Driver distraction (e.g., due to increased cognitive demands) is increasingly recognised as a significant source of injuries and accidents. Accordingly, many researchers have investigated factors that affect driving performance. But provisions for cyclists (e.g., cycle paths and lanes) are increasing in major cities and towns – as are the numbers of cyclists accordingly. Hence, our aim is to develop a better understanding of traffic perception and hazard avoidance when cycling in urban environments. We are also interested in the relationship between a measure of decision-making tendencies and cycling behaviour. We are collecting cycling performance data (pedalling cadence, braking frequency), gaze data, and questionnaire data in order to do so.
Participants will attend one 1-hour session in a laboratory in the SIM Lab, Department of Life Sciences, dressed in clothing suitable for cycling at a light intensity for approximately 10 minutes.
After completion of two questionnaires, they must ride a spinning bike whilst wearing a cycle helmet and eye tracking glasses. Their task will be to observe video footage taken from the first-person perspective of a cyclist navigating a busy urban street, and to respond to hazards as they normally would when riding a bike.
It is expected that the data from this study will inform subsequent cycling proficiency instruction practices in future.
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Related Research Group(s)
Cognitive and Clinical Neuroscience - Fundamental and applied research into brain function using techniques such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), electromyography (EMG), eye-tracking, transcranial magnetic stimulation (TMS), transcranial direct-current stimulation (tDCS), infrared thermography together with psychophysics and cognitive behavioural paradigms in health and disease.
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Project last modified 14/07/2021