Aug. 11, 2023, 6:47 a.m. | Adu-Gyamfi Kojo, Kandiboina Raghupathi, Ravichandra-Mouli Varsha, Knickerbocker Skylar, Hans Zachary N, Hawkins, Neal R, Sharma Anuj

stat.ML updates on arXiv.org arxiv.org

In today's rapidly evolving urban landscapes, efficient and accurate mapping
of road infrastructure is critical for optimizing transportation systems,
enhancing road safety, and improving the overall mobility experience for
drivers and commuters. Yet, a formidable bottleneck obstructs progress - the
laborious and time-intensive manual identification of intersections. Simply
considering the shear number of intersections that need to be identified, and
the labor hours required per intersection, the need for an automated solution
becomes undeniable. To address this challenge, we propose …

arxiv data deep learning experience extraction infrastructure mapping mobility progress road safety safety systems transportation urban

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