Parametric trajectory prediction of surrounding vehicles

C. Kang, S. Jeon, Seung-Hi Lee, C. Chung
{"title":"Parametric trajectory prediction of surrounding vehicles","authors":"C. Kang, S. Jeon, Seung-Hi Lee, C. Chung","doi":"10.1109/ICVES.2017.7991896","DOIUrl":null,"url":null,"abstract":"For advanced driver assistance system (ADAS) which are related to risk assessment or collision avoidance, predicting object vehicle's path is needed beyond the precise and reliable sensor data to improve the performance of path prediction. This paper proposes an object vehicle path prediction method using parametric interpolation. To obtain a precise and reliable sensor data, multirate sensor data fusion was applied. After that, by using the parametric interpolation, we can predict the object vehicle's motion based on a fused relative vehicle motion data. The performance of the object vehicle path prediction method was validated via simulation and, experimental test with DELPHI 77Hz long range radar and Mobileye camera.","PeriodicalId":303389,"journal":{"name":"2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVES.2017.7991896","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

For advanced driver assistance system (ADAS) which are related to risk assessment or collision avoidance, predicting object vehicle's path is needed beyond the precise and reliable sensor data to improve the performance of path prediction. This paper proposes an object vehicle path prediction method using parametric interpolation. To obtain a precise and reliable sensor data, multirate sensor data fusion was applied. After that, by using the parametric interpolation, we can predict the object vehicle's motion based on a fused relative vehicle motion data. The performance of the object vehicle path prediction method was validated via simulation and, experimental test with DELPHI 77Hz long range radar and Mobileye camera.
周边车辆参数轨迹预测
对于与风险评估或避碰相关的高级驾驶辅助系统(ADAS),除了需要精确可靠的传感器数据外,还需要预测目标车辆的路径,以提高路径预测的性能。提出了一种基于参数插值的目标车辆路径预测方法。为了获得精确可靠的传感器数据,采用多速率传感器数据融合技术。然后,通过参数插值,基于融合的相对车辆运动数据预测目标车辆的运动。通过DELPHI 77Hz远程雷达和Mobileye相机的仿真和实验验证了目标车辆路径预测方法的性能。
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:604180095
Book学术官方微信