The objectives of this project are (1) to make use of the newly emerging transit data sources for evaluating the variations in transit services (especially headway), and (2) to help passengers find optimal routing strategies to hedge against these service variations. The project first develops a data analysis tool (Transit Data Viewer) that is capable of building and visualizing empirical distributions of key transit operational parameters (headway, segment running time, dwell time and deviation from schedule) using space-time trajectories of transit vehicles. Statistical analysis is then performed to fit the processed headway data using various distributions. Based on the best fitted headway distribution, the project develops and implements a transit routing tool built on the notion of hyperpath (Transit Router). Note that transit systems are affected by variations in road traffic conditions and demand patterns, as well as major disruptions caused by extreme weather conditions, serious traffic accidents, unforeseeable mechanical failures and human errors. To cope with uncertainty, the proposed routing tool aims at finding an optimal hyperpath to minimize the expected journey time. The proposed tools are evaluated in a large-scale case study built from real data provided by the Chicago Transit Authority.
The time spent waiting by bus patrons at bus stops is a primary measure for assessing the reliability of transit services. Uncertainty associated with...
The time spent waiting by bus patrons at bus stops is a primary measure for assessing the reliability of transit services. Uncertainty associated with...
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United States Department of Transportation
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