TranViT: An Integrated Vision Transformer Framework for Discrete Transit Travel Time Range Prediction. (arXiv:2211.12322v1 [cs.CV])

Accurate travel time estimation is paramount for providing transit users with
reliable schedules and dependable real-time information. This paper proposes
and evaluates a novel end-to-end framework for transit and roadside image data
acquisition, labeling, and model training to predict transit travel times
across a segment of interest. General Transit Feed Specification (GTFS)
real-time data is used as an activation mechanism for a roadside camera unit
monitoring a segment of Massachusetts Avenue in Cambridge, MA. Ground truth
labels are generated for …

arxiv framework prediction transformer transit travel vision