用概率碰撞风险模型提升视障者导航安全预警准确率
Probabilistic Collision Risk Estimation for Pedestrian Navigation
- 引入自动驾驶中的概率碰撞风险模型，替代传统距离和时间指标
- 在真实数据上风险模型预警准确率达67%，远超51%的基准方法
- 特别适合开发面向视障人群的智能导航辅助设备
面向视障人群的智能辅助设备正日益普及，但其发展仍落后于自动驾驶辅助系统的进步。本文首次将自动驾驶中已验证的碰撞风险模型引入视障导航系统。该模型基于物体轨迹计算概率性碰撞风险，相比传统的距离或时间到碰撞指标，能更准确反映潜在碰撞威胁。实验结果表明，在真实场景数据下，该风险模型的预警准确率达到67%，而距离与时间到碰撞方法仅达51%。结果证明该模型在视障导航中具有显著优势。
原文摘要 · Abstract (English)
Intelligent devices for supporting persons with vision impairment are becoming more widespread, but they are lacking behind the advancements in intelligent driver assistant system. To make a first step forward, this work discusses the integration of the risk model technology, previously used in autonomous driving and advanced driver assistance systems, into an assistance device for persons with vision impairment. The risk model computes a probabilistic collision risk given object trajectories which has previously been shown to give better indications of an object's collision potential compared to distance or time-to-contact measures in vehicle scenarios. In this work, we show that the risk model is also superior in warning persons with vision impairment about dangerous objects. Our experiments demonstrate that the warning accuracy of the risk model is 67% while both distance and time-to-contact measures reach only 51% accuracy for real-world data.
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