Intelligent Planning and Research on Urban Traffic Congestion

Qigang Zhu, Yifan Liu, Ming Liu, Shuaishuai Zhang, Guangyang Chen and Hao Meng
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Qigang Zhu: Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan 250031, China
Yifan Liu: Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan 250031, China
Ming Liu: Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan 250031, China
Shuaishuai Zhang: Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan 250031, China
Guangyang Chen: Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan 250031, China
Hao Meng: Department of Electrical Engineering & Information Technology, Shandong University of Science and Technology, Jinan 250031, China

Future Internet, 2021, vol. 13, issue 11, 1-17

Abstract: For large and medium-sized cities, the planning and development of urban road networks may not keep pace with the growth of urban vehicles, resulting in traffic congestion on urban roads during peak hours. Take Jinan, a mid-sized city in China’s Shandong Province, for example. In view of the daily traffic jam of the city’s road traffic, through investigation and analysis, the existing problems of the road traffic are found out. Based on real-time, daily road traffic data, combined with the existing road network and the planned road network, the application of a road intelligent transportation system is proposed. Combined with the application of a road intelligent transportation system, this paper discusses the future development of urban road traffic and puts forward improvement suggestions for road traffic planning. This paper has reference value for city development, road network construction, the application of intelligent transportation systems, and road traffic planning.

Keywords: smart cities; intelligent transportation system; Python; traffic congestion; urban health analytics (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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