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Dynamic Schedule-Based Assignment Model for Urban Rail Transit Network with Capacity Constraints

机译:具有容量约束的基于动态时间表的城市轨道交通分配模型

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摘要

There is a great need for estimation of passenger flow temporal and spatial distribution in urban rail transit network. The literature review indicates that passenger flow assignment models considering capacity constraints with overload delay factor for in-vehicle crowding are limited in schedule-based network. This paper proposes a stochastic user equilibrium model for solving the assignment problem in a schedule-based rail transit network with considering capacity constraint. As splitting the origin-destination demands into the developed schedule expanded network with time-space paths, the model transformed into a dynamic schedule-based assignment model. The stochastic user equilibrium conditions can be equivalent to the equilibrium passenger overload delay with crowding penalty in the transit network. The proposal model can estimate the path choice probability according to the equilibrium condition when passengers minimize their perceptive cost in a schedule-based network. Numerical example in Beijing urban rail transit (BURT) network is used to demonstrate the performance of the model and estimate the passenger flow temporal and spatial distribution more reasonably and dynamically with train capacity constraints.
机译:迫切需要估算城市轨道交通网络中的客流时空分布。文献综述表明,在基于时间表的网络中,考虑载流量限制和载客量延迟的客流分配模型在车内拥挤方面受到限制。提出了一种基于容量约束的随机用户平衡模型,用于求解基于调度的轨道交通网络中的分配问题。随着将起点-目的地需求划分为具有时空路径的已开发计划扩展网络,该模型转换为基于动态计划的分配模型。随机的用户平衡条件可以等效于公交网络中拥挤惩罚的平衡乘客超载延迟。当乘客在基于时间表的网络中最小化其感知成本时,该建议模型可以根据均衡条件估计路径选择概率。以北京城市轨道交通(BURT)网络为例,通过算例验证了模型的性能,并在列车通行能力约束下更合理,更动态地估计了客流的时空分布。

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