Emerging Technology in Road Transport Eyes on Fatigue Project Summary

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Wishart, Darren
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Heavy Vehicle Road Incidence Whilst contributing to a minority of road traffic (only 7% of total vehicle travel), heavy vehicles are disproportionally involved in road crash incidents resulting in fatalities (at approximately 16%). Although Australian statistics indicate a steady decline in the prevalence of road fatalities events since 2011,figures related to incidents involving heavy rigid vehicles has remained steady (2006-2011; BITRE, 2016). Despite a range of policy and design changes to increase safety, these road traffic incidents persist. This is in part due to the long-shifts required to maintain Australia’s transport network. Human factors such as driver fatigue and distraction have been identified as critical safety concerns related to heavy vehicle incidents. Driver Fatigue Fatigue is estimated to contribute to 20-30% of all road accidents (including non-transit vehicles; Australian Transport Council, 2011). It is estimated that between 17-19 hours without sleep is equivalent to driving with a blood alcohol rating of .05% (Dawson & Reid,1997; Williamson, 2000). Operating a vehicle with less than 4 hours sleep has been linked to an eleven-fold increase inroad accident incident (compared to 7 hours sleep; AAA Foundation for Traffic Safety, 2016). Driver Distraction Driver distraction is estimated to contribute to 25% of all road incidents (Young et al., 2003),and increasing to 71% for truck related crashes(Olson et al., 2009). Simply reaching for an in-cabin object is related to a nine-fold increase in accident rates, whilst observing an external object increases this rate seven-fold (Young, 2020). Research Aims To pilot the effectiveness of Guardian, an automated in-cabin detection and warning system to reduce incidents of driver distraction and fatigue. Guardian uses computer vision sensors to track drivers' eye movement and head position. If a fatigue or distraction event is detected (while in motion), Guardian will notify drivers using audio and/or vibration alerts. This project aimed to explore: The efficacy of the Guardian technology in detecting and categorizing driver fatigue and distraction, and Drivers' expectations, experiences, and reflections of using this novel technology. Data for this study was collected over 8 months, and included surveys, interviews,and the evaluation of over 250,000 driver events. Key Findings Survey results suggest that upon trial completion 75% of drivers reported they found the technology helpful for increasing road safety. By far the largest challenge remains further developing the technology, with the largest portion of events being identified as being false positives (73% of all events detected). This is both distracting and annoying, whilst also undermining the perceived effectiveness of the technology. Although driver behavioural change was observed, behaviour may have changed to reduce detection of events, rather than actual reduction in fatigue or distraction. Recommendations It is recommended that further research is conducted to understand the long-term effects of the technology on both driver behaviours but also the development of organisational safety cultures. It is recommended collaborative partnerships are developed between the MAIC and QLD Trucking Association to investigate potential methods to maximise the utility of the Guardian technology to increase safety within heavy vehicle transport operations.

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© Griffith University 2021.
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See full report at http://hdl.handle.net/10072/410092
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Road transportation and freight services
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Wishart, D, Emerging Technology in Road Transport Eyes on Fatigue Project Summary, 2022