Adapting a Driving Simulator to Study Pedestrians' Street-Crossing Decisions: A Feasibility Study

Area of Science:

• Neuroscience
• Human Factors Engineering
• Transportation Safety

Background:

• Street-crossing decisions require complex perception and cognition.
• These abilities decline with normal aging, neurodegenerative disorders, and brain injury.
• Studying these declines is crucial for public safety and rehabilitation.

Purpose of the Study:

• To adapt driving simulators for studying pedestrian street-crossing decisions.
• To evaluate the feasibility, usability, and effectiveness of this novel methodology.
• To compare street-crossing performance across different age groups and neurological conditions.

Main Methods:

• Utilized a driving simulator's projection system and virtual environment to create street-crossing scenarios.
• Integrated new sensors to precisely measure the initiation of street crossing.
• Assessed feasibility, usability, task performance, and visual exploration in 15 young adults, 15 older adults, and 5 post-stroke patients.

Main Results:

• The driving simulator methodology proved feasible and usable for studying street-crossing decisions.
• Patients with post-stroke conditions exhibited significantly more crashes than younger (p = .001) and older (p = .003) healthy participants.
• Younger and older participants differed significantly in performance when faced with high-speed approaching vehicles (p = .038).

Conclusions:

• Driving simulators offer a viable and accepted platform for researching pedestrian street-crossing behavior.
• The study successfully demonstrated significant performance differences related to age and neurological status.
• This approach provides valuable insights into the perceptual and cognitive demands of safe street crossing.