检索结果-南通市图书馆

Towards trustworthy multi-modal motion prediction:Holistic evaluation and interpretability of outputs

CAAI Transactions on Intelligence Technology 2024年第3期9卷 557-572页

作者： Sandra Carrasco Limeros Sylwia Majchrowska Joakim Johnander Christoffer Petersson MiguelÁngel Sotelo david fernández llorca Computer Engineering Department Polytechnic SchoolUniversity of AlcalaMadridSpain AI Sweden GothenburgSweden Zenseact AB GothenburgSweden Department of Electrical Engineering Linköping UniversityLinköpingSweden Chalmers University of Technology GothenburgSweden European Commission Joint Research CentreSevilleSpain

Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path *** task is very complex,as the behaviour of road agents depends on many factors and the number of possible future trajectories can be consid-erable(multi-modal).Most prior approaches proposed to address multi-modal motion prediction are based on complex machine learning systems that have limited ***,the metrics used in current benchmarks do not evaluate all aspects of the problem,such as the diversity and admissibility of the *** authors aim to advance towards the design of trustworthy motion prediction systems,based on some of the re-quirements for the design of Trustworthy Artificial *** focus is on evaluation criteria,robustness,and interpretability of ***,the evaluation metrics are comprehensively analysed,the main gaps of current benchmarks are identified,and a new holistic evaluation framework is ***,a method for the assessment of spatial and temporal robustness is introduced by simulating noise in the perception *** enhance the interpretability of the outputs and generate more balanced results in the proposed evaluation framework,an intent prediction layer that can be attached to multi-modal motion prediction models is *** effectiveness of this approach is assessed through a survey that explores different elements in the visualisation of the multi-modal trajectories and *** proposed approach and findings make a significant contribution to the development of trustworthy motion prediction systems for autono-mous vehicles,advancing the field towards greater safety and reliability.

关键词： autonomous vehicles evaluation interpretability multi-modal motion prediction robustness trustworthy AI

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：