.png){kind=icon}
返回
Driver Identification Through Formal Methods
.png){kind=icon}
PRE
AI
DOI：10.1109/TITS.2021.3055347.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recently, several research efforts have been focused on automotive safety, due to the increasing technology embedded in our vehicles. Research community have produced different methods aimed, for instance, to profile driver behaviour, starting from a feature set gathered by the vehicle. The provided methods are mainly machine learning-based: these solutions, as largely demonstrate in literature, suffer from several issues, due to the context variability but also because they are not able to provide a rational reason for the specific prediction. To overcome these limitations, in this paper we propose a novel model checking based approach to driver identification. Furthermore, a novel automatic procedure able to infer a logical representation of the driver behaviour is discussed. Two real-world datasets for the evaluation of the proposed method are considered, obtaining interesting results in driver identification.
Keyword:
Vehicles
Hidden Markov models
Model checking
Feature extraction
Automobiles
Brakes
Data models
Automotive
formal methods
model checking
safety
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
8.4
论文数:
9.9K
被引数:
6.3W
机构
引用论文
.png){kind=icon}
分享收藏
查看更多内容