Identifying Driver Behaviors using Trajectory Features for Vehicle Navigation

TL;DR

This paper introduces a new method to identify driver behaviors from vehicle trajectories, enhancing autonomous vehicle navigation safety by using novel features and a data-driven approach validated through simulations.

Contribution

It presents a novel set of trajectory features and a data-driven mapping to classify driver behaviors, improving real-time navigation safety in autonomous vehicles.

Findings

Effective identification of driver behaviors from trajectory features

Enhanced safety in vehicle navigation simulations

Ability to detect aggressive or dangerous drivers

Abstract

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.