The decision when to cross a street safely is a challenging task that poses high demands on perception and cognition. Both can be affected by normal aging, neurodegenerative disorder, and brain injury, and there is an increasing interest in studying street-crossing decisions. In this article, we describe how driving simulators can be modified to study pedestrians' street-crossing decisions. The driving simulator's projection system and the virtual driving environment were used to present street-crossing scenarios to the participants. New sensors were added to measure when the test person starts to cross the street. Outcome measures were feasibility, usability, task performance, and visual exploration behavior, and were measured in 15 younger persons, 15 older persons, and 5 post-stroke patients. The experiments showed that the test is feasible and usable, and the selected difficulty level was appropriate. Significant differences in the number of crashes between young participants and patients (p = .001) as well as between healthy older participants and patients (p = .003) were found. When the approaching vehicle's speed is high, significant differences between younger and older participants were found as well (p = .038). Overall, the new test setup was well accepted, and we demonstrated that driving simulators can be used to study pedestrians' street-crossing decisions.
Keywords: eye-tracking; head-tracking; pedestrian; simulation; street-crossing.