A quasi-dynamic capacity constrained frequency-based transit assignment model
A quasi-dynamic capacity constrained frequency-based transit assignment model
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DOI：
10.1016/j.trb.2008.02.001
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发表时间：
2008-12
影响因子：
6.8
通讯作者：
Jan-Dirk Schmöcker;M. Bell;F. Kurauchi
中科院分区：
文献类型：
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作者：
Jan-Dirk Schmöcker;M. Bell;F. Kurauchi
本文首先提出了一种基于频率的动态公交分配方法。因此，该模型旨在缩小基于时间表的模型和基于频率的模型之间的差距。然而，与基于调度的模型相比，基于频率的方法具有一些优势，然而，当对高度拥塞的网络进行建模时，基于静态频率的方法是不够的，因为它不能揭示容量问题的峰值性质。处理线路容量限制的中心想法是引入“上车失败”的概率，因为在某些情况下，由于过度拥挤，乘客无法登上第一班到达的服务。公共线路问题被考虑在内，最短超路径的搜索受到失败概率的影响。乘客在站台上混杂的假设允许马尔可夫网络装载过程，该过程尊重船上乘客相对于希望登上的乘客的优先级。研究期间分为几个时段，未能登机的乘客将被添加到随后的时段的需求中，因此可能会重新考虑他们的路线选择。超过一个时间间隔的行程也会延续到随后的时间间隔。该方法首先通过一个小的示例网络进行说明，然后通过与伦敦相关的案例研究来说明，在伦敦，交通容量问题在高峰时期每天都会遇到。
This paper presents a first approach to dynamic frequency-based transit assignment. As such the model aims to close the gap between schedule-based and frequency-based models. Frequency-based approaches have some advantages compared to schedule-based models, however, when modelling highly congested networks a static frequency-based approach is not sufficient as it does not reveal the peaked nature of the capacity problem. The central idea for dealing with the line capacity constraints is the introduction of a “fail-to-board” probability as in some circumstances passengers are not able to board the first service arriving due to overcrowding. The common line problem is taken into account and the search for the shortest hyperpath is influenced by the fail-to-board probability. An assumption that passengers mingle on the platform allows a Markov network loading process which respects the priority of on-board passengers with respect to those wishing to board. The study period is divided into several time intervals and those passengers who failed to board are added to the demand in the subsequent time interval and so might reconsider their route choice. Trips that are longer than one interval are also carried over to subsequent time intervals. The approach is first illustrated with a small example network and then with a case study relating to London, where transit capacity problems are experienced daily during the peak period.