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Dynamic macroscopic simulation of on-street parking search: A trip-based approach

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  • Leclercq, Ludovic
  • Sénécat, Alméria
  • Mariotte, Guilhem

Abstract

This paper extends a trip-based aggregate dynamic traffic model to account for on-street parking search. The trip-based approach for a road network defined as a reservoir characterizes the internal traffic states by a macroscopic fundamental diagram (MFD) in speed while individualizing all vehicle travel distances. This paper first investigates distances to park for on-street parking based on real data in Lyon (France) and stochastic numerical experiments. An updated formulation compared to the existing literature is proposed for the relation between such distances and the parking occupancy. This new formulation is then incorporated into an event-based numerical scheme that solves the trip-based MFD model. The complete framework is able to account for different vehicle categories with respect to their parking strategies and to finely tune the related travel distances. Finally, the capabilities of the full framework are illustrated based on three different scenarios. The first two correspond to strategies with static and dynamic (reactive) switch of the demand from on- to off-street parking. While being very classical, they permit to demonstrate that the proposed model reacts as expected in such cases. The third scenario assesses the effect of a smart-parking technology that informs the users when a free parking spot is available on one of the downstream links at each intersection. In such a case, the model permits to estimate the benefit for the equipped users but also the impacts on all other vehicle categories. The three scenarios highlight that the proposed framework is versatile and can quickly provide a first assessment with a low calibration burden of different parking strategies or policies.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:transb:v:101:y:2017:i:c:p:268-282
    DOI: 10.1016/j.trb.2017.04.004
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    References listed on IDEAS

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    Cited by:

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    2. Zhong, R.X. & Huang, Y.P. & Chen, C. & Lam, W.H.K. & Xu, D.B. & Sumalee, A., 2018. "Boundary conditions and behavior of the macroscopic fundamental diagram based network traffic dynamics: A control systems perspective," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 327-355.
    3. 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.
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    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. Clélia Lopez & Chuan-Lin Zhao & Stéphane Magniol & Nicolas Chiabaut & Ludovic Leclercq, 2019. "Microscopic Simulation of Cruising for Parking of Trucks as a Measure to Manage Freight Loading Zone," Sustainability, MDPI, vol. 11(5), pages 1-14, February.
    7. Paipuri, Mahendra & Leclercq, Ludovic, 2020. "Bi-modal macroscopic traffic dynamics in a single region," Transportation Research Part B: Methodological, Elsevier, vol. 133(C), pages 257-290.
    8. 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.
    9. Tian, Qiong & Yang, Li & Wang, Chenlan & Huang, Hai-Jun, 2018. "Dynamic pricing for reservation-based parking system: A revenue management method," Transport Policy, Elsevier, vol. 71(C), pages 36-44.
    10. Niu, Xiao-Jing & Zhao, Xiao-Mei & Xie, Dong-Fan & Liu, Feng & Bi, Jun & Lu, Chaoru, 2022. "Impact of large-scale activities on macroscopic fundamental diagram: Field data analysis and modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 161(C), pages 241-268.
    11. 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.
    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. Ding, Heng & Qian, Yu & Zheng, Xiaoyan & Bai, Haijian & Wang, Shiguang & Zhou, Jingwen, 2022. "Dynamic parking charge–perimeter control coupled method for a congested road network based on the aggregation degree characteristics of parking generation distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).

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