Abstract

Appertaining parking lots of public buildings provide a large proportion of parking supply in cities. However, these parking lots mainly serve the parking demands of public buildings, leading to a low utilization ratio of parking spaces. It is therefore required to implement a shared parking strategy for these parking lots. In this study, a parking space allocation method (PSAM) at the network level is proposed to allocate the parking demand to a parking lot and then the parking space. The users are divided into M-users (users of the buildings) and P-users (public users). The shared parking strategy is analyzed from the aspects of open window, parking fee, and ratio of reservation spaces. The users are allocated to a parking lot by a multinomial logit(MNL) model. Specifically, it is determined whether they can enter parking lot and which space they are allocated according to the specific rules. After all the users are allocated with a parking space, the rejection number of M-users, occupancy rate, and profits of each parking lot are collected and a NSGA-II (non-dominated sorting genetic algorithm II) algorithm is designed to determine the optimal strategy for each parking lot according to the above. Compared with the results of all-time all-space shared parking strategy, our method shows better performance in balancing the interests of all appertaining parking lots and protecting the interests of M-users while obtaining considerable profits for the parking lots.

Highlights

  • At present, the rapid increase in car ownership in China has far exceeded the supply capacity of urban parking lots [1,2]

  • The parking demand set of origin o is denoted as PDo(PAk,ATk,PTk), o = 1, 2, . . . , O, and k = 1, 2, . . . , K, where PAk is the personal attributes set of user k, ATk is the arrival time of user k, and PTk is the parking time of user k

  • The personal attributes set of the user k is denoted as PAk(AGEk,DEk,INCk,FAk,RISKkn,WTkn), where AGEk, DEk, INCk, and FAk represent the age, driving experience, income, and familiarity with the surrounding parking lot of user k, respectively

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Summary

Introduction

The rapid increase in car ownership in China has far exceeded the supply capacity of urban parking lots [1,2]. Based on this method, an NSGA-II algorithm is designed in Section 3 to determine the optimal strategy for Sustainability 2019, 11, 120 each parking lot. A method which considers both the user attributes and parking data is proposed, with the function of allocating a user to a specific parking space of a parking lot. This is called the parking space allocation method (PSAM)in this paper. 4. After all users are allocated to a parking space, collect all the related indices of each parking lot, and use the NSGA-II algorithm to determine the optimal shared parking strategy. This method of inputting all the parking data to PRMn is called the parking resource matrix method (PRMM) in this paper

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The Allocation of Parking Demand
The Multinomial Logistic Regression Model
Phase 1
Phase 2
Algorithm
Calculation Results of the Parking Space Allocation Method
Comparison with All Shared Parking Strategy
CoTnhcislusstiuodnysmakes the following three significant contributions
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