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Visually Exploring Transportation Schedules.

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    Transportation analysts can now identify service issues with TR-EX, a visual tool. It helps analyze planned versus real transit performance, improving future timetables.

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    Area of Science:

    • Transportation science
    • Information visualization
    • Human-computer interaction

    Background:

    • Public transportation agencies design schedules to optimize service quality within constraints.
    • Actual transit service often deviates from planned schedules, leading to performance issues.
    • Analyzing these deviations using traditional statistical methods is challenging due to data complexity and scale.

    Purpose of the Study:

    • To develop a visual exploration tool, TR-EX, to aid transportation analysts in identifying, inspecting, and comparing spatio-temporal patterns in planned and real transit service.
    • To address the limitations of purely statistical tools in handling large, multi-attribute datasets and multi-scale pattern searching.

    Main Methods:

    • TR-EX combines two novel visual encodings: Trips Explorer for trip-level analysis (frequency, deviation, speed) and Stops Explorer for station-level analysis (delay, wait time, reliability, bunching).
    • The system employs variable kernel bandwidths to manage overplotting and provide robust multi-scale representations of numerous trips and stops.
    • Design decisions were informed by close collaboration with transportation experts and specific analytical needs.

    Main Results:

    • TR-EX facilitates the identification and inspection of spatio-temporal patterns in transit service.
    • The tool enables comparison between planned and actual service performance at both trip and station levels.
    • Case studies using NYC subway data demonstrated TR-EX's efficacy in confirming hypotheses and generating new insights.

    Conclusions:

    • TR-EX offers a powerful visual approach for transportation analysts to understand and address service performance issues.
    • The tool's design effectively tackles challenges related to data scale, complexity, and multi-scale analysis.
    • Visual exploration with TR-EX can lead to improved transit timetable creation and enhanced service quality.