Abstract

Predicting Connected Vehicle Alert Classification Based on Topography
Track: Highways and Roads
Authors: Leslie Harwood, Zachary Doerzaph

Connected vehicle (CV) technology is projected to address approximately 4.5 million vehicle crashes and result in crash reduction benefits of $110 billion. However, it is expected that CV communications have degraded performance in areas of high occlusion, such as urban environments. This project modeled environments using LiDAR-derived data and used ESRI’s 3D Analyst extension to determine whether binary connected vehicle alert classifications could be predicted based on surrounding topography.