Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with Attention

TL;DR

This paper introduces a deep generative model with attention for detecting interactions between vehicles and vulnerable road users at intersections, enhancing traffic safety analysis and autonomous driving systems.

Contribution

It presents a novel conditional variational auto-encoder model that probabilistically predicts interactions using video data, improving accuracy in complex traffic scenarios.

Findings

Achieved F1-score above 0.96 at a German intersection

Achieved F1-score of 0.89 at a Japanese intersection

Validated on real-world datasets from two different countries

Abstract

Intersections where vehicles are permitted to turn and interact with vulnerable road users (VRUs) like pedestrians and cyclists are among some of the most challenging locations for automated and accurate recognition of road users' behavior. In this paper, we propose a deep conditional generative model for interaction detection at such locations. It aims to automatically analyze massive video data about the continuity of road users' behavior. This task is essential for many intelligent transportation systems such as traffic safety control and self-driving cars that depend on the understanding of road users' locomotion. A Conditional Variational Auto-Encoder based model with Gaussian latent variables is trained to encode road users' behavior and perform probabilistic and diverse predictions of interactions. The model takes as input the information of road users' type, position and motion automatically extracted by a deep learning object detector and optical flow from videos, and generates frame-wise probabilities that represent the dynamics of interactions between a turning vehicle and any VRUs involved. The model's efficacy was validated by testing on real--world datasets acquired from two different intersections. It achieved an F1-score above 0.96 at a right--turn intersection in Germany and 0.89 at a left--turn intersection in Japan, both with very busy traffic flows.