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

Fuente: arXiv
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Main Authors: Yehia, Ahmad, Byeon, Jiseop, Wang, Tianyi, Wang, Huihai, Xu, Yiming, Jiao, Junfeng, Claudel, Christian
Format: Preprint
Published: 2025
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author Yehia, Ahmad
Byeon, Jiseop
Wang, Tianyi
Wang, Huihai
Xu, Yiming
Jiao, Junfeng
Claudel, Christian
author_facet Yehia, Ahmad
Byeon, Jiseop
Wang, Tianyi
Wang, Huihai
Xu, Yiming
Jiao, Junfeng
Claudel, Christian
contents 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° 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.
format Preprint
id arxiv_https___arxiv_org_abs_2512_05299
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle ARCAS: An Augmented Reality Collision Avoidance System with SLAM-Based Tracking for Enhancing VRU Safety
Yehia, Ahmad
Byeon, Jiseop
Wang, Tianyi
Wang, Huihai
Xu, Yiming
Jiao, Junfeng
Claudel, Christian
Systems and Control
Hardware Architecture
Computer Vision and Pattern Recognition
Emerging Technologies
Robotics
Image and Video Processing
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° 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.
title ARCAS: An Augmented Reality Collision Avoidance System with SLAM-Based Tracking for Enhancing VRU Safety
topic Systems and Control
Hardware Architecture
Computer Vision and Pattern Recognition
Emerging Technologies
Robotics
Image and Video Processing
url https://arxiv.org/abs/2512.05299