Semantic Tagging of CAN and Dash Camera Data from Naturalistic Drives

Kate Sanborn, Alex Richardson, J. Sprinkle
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引用次数: 1

Abstract

The goal of this paper is to automate the creation of naturalistic driving data sets of dash camera footage that is tagged with information captured from the vehicle's Controller Area Network (CAN) bus, using only a standard dash camera and CAN reader. The paper describes pairing and synchronizing dash camera videos with CAN bus data gathered from a vehicle with advanced driver assistance features. That data is then used to label the dash camera videos with telemetric information. Further, with the synchronized videos and CAN bus data, it is possible to identify video clips with meaningful events such as following a lead vehicle, cars passing in front of the vehicle, braking, turns, etc. This method of data-gathering and data set creation is significantly cheaper and more scalable than other driving data sets, while having competitive quality in terms of telemetric attributes. This could significantly increase the quantity, diversity, and in turn, quality of driving data sets in the future.
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自然驱动中CAN和Dash相机数据的语义标注
本文的目标是自动创建自然的驾驶数据集,这些数据集是用从车辆的控制器区域网络(CAN)总线捕获的信息标记的,仅使用标准的dash摄像头和CAN读取器。本文介绍了从具有高级驾驶员辅助功能的车辆收集的CAN总线数据与行车记录仪视频的配对和同步。然后,这些数据被用来给行车记录仪的视频贴上遥测信息的标签。此外,通过同步视频和CAN总线数据,可以识别具有重要事件的视频片段,例如跟随领先车辆,车辆前方经过,制动,转弯等。与其他驾驶数据集相比,这种数据收集和数据集创建方法的成本要低得多,而且更具可扩展性,同时在遥测属性方面具有竞争力。这将显著增加未来驾驶数据集的数量、多样性,进而提高质量。
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