Autonomous vehicles are expected to operate safely in real-life road conditions in the next years. Nevertheless, unanticipated events such as the existence of unexpected objects in the range of the road, can put safety at risk. The advancement of sensing and communication technologies and Internet of Things may facilitate the recognition of hazardous situations and information exchange in a cooperative driving scheme, providing new opportunities for the increase of collaborative situational awareness. Safe and unobtrusive visualization of the obtained information may nowadays be enabled through the adoption of novel Augmented Reality (AR) interfaces in the form of windshields. Motivated by these technological opportunities, we propose in this work a saliency-based distributed, cooperative obstacle detection and rendering scheme for increasing the driver's situational awareness through (i) automated obstacle detection, (ii) AR visualization and (iii) information sharing (upcoming potential dangers) with other connected vehicles or road infrastructure. An extensive evaluation study using a variety of real datasets for pothole detection showed that the proposed method provides favorable results and features compared to other recent and relevant approaches.

翻译：自主驾驶汽车预计在未来几年内能够在真实道路条件下安全运行。然而，诸如道路范围内出现意外物体等不可预见事件可能危及安全。传感与通信技术的进步以及物联网的发展，有助于在协同驾驶方案中识别危险情况并实现信息交换，为提升协作式态势感知能力提供了新机遇。通过采用新型风挡式增强现实接口，如今可以实现对所得信息的安全且无干扰的可视化呈现。基于这些技术机遇，本文提出了一种基于显著性的分布式协同障碍物检测与渲染方案，通过（i）自动化障碍物检测、（ii）增强现实可视化以及（iii）与其他联网车辆或道路基础设施共享信息（即将到来的潜在危险），来提升驾驶员的态势感知能力。使用多种真实数据集进行坑洞检测的广泛评估研究表明，与近期其他相关方法相比，所提方法在性能与特性方面均展现出优势。