The Study on Allocation Model of Shared Parking Slots in Multi-parking Lots

Yang, Bo; Yuan, Zhenzhou; Yang, Yang; Yin, Ruiqin; Wang, Yinhu

doi:10.2991/icmmcce-17.2017.87

Cited by 13 publications

(7 citation statements)

References 4 publications

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“…Moreover, shared parking can provide potential flow income for public, commercial, and residential buildings owners. Several researchers proposed optimizing reservation and allocation systems [ 16 , 17 , 18 , 19 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking

Chou

Dewabharata

Zulvia

2021

Sensors

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The size of cities has been continuously increasing because of urbanization. The number of public and private transportation vehicles is rapidly increasing, thus resulting in traffic congestion, traffic accidents, and environmental pollution. Although major cities have undergone considerable development in terms of transportation infrastructure, problems caused by a high number of moving vehicles cannot be completely resolved through the expansion of streets and facilities. This paper proposes a solution for the parking problem in cities that entails a shared parking system. The primary concept of the proposed shared parking system is to release parking lots that are open to specific groups for public usage without overriding personal usage. Open-to-specific-groups parking lots consist of parking spaces provided for particular people, such as parking buildings at universities for teachers, staff, and students. The proposed shared parking system comprises four primary steps: collecting and preprocessing data by using an Internet of Things system, predicting internal demand by using a recurrent neural network algorithm, releasing several unoccupied parking lots based on prediction results, and continuously updating the real-time data to improve future internal usage prediction. Data collection and data forecasting are performed to ensure that the system does not override personal usage. This study applied several forecasting algorithms, including seasonal ARIMA, support vector regression, multilayer perceptron, convolutional neural network, long short-term memory recurrent neural network with a many-to-one structure, and long short-term memory recurrent neural network with a many-to-many structure. The proposed system was evaluated using artificial and real datasets. Results show that the recurrent neural network with the many-to-many structure generates the most accurate prediction. Furthermore, the proposed shared parking system was evaluated for some scenarios in which different numbers of parking spaces were released. Simulation results show that the proposed shared parking system can provide parking spaces for public usage without overriding personal usage. Moreover, this system can generate new income for parking management and/or parking lot owners.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking

Chou

Dewabharata

Zulvia

2021

Sensors

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“…Some scholars, foreign and domestic, have verified the feasibility and effectiveness of shared parking from multiple perspectives [11,12]. Stin and Resha [13] analyzed the potential of shared parking for different purposes of building facilities and explored the feasibility of building shared parking lots.…”

Section: Related Workmentioning

confidence: 99%

How Does Bilateral Preference Affect Shared Parking in Sharing Economy?

Zhang

Wen

Zhao

et al. 2020

Mathematical Problems in Engineering

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Sharing economy is seen as an essential building block for sustainability. Yet, inefficient utilizing of parking spaces needs more attention, by which both direct and indirect traffic congestions may be caused, jeopardizing the economic potential of sustainable development. Conventional parking service may gradually lose favour in analogy to its counterpart, of which a novel approach solving shortage of urban parking resources is offered by shared parking. Hence, in this paper, problems of how to redistribute the available private-owned parking slots that be shared are focused due to the parking slot location properties that can be labelled as random, disordered, unstable, widely distributed, etc. Specifically, shared parking greatly enhances reasonability by considering satisfaction. Based on the mechanism of time matching between supply and demand, this paper thoroughly takes the bilateral preference of both parking demanders and parking space suppliers into account in terms of maximization of the utilization rate of shared parking spaces as well as the satisfaction of parking demanders, in which a multiobjective optimization model is established and the weighted sum method combined with the Hungarian method is adopted. Compared with the first-come-first-served (FCFS) strategy, the performance of the proposed method enjoys more advantages in utilizing shared parking spaces and in satisfying parking demanders. The model established and algorithm conducted in this paper meet the requirements induced by parking space redistribution in which inequalities exist between supply and demand, facilitating automobile parking and realizing higher efficiencies in using public resources regarding shortage of parking spaces in urban areas.

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“…As a result of commuting, a large number of private parking spots located in residential areas remain idle, which is complementary to the parking supply of other facilities. Under the background of 'Internet +', through the systematic integration of existing parking spot resources in residential areas and the application of modern information operation and management technologies, the efficiency of the existing parking lot resources can be fully improved, and the current urban parking issue can be addressed and alleviated to a certain extent [5].…”

Section: Introductionmentioning

confidence: 99%

Modelling and comparing two modes of sharing parking spots at residential area: Real‐time and fixed‐time allocation

Yang

Yang²,

Yuan

et al. 2023

IET Intelligent Trans Sys

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This research aims to improve the utilization efficiency of parking facilities in residential areas. The real‐time and fixed‐time shared parking spot allocation models based on a time window constraint are proposed, respectively. The real‐time model adopts the dynamic response service mechanism, introducing a multi‐objective decision weighting method to construct the weighted evaluation function. Then, the 0–1 planning model with user optimization is established, utilizing branch‐bound algorithm for a solution. The fixed‐time model adopts the periodic service mechanism, where a rejection penalty factor is introduced to add penalty cost. Then, the 0–1 programming model with system optimization is constructed, where genetic annealing algorithm solves the large‐scale calculation problem. The results from this case study illustrate the fixed‐time allocation mode has more balanced utilization of parking facilities, whereas over‐utilization of preferred parking lots occurs in the real‐time model; additionally, when supply and demand are in balance, the fixed‐time model can obtain higher system revenues, reduce effective rejection rate by 9.43%, and increase resource utilization efficiency by 5.28%. In conclusion, the real‐time allocation mode reflects the advantage of a user's optimal allocation mode when supply is greater than demand; conversely, the fixed‐time allocation mode has the advantage of optimum system resources utilization efficiency.

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The Study on Allocation Model of Shared Parking Slots in Multi-parking Lots

Cited by 13 publications

References 4 publications

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking

Dynamic Space Allocation Based on Internal Demand for Optimizing Release of Shared Parking

How Does Bilateral Preference Affect Shared Parking in Sharing Economy?

Modelling and comparing two modes of sharing parking spots at residential area: Real‐time and fixed‐time allocation

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