ. A., Macroscopic Urban Dynamics: Analytical and Numerical Comparisons of Existing Models. Transportation Research Part B: Methodological, Vol. 101, 2017, pp. 245–267.
26.
MariotteG.LeclercqL.Flow Exchanges in Multi-Reservoir Systems with Spillbacks. Transportation Research Part B: Methodological, 2018 (forthcoming).
27.
NewellG.A Simplified Car-following Theory: A Lower Order Model. Transportation Research Part B: Methodological, Vol. 36, No. 3, 2002, pp. 195–205.
28.
LeclercqL.LavalJ.ChevallierE.The Lagrangian Coordinates and What It Means for First Order Traffic Flow Models. Proc., 17th International Symposium on Transportation and Traffic Theory, Elsevier, London, 2007, pp. 735–753.
29.
DialR. B.A Probabilistic Multipath Traffic Assignment Model Which Obviates Path Enumeration. Transportation Research, Vol. 5, No. 2, 1971, pp. 83–111.
30.
MariotteG.LeclercqL.MFD-Based Simulation: Spillbacks in Multi-Reservoir Networks. Presented at 97th Annual Meeting of the Transportation Research Board, Washington, D.C., 2018.
31.
LamotteR.GeroliminisN.The Morning Commute in Urban Areas with Heterogeneous Trip Lengths. Transportation Research Part B: Methodological, Vol. 117, 2017, pp. 794–810.
32.
MerchantD. K.NemhauserG. L.A Model and an Algorithm for the Dynamic Traffic Assignment Problems. Transportation Science, Vol. 12, No. 3, 1978, pp. 183–199.
33.
FrieszT. L.LuqueJ.TobinR. L.WieB.-W.Dynamic Network Traffic Assignment Considered as a Continuous Time Optimal Control Problem. Operations Research, Vol. 37, No. 6, 1989, pp. 893–901.
