Lateral control assistance in car driving: classification, review and future prospects
Lateral control assistance in car driving: classification, review and future prospects
- Author(s): J. Navarro ; F. Mars ; M.S. Young
- DOI: 10.1049/iet-its.2010.0087
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- Author(s): J. Navarro 1 ; F. Mars 2 ; M.S. Young 3
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View affiliations
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Affiliations:
1: Laboratoire d'Etude des Mécanismes Cognitifs (EMC), Université Lumière Lyon 2, Bron, France
2: Laboratoire d'Etude des Mécanismes Cognitifs (EMC), LUNAM Université, CNRS, IRCCyN (Institut de Recherche en Communications et Cybernétique de Nantes), Nantes, France
3: Ergonomics Research Group, School of Engineering and Design, Brunel University, London, UK
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Affiliations:
1: Laboratoire d'Etude des Mécanismes Cognitifs (EMC), Université Lumière Lyon 2, Bron, France
- Source:
Volume 5, Issue 3,
September 2011,
p.
207 – 220
DOI: 10.1049/iet-its.2010.0087 , Print ISSN 1751-956X, Online ISSN 1751-9578
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This study puts forward a classification of driver lateral control assistance devices based on distinctions among several cooperative activities between the driver and the assistance devices. The proposed classification is based on prior work by Hoc, Young and Blosseville and Young, Stanton and Harris, who put forward related theoretical frameworks on human–machine cooperation with automation. The particular application here to lateral control allows for a human-centred categorisation of existing and potential (i.e. near-future) driver assistance devices. Four human–machine cooperation levels based on drivers' activities have been adopted. All of the proposed categories are reviewed in three steps. First, each device category is functionally defined. Next, the impact of the devices on driving behaviour is presented. A third part sums up the effectiveness of each assistance category, particularly with regard to accident data. The general conclusion synthesises the main insights for each human–machine category proposed and highlights a number of design recommendations.
Inspec keywords: automobiles; man-machine systems; driver information systems
Other keywords:
Subjects: Traffic engineering computing
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