Robust Automated Driving in Extreme Weather (ROADVIEW)

复杂的环境和交通条件对联网和自动驾驶汽车的安全性和运行产生重大影响。天气不仅会影响车辆性能，还会影响道路基础设施，从而增加碰撞风险和交通场景变化。到目前为止，大多数自动驾驶汽车主要是在具有清晰能见度的最佳天气和道路条件下进行训练和测试的。然而，在被广泛接受和采用之前，这些系统必须证明它们在任何天气和路况下都同样可靠和准确。ROADVIEW集成了一个复杂的车载系统的系统，能够执行先进的环境和交通识别和预测，并确定CAV在现实环境（包括恶劣天气条件）中的适当行动方案。ROADVIEW开发了一种嵌入式车载感知和决策系统，该系统基于增强的传感、定位和改进的物体/人分类（包括脆弱的道路使用者）。ROADVIEW的突破性创新基于成本效益高的多传感器设置、传感器噪声建模和过滤、协同感知、模拟辅助方法测试以及不同场景和天气条件下的集成和演示，在项目结束时达到TRL 7。ROADVIEW实施了共同编程的欧洲伙伴关系“连接、合作和自动移动”（CCAM）伙伴关系，为开发更强大、故障安全、弹性和天气感知技术做出了贡献。该联盟是该领域的顶尖大学和研究机构、高科技中小企业和强大的行业领导者的完美结合。除了他们卓越的研究成果，联盟成员还带来了独特的测试场地和测试基础设施组合，从硬件测试设施、雨风洞到北极圈以北的测试轨道。

Complex environment and traffic conditions have major impact on the safety and operations of Connected and Automated Vehicles (CAVs). Weather affects not only the vehicle performance but also the roadway infrastructure, thereby increases the risk of collision and traffic scenarios variations. So far, most automated vehicles have been primarily trained and tested under optimal weather and road conditions with clear visibility. However, the systems will have to prove that they are equally reliable and accurate under any weather and road condition before they can see widespread acceptance and adoption. ROADVIEW integrates a complex in-vehicle system-of-systems able to perform advanced environment and traffic recognition and prediction and determine the appropriate course of action of a CAV in a real-world environment, including harsh weather conditions. ROADVIEW develops an embedded in-vehicle perception and decision making system based on enhanced sensing, localisation, and improved object/person classification (including vulnerable road users). ROADVIEW ground-breaking innovations are grounded on a cost-effective multisensory setup, sensor noise modelling and filtering, collaborative perception, testing by simulation-assisted methods and integration and demonstration under different scenarios and weather conditions, reaching TRL 7 by the end of the project. ROADVIEW implements the co-programmed European Partnership “Connected, Cooperative and Automated Mobility” (CCAM) partnership by contributing to the development of a more powerful, fail-safe, resilient and weather-aware technologies. The consortium is a perfect combination of leading universities in the field and research institutes, high tech SMEs, and strong industry leaders. Beyond their research excellence, the consortium members bring a unique portfolio of testing sites and testing infrastructure, ranging from hardware-testing facilities and rain and wind tunnels to test tracks north of the Arctic Circle.