Floating Charge Method Based on Shared Parking
Jun Hao,
Jun Chen and
Qin Chen
Additional contact information
Jun Hao: Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
Jun Chen: Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 211189, China
Qin Chen: Qixia District Transportation Integrated Management Institute, Nanjing 211189, China
Sustainability, 2018, vol. 11, issue 1, 1-14
Abstract:
With the cultivation of the shared economy, shared parking provides a new solution to the urban parking resource shortage problem. In this paper, the shared parking mode is taken as the research object to improve the utilization efficiency of parking spaces. The stated preference (SP) survey is used to collect the intention of sharing parking behavior in a typical shared parking mode situation. The behavior selection characteristics of the person sharing parking are analyzed and a binary logit model is used to establish the parking behavior selection model. The key parameters of a floating charge are proposed. Based on the above research, a dynamic balance adjustment method for shared parking floating charges is proposed and an empirical analysis is carried out. The research results showed that compared with fixed fees, the floating charge method can improve the utilization rate of idle spaces by more than 60% and control the occupancy rate of spaces by 60–80%. The floating charge method not only guarantees its own parking demand but also exploits the potential of shard parking facilities, which is good for promoting the sustainable and healthy development of urban transportation.
Keywords: shared parking; shared parking mode; parking behavior selection model; floating charge method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2018:i:1:p:72-:d:192731
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