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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 1/2015

01.01.2015

The Adaptive Recommendation Mechanism for Distributed Parking Service in Smart City

verfasst von: Gwo-Jiun Horng

Erschienen in: Wireless Personal Communications | Ausgabe 1/2015

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Abstract

Recently, there are many researchers investigate about the recommendation system for improving the parking experience. In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and parking space requirement to parking congestion cloud center (PCCC) when the drivers need to find a parking space. Moreover we use cellular automata model mechanism for those parking spaces in the parking lot, it can adjust the situation that some parking lots are full and some are not. We also adopted the Artificial Fish Swarm Algorithm to build this two parts parking recommendation mechanism. Here the PCCC can compute with vehicle location information, nearest parking lot, parking lot status and the same or opposite driving direction. We take the driving direction into consideration can reduce road congestion and speed up finding a parking space from vehicles turning around. The current study evaluates the performance of the approach by conducting computer simulations. Simulation results the strengths of the proposed smart parking mechanism in terms of increased congestion avoiding and decrease parking space finding time.
Vorheriger Artikel A Survey on Scalable Multicasting in Mobile Ad Hoc Networks
Nächster Artikel A Coalitional Game-Based Algorithm for OFDMA Resource Allocation in Multicast Cognitive Radio Networks

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Metadaten
Titel
The Adaptive Recommendation Mechanism for Distributed Parking Service in Smart City
verfasst von
Gwo-Jiun Horng
Publikationsdatum
01.01.2015
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2015
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-014-2017-3

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