U&I Aware: A Framework Using Data Mining and Collision Detection to Increase Awareness for Intersection Users

Flora D. Salim, S. Loke, A. Rakotonirainy, S. Krishnaswamy
{"title":"U&I Aware: A Framework Using Data Mining and Collision Detection to Increase Awareness for Intersection Users","authors":"Flora D. Salim, S. Loke, A. Rakotonirainy, S. Krishnaswamy","doi":"10.1109/AINAW.2007.360","DOIUrl":null,"url":null,"abstract":"An intersection safety system should adapt to the particular characteristics that identify an intersection, by mining traffic and collision data. Given the large amount of sensor data that are obtained for intersections and from sensor-equipped cars, analysis and learning of such data is essential. This paper presents a new method to improve safety at intersections using a combination of a mathematical based collision detection algorithm and data mining. A number of scenarios at a simulated intersection are explored with encouraging results from our data mining implementation. The results suggest that our approach can help improve situation awareness and automate understanding of intersections, which, in turn, can be used to increase safety at intersections.","PeriodicalId":338799,"journal":{"name":"21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)","volume":"444 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINAW.2007.360","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19

Abstract

An intersection safety system should adapt to the particular characteristics that identify an intersection, by mining traffic and collision data. Given the large amount of sensor data that are obtained for intersections and from sensor-equipped cars, analysis and learning of such data is essential. This paper presents a new method to improve safety at intersections using a combination of a mathematical based collision detection algorithm and data mining. A number of scenarios at a simulated intersection are explored with encouraging results from our data mining implementation. The results suggest that our approach can help improve situation awareness and automate understanding of intersections, which, in turn, can be used to increase safety at intersections.
U&I Aware:一个使用数据挖掘和碰撞检测来提高交叉路口用户意识的框架
交叉口安全系统应通过挖掘交通和碰撞数据来适应交叉口的特殊特征。考虑到从十字路口和配备传感器的汽车中获得的大量传感器数据,对这些数据的分析和学习至关重要。本文提出了一种将基于数学的碰撞检测算法与数据挖掘相结合来提高交叉口安全性的新方法。我们的数据挖掘实现探索了模拟十字路口的许多场景,并获得了令人鼓舞的结果。结果表明,我们的方法可以帮助提高交叉口的态势感知和自动理解,从而可以用于提高交叉口的安全性。
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 求助全文
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