确定横截面载荷密度的车辆轨迹可视化分析

Q3 Engineering Transactions on Transport Sciences Pub Date : 2019-07-24 DOI:10.5507/TOTS.2019.002
Roman Juránek, Jakub Špaňhel, Jakub Sochor, A. Herout, J. Novák
{"title":"确定横截面载荷密度的车辆轨迹可视化分析","authors":"Roman Juránek, Jakub Špaňhel, Jakub Sochor, A. Herout, J. Novák","doi":"10.5507/TOTS.2019.002","DOIUrl":null,"url":null,"abstract":"The goal of this work was to analyze the behavior of drivers on third class roads with and without horizontal lane marking. The roads have low traffic volume, and therefore a conventional short-term study would not be able to provide enough data. We used recording devices for long-term (weeks) recording of the traffic and designed a system for analyzing the trajectories of the vehicles by means of computer vision. We collected a dataset at 6 distinct locations, containing 1 010 hours of day-time video. In this dataset, we tracked over 12 000 cars and analyzed their trajectories. The results show that the selected approach is functional and provides information that would be difficult to mine otherwise. After application of the horizontal markings, the drivers slowed down and shifted slightly towards the outer side of the curve.","PeriodicalId":52273,"journal":{"name":"Transactions on Transport Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visual Analysis of Vehicle Trajectories for Determining Cross-Sectional Load Density\",\"authors\":\"Roman Juránek, Jakub Špaňhel, Jakub Sochor, A. Herout, J. Novák\",\"doi\":\"10.5507/TOTS.2019.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The goal of this work was to analyze the behavior of drivers on third class roads with and without horizontal lane marking. The roads have low traffic volume, and therefore a conventional short-term study would not be able to provide enough data. We used recording devices for long-term (weeks) recording of the traffic and designed a system for analyzing the trajectories of the vehicles by means of computer vision. We collected a dataset at 6 distinct locations, containing 1 010 hours of day-time video. In this dataset, we tracked over 12 000 cars and analyzed their trajectories. The results show that the selected approach is functional and provides information that would be difficult to mine otherwise. After application of the horizontal markings, the drivers slowed down and shifted slightly towards the outer side of the curve.\",\"PeriodicalId\":52273,\"journal\":{\"name\":\"Transactions on Transport Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transactions on Transport Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5507/TOTS.2019.002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions on Transport Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5507/TOTS.2019.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

摘要

这项工作的目的是分析驾驶员在有和没有水平车道标记的三级道路上的行为。道路交通量低,因此传统的短期研究将无法提供足够的数据。我们使用记录设备对交通进行了长期(数周)的记录,并设计了一个系统,通过计算机视觉来分析车辆的轨迹。我们在6个不同的地点收集了一个数据集,包含1010小时的日间视频。在这个数据集中,我们跟踪了超过12000辆汽车并分析了它们的轨迹。结果表明,所选择的方法是功能性的,并提供了难以挖掘的信息。在应用水平标记后,驾驶员减速并向曲线外侧轻微移动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Visual Analysis of Vehicle Trajectories for Determining Cross-Sectional Load Density
The goal of this work was to analyze the behavior of drivers on third class roads with and without horizontal lane marking. The roads have low traffic volume, and therefore a conventional short-term study would not be able to provide enough data. We used recording devices for long-term (weeks) recording of the traffic and designed a system for analyzing the trajectories of the vehicles by means of computer vision. We collected a dataset at 6 distinct locations, containing 1 010 hours of day-time video. In this dataset, we tracked over 12 000 cars and analyzed their trajectories. The results show that the selected approach is functional and provides information that would be difficult to mine otherwise. After application of the horizontal markings, the drivers slowed down and shifted slightly towards the outer side of the curve.
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
Transactions on Transport Sciences
Transactions on Transport Sciences Environmental Science-Management, Monitoring, Policy and Law
CiteScore
1.40
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊最新文献
Evaluation of Shared Space Feasibility Based on Traffic-Engineering Data Exploring Lane Changing Dynamics: A Comprehensive Review of Modeling Approaches, Traffic Impacts, and Future Directions in Traffic Engineering Research Between Investment Risk and Economic Benefit: Potential Analysis for the Reactivation of the Hershey Railway in Cuba Consumer Preferences and Determinants of Transportation Mode Choice Behaviors in the Era of Autonomous Vehicles A Comprehensive Evaluation and Mitigation Approaches for Traffic-Related Noise in the Sungai Long Region, Malaysia
×
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