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An Urban Road-Traffic Commuting Dynamics Study Based on Hotspot Clustering and a New Proposed Urban Commuting Electrostatics Model

1
Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China
2
Beijing Key Laboratory of City Integrated Emergency Response Science, Tsinghua University, Beijing 100084, China
3
Electric Power Planning and Engineering Institute, 65 Ande Road, Xicheng District, Beijing 100084, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(4), 190; https://doi.org/10.3390/ijgi8040190
Received: 20 February 2019 / Revised: 1 April 2019 / Accepted: 9 April 2019 / Published: 11 April 2019
(This article belongs to the Special Issue Algorithms and Techniques in Urban Monitoring)
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Abstract

With the recent rapid development of cities, the dynamics of urban road-traffic commuting are becoming more and more complex. In this research, we study urban road-traffic commuting dynamics based on clustering analysis and a new proposed urban commuting electrostatics model. As a case study, we investigate the characteristics of urban road-traffic commuting dynamics during the morning rush hour in Beijing, China, using over 1.3 million Global Positioning System (GPS) data records of vehicle trajectories. The hotspot clusters are identified using clustering analysis, after which the urban commuting electric field is simulated based on an urban commuting electrostatics model. The results show that the areas with high electric field intensity tend to have slow traffic, and also that the vehicles in most areas tend to head in the same direction as the electric field. The results above verify the validity of the model, in that the electric field intensity can reflect the traffic pressure of an area, and that the direction of the electric field can reflect the traffic direction in that area. This new proposed urban commuting electrostatics model helps greatly in understanding urban road-traffic commuting dynamics and has broad applicability for the optimization of urban and traffic system planning. View Full-Text
Keywords: urban road-traffic commuting dynamics; spatial data mining; O-D hotspot clustering model; urban commuting electrostatics model urban road-traffic commuting dynamics; spatial data mining; O-D hotspot clustering model; urban commuting electrostatics model
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Ni, X.; Huang, H.; Meng, Y.; Zhou, S.; Su, B. An Urban Road-Traffic Commuting Dynamics Study Based on Hotspot Clustering and a New Proposed Urban Commuting Electrostatics Model. ISPRS Int. J. Geo-Inf. 2019, 8, 190.

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