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Smart city article details

Title	Making Smart Parking Decisions: A Driver'S Perspective
ID_Doc	36188
Authors	Miao L.
Year	2019
Published	Proceedings - 2019 4th International Conference on Computational Intelligence and Applications, ICCIA 2019
DOI	http://dx.doi.org/10.1109/ICCIA.2019.00024
Abstract	The difficulty of finding parking spots in urban areas has severely aggravated traffic congestion, increased CO2 emission, and caused waste of fuel and drivers' time. Therefore, the ability to accommodate 'smart parking' is a crucial component in 'smart cities'. With many papers in the literature focusing on parking spot detection and optimization for centralized parking reservation systems, we study how to make smart parking decisions from the perspective of a driver. Our research is motivated by the fact that centralized parking assignment may be either unavailable or suboptimal to the driver. In this paper, we let the driver come up with the best parking strategies using real-time parking and traffic information, and machine learning algorithms trained by historical data. Specifically, we propose a Q-learning based approach and also an artificial neural network based greedy algorithm. We run simulation to verify the performance of the proposed mechanisms. © 2019 IEEE.
Author Keywords	Artificial neural networks; Intelligent transportation systems; Optimization; Q learning

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