Determination of extreme values in autonomous driving based on multifractals and dynamic scaling

J. Z. Szabó, P. Bakucz
{"title":"Determination of extreme values in autonomous driving based on multifractals and dynamic scaling","authors":"J. Z. Szabó, P. Bakucz","doi":"10.1109/SACI51354.2021.9465582","DOIUrl":null,"url":null,"abstract":"This talk will be a review of two methods based on the dynamic scaling and multifractal statistic of corner radar sensor time series with the ultimate aim to estimate extreme values for highly autonomous driving test signals. It is assumed that the extremity of the influencing parameter of the sensor correlates with the probability of collision of the vehicle.The method of dynamic scaling is derived originally from the surface or interface physics. The sensor parameter time series can be considered as fractal surface or interface and grows adequately to a specified scale invariant dynamical equation. It is demonstrated that multifractal statistic can be useful searching for statistical analogous time series, disposed similar multifractal spectrum as the original sensor time series.","PeriodicalId":321907,"journal":{"name":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"44 8","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI51354.2021.9465582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This talk will be a review of two methods based on the dynamic scaling and multifractal statistic of corner radar sensor time series with the ultimate aim to estimate extreme values for highly autonomous driving test signals. It is assumed that the extremity of the influencing parameter of the sensor correlates with the probability of collision of the vehicle.The method of dynamic scaling is derived originally from the surface or interface physics. The sensor parameter time series can be considered as fractal surface or interface and grows adequately to a specified scale invariant dynamical equation. It is demonstrated that multifractal statistic can be useful searching for statistical analogous time series, disposed similar multifractal spectrum as the original sensor time series.
基于多重分形和动态标度的自动驾驶极值确定
本讲座将回顾两种基于转角雷达传感器时间序列的动态标度和多重分形统计的方法,最终目的是估计高度自动驾驶测试信号的极值。假设传感器影响参数的极值与车辆的碰撞概率相关。动态标度的方法最初来源于表面或界面物理。传感器参数时间序列可以看作是分形曲面或分形界面,并充分成长为指定尺度不变的动力学方程。结果表明,多重分形统计量可以有效地搜索统计相似的时间序列,处理出与原始传感器时间序列相似的多重分形谱。
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