Kai Monast, North Carolina State University
Ruth Steiner, University of Florida
Terry Karlson, North Carolina State University
School and public transportation buses subjected to recurring congestion delays result in these modes becoming both more expensive to operate and often less-competitive as mobility options. Maintaining existing coverage and frequency requires increases in operating and capital expenses. Failing to maintain coverage and frequency encourages mode shifts which may exacerbate congestion in these corridors. This project combines three large datasets, 1) EDULOG school transportation routes, 2) GTFS public transportation routes, and 3) RITIS congestion data. Combined, these three datasets inform when and where publicly-funded transportation vehicles are operating and allow the estimation of the delay experienced by each vehicle. The delay costs can then be calculated both temporally and spatially, allowing for identification of locations and times where mitigation strategies may be most-appropriate. Strategies may include route diversion, lane dedication, signal prioritization, queue jumping and many others.