Project
Understanding Bicyclists’ Behaviors Through Learning from Big Trip Data
This research aims to understand the behaviors of bicyclists on the road under various scenarios through applying deep learning techniques on trip data collected. Specifically, the project will explore if deep learning models can help us identify key factors (e.g., fast-moving vehicles, road conditions and infrastructure, weather conditions) in the sight of the bike riders and automatically learn the relationship between the presence of such factors and the decisions made by the rider (e.g., turns, route choice, speed change, hazard avoidance).
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Webinar
