Decoding pedestrian and automated vehicle interactions using immersive virtual reality and interpretable deep learning

Abstract

Presentation of our research on pedestrian wait time in mixed traffic conditions in University of Toronto ITE Student Chapter. In our proposed method, we incorporate auxiliary contextual information from the roads into time-series information from pedestrian movements to enhance the prediction of their trajectory.

Date
Location
University of Toronto, Toronto, Ontario