Traffic analysis is crucial for urban operations and planning, while the availability of dense urban traffic data beyond loop detectors is still scarce. We present a large-scale floating vehicle dataset of per-street segment traffic information, Metropolitan Segment Traffic Speeds from Massive Floating Car Data in 10 Cities (MeTS-10), available for 10 global cities with a 15-minute resolution for collection periods ranging between 108 and 361 days in 2019-2021 and covering more than 1500 square kilometers per metropolitan area. MeTS-10 features traffic speed information at all street levels from main arterials to local streets for Antwerp, Bangkok, Barcelona, Berlin, Chicago, Istanbul, London, Madrid, Melbourne and Moscow. The dataset leverages the industrial-scale floating vehicle Traffic4cast data with speeds and vehicle counts provided in a privacy-preserving spatio-temporal aggregation. We detail the efficient matching approach mapping the data to the OpenStreetMap road graph. We evaluate the dataset by comparing it with publicly available stationary vehicle detector data (for Berlin, London, and Madrid) and the Uber traffic speed dataset (for Barcelona, Berlin, and London). The comparison highlights the differences across datasets in spatio-temporal coverage and variations in the reported traffic caused by the binning method. MeTS-10 enables novel, city-wide analysis of mobility and traffic patterns for ten major world cities, overcoming current limitations of spatially sparse vehicle detector data. The large spatial and temporal coverage offers an opportunity for joining the MeTS-10 with other datasets, such as traffic surveys in traffic planning studies or vehicle detector data in traffic control settings.

翻译：交通分析对城市运行与规划至关重要，但除环形线圈检测器外，高密度城市交通数据的获取仍十分有限。我们呈现了一个大规模浮动车数据集，包含逐街道路段交通信息——基于10个城市大规模浮动车数据构建的城市路段交通速度数据集（MeTS-10），该数据集覆盖2019-2021年间108至361天的采集周期，以15分钟为分辨率覆盖全球10个城市，每个都市圈面积超过1500平方公里。MeTS-10提供了安特卫普、曼谷、巴塞罗那、柏林、芝加哥、伊斯坦布尔、伦敦、马德里、墨尔本和莫斯科等城市从主干道到地方街道所有等级路段的交通速度信息。该数据集利用工业级浮动车Traffic4cast数据，通过保护隐私的时空聚合方式提供车速与车辆计数信息。我们详细阐述了将数据映射至OpenStreetMap道路图的高效匹配方法，并通过与公开的固定车辆检测器数据（柏林、伦敦、马德里）及优步交通速度数据集（巴塞罗那、柏林、伦敦）进行对比评估。对比结果揭示了数据集间时空覆盖范围的差异，以及由分箱方法导致的交通报告值差异。MeTS-10突破了当前空间稀疏的车辆检测器数据局限，实现了对全球十大主要城市移动性与交通模式的新型全域分析。其广阔的空间与时间覆盖范围为将MeTS-10与其他数据集（如交通规划研究中的交通调查数据、交通控制场景下的车辆检测器数据）进行联合分析提供了契机。