A healthy and efficient transit system is indispensable to reduce congestion, emissions, energy consumption, and car use in urban areas. This research aims to develop methods to evaluate and visualize bus service reliability for transit agencies; identify the unreliability trends of bus routes to understand their causes and effects; and model service times using linear regression models.
Six months of vehicle location and passenger count data from a low-performance route in Portland was used for this research. Route 15 has experienced problems with schedule adherence and headway regularity. We developed methods to summarize causes of bus bunching, first determining the frequency of each cause. Next we demonstrated how results change using varying difficulty levels of bus bunching thresholds. Finally we investigated how results vary in different areas. This research also developed new ways to summarize and visualize vast amounts of bus route data in an insightful and intuitive manner.
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