IPARK: Location-Aware-Based Intelligent Parking Guidance over Infrastructureless VANETs

Hui Zhao, Li Lu, Chao Song and Yue Wu

International Journal of Distributed Sensor Networks, 2012, vol. 8, issue 12, 280515

Abstract: It has been pointed out that about 30% of the traffic congestion is caused by vehicles cruising around their destination and looking for a place to park. Therefore, addressing the problems associated with parking in crowded urban areas is of great significance. One effective solution is providing guidance for the vehicles to be parked according to the occupancy status of each parking lot. However, the existing parking guidance schemes mainly rely on deploying sensors or RSUs in the parking lot, which would incur substantial capital overhead. To reduce the aforementioned cost, we propose IPARK, which taps into the unused resources (e.g., wireless device, rechargeable battery, and storage capability) offered by parked vehicles to perform parking guidance. In IPARK, the cluster formed by parked vehicles generates the parking lot map automatically, monitors the occupancy status of each parking space in real time, and provides assistance for vehicles searching for parking spaces. We propose an efficient architecture for IPARK and investigate the challenging issues in realizing parking guidance over this architecture. Finally, we investigate IPARK through realistic experiments and simulation. The numerical results obtained verify that our scheme achieves effective parking guidance in VANETs.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:8:y:2012:i:12:p:280515

DOI: 10.1155/2012/280515

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