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Parking Allocation Index Analysis of Office Building Based on the TOD Measurement Method

Author

Listed:
  • Xiang Tang

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210000, China)

  • Jianxiao Ma

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210000, China)

  • Peng He

    (Nanjing Institute of City & Transport Planning Co., Ltd., Nanjing 210000, China)

  • Chubo Xu

    (College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210000, China)

Abstract

Under the overall strategic guidance of emission peaks and carbon neutrality, an increasing number of cities are focusing on sustainable transportation development as an important measure for sustainable transportation development. Transit-oriented development (TOD) can guide residents to green trip options and reduce the dependence on private cars. Many cities have qualitatively reduced the parking allocation index of office buildings around rail stations, and quantitative research on the influence area and degree of TOD is lacking. This paper selects office buildings in the rail transit station influence area as the research object, puts forward the TOD measurement method of rail transit stations based on the improved “Node-Place” model, and clusters the stations under different measurement indices by the K-means algorithm. For different types of stations, the multinomial logit (MNL) model is used to build different types of trip mode split models to put forward the reduction calculation method of the parking allocation index of office buildings in the rail transit station influence area. Finally, this paper applies the revision of Nanjing’s allocation index in 2019, and the TOD measurement is identified through the “Node-Place-Connection” model. The optimized calculation method of the parking allocation index for office buildings is proposed. The results indicate that the method can reduce parking allocations to encourage the use of green transportation and guide the construction of urban sustainable transportation systems.

Suggested Citation

  • Xiang Tang & Jianxiao Ma & Peng He & Chubo Xu, 2022. "Parking Allocation Index Analysis of Office Building Based on the TOD Measurement Method," Sustainability, MDPI, vol. 14(5), pages 1-14, February.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2482-:d:755204
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    References listed on IDEAS

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    1. Simon McDonnell & Josiah Madar & Vicki Been, 2011. "Minimum parking requirements and housing affordability in New York City," Housing Policy Debate, Taylor & Francis Journals, vol. 21(1), pages 45-68, January.
    2. Vale, David S., 2015. "Transit-oriented development, integration of land use and transport, and pedestrian accessibility: Combining node-place model with pedestrian shed ratio to evaluate and classify station areas in Lisbo," Journal of Transport Geography, Elsevier, vol. 45(C), pages 70-80.
    3. Guang Tian & Reid Ewing & Rachel Weinberger & Kevin Shively & Preston Stinger & Shima Hamidi, 2017. "Trip and parking generation at transit-oriented developments: a case study of Redmond TOD, Seattle region," Transportation, Springer, vol. 44(5), pages 1235-1254, September.
    4. Songyot Kitthamkesorn & Anthony Chen & Sathaporn Opasanon & Suwicha Jaita, 2021. "A P-Hub Location Problem for Determining Park-and-Ride Facility Locations with the Weibit-Based Choice Model," Sustainability, MDPI, vol. 13(14), pages 1-16, July.
    5. Al-Sahili, Khaled & Hamadneh, Jamil, 2016. "Establishing parking generation rates/models of selected land uses for Palestinian cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 213-222.
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