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With the rapid development of urbanization and the surge in the number of motor vehicles, urban road congestion has become a major challenge for many cities. Taking the E title of this year’s National Mathematical Contest in Modeling for College Students in Higher Education Society Cup as an example, this chapter analyzes the existing traffic flow by using operational research and statistics principles and the K-means algorithm and constructs a dual-objective programming model aiming at maximizing the average speed of traffic flow and minimizing the delay time of vehicles and uses a genetic algorithm to solve the model. The optimal configuration scheme of signal lights is obtained to alleviate traffic congestion and optimize traffic flow control.

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Research on Vehicle Flow Optimization Based on K-Means Clustering Model—Take Higher Education Society Cup National College Students Mathematical Contest in Modeling as an Example

  • 会议论文

  • 发表日期：

    2026年

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  • Hongge Zhao,
  • Anjun Zhao,
  • Shenghua Zhou

摘要

With the rapid development of urbanization and the surge in the number of motor vehicles, urban road congestion has become a major challenge for many cities. Taking the E title of this year’s National Mathematical Contest in Modeling for College Students in Higher Education Society Cup as an example, this chapter analyzes the existing traffic flow by using operational research and statistics principles and the K-means algorithm and constructs a dual-objective programming model aiming at maximizing the average speed of traffic flow and minimizing the delay time of vehicles and uses a genetic algorithm to solve the model. The optimal configuration scheme of signal lights is obtained to alleviate traffic congestion and optimize traffic flow control.