Analysis on cruising process for on‐street parking using an spectral clustering method. Issue 14 (26th February 2021)

• Record Type: Journal Article
• Authors: Qin, Huanmei; Pang, Qianqian; Yu, Binhai; Wang, Zhongfeng
• Is Part Of: IET intelligent transport systems. Volume 14:Issue 14(2020)
• Page Start: 2113
• Page End: 2121
• Publication Date: 2021-02-26
• Subjects: pattern clustering -- road traffic -- road vehicles -- traffic engineering computing -- hidden Markov models -- intelligent transportation systems; on‐street parking -- spectral clustering -- parking problems -- parking spaces -- traffic congestion -- cruising vehicles -- hidden Markov model -- cruising trajectories -- three‐dimensional trajectory data -- intelligent parking guidance -- parking location -- parking status -- intercepted trajectory lengths -- cruising trajectory length -- intelligent parking systems -- parking efficiency -- environmental pollution -- Beijing -- HMM -- road traffic; Intelligent transportation systems -- Periodicals; Electronics in transportation -- Periodicals; 388.31205
• DOI: 10.1049/iet-its.2020.0459
• Languages: English
• ISSNs: 1751-956X

Abstract

Abstract : Parking problems caused by a lack of parking spaces have exacerbated traffic congestion and worsened environmental pollution. An analysis of the cruising process for parking can provide new perspectives to reduce cruising. Based on a parking survey conducted in Beijing, the authors collected a large amount of trajectory data of cruising vehicles. Then, fluctuation indexes of trajectories were proposed to analyse travellers' cruising processes for parking. The spectral clustering method based on a hidden Markov model (HMM) was used to recognise the cruising trajectories. The recognition performance for three‐dimensional trajectory data is better. Cruising trajectories for Clusters 1, 2, 3, 4, and 6 have large fluctuations and a weightier effect on road traffic. These groups can be taken as target groups for intelligent parking guidance and recommendations. The recognition accuracies for parking location and parking status increase with increasing intercepted trajectory lengths. 150 m from far to near the desired destination can be used as a threshold of the cruising trajectory length to accurately predict travellers' parking location and status. These research results can be applied in intelligent parking systems to dynamically predict parking situations, formulate parking guidance schemes and information release strategies, and improve parking efficiency.