Previous studies on measuring transit accessibility under travel time uncertainty often introduced complex measures based on non-standard data formats, hindering reproducibility and replicability in research and planning. To address this, we present a practical framework that leverages a standardized format for real-time transit data: Realtime General Transit Feed Specification (GTFS), to generate easy-to-use transit accessibility measures under travel time uncertainty. This framework first produces two datasets by correcting Scheduled GTFS data using Realtime GTFS information: Realtime P50 GTFS and Realtime P85 GTFS, which are used to compute two accessibility measures: median-corrected accessibility (using Realtime P50 GTFS) and dispersion-corrected accessibility (using Realtime P85 GTFS). These accessibility measures are applied in Columbus, Ohio, USA for an empirical study examining how overlooking travel time uncertainty issues can distort the analysis results of healthcare accessibility, inequality, and new transit project evaluation. Results indicate that scheduled accessibility (using Scheduled GTFS data) which overlooks travel time uncertainty overestimates healthcare accessibility by approximately 10.97 %. Moreover, this oversight fails to capture the benefits of the new transit service in improving accessibility and reducing inequality. Furthermore, although findings consistently suggest that lower-income neighbourhoods experience greater gains in healthcare accessibility compared to wealthier counterparts, our analysis unveils statistically significant differences when using the scheduled and dispersion-corrected accessibility measures. These findings underscore the importance of incorporating travel time uncertainty into public transit planning and evaluation. Our framework allows transit authorities and researchers to accurately measure accessibility and evaluate projects under travel time uncertainty using a standardized data format.

中文翻译：

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在出行时间不确定性下，使用实时 GTFS 生成易于使用的交通无障碍措施

以前关于在出行时间不确定性下测量交通可达性的研究经常引入基于非标准数据格式的复杂措施，阻碍了研究和规划中的可重复性和可复制性。为了解决这个问题，我们提出了一个实用的框架，该框架利用实时交通数据的标准化格式：实时通用交通源规范 （GTFS），在出行时间不确定性下生成易于使用的交通无障碍措施。该框架首先通过使用实时 GTFS 信息校正计划 GTFS 数据来生成两个数据集：实时 P50 GTFS 和实时 P85 GTFS，它们用于计算两个可访问性度量：中位数校正的可访问性（使用实时 P50 GTFS）和色散校正的可访问性（使用实时 P85 GTFS）。这些无障碍措施在美国俄亥俄州哥伦布市进行了一项实证研究，研究了忽视旅行时间不确定性问题如何扭曲医疗保健可及性、不平等和新交通项目评估的分析结果。结果表明，忽略了旅行时间不确定性的计划可访问性（使用计划的 GTFS 数据）高估了医疗保健的可访问性约 10.97%。此外，这种疏忽未能捕捉到新公交服务在提高可达性和减少不平等方面的好处。此外，尽管研究结果一致表明，与较富裕的社区相比，低收入社区在医疗保健可及性方面取得了更大的进步，但我们的分析揭示了在使用预定和离散校正的可及性措施时具有统计学上的显着差异。 这些发现强调了将出行时间不确定性纳入公共交通规划和评估的重要性。我们的框架允许交通管理部门和研究人员使用标准化数据格式准确测量可达性，并在出行时间不确定性下评估项目。