@article{Grüner_Ansorge_2017, title={Mobile eye tracking during real-world night driving: A selective review of findings and recommendations for future research}, volume={10}, url={https://bop.unibe.ch/JEMR/article/view/3384}, DOI={10.16910/jemr.10.2.1}, abstractNote={<p>We exhaustively review the published research on eye movements during real-world night driving, which is an important field of research as fatal road traffic accidents at night outnumber fatal accidents during the daytime. Eye tracking provides a unique window into the underlying cognitive processes. The studies were interpreted and evaluated against the background of two descriptions of the driving task: Gibson and Crooks’ (1938) description of driving as the visually guided selection of a driving path through the unobstructed field of safe travel; and Endsley’s (1995) situation awareness model, highlighting the influence of drivers’ interpretations and mental capacities (e.g., cognitive load, memory capacity, etc.) for successful task performance. Our review unveiled that drivers show expedient looking behavior, directed to the boundaries of the field of safe travel and other road users. Thus, the results indicated that controlled (intended) eye movements supervened, but some results could have also reflected automatic gaze attraction by salient but task-irrelevant distractors. Also, it is not entirely certain whether a wider dispersion of eye fixations during daytime driving (compared to night driving) reflected controlled and beneficial strategies, or whether it was (partly) due to distraction by stimuli unrelated to driving. We concluded by proposing a more fine-grained description of the driving task, in which the contribution of eye movements to three different subtasks is detailed. This model could help filling an existing gap in the reviewed research: Most studies did not relate eye movements to other driving performance measurements for the evaluation of real-world night driving performance.</p>}, number={2}, journal={Journal of Eye Movement Research}, author={Grüner, Markus and Ansorge, Ulrich}, year={2017}, month={Mar.} }