2018•International Conference on Transportation and Development 2018Requires access

Development of Hazard Based-Models for the Metrorail of the Washington Metropolitan Area Transit Authority

Kathleen Libnao, Bismark R. D. K. Agbelie

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Abstract

The present study developed duration models to predict the duration of delay of the Washington Metropolitan Area Transit Authority’s Metrorail based on incident data from June 2015 to May 2016. Three fixed-parameter hazard-based models (log-logistic, log-normal, and Weibull) were developed and compared. Out of the three models, the log-logistic gave the best results based on the Akaike information criterion (AIC) value and the log-likelihood values. From the results, incidents during peak hours, weekends, and on some specific metro lines yielded shorter delays. The results would enable transit authorities to identify the significant causes of delay to improve travel time reliability for transit riders.

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What this paper is about

The present study developed duration models to predict the duration of delay of the Washington Metropolitan Area Transit Authority’s Metrorail based on incident data from June 2015 to May 2016. Three fixed-parameter hazard-based models (log-logistic, log-normal, and Weibull) were developed and compared. Out of the three models, the log-logistic gave the best results based on the Akaike information criterion (AIC) value and the log-likelihood values. From the results, incidents during peak hours, weekends, and on some specific metro lines yielded shorter delays. The results would enable transit authorities to identify the significant causes of delay to improve travel time reliability for transit riders.

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Available abstract

The present study developed duration models to predict the duration of delay of the Washington Metropolitan Area Transit Authority’s Metrorail based on incident data from June 2015 to May 2016. Three fixed-parameter hazard-based models (log-logistic, log-normal, and Weibull) were developed and compared. Out of the three models, the log-logistic gave the best results based on the Akaike information criterion (AIC) value and the log-likelihood values. From the results, incidents during peak hours, weekends, and on some specific metro lines yielded shorter delays. The results would enable transit authorities to identify the significant causes of delay to improve travel time reliability for transit riders.

Key concepts: Metropolitan area, Transit (satellite), Hazard, Computer science, Transport engineering, Regional science, Public transport, Geography

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