As autonomous vehicles continue to revolutionize transportation, addressing challenges posed by adverse weather conditions, particularly during winter, becomes paramount for ensuring safe and efficient operations. One of the most important aspects of a road safety inspection during adverse weather is when a limited lane width can reduce the capacity of the road and raise the risk of serious accidents involving autonomous vehicles. In this research, a method for improving driving challenges on roads in winter conditions, with a model that segments and estimates the width of the road from the perspectives of Uncrewed aerial vehicles and autonomous vehicles. The proposed approach in this article is needed to empower self-driving cars with up-to-date and accurate insights, enhancing their adaptability and decision-making capabilities in winter landscapes.

翻译：随着自动驾驶车辆持续革新交通运输领域，应对恶劣天气条件（尤其是冬季）带来的挑战，对于确保安全高效运行至关重要。恶劣天气下道路安全检查最重要的方面之一，是当有限的车道宽度可能降低道路通行能力并增加涉及自动驾驶车辆的严重事故风险时。本研究提出了一种改善冬季道路驾驶挑战的方法，通过从无人机和自动驾驶车辆的视角对道路进行分割和宽度估计的模型。本文提出的方法旨在为自动驾驶汽车提供最新且准确的洞察，从而增强其在冬季环境中的适应性和决策能力。