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arXiv cs.AI· Eren Erdal Aksoy, Abu Mohammed Raisuddin, Thien-Thu Ngo, Eren Aydemir, Osman Tahir Ek\c{s}i, Paula Litkey, Petri Manninen, Heikki Hyyti, Jyri Maanp\"a\"a, Tarmo Kivioja, Tuomas Herranen, V\"ais\"anen 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·· 1 天前AI 评分31

雪天自动驾驶准备好了吗?极端天气下鲁棒自动驾驶的挑战

Are We Ready for Snow-tonomous Driving? Challenges Toward Robust Automated Driving in Extreme Weather

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欧盟 Horizon Europe 项目 ROADVIEW 基于四年大规模开发和多平台真实演示,总结出阻碍全天候自动驾驶的十项关键挑战,包括数据稀缺、域偏移、多模态感知局限、控制鲁棒性不足和验证缺口。研究聚焦雪、雨、雾等恶劣天气下感知与控制任务性能显著下降的问题,并给出未来研究与标准化方向。

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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

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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