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Network-wide Emissions Estimation Using the Macroscopic Fundamental Diagram

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  • Laval, Jorge A.
  • Aghamohammadi, Rafegh

Abstract

This report presents a review of the studies incorporating the Macroscopic Fundamental Diagram (MFD) dynamics for emissions estimation using various microscopic estimation frameworks. These studies show the potential of applicability of the MFD-basedtools for emissions estimation. However, the accuracy of existing models in estimating the emissions of large-scale urban networks is questionable due to their inability in capturing the variations in traffic conditions across such networks. As a solution to this problem, we have proposed to develop a multi-reservoir emissions estimation framework by partitioning large-scale networks into smaller regions with homogeneous traffic conditions and low-scatter MFDs like the multi-reservoir Dynamic TrafficAssignment (DTA) models, which can result in more accurate network-wide emissions estimation. The key component of this framework is finding a method to accurately estimate the emissions using aggregated network representation and its corresponding variables. A numerical experiment on an arbitrary network shows that the estimation efficiency can increase significantly by implementing aggregated network representation, albeit the results will be less accurate the more aggregated the representation becomes. The possible reasons and considerations for future applications have been discussed, which would lead to developing calibrated aggregated-level methods, which can estimate the emissions efficiently and accurately. After calibrating the MFD-based emissions estimation method to acceptable levels of accuracy and efficiency, traffic control strategies can be proposed to optimize the energy consumption and emissions of CO, CO2, NOx, PM2.5, CH4, VOC, etc. The proposed control strategies can include perimeter control strategies in the boundaries of the regions, ramp-metering strategies at the connections to the freeways and signal timing strategies, which is known to influence the shape of the MFD. View the NCST Project Webpage

Suggested Citation

  • Laval, Jorge A. & Aghamohammadi, Rafegh, 2022. "Network-wide Emissions Estimation Using the Macroscopic Fundamental Diagram," Institute of Transportation Studies, Working Paper Series qt8670m9jh, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt8670m9jh
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    References listed on IDEAS

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    1. Hughes, Roger L., 2002. "A continuum theory for the flow of pedestrians," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 507-535, July.
    2. Aghamohammadi, Rafegh & Laval, Jorge A., 2020. "A continuum model for cities based on the macroscopic fundamental diagram: A semi-Lagrangian solution method," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 101-116.
    3. Du, Jie & Wong, S.C. & Shu, Chi-Wang & Zhang, Mengping, 2015. "Reformulating the Hoogendoorn–Bovy predictive dynamic user-optimal model in continuum space with anisotropic condition," Transportation Research Part B: Methodological, Elsevier, vol. 79(C), pages 189-217.
    4. Cao, Jin & Menendez, Monica, 2015. "System dynamics of urban traffic based on its parking-related-states," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 718-736.
    5. Siamak Ardekani & Robert Herman, 1987. "Urban Network-Wide Traffic Variables and Their Relations," Transportation Science, INFORMS, vol. 21(1), pages 1-16, February.
    6. Leclercq, Ludovic & Sénécat, Alméria & Mariotte, Guilhem, 2017. "Dynamic macroscopic simulation of on-street parking search: A trip-based approach," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 268-282.
    7. Amirgholy, Mahyar & Shahabi, Mehrdad & Gao, H. Oliver, 2017. "Optimal design of sustainable transit systems in congested urban networks: A macroscopic approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 261-285.
    8. Daganzo, Carlos F. & Geroliminis, Nikolas, 2008. "An analytical approximation for the macroscopic fundamental diagram of urban traffic," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 771-781, November.
    9. Laval, Jorge A. & Castrillón, Felipe, 2015. "Stochastic approximations for the macroscopic fundamental diagram of urban networks," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 904-916.
    10. Long, Jiancheng & Szeto, W.Y. & Du, Jie & Wong, R.C.P., 2017. "A dynamic taxi traffic assignment model: A two-level continuum transportation system approach," Transportation Research Part B: Methodological, Elsevier, vol. 100(C), pages 222-254.
    11. Ramezani, Mohsen & Haddad, Jack & Geroliminis, Nikolas, 2015. "Dynamics of heterogeneity in urban networks: aggregated traffic modeling and hierarchical control," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 1-19.
    12. Haddad, Jack, 2017. "Optimal perimeter control synthesis for two urban regions with aggregate boundary queue dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 1-25.
    13. Geroliminis, Nikolas & Daganzo, Carlos F., 2008. "Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 759-770, November.
    14. Jiang, Yanqun & Wong, S.C. & Ho, H.W. & Zhang, Peng & Liu, Ruxun & Sumalee, Agachai, 2011. "A dynamic traffic assignment model for a continuum transportation system," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 343-363, February.
    15. Kouvelas, Anastasios & Saeedmanesh, Mohammadreza & Geroliminis, Nikolas, 2017. "Enhancing model-based feedback perimeter control with data-driven online adaptive optimization," Transportation Research Part B: Methodological, Elsevier, vol. 96(C), pages 26-45.
    16. Batista, S.F.A. & Leclercq, Ludovic & Geroliminis, Nikolas, 2019. "Estimation of regional trip length distributions for the calibration of the aggregated network traffic models," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 192-217.
    17. Liu, Haobing & Xu, Yanzhi Ann & Rodgers, Michael O & Akanser, Alper & Guensler, Randall, 2016. "Improved Energy and Emissions Modeling for Project Evaluation (MOVES-Matrix)," Institute of Transportation Studies, Working Paper Series qt99w4w4cr, Institute of Transportation Studies, UC Davis.
    18. Aghamohammadi, Rafegh & Laval, Jorge A., 2020. "Dynamic traffic assignment using the macroscopic fundamental diagram: A Review of vehicular and pedestrian flow models," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 99-118.
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