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Parking search equilibrium on a network

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  • Boyles, Stephen D.
  • Tang, Shoupeng
  • Unnikrishnan, Avinash

Abstract

This paper describes an equilibrium formulation for incorporating parking search into traffic network assignment models. The proposed model allows general network topologies and reflects uncertainty related to parking availability, including the possibility of cycling behavior as drivers search for parking. The equilibrium framework represents the mutual dependence between the probabilities of finding parking at different locations and the search processes employed by drivers to minimize total expected journey time (or cost). In this framework, network loading is represented by a system of nonlinear flow conservation networks, and feasibility and uniqueness issues are discussed. The equilibrium problem is formulated as a variational inequality and a convex combinations heuristic is proposed. Numerical results show that neglecting parking search can substantially underestimate network flows, and quantitatively demonstrate the relationship between parking duration effects and the cost of time spent walking relative to driving, and the expected driving and walking times.

Suggested Citation

  • Boyles, Stephen D. & Tang, Shoupeng & Unnikrishnan, Avinash, 2015. "Parking search equilibrium on a network," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 390-409.
  • Handle: RePEc:eee:transb:v:81:y:2015:i:p2:p:390-409
    DOI: 10.1016/j.trb.2014.09.017
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Jin Cao & Monica Menendez & Rashid Waraich, 2019. "Impacts of the urban parking system on cruising traffic and policy development: the case of Zurich downtown area, Switzerland," Transportation, Springer, vol. 46(3), pages 883-908, June.
    2. Karaliopoulos, Merkouris & Katsikopoulos, Konstantinos & Lambrinos, Lambros, 2017. "Bounded rationality can make parking search more efficient: The power of lexicographic heuristics," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 28-50.
    3. Gu, Ziyuan & Li, Yifan & Saberi, Meead & Rashidi, Taha H. & Liu, Zhiyuan, 2023. "Macroscopic parking dynamics and equitable pricing: Integrating trip-based modeling with simulation-based robust optimization," Transportation Research Part B: Methodological, Elsevier, vol. 173(C), pages 354-381.
    4. Maëlle Zimmermann & Emma Frejinger & Patrice Marcotte, 2021. "A Strategic Markovian Traffic Equilibrium Model for Capacitated Networks," Transportation Science, INFORMS, vol. 55(3), pages 574-591, May.
    5. Chai, Huajun, 2019. "Dynamic Traffic Routing and Adaptive Signal Control in a Connected Vehicles Environment," Institute of Transportation Studies, Working Paper Series qt9ng3z8vn, Institute of Transportation Studies, UC Davis.
    6. Rambha, Tarun & Boyles, Stephen D. & Unnikrishnan, Avinash & Stone, Peter, 2018. "Marginal cost pricing for system optimal traffic assignment with recourse under supply-side uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 104-121.
    7. Cao, Jin & Menendez, Monica, 2018. "Quantification of potential cruising time savings through intelligent parking services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 151-165.
    8. Nourinejad, Mehdi & Bahrami, Sina & Roorda, Matthew J., 2018. "Designing parking facilities for autonomous vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 110-127.
    9. Junheng Yang & Xiaodong Zang & Qiang Luo & Liming Shao, 2021. "Analysis on Stability of Roadside Parking System in a Rail-Integrated Transport Hub," Sustainability, MDPI, vol. 13(9), pages 1-16, April.
    10. Michael W. Levin & Stephen D. Boyles, 2020. "Optimal Guidance Algorithms for Parking Search with Reservations," Networks and Spatial Economics, Springer, vol. 20(1), pages 19-45, March.
    11. 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.
    12. Yi LIU, 2020. "Impact Of Parking Fees On Social Benefits Based On The Emergence Of Shared Parking," Theoretical and Empirical Researches in Urban Management, Research Centre in Public Administration and Public Services, Bucharest, Romania, vol. 15(1), pages 54-74, February.
    13. Xiao, Jun & Lou, Yingyan & Frisby, Joshua, 2018. "How likely am I to find parking? – A practical model-based framework for predicting parking availability," Transportation Research Part B: Methodological, Elsevier, vol. 112(C), pages 19-39.
    14. Pel, Adam J. & Chaniotakis, Emmanouil, 2017. "Stochastic user equilibrium traffic assignment with equilibrated parking search routes," Transportation Research Part B: Methodological, Elsevier, vol. 101(C), pages 123-139.
    15. Wei Wu & Wei Liu & Fangni Zhang & Vinayak Dixit, 2021. "A New Flexible Parking Reservation Scheme for the Morning Commute under Limited Parking Supplies," Networks and Spatial Economics, Springer, vol. 21(3), pages 513-545, September.
    16. 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.
    17. Zakharenko, Roman, 2016. "The time dimension of parking economics," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 211-228.
    18. Nourinejad, Mehdi & Gandomi, Amir & Roorda, Matthew J., 2020. "Illegal parking and optimal enforcement policies with search friction," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    19. 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.

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