Identifying Driver Behaviors using Trajectory Features for Vehicle Navigation

We present a novel approach to automatically identify driver behaviors from vehicle trajectories and use them for safe navigation of autonomous vehicles. We propose a novel set of features that can be easily extracted from car trajectories. We derive a data-driven mapping between these features and six driver behaviors using an elaborate web-based user study. We also compute a summarized score indicating a level of awareness that is needed while driving next to other vehicles. We also incorporate our algorithm into a vehicle navigation simulation system and demonstrate its benefits in terms of safer real-time navigation, while driving next to aggressive or dangerous drivers.

ERNEST CHEUNG, ANIKET BERA,
DINESH MANOCHA

GAMMA RESEARCH GROUP
Department of Computer Science
University of North Carolina Chapel Hill

eMILY kUBIN, KURT GRAY

Department of Psychology and Neuroscience
University of North Carolina at Chapel