The long term behaviour of day-to-day traffic assignment models
The long term behaviour of day-to-day traffic assignment models
复制标题
DOI：
10.1080/18128602.2012.751683
复制
发表时间：
2014-05
期刊：
影响因子：
--
通讯作者：
Mike J. Smith;M. Hazelton;H. Lo;G. Cantarella;D. Watling
中科院分区：
文献类型：
--
作者：
Mike J. Smith;M. Hazelton;H. Lo;G. Cantarella;D. Watling
确定性过程、日常交通分配模型的动态行为有时表现为收敛到各种不同的固定平衡点，这取决于初始流型，即使对于给定的起始点，各个轨迹是唯一的。这种非唯一性似乎与随机过程、日常模型的演变形成鲜明对比；在某些假设下，无论起点如何，这些模型都按规律收敛到唯一的平稳分布。在这篇文章中，我们展示了如何构建既具有确定性模型又具有随机性模型的模型，并用一个简单的例子网络来说明其思想。
The dynamical behaviour of deterministic process, day-to-day traffic assignment models is sometimes characterised by convergence to a variety of different fixed equilibrium points dependent upon the initial flow pattern, even though individual trajectories are unique for a given start point. This non-uniqueness is seemingly in sharp contrast to the evolution of stochastic process, day-to-day models; under certain assumptions these converge in law to a unique stationary distribution, irrespective of the start point. In this article, we show how models may be constructed which exhibit characteristics of both deterministic models and stochastic models, and illustrate the ideas by using a simple example network.