Paying attention behind the wheel: a framework for studying the role of attention in driving

Abstract

Driver inattention is thought to cause many automobile crashes. However, the research on attention is fragmented, and the applied research on driving and attention is further split between three largely independent traditions: the experimental research, the differential crash rate research, and the automation research. The goal of this review is to provide a conceptual framework to unify the research—a framework based on the combination of two fundamental dimensions of attentional selection: selection with and without conscious awareness (controlled and automatic), and selection by innate and acquired cognitive mechanisms (exogenous and endogenous). When applied to studies chosen to represent a broad range within the experimental literature, it reveals links between a variety of factors, including inexperience, inebriation, distracting stimuli, heads-up displays, fatigue, rumination, and secondary tasks such as phone conversations. This framework also has clear implications for the differential crash literature and the study of automated systems that support or replace functions of the driver. We conclude that driving research and policy could benefit from consideration of the different modes of attentional selection insofar as they integrate literatures, reveal directions for future research, and predict the effectiveness of interventions for crash-prevention.

Keywords:

• Driving
• attention
• crash-risk
• fatigue
• inebriation
• inexperience
• habits
• workload

Acknowledgements

This project was funded by a grant from the Insurance Corporation of British Columbia (the Strategic Monitoring and Assessment of Research on Transportation program). We would like to thank the following individuals for their help in gathering materials for this project: Jeff Caird, Bob Dewar, Joanne Harbluk, Clark Lim, Jeanette Lum, Frank Navin, Ian Noy, Dan Robinson, Tarek Sayed, Allison Sekuler, and Alison Smiley. We would also like to thank Kevin Hamilton for his helpful comments on an earlier draft of this paper.