Hazard Perception in Driving

Guest Speaker:
Cheng Lim (University of Nebraska-Lincoln, USA)
Host:
Dr Treshi-Marie Perera (School of Psychology, University of Reading Malaysia)
Subject Area:
Psychology
Activity:
Seminar
Date & Time:
Wed, 15. February 2017, 13:00 h - 14:00 h
Venue:
N3.24, University of Reading Malaysia - EduCity@Iskandar​

Abstract
Hazard perception is the ability to perceive hazards on the road. It is one of the only driving-specific skills that has been linked to accident rates, with higher levels of skill corresponding to decreased incidents. Because of this, several countries such as the UK and Australia have incorporated a hazard perception test as part of the driver licensing process. While most hazard perception research focuses on developed countries, the vast majority of the world’s road deaths occur in developing countries. We compare hazard perception ability in Malaysian and UK drivers using video-based test paradigms that have been successfully employed in developed countries. Malaysian drivers took longer to react to hazards and were also less accurate at predicting imminent hazards compared to UK drivers, suggesting drivers in more hazardous environments have decreased sensitivity to hazards, which in turn may affect their ability to predict (and thus avoid) them. We discuss the cognitive implications and practical considerations for hazard perception testing in developing countries.

Photo

Biography
Cheng obtained an undergraduate degree in psychology at Duke University (North Carolina, USA), then spent several years in Malaysia working as a consultant in human resources and psychometrics. Eventually she returned to academia at the University of Nottingham Malaysia Campus, comparing how drivers in Malaysia and the UK perceive hazards, and completed her PhD in 2016. She is currently a postdoctoral scholar at the University of Nebraska-Lincoln in the USA, where she researches attention and perception using electroencephalography (EEG) and functional magnetic resonance imagining (fMRI), applying deep learning methods to decode patterns of brain activity.

  • Admission is free.​
  • Tea break will be served at 2:00 pm.
  • UoRM staff RSVP by responding to the internal event invitation.
  • All are welcome, RSVP by 14 February 2017.

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