This work presents an extended version of the Vehicle Energy Dataset (VED), which is a openly released large-scale dataset for vehicle energy consumption analysis. Compared with its original version, the extended VED (eVED) dataset is enhanced with accurate vehicle trip GPS coordinates, serving as a basis to associate the VED trip records with external information, e.g., road speed limit and intersections, from accessible map services to accumulate attributes that is essential in analyzing vehicle energy consumption. In particularly, we calibrate all the GPS trace records in the original VED data, upon which we associated the VED data with attributes extracted from the Geographic Information System (QGIS), the Overpass API, the Open Street Map API, and Google Maps API. The associated attributes include 12,609,170 records of road elevation, 12,203,044 of speed limit, 12,281,719 of speed limit with direction (in case the road is bi-directional), 584,551 of intersections, 429,638 of bus stop, 312,196 of crossings, 195,856 of traffic signals, 29,397 of stop signs, 5,848 of turning loops, 4,053 of railway crossings (level crossing), 3,554 of turning circles, and 2,938 of motorway junctions. With the accurate GPS coordinates and enriched features of the vehicle trip record, the obtained eVED dataset can provide a precise and abundant medium to feed a learning engine, especially a deep learning engine that is more demanding on data sufficiency and richness. Moreover, our software work for data calibration and enrichment can be reused to generate further vehicle trip datasets for specific user cases, contributing to deep insights into vehicle behaviors and traffic dynamics analyses. We anticipate that the eVED dataset and our data enrichment software can serve the academic and industrial automotive section as apparatus in developing future technologies.
翻译:这项工作展示了车辆能源数据集(VED)的扩大版,这是一个公开发布的用于车辆能源消耗分析的大规模大规模数据集。与最初版本相比,扩大的VED(eVED)数据集以精确的车辆出行全球定位系统全球定位系统坐标得到加强,作为将VED旅行记录与外部信息(例如,道路速度限制和交叉点)联系起来的基础,从无障碍的地图服务到积累分析车辆能源消耗所必不可少的特征。特别是,我们校准了VED原始数据中的所有全球定位系统跟踪记录,根据这些数据,我们将VED数据与从地理信息系统(QGIS)、AVPI、Opop Street Street API和Google Maps API提取的属性联系起来。相关的属性包括12 609 170条公路出行记录,12 203 044条速度限制和12 281 719条速度限制与方向(如果道路是双向的),584 551号路路路段、42938号路况、路段路况、路况、电子交通信号、195路段路段的交通信号、29395路段、路路段、路段、路段数据转换数据更新8路段、路路段、路段、路段的数据路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段路段路段、路段、路段、路段、路段、路段路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路段、路路路段、路段、路段、路