IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt8670m9jh.html
   My bibliography  Save this paper

Network-wide Emissions Estimation Using the Macroscopic Fundamental Diagram

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/8670m9jh.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    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. 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.
    13. 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.
    14. Siamak Ardekani & Robert Herman, 1987. "Urban Network-Wide Traffic Variables and Their Relations," Transportation Science, INFORMS, vol. 21(1), pages 1-16, February.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Ambühl, Lukas & Loder, Allister & Bliemer, Michiel C.J. & Menendez, Monica & Axhausen, Kay W., 2020. "A functional form with a physical meaning for the macroscopic fundamental diagram," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 119-132.
    4. Saeedmanesh, Mohammadreza & Geroliminis, Nikolas, 2017. "Dynamic clustering and propagation of congestion in heterogeneously congested urban traffic networks," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 193-211.
    5. Guo, Qiangqiang & Ban, Xuegang (Jeff), 2020. "Macroscopic fundamental diagram based perimeter control considering dynamic user equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 87-109.
    6. Liu, Wei & Szeto, Wai Yuen, 2020. "Learning and managing stochastic network traffic dynamics with an aggregate traffic representation," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 19-46.
    7. Mariotte, Guilhem & Leclercq, Ludovic, 2019. "Flow exchanges in multi-reservoir systems with spillbacks," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 327-349.
    8. Haddad, Jack & Zheng, Zhengfei, 2020. "Adaptive perimeter control for multi-region accumulation-based models with state delays," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 133-153.
    9. Li, Ye & Mohajerpoor, Reza & Ramezani, Mohsen, 2021. "Perimeter control with real-time location-varying cordon," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 101-120.
    10. Wada, Kentaro & Satsukawa, Koki & Smith, Mike & Akamatsu, Takashi, 2019. "Network throughput under dynamic user equilibrium: Queue spillback, paradox and traffic control," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 391-413.
    11. Yildirimoglu, Mehmet & Ramezani, Mohsen, 2020. "Demand management with limited cooperation among travellers: A doubly dynamic approach," Transportation Research Part B: Methodological, Elsevier, vol. 132(C), pages 267-284.
    12. Gu, Ziyuan & Safarighouzhdi, Farshid & Saberi, Meead & Rashidi, Taha H., 2021. "A macro-micro approach to modeling parking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 220-244.
    13. Zhong, R.X. & Chen, C. & Huang, Y.P. & Sumalee, A. & Lam, W.H.K. & Xu, D.B., 2018. "Robust perimeter control for two urban regions with macroscopic fundamental diagrams: A control-Lyapunov function approach," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 687-707.
    14. Amirgholy, Mahyar & Gao, H. Oliver, 2017. "Modeling the dynamics of congestion in large urban networks using the macroscopic fundamental diagram: User equilibrium, system optimum, and pricing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 215-237.
    15. 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.
    16. Mohajerpoor, Reza & Saberi, Meead & Vu, Hai L. & Garoni, Timothy M. & Ramezani, Mohsen, 2020. "H∞ robust perimeter flow control in urban networks with partial information feedback," Transportation Research Part B: Methodological, Elsevier, vol. 137(C), pages 47-73.
    17. Anupriya, & Bansal, Prateek & Graham, Daniel J., 2023. "Congestion in cities: Can road capacity expansions provide a solution?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    18. Mariotte, Guilhem & Leclercq, Ludovic & Batista, S.F.A. & Krug, Jean & Paipuri, Mahendra, 2020. "Calibration and validation of multi-reservoir MFD models: A case study in Lyon," Transportation Research Part B: Methodological, Elsevier, vol. 136(C), pages 62-86.
    19. Huang, Y.P. & Xiong, J.H. & Sumalee, A. & Zheng, N. & Lam, W.H.K. & He, Z.B. & Zhong, R.X., 2020. "A dynamic user equilibrium model for multi-region macroscopic fundamental diagram systems with time-varying delays," Transportation Research Part B: Methodological, Elsevier, vol. 131(C), pages 1-25.
    20. Ma, Wenfei & Huang, Yunping & Jin, Xiao & Zhong, Renxin, 2024. "Functional form selection and calibration of macroscopic fundamental diagrams," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 640(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsdav:qt8670m9jh. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.