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Machine vision for automated inspection of railway traffic recordings

机译:机器视觉自动检查铁路交通记录

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For the 9000 train accidents reported each year in the European Union, the Recording Strip (RS) and Filling-Card (FC) related to the train activities represent the only usable evidence for SNCF (the French railway operator) and most of National authorities. More precisely, the RS contains information about the train journey, speed and related Driving Events (DE) such as emergency brakes, while the FC gives details on the departure/arrival stations. In this context a complete checking for 100% of the RS was recently voted by French law enforcement authorities (instead of the 5% currently performed), which raised the question of an automated and efficient inspection of this huge amount of recordings. To do so, we propose a machine vision prototype, constituted with cassettes receiving RS and FC to be digitized Then, a video analysis module firstly determines the type of RS among eight possible types; time/speed curves are secondly extracted to estimate the covered distance, speed and stops, while associated DE are finally detected using convolution process. A detailed evaluation on 15 RS (8000 kilometers and 7000 DE) shows very good results (100% of good detections for the type of band, only 0.28% of non detections for the DE). An exhaustive evaluation on a panel of about 100 RS constitutes the perspectives of the work.
机译:对于欧盟每年报告的9000起火车事故,与火车活动有关的记录带(RS)和加油卡(FC)是SNCF(法国铁路运营商)和大多数国家当局的唯一可用证据。更准确地说,RS包含有关火车行程,速度和相关驾驶事件(DE)(例如紧急制动)的信息,而FC则提供了出发/到达车站的详细信息。在这种情况下,法国执法机构最近对100%的RS进行了全面检查(而不是目前执行的5%),从而提出了自动,高效检查大量录音的问题。为此,我们提出了一种机器视觉原型,该原型由接收RS和FC的盒式磁带组成,然后将其数字化。然后,视频分析模块首先在八种可能的类型中确定RS的类型。然后提取时间/速度曲线以估计覆盖距离,速度和停靠点,同时最终使用卷积过程检测相关的DE。对15个RS(8000公里和7000 DE)的详细评估显示出非常好的结果(对频段类型的良好检测为100%,对于DE的未检测仅为0.28%)。在约100 RS的面板上进行详尽的评估构成了作品的观点。

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