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Article type: Research Article
Authors: Ni, Xun-Youa; * | Lu, Weitea | Zhang, Chunqina | Liu, Yonga | Zhao, Jingb
Affiliations: [a] School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, China | [b] Department of Traffic Engineering, University of Shanghai for Science and Technology, Shanghai, China
Correspondence: [*] Corresponding author. Xun-You Ni, School of Civil Engineering and Architecture, Zhejiang Sci-Tech University, Hangzhou, China. E-mail: [email protected].
Abstract: Parking spaces are insufficient and are plagued by over-consumption in hot areas. To assist drivers easily in identifying available parking spaces, parking variable message signs are commonly adopted to display information on space availability. This paper analyzes the performance of various information provision strategies. To achieve this objective, we first present the mechanisms of the information provision strategies. Then, the information provision strategies are classified into three categories: regular, symmetric, and discriminative. The regular strategies provide the collected parking information directly to drivers; the symmetric schemes employ the equal threshold values for all parking lots; and the discriminative schedules adopt an independent threshold value for each parking lot. The threshold value provides an upper limit for the Space Occupancy Percentage (SOP): when the SOP is larger than the threshold value, the parking lot status becomes FULL; otherwise, it is displayed having available spaces. Finally, an agent-based simulation model is introduced to describe the parking and traffic conditions. The results indicate that both the symmetric and discriminative strategies significantly decrease the highest failure rate and average travel time, whereas the latter performs better. The results of this comparative analysis can assist in the configuration and operation of an urban parking guidance and information system.
Keywords: Intelligent transportation system, parking VMS, display problem, provision strategies, agent-based simulation
DOI: 10.3233/JIFS-190962
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 2725-2735, 2020
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