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Implicit personalization in driving assistance : state-of-the-art and open issues
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Yi, Dewei, Su, Jinya, Hu, Liang, Liu, Cunjia, Quddus, Mohammed, Dianati, Mehrdad and Chen, Wen-Hua (2020) Implicit personalization in driving assistance : state-of-the-art and open issues. IEEE Transactions on Intelligent Vehicles, 5 (3). pp. 397-413. doi:10.1109/TIV.2019.2960935
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WRAP-implicit-personalization-driving-assistance-state-of-the-art-open-issues-Yi-2019.pdf - Accepted Version - Requires a PDF viewer. Download (1716Kb) | Preview |
Official URL: https://doi.org/10.1109/TIV.2019.2960935
Abstract
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.
| Item Type: | Journal Article | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TE Highway engineering. Roads and pavements T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
| Library of Congress Subject Headings (LCSH): | Automated vehicles, Intelligent transportation systems, Automobiles -- Automatic control, Automobile driving -- Human factors, Human-computer interaction, Driver assistance systems | ||||||||
| Journal or Publication Title: | IEEE Transactions on Intelligent Vehicles | ||||||||
| Publisher: | Institute of Electrical and Electronics Engineers | ||||||||
| ISSN: | 2379-8858 | ||||||||
| Official Date: | September 2020 | ||||||||
| Dates: |
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| Date of first compliant deposit: | 2 January 2020 | ||||||||
| Volume: | 5 | ||||||||
| Number: | 3 | ||||||||
| Page Range: | pp. 397-413 | ||||||||
| DOI: | 10.1109/TIV.2019.2960935 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Publisher Statement: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
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