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A meta-analysis of in-vehicle and nomadic voice-recognition system interaction and driving performance.
- Source :
-
Accident; analysis and prevention [Accid Anal Prev] 2017 Sep; Vol. 106, pp. 31-43. Date of Electronic Publication: 2017 May 29. - Publication Year :
- 2017
-
Abstract
- Driver distraction is a growing and pervasive issue that requires multiple solutions. Voice-recognition (V-R) systems may decrease the visual-manual (V-M) demands of a wide range of in-vehicle system and smartphone interactions. However, the degree that V-R systems integrated into vehicles or available in mobile phone applications affect driver distraction is incompletely understood. A comprehensive meta-analysis of experimental studies was conducted to address this knowledge gap. To meet study inclusion criteria, drivers had to interact with a V-R system while driving and doing everyday V-R tasks such as dialing, initiating a call, texting, emailing, destination entry or music selection. Coded dependent variables included detection, reaction time, lateral position, speed and headway. Comparisons of V-R systems with baseline driving and/or a V-M condition were also coded. Of 817 identified citations, 43 studies involving 2000 drivers and 183 effect sizes (r) were analyzed in the meta-analysis. Compared to baseline, driving while interacting with a V-R system is associated with increases in reaction time and lane positioning, and decreases in detection. When V-M systems were compared to V-R systems, drivers had slightly better performance with the latter system on reaction time, lane positioning and headway. Although V-R systems have some driving performance advantages over V-M systems, they have a distraction cost relative to driving without any system at all. The pattern of results indicates that V-R systems impose moderate distraction costs on driving. In addition, drivers minimally engage in compensatory performance adjustments such as reducing speed and increasing headway while using V-R systems. Implications of the results for theory, design guidelines and future research are discussed.<br /> (Copyright © 2017 Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1879-2057
- Volume :
- 106
- Database :
- MEDLINE
- Journal :
- Accident; analysis and prevention
- Publication Type :
- Academic Journal
- Accession number :
- 28554063
- Full Text :
- https://doi.org/10.1016/j.aap.2017.05.013