Random Forest Based Bus Operation States Classification Using Vehicle Sensor Data

T. Yonezawa, Ismail Arai, Toyokazu Akiyama, K. Fujikawa
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引用次数: 4

Abstract

In bus companies, it is important for an operation manager to grasp operation states of vehicles from a viewpoint of safety management and improving an operation efficiency. Currently, for allowing operation managers to grasp operation states of vehicles, drivers should record operation states by man- ually operating a recorder called ”Digital-tachograph.” However, operating the digital tachograph is a heavy burden to the driver. In addition, the records may have driver’s human error. In order to solve these problems and to realize efficient operation, we propose a method for automatic classification of operation states using sensor data obtained from buses. We implemented a classifier using Random Forest with the sensor data. As a results of experiments, the correct answer rate was 0.92 or more in each condition unless it was irregular operation.
基于车辆传感器数据的随机森林公交运行状态分类
在公交公司中,从安全管理和提高运营效率的角度把握车辆的运行状态是运营管理者的重要任务。目前,为了让运营管理者掌握车辆的运行状态,司机应该通过人工操作一种名为“数字行车记录仪”的记录仪来记录车辆的运行状态。然而,操作数字行车记录仪对司机来说是一个沉重的负担。此外,记录可能有司机的人为失误。为了解决这些问题,实现高效运行,我们提出了一种利用公交车传感器数据对运行状态进行自动分类的方法。我们使用随机森林对传感器数据实现了分类器。实验结果表明,除不规则操作外,每种情况下的正确率均在0.92以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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