为铁路自动驾驶研发超700万标注数据集，助力智能感知
A Multi-Sensor Dataset for Monitoring the Operational Environment of Rail Vehicles
- 构建多传感器融合数据集，覆盖多种运行场景
- 含700万+高质量标注，涵盖铁路与通用物体
- 适合铁路AI感知研究者使用，支持自动化系统开发
可靠的环境监测对自动化铁路系统（涵盖部分自动化至完全自动化）的安全高效运行至关重要。人工智能在实时检测、分类并响应潜在风险中发挥核心作用。开发此类AI感知系统需大量精确标注的数据用于训练与验证。在德国数字铁路计划（Digitale Schiene Deutschland, DSD）框架下，DB InfraGO AG与understandAI GmbH共同开发了一套面向铁路环境感知的多传感器数据集。该数据集包含超过700万条高质量标注，涵盖铁路特定及通用感知对象，并在不同运行场景下采集。目前数据集已可向DB InfraGO AG申请，是推动铁路领域AI驱动环境监测的重要资源。
原文摘要 · Abstract (English)
Reliable environment monitoring is essential for the safe and efficient operation of automated railway systems, covering all Grades of Automation (GoA), from partially automated (GoA2) to fully automated operation (GoA4). Artificial Intelligence (AI) plays a central role in enabling these systems to detect, classify, and react to potential hazards in real time. The development of such AI-based perception systems requires large volumes of accurately annotated data for training and validation. Within the Digitale Schiene Deutschland (DSD) program, DB InfraGO AG and understandAI GmbH have developed a comprehensive multi- sensor dataset tailored to the needs of railway environment perception. This dataset contains over 7 million high-quality annotations of both railway-specific and general perception objects, captured under varying operational scenarios. The finalized dataset can now be requested at the DB InfraGO AG and serve as a valuable resource for advancing AI-driven environment monitoring in the railway domain.
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