ARCAS: An Augmented Reality Collision Avoidance System with SLAM-Based Tracking for Enhancing VRU Safety

TL;DR

ARCAS is a real-time augmented reality system that enhances VRU safety by providing personalized collision alerts through wearable AR headsets, using LiDAR and SLAM for accurate hazard overlay in urban environments.

Contribution

The paper introduces ARCAS, a novel AR-based collision avoidance system for VRUs that integrates LiDAR, SLAM tracking, and multi-headset coordination for improved safety.

Findings

Nearly doubles pedestrians' time to collision.

Increases reaction margins of other road users by up to 4x.

Demonstrates feasibility and effectiveness of LiDAR-driven AR safety guidance.

Abstract

Vulnerable road users (VRUs) face high collision risks in mixed traffic, yet most existing safety systems prioritize driver or vehicle assistance over direct VRU support. This paper presents ARCAS, a real-time augmented reality (AR) collision avoidance system that provides personalized spatial alerts to VRUs via wearable AR headsets. By fusing roadside 360{\deg} 3D LiDAR with SLAM-based headset tracking and an automatic 3D calibration procedure, ARCAS accurately overlays world-locked 3D bounding boxes and directional arrows onto approaching hazards in the user's passthrough view. The system also enables multi-headset coordination through shared world anchoring. Evaluated in real-world pedestrian interactions with e-scooters and vehicles (180 trials), ARCAS nearly doubles pedestrians' time to collision and increases counterparts' reaction margins by up to 4x compared to unaided eye conditions. Results validate the feasibility and effectiveness of LiDAR-driven AR guidance and highlight the potential of wearable AR as a promising next generation safety tool for urban mobility.