Dynamic traffic assignment and vehicle route guidance have been important problems in ITS for some time. This paper proposes a new model for VRGS, which takes into consideration of the information propagation, user selection and information reaction. Parameter p is then defined as the updating weight for computing cost of traffic based on a distributive learning scheme. p is calculated through a function which denotes information propagation over time and space and the function needs further optimization. Comparison to static traffic assignment, DTA and feasible strategies are given, and future work is also stated.

翻译：动态交通分配与车辆路径引导长期以来一直是智能交通系统中的重要问题。本文提出了一种新的车辆路径引导系统模型，该模型综合考虑了信息传播、用户选择及信息反应过程。通过定义参数p作为基于分布式学习方案的交通成本更新权重，该参数通过表征信息时空传播的函数计算得出，且该函数需要进一步优化。本文还给出了与静态交通分配、动态交通分配及可行策略的比较，并阐述了未来研究方向。