ROADVIEW 项目解析极端天气下自动驾驶面临的十大挑战
Are We Ready for Snow-tonomous Driving? Challenges Toward Robust Automated Driving in Extreme Weather
欧盟 Horizon Europe 资助的 ROADVIEW 项目团队总结四年大规模研发与多平台真实路测的经验，梳理出阻碍恶劣天气下自动驾驶落地的十大关键挑战，涵盖数据稀缺、域偏移、多模态感知局限、控制鲁棒性与验证缺口等。自动驾驶研发长期聚焦晴好天气场景，雪、雨、雾条件仍是导致感知与控制性能显著下降的主要障碍。论文为未来研究与标准化方向提供了参考。
Authors:Eren Erdal Aksoy, Abu Mohammed Raisuddin, Thien-Thu Ngo, Eren Aydemir, Osman Tahir Ekşi, Paula Litkey, Petri Manninen, Heikki Hyyti, Jyri Maanpää, Tarmo Kivioja, Tuomas Herranen, Väisänen Sofie, Niemi Kalle, Isabelle Morvan, Pierre Duthon, Ian Marsh, Martin Sanfridson, Henrik Toss, Thanh Bui, Yuri Poledna, Maikol Funk Drechsler, Mikko Tarkiainen, Matti Kutila, Topi Miekkala, Stefan Parzefall, Valentina Donzella, Pak Hung Chan, Sogol Kharrazi, Mario Ceccarelli
Abstract:Automated driving has gained remarkable momentum over the past decade, with both industry and academia investing substantial resources in developing perception and control solutions to advance vehicle autonomy. However, these efforts have largely focused on clear-weather scenarios, leaving harsh conditions, such as snow, rain, and fog, comparatively understudied. As a result, inclement weather remains one of the most significant hurdles for autonomous vehicles, often leading to substantial performance degradation in downstream perception and control tasks.
In this paper, we present insights from the EU-funded Horizon Europe project ROADVIEW, which aims to develop robust, weather-aware perception and control modules for connected and automated vehicles operating under severe conditions, including snow, rain, and fog. Drawing on four years of large-scale development and real-world demonstrations across multiple vehicle platforms in different locations, we identify ten key challenges that hinder the development of weather-resilient autonomy, including data scarcity, domain shifts, limitations in multimodal perception, control robustness, and validation gaps, among others. We summarize these challenges and lessons learned toward enabling reliable snow-autonomous driving, highlighting critical directions for future research and standardization.
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV) |
| Cite as: | arXiv:2611.15217 [cs.RO] |
| (or arXiv:2611.15217v1 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2611.15217 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Eren Aksoy [view email]
[v1]
Wed, 11 Nov 2026 09:10:13 UTC (67,911 KB)
来源：arXiv cs.AI · arxiv.org