The introduction of Highly Automated Vehicles (HAVs) has the potential to increase the independence of blind and visually impaired people (BVIPs). However, ensuring safety and situation awareness when exiting these vehicles in unfamiliar environments remains challenging. To address this, we conducted an interactive workshop with N=5 BVIPs to identify their information needs when exiting an HAV and evaluated three prior-developed low-fidelity prototypes. The insights from this workshop guided the development of PathFinder, a multimodal interface combining visual, auditory, and tactile modalities tailored to BVIP's unique needs. In a three-factorial within-between-subject study with N=16 BVIPs, we evaluated PathFinder against an auditory-only baseline in urban and rural scenarios. PathFinder significantly reduced mental demand and maintained high perceived safety in both scenarios, while the auditory baseline led to lower perceived safety in the urban scenario compared to the rural one. Qualitative feedback further supported PathFinder's effectiveness in providing spatial orientation during exiting.

翻译：高度自动化车辆（HAVs）的引入有望提升盲人与视障人士（BVIPs）的独立性。然而，在陌生环境中离开此类车辆时，如何确保安全与情境感知仍具挑战。为此，我们与N=5名BVIPs开展互动研讨会，明确其离开HAV时的信息需求，并评估了三个先前开发的低保真原型。基于研讨会所得洞见，我们开发了PathFinder——一种融合视觉、听觉与触觉模态的多模态界面，专为BVIPs的特殊需求量身定制。通过一项包含N=16名BVIPs的三因素混合设计研究，我们在城市场景与乡村场景中将PathFinder与纯听觉基线系统进行对比评估。结果显示，PathFinder在两种场景中均显著降低认知负荷并保持较高的感知安全性；而纯听觉基线在城市场景中的感知安全性显著低于乡村场景。质性反馈进一步证实了PathFinder在离车过程中提供空间导向的有效性。