Demand-Responsive Pricing on the Cheap Estimating Parking Occupancy with Meter Payment Data

被引:4
|
作者
Demisch, Alex [1 ]
机构
[1] San Francisco Municipal Transportat Agcy, 1 South Van Ness Ave, San Francisco, CA 94103 USA
关键词
TIME;
D O I
10.3141/2543-14
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The SFpark pilot by the San Francisco Municipal Transportation Agency in California was the first large-scale test of demand-responsive parking pricing in a major city. Several evaluations of the pilot showed that the project yielded substantial benefits. However, measuring parking occupancy is critical to implementing demand-responsive pricing. San Francisco relied on wireless in-ground parking sensors to measure parking occupancy for the SFpark pilot, but those sensors met the end of their useful lives and were deactivated. Parking sensors are still a nascent and costly technology that presents a great deal of risk to cities. Yet many cities, including San Francisco, are adopting new parking meters that make meter payment data widely available. Using sensor and meter data from the SFpark pilot, the agency developed a sensor independent rate adjustment model that estimated parking occupancy by using meter payment data. Although not everyone pays the meter when they park, the model can reliably estimate occupancy to support demand-responsive pricing. This capability allows San Francisco to continue its SFpark program and lays the foundation for other cities to implement demand-responsive pricing and promote the benefits of better parking policy more widely.
引用
收藏
页码:125 / 133
页数:9
相关论文
共 13 条
  • [1] Turning meter transactions data into occupancy and payment behavioral information for on-street parking
    Yang, Shuguan
    Qian, Zhen
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2017, 78 : 165 - 182
  • [2] Demand-responsive pricing in open wireless access markets
    Blomgren, Mats
    Hultell, Johan
    [J]. 2007 IEEE 65TH VEHICULAR TECHNOLOGY CONFERENCE, VOLS 1-6, 2007, : 2990 - 2995
  • [3] Improving accuracy of occupancy detection by estimating actual demand from smart meter data
    Hattori, Shunichi
    Shinohara, Yasushi
    [J]. IEEJ Transactions on Electronics, Information and Systems, 2017, 137 (09): : 1296 - 1303
  • [4] Demand-responsive pricing method for the product line of Taiwan high-speed rail
    Lee, CK
    Tsai, TH
    [J]. RAILROADS: HIGH-SPEED PASSENGER RAIL, RAILWAY BRIDGES, AND TRACK DESIGN AND MAINTENANCE, 2004, (1863): : 1 - 8
  • [5] Estimating bicycle parking demand with limited data availability
    Pfaffenbichler, Paul Christian
    Brezina, Tadej
    [J]. PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-ENGINEERING SUSTAINABILITY, 2016, 169 (02) : 76 - 84
  • [6] The effect of data science on urban sustainability through the optimization of demand-responsive transportation
    Raed Nayif A. Alahmadi
    Abdulaziz Alzahrani
    [J]. Journal of Umm Al-Qura University for Engineering and Architecture, 2023, 14 (3): : 172 - 187
  • [7] Optimal occupancy-driven parking pricing under demand uncertainties and traveler heterogeneity: A stochastic control approach
    Qian, Zhen
    Rajagopal, Ram
    [J]. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2014, 67 : 144 - 165
  • [8] D-Pro: Dynamic Data Center Operations With Demand-Responsive Electricity Prices in Smart Grid
    Wang, Peijian
    Rao, Lei
    Liu, Xue
    Qi, Yong
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2012, 3 (04) : 1743 - 1754
  • [9] Demand-Responsive Transport for Urban Mobility: Integrating Mobile Data Analytics to Enhance Public Transportation Systems
    Melo, Sandra
    Gomes, Rui
    Abbasi, Reza
    Arantes, Amilcar
    [J]. SUSTAINABILITY, 2024, 16 (11)
  • [10] Data-Driven Approach to Evaluate the Level of Service (LOS) of Demand-Responsive Transport for the Disabled (DRTD) with an ANFIS Algorithm
    Park, Seohyeon
    Park, Sooyeon
    Choi, Hosik
    Kim, Do-Gyeong
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2024, 2024