Chapter
Jul 2, 2019
Study of Data-Driven Traffic Congestion Level—Taking Yangzhou as an Example
Authors: Lu Liu [email protected], Kai Guo [email protected], Bin Yang [email protected], and Zhanglei Bian [email protected]Author Affiliations
Publication: CICTP 2019
Abstract
Traffic congestion levels change with traffic conditions of different cities. In this paper, we carry out data mining based on traffic flow data obtained by vehicle positioning and video detection. Three basic indicators are selected to measure traffic congestion level, including speed ratio, road link saturation, and intersection saturation. The index weight is determined by expert scoring and hierarchical analysis. A fuzzy evaluation method is developed to calculate the road link congestion level based on the principle of maximum membership degree. The secondary fuzzy evaluation method is applied to evaluate the regional congestion level considering the total driving time of each road link. According to the principle of congestion level division, the traffic congestion level surrounding scenic spots in Yangzhou is studied, and the disturbances of different influencing factors for typical regional traffic congestion are analyzed.
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Published In
CICTP 2019
Pages: 2568 - 2575
Copyright
© 2019 American Society of Civil Engineers.
History
Published online: Jul 2, 2019
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Authors
Affiliations
College of Civil Science and Engineering, Yangzhou Univ., Yangzhou, Jiangsu 225127, China. E-mail: [email protected]
Guangling College of Yangzhou Univ., Yangzhou, Jiangsu 225000, China. E-mail: [email protected]
Traffic Police Detachment, Yangzhou Public Security Bureau, Yangzhou, Jiangsu 225127, China. E-mail: [email protected]
College of Civil Science and Engineering, Yangzhou Univ., Yangzhou, Jiangsu 225127, China. E-mail: [email protected]
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