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城市交通系统是一个复杂的大系统，针对交通流的不确定性，本文基于动态规划思想提出了交通流预测与分配的方法。考虑路段容量对交通分配的影响，建立了路网流量预测和分配模型。为了保持并充分利用传统网络模型的性质和特征，引入惩罚函数，将容量约束条件转换到目标函数中，使模型符合传统均衡网络流结构。将凸规划法作为一个子过程植入惩罚函数，得到模型的求解算法。控制策略上采取预测控制、反馈校正和滚动优化的方式。最后，通过算例分析，进一步阐述模型和算法的应用，验证算法的有效性。为交通流预测和分配提供一定的参考。

Urban Traffic Flow Prediction and Assignment with Dynamic Programming

In view of the uncertainty of the complex urban traffic system, this paper presents a traffic flow prediction and assignment method with dynamic programming. The model is developed by considering the capacity limitation in each section of the road network. In this model, the newly-added restraint condition is transferred by introducing punishment function, and the fine characters of traditional assignment model are maintained. Then, the algorithm is documented, in which Frank-Wolfe algorithm is combined with the punishment function. The control strategy consists of prediction control, feedback correction, and rolling optimization. Finally, a numerical example is used to illustrate the availability of the proposed method which provides reference for traffic flow prediction and assignment.