数学建模及其应用

为缓解道路交通拥堵问题并提升通行效率，本文基于2024年“高教社杯”全国大学生数学建模竞赛E题提供的交通数据，针对某小镇的经中路-纬中路车辆信息，构建以绿波带宽最大化与延误时间最小化为目标的动态规划模型，综合考虑信号配时、相位差协调、流量波动及通行方向特征，实现主干道交通的时变优化控制.最后，通过遗传算法以及Tf-Lite仿真验证，系统解决了交通时段划分、信号配时优化、停车需求预测与管控效果评估四大问题，为城市道路交通信号的智能化管控提供参考.

To alleviate road congestion and improve traffic efficiency, this study develops a dynamic programming-based optimization model for traffic flow control using data from Problem E of the 2024 Higher Education Press Cup National College Student Mathematical Modeling Contest. Taking Jingzhong-Weizhong Road in a small town as a case study, the model aims to maximize green wave bandwidth and minimize delay time, while integrating signal timing, phase difference coordination, flow fluctuations, and directional features to achieve time-varying control of arterial traffic. A genetic algorithm is applied for parameter optimization, and Tf-Lite simulation is used for performance verification. The proposed approach effectively addresses four key issues: traffic period division, signal timing optimization, parking demand prediction, and control performance evaluation. The results demonstrate that the model enhances green wave coordination and reduces congestion, providing a practical framework for the intelligent optimization of urban traffic signal systems.