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Cited by 373

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Visual attention and the transition from novice to advanced driver

Underwood, G.·2007·Ergonomics

Abstract

Inexperienced drivers are particularly vulnerable to road traffic accidents, and inattention emerges as a factor in these accidents. What do these drivers attend to and how can their observation skills be developed? When drivers scan the road around them, differences are observed as function of driving experience and training, with experienced drivers increasing their visual scanning on roadways of increasing complexity. Trained police drivers showed this effect of increased scanning even more than experienced drivers. This suggests that the driver's understanding of the task develops with experience, such that roads that demand increased monitoring (e.g. interweaving traffic on a multi-lane highway) receive more extensive scanning than roads that are simpler (e.g. light traffic on a straight rural road). Novice drivers do not show this sensitivity to road complexity, suggesting that they fail to attend to potential dangers involving the behaviour of other road users. Encouragingly, a simple training intervention can increase the visual scanning of novices.

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Metadata

Authors
Underwood, G.
Venue
Ergonomics
Published
2007-08
Volume
50
Issue
8
Pages
1235-1249
ISSN
  • 0014-0139 (ISSN-L)
  • 1366-5847
OpenAlex
W2050064812
Cited by
373
References
2
FWCI
16.97
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Visual attention and the transition from novice to advanced driver. https://app.cochat.ai/papers/10.1080/00140130701318707
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Underwood, G. (2007). Visual attention and the transition from novice to advanced driver. Ergonomics. https://doi.org/10.1080/00140130701318707

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.