Implicit Personalization in Driving Assistance: State-of-the-Art and Open Issues

被引:35
|
作者
Yi, Dewei [1 ]
Su, Jinya [2 ]
Hu, Liang [2 ]
Liu, Cunjia [3 ]
Quddus, Mohammed [4 ]
Dianati, Mehrdad [1 ]
Chen, Wen-Hua [3 ]
机构
[1] Univ Warwick, Warwick Mfg Grp, Coventry CV4 7AL, W Midlands, England
[2] Univ Essex, Sch Comp Sci & Elect Engn, Colchester CO4 3SQ, Essex, England
[3] Loughborough Univ, Dept Aeronaut & Automot Engn, Loughborough LE11 3TU, Leics, England
[4] Loughborough Univ, Sch Civil & Bldg Engn, Loughborough LE11 3TU, Leics, England
来源
基金
英国工程与自然科学研究理事会;
关键词
Intelligent vehicles; driver behavior analysis; personalization; Advanced Driver Assistance Systems; INTELLIGENT-TRANSPORTATION-SYSTEMS; HIDDEN MARKOV-MODELS; IN-VEHICLE; DRIVER ASSISTANCE; UNCERTAIN ENVIRONMENTS; LOGISTIC-REGRESSION; CRUISE CONTROL; BEHAVIOR; ALGORITHM; CLASSIFICATION;
D O I
10.1109/TIV.2019.2960935
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent decades, driving assistance systems have been evolving towards personalization for adapting to different drivers. With the consideration of driving preferences and driver characteristics, these systems become more acceptable and trustworthy. This article presents a survey on recent advances in implicit personalized driving assistance. We classify the collection of work into three main categories: 1) personalized Safe Driving Systems (SDS), 2) personalized Driver Monitoring Systems (DMS), and 3) personalized In-vehicle Information Systems (IVIS). For each category, we provide a comprehensive review of current applications and related techniques along with the discussion of industry status, benefits of personalization, application prospects, and future focal points. Both relevant driving datasets and open issues about personalized driving assistance are discussed to facilitate future research. By creating an organized categorization of the field, we hope that this survey could not only support future research and the development of new technologies for personalized driving assistance but also facilitate the application of these techniques within the driving automation community.
引用
收藏
页码:397 / 413
页数:17
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