Abstract
Efficient parking tends to be challenging in most large cities in China. Drivers often spend substantial amounts of time looking for parking lots while driving at low speeds, thereby resulting in interference with road traffic. This paper focuses on efficiently allocating parking spaces to the demanders. A double-objective model is proposed that considers both the utilizing rate and the walking distance. First, managers want to utilize parking resources fully. Therefore, they tend to prioritize the efficient distribution of parking spaces in response to parking demands. However, demanders typically choose parking spaces according to convenience. The second objective is the acceptable walking distance from the parking space to the destination. The particle swarm optimization (PSO) algorithm is used to solve this model. We collected parking demand and supply data in a central business district (CBD) of Harbin in China and evaluated the feasibility of the model. The results demonstrate that the proposed model increases the occupying rates of parking lots in residential zones while decreasing the walking distance. The shared use of parking spaces maximizes the utility and alleviates the shortage of parking spaces in downtown.
Highlights
Parking efficiently is a significant concern in traffic planning in many modern cities due to the fast increase in the number of private cars [1]
Many residential parking spaces near a central business district (CBD) are available after the owners go out in daytime. ese vacant parking spaces can be provided for demanders who go shopping or do other things in a CBD. is mode of availability is cycled every day, which provides a parking gap for demanders who come to CBD in the daytime
Based on the data collected from CBD in Harbin, China, a numerical simulation is conducted in Section 4. e last section presents the conclusions of this paper and provides perspectives
Summary
Parking efficiently is a significant concern in traffic planning in many modern cities due to the fast increase in the number of private cars [1]. Is mode of availability is cycled every day, which provides a parking gap for demanders who come to CBD in the daytime. This gap parking mode, which is called shared parking, helps the parking space owners get extra profits and substantially alleviates the urgent parking needs downtown. E drivers could choose the parking spaces in advance, and the searching time was decreased [18]. Erefore, managers can more plan parking lots and drivers can more locate available parking spaces. The “Smart Parking” and “Parking guidance” systems can intelligently assign a selected parking space to a driver [27, 28]. Based on the data collected from CBD in Harbin, China, a numerical simulation is conducted in Section 4. e last section presents the conclusions of this paper and provides perspectives
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