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Intelligent Planning and Research on Urban Traffic Congestion

Author

Listed:
  • 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
    Division of Information Science and Technology, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, 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)

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.

Suggested Citation

  • Qigang Zhu & Yifan Liu & Ming Liu & Shuaishuai Zhang & Guangyang Chen & Hao Meng, 2021. "Intelligent Planning and Research on Urban Traffic Congestion," Future Internet, MDPI, vol. 13(11), pages 1-17, November.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:11:p:284-:d:674690
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    References listed on IDEAS

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    1. Sura Mahmood Abdullah & Muthusamy Periyasamy & Nafees Ahmed Kamaludeen & S. K. Towfek & Raja Marappan & Sekar Kidambi Raju & Amal H. Alharbi & Doaa Sami Khafaga, 2023. "Optimizing Traffic Flow in Smart Cities: Soft GRU-Based Recurrent Neural Networks for Enhanced Congestion Prediction Using Deep Learning," Sustainability, MDPI, vol. 15(7), pages 1-21, March.

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