基于车辆传感器数据的随机森林公交运行状态分类

T. Yonezawa, Ismail Arai, Toyokazu Akiyama, K. Fujikawa
{"title":"基于车辆传感器数据的随机森林公交运行状态分类","authors":"T. Yonezawa, Ismail Arai, Toyokazu Akiyama, K. Fujikawa","doi":"10.1109/PERCOMW.2018.8480291","DOIUrl":null,"url":null,"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.","PeriodicalId":190096,"journal":{"name":"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Random Forest Based Bus Operation States Classification Using Vehicle Sensor Data\",\"authors\":\"T. Yonezawa, Ismail Arai, Toyokazu Akiyama, K. Fujikawa\",\"doi\":\"10.1109/PERCOMW.2018.8480291\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":190096,\"journal\":{\"name\":\"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PERCOMW.2018.8480291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2018.8480291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

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。
Random Forest Based Bus Operation States Classification Using Vehicle Sensor Data
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信