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Bus Probes

Recurrent Traffic Congestion Patterns

A methodology has been developed to identify recurrent traffic congestion patterns over space and time using buses as “traffic probes”. Patterns observed in the Automatic Vehicle Location (AVL) data led to the methodological framework. Also the location and timing of vehicular traffic patterns as well as pedestrian and roadwork activities occurring on campus have been used to validate the ability of this methodology to efficiently process AVL data and produce meaningful indicators of recurring traffic congestion. The uniqueness of the recurring congestion approach and the validation studies on the Campus Transit Lab have separated these studies from others that attempt to use buses as traffic congestion probes.

Campus Transit Lab (CTL) is currently investigating whether data from different routes with overlapping locations could be pooled together to infer recurrent congestion. Once this investigation is validated, it would not only increase the confidence of the methodology but also increase the number of observations upon which this method could be applied to. Increasing the number of observations would conceptually improve the results produced by this method. CTL is also investigating the detection of changes in recurrent congestion. Detecting changes in recurrent congestion is potentially useful for planning or operation purposes.
Detection of Changes in Congestion Patterns

The application of Automated Vehicle Location (AVL) technologies in public transportation is becoming more prevalent. In addition, AVL data offer an opportunity to infer traffic conditions on the roadway network where transit vehicles operate. This study focuses on the identification of detection of congestion indications and changes in recurrent congestion patterns, whether temporary (e.g., over weeks or months) or permanent in nature.