Maintaining a consistent headway is a primary goal in bus operation, but it poses a significant challenge because of fluctuating traffic conditions and uneven passenger demand. This leads to inconsistent headways and even bus bunching, resulting in negative consequences such as increased travel time and reduced vehicle capacity. Various control strategies have been developed to alleviate headway inconsistencies, but most of them have focused on whether an inconsistency occurs while overlooking its duration. This study proposes a resilience-based approach to measure headway inconsistencies considering both the depth and duration of the impacts with deviations from the optimal headway. The approach is devised to analyze the cumulative impacts of inconsistent headways comprehensively. It goes beyond addressing only extreme cases, such as bus bunching, and considers persistently uneven headways. We first identify vehicle trajectories from smart card data, then compute deviations from the center of the preceding and following vehicles as an index of impact. Using the concept of resilience, cumulative impacts are measured and their distribution is utilized to set the failure criterion. The approach is applied to 320 bus lines in Seoul to measure the deviations of headways and is used to analyze the characteristics of the bus lines and links where inconsistencies frequently occur. The proposed method enables transportation planners to identify factors that can lead to headway inconsistency, facilitating tailored and data-informed planning processes. This study provides a comprehensive framework that recognizes line-specific and link-specific factors, thereby contributing to enhancing the reliability and efficiency of public transportation systems.


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    Title :

    Resilience-Based Approach to the Measurement of Headway Inconsistency


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2024-07-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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