An investigation of the effect of texting on hazard perception using fuzzy signal detection theory (fSDT)

No Thumbnail Available
Authors
Burge, Rondell J.
Chaparro, Alex
Advisors
Issue Date
2018-10
Type
Article
Keywords
Hazard perception , Driver distraction , Texting , Fuzzy signal detection
Research Projects
Organizational Units
Journal Issue
Citation
Burge, Rondell J.; Chaparro, Alex. 2018. An investigation of the effect of texting on hazard perception using fuzzy signal detection theory (fSDT). Transportation Research Part F: Traffic Psychology and Behaviour, vol. 58:pp 123-132
Abstract

Hazard perception is a multi-faceted process that requires drivers to maintain awareness of a complex driving environment. Most research studies, however, utilize behavioral responses to a small number of discrete hazardous events (e.g., response to a braking lead vehicle, vehicle lane deviations, or pedestrians) to assess a driver's hazard perception ability. The purpose of this study was to explore how performing a texting task impacts a driver's hazard perception ability while viewing real-world driving scenes using JSDT metrics. The results showed that texting increased perceived mental workload and reduced the participants' ability to discriminate hazards and reduced their likelihood of responding to a hazard. The results highlight changes in the hazard perception process, suggesting that distraction causes both a loss in sensitivity and a shift in response bias. Additionally, the results indicate that these shifts are at least in part, moderated by changes in cognitive load due to the secondary task and the current driving environment. These results also highlight the complexity in which distraction can impact both the allocation of cognitive resources as well as attentional selection.

Table of Contents
Description
Click on the DOI link to access the article (may not be free).
Publisher
Elsevier
Journal
Book Title
Series
Transportation Research Part F: Traffic Psychology and Behaviour;v.58
PubMed ID
DOI
ISSN
1369-8478
EISSN