Abstract
The train operation plan plays an essential role in metro systems and directly affects transportation organization efficiency and passenger service level. In metro systems, passengers have paid more attention to the travel time reliability (TTR), reflecting the reliability of metro operation management. This article proposes an analysis method of train operation plan based on TTR in the station dimension. First, an automated fare collection (AFC) data-driven framework is established to calculate the station travel time reliability (STTR) and analyze the train operation plan at different periods. The framework structure consists of four steps: AFC data preprocessing, STTR calculation and assignment, clustering algorithm design based on SOM neural network, and train operation plan analysis and optimization. Second, the proposed method is applied to the Beijing metro network as a case study. Several promising results are analyzed that allow the optimization of the existing train operation plan. Our research shows that STTR is a good supplement for the existing metro operation assignment studies, which can help analyze and optimize the train operation plan effectively. This study is also applicable to other metro networks with AFC systems.
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