Validity of GPS data in driving cycles

IF 2.3 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Intelligent Transport Systems Pub Date : 2024-10-13 DOI:10.1049/itr2.12574
Harry Smith II, Suhail Akhtar, Brian Caulfield, Margaret O'Mahony
{"title":"Validity of GPS data in driving cycles","authors":"Harry Smith II,&nbsp;Suhail Akhtar,&nbsp;Brian Caulfield,&nbsp;Margaret O'Mahony","doi":"10.1049/itr2.12574","DOIUrl":null,"url":null,"abstract":"<p>There is continuous research into driving cycles (DCs) as researchers across the globe seek to define driving characteristics, energy consumption, and emissions in a local context. For decades, data collection for the development of DCs has been conducted in three ways: chase car, instrumented vehicle, or a combination of both. Many studies have moved on to cheap and easily available global positioning system (GPS) technology, while others record vehicle data directly through the on-board diagnostics (OBD) port. However, there are major limitations to GPS data collection such as frequent inaccuracies and loss of coverage in urban environments. For this reason, both OBD and GPS vehicle speed data have been collected. Then, the recorded data has been analysed to capture any differences in sampling rates and dropping data. Finally, basic DCs were created from smoothed GPS and OBD data and compared. DCs were developed with a microtrip-based method, and a relative error term was used to compare candidate DCs to the collected data. DCs were compared based on kinematic characteristic parameters that are most used in the field. The results of this study could be used to assess the validity of GPS-based DCs compared to OBD cycles using low-cost devices.</p>","PeriodicalId":50381,"journal":{"name":"IET Intelligent Transport Systems","volume":"18 S1","pages":"3034-3040"},"PeriodicalIF":2.3000,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/itr2.12574","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Intelligent Transport Systems","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/itr2.12574","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

There is continuous research into driving cycles (DCs) as researchers across the globe seek to define driving characteristics, energy consumption, and emissions in a local context. For decades, data collection for the development of DCs has been conducted in three ways: chase car, instrumented vehicle, or a combination of both. Many studies have moved on to cheap and easily available global positioning system (GPS) technology, while others record vehicle data directly through the on-board diagnostics (OBD) port. However, there are major limitations to GPS data collection such as frequent inaccuracies and loss of coverage in urban environments. For this reason, both OBD and GPS vehicle speed data have been collected. Then, the recorded data has been analysed to capture any differences in sampling rates and dropping data. Finally, basic DCs were created from smoothed GPS and OBD data and compared. DCs were developed with a microtrip-based method, and a relative error term was used to compare candidate DCs to the collected data. DCs were compared based on kinematic characteristic parameters that are most used in the field. The results of this study could be used to assess the validity of GPS-based DCs compared to OBD cycles using low-cost devices.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
驾驶周期中 GPS 数据的有效性
随着全球各地的研究人员试图在当地背景下定义驾驶特性、能耗和排放,对驾驶循环(DCs)的研究也在不断进行。几十年来,DCs开发的数据收集一直以三种方式进行:追逐车、仪表车或两者的组合。许多研究已经转向廉价且容易获得的全球定位系统(GPS)技术,而其他研究则直接通过车载诊断(OBD)端口记录车辆数据。然而,GPS数据收集存在主要限制,例如在城市环境中经常出现不准确和失去覆盖范围。因此,OBD和GPS车辆速度数据都被收集。然后,对记录的数据进行分析,以捕获采样率和下降数据的任何差异。最后,对GPS和OBD数据进行平滑处理,建立基本dc,并进行比较。采用基于微行程的方法开发DCs,并使用相对误差项将候选DCs与收集的数据进行比较。根据现场最常用的运动学特征参数对DCs进行了比较。本研究的结果可用于评估基于gps的DCs与使用低成本设备的OBD周期的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
期刊最新文献
Evaluation of automated driving safety in urban mixed traffic environments Development of an enhanced base unit generation framework for predicting demand in free-floating micro-mobility Review of driver behaviour modelling for highway on-ramp merging Driving range estimation for electric bus based on atomic orbital search and back propagation neural network Intersection decision making for autonomous vehicles based on improved PPO algorithm
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1