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  3. Adapting a driving simulator to study pedestrians' street-crossing decisions: A feasibility study
 

Adapting a driving simulator to study pedestrians' street-crossing decisions: A feasibility study

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Publisher DOI
10.1080/10400435.2014.929193
PubMed ID
26132219
Description
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.
Date of Publication
2015
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
600 Technology > 620 Engineering
Keyword(s)
eye-tracking
•
head-tracking
•
pedestrian
•
simulation
•
street-crossing
Language(s)
en
Contributor(s)
Jäger, Michael
ARTORG - Gerontechnology and Rehabilitation
Nyffeler, Thomas
Luzerner Kantonsspital, Zentrum für Neurologie und Neurorehabilitation,
Müri, René Martinorcid-logo
Universitätsklinik für Neurologie
Mosimann, Urs Peter
Universitätsklinik für Alterspsychiatrie und Psychotherapie (APP)
Nef, Tobiasorcid-logo
ARTORG - Gerontechnology and Rehabilitation
Additional Credits
ARTORG - Gerontechnology and Rehabilitation
Luzerner Kantonsspital, Zentrum für Neurologie und Neurorehabilitation,
Universitätsklinik für Neurologie
Universitätsklinik für Alterspsychiatrie und Psychotherapie (APP)
Series
Assistive Technology
Publisher
Taylor & Francis
ISSN
1040-0435
Access(Rights)
metadata.only
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