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Transit-based smart parking: An evaluation of the San Francisco Bay area field test

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  • Rodier, Caroline J
  • Shaheen, Susan A

Abstract

This paper presents an evaluation of the first transit-based smart parking project in the US at the San Francisco Bay Area Rapid Transit (BART) District station in Oakland, California. The paper begins with a review of the smart parking literature; next the smart parking field test is described including its capital, operational, and maintenance costs; and finally the results of the participant survey analysis are presented. Some key user response results are: (1) most participants used the smart parking system 1–3 days a month for commute travel and (2) 37% of respondents had seen the changeable message signs with parking information, but only 32% of those used this information to decide whether to continue driving or take BART. Some key changes in participant travel behavior include: (1) increases in BART mode share, (2) reductions in drive alone modal share, (3) decreased average commute time, and (4) an overall reduction in total vehicle miles of travel.

Suggested Citation

  • Rodier, Caroline J & Shaheen, Susan A, 2010. "Transit-based smart parking: An evaluation of the San Francisco Bay area field test," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6c6613ks, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt6c6613ks
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    References listed on IDEAS

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    1. Kolozsvari, Douglas & Shoup, Donald, 2003. "Turning Small Change into Big Changes," University of California Transportation Center, Working Papers qt3vq8794s, University of California Transportation Center.
    2. Rodier, Caroline J. & Shaheen, Susan A. & Eaken, Amanda M., 2004. "Transit-Based Smart Parking in the San Francisco Bay Area: an Assessment of User Demand and Behavioral Effects," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt5k15z9gp, Institute of Transportation Studies, UC Berkeley.
    3. Merriman, David, 1998. "How many parking spaces does it take to create one additional transit passenger?," Regional Science and Urban Economics, Elsevier, vol. 28(5), pages 565-584, September.
    4. B J Waterson & N B Hounsell & K Chatterjee, 2001. "Quantifying the potential savings in travel time resulting from parking guidance systems — a simulation case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(10), pages 1067-1077, October.
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    Cited by:

    1. Niu, Zhipeng & Hu, Xiaowei & Fatmi, Mahmudur & Qi, Shouming & Wang, Siqing & Yang, Haihua & An, Shi, 2023. "Parking occupancy prediction under COVID-19 anti-pandemic policies: A model based on a policy-aware temporal convolutional network," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    2. Rui Mu & Martin De Jong, 2018. "A Tale of Two Chinese Transit Metropolises and the Implementation of Their Policies: Shenyang and Dalian (Liaoning Province, China)," Energies, MDPI, vol. 11(3), pages 1-18, February.
    3. Hamilton de França Júnior & Cláudio Tavares de Alencar & Vanderley Moacyr John, 2011. "Evolução Do Espaço Destinado À Automóveis Em Relação A Área Total Construída Dos Edifícios De São Paulo," LARES lares-2011-506-769-3-rv, Latin American Real Estate Society (LARES).
    4. Gaetano Rocco & Claudia Pipino & Claudio Pagano, 2023. "An Overview of Urban Mobility: Revolutionizing with Innovative Smart Parking Systems," Sustainability, MDPI, vol. 15(17), pages 1-17, September.
    5. Sayarshad, Hamid R. & Sattar, Shahram & Oliver Gao, H., 2020. "A scalable non-myopic atomic game for a smart parking mechanism," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).

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