Three QUT research proposals have received more than $600,000 funding from the Department of Infrastructure, Transport, Regional Development and Communications’ Road Safety Innovation Fund for projects that aim to harness the latest technology to increase safety for cyclists and pedestrians, motorcyclists and automatic car users.
The projects are:
A novel real-time risk assessment system for vulnerable road users at signalised intersections using AI-based video analytics
A project to develop a novel risk assessment system for proactively and efficiently managing safety of vulnerable road users such as pedestrians and cyclists has received $325,500.
The project will be led by Associate Professor Shimul Haque in the School of Civil and Environmental Engineering and will use artificial intelligence technologies in the emerging field of conflict-based safety assessment to develop new technology for real-time risk management.
“The methodology we will use departs fundamentally from the past 50 years of reactive safety management research,” Professor Haque said.
“Our proposed safety assessment system for vulnerable road users (VRU) could transform the safety management of transport infrastructure globally and reduce road deaths and injuries.
“In Australia, vulnerable road users accounted for about 200 deaths and more than 9700 hospitalised injuries in 2017 with more than one third of VRU crashes occurring at urban signalised intersections.”
Co-investigators on this project are Dr Yasir Ali in the School of Civil and Environmental Engineering, and Dr Shamsunnahar Yasmin and Dr Oscar Oviedo-Trespalacios from QUT’s Centre for Accident Research and Road Safety-Queensland (CARRS-Q).
Barriers associated with the uptake and acceptability of advance rider assistance systems
A CARRS-Q research team has received $107,139 to investigate strategies to encourage greater uptake by motorcyclists of advanced rider assistance systems (ARAS) to reduce the significant proportion of road deaths this group represents.
Led by Dr Sherrie-Anne Kaye, the team will undertake three research studies to develop, concept-test and evaluate education messages designed to increase motorcyclists’ adoption of ARAS.
“The use of ARAS can reduce crashes and serious injuries, but motorcyclists’ acceptance and appropriate use of such technologies is crucial to their effectiveness,” Dr Kaye said.
“As this research aims for a comprehensive understand of the barriers and facilitators for riders’ use of ARAS, we will investigate their awareness of ARAS, their intentions to buy and use those systems which are currently available, as well as their likelihood of acceptance of future ARAS as they become available.
“The project’s tangible outcomes will be a range of evidence-based educational message concepts which can guide the development of future education strategies to encourage greater uptake of ARAS.”
The research team includes Dr Ross Blackman, Dr Oscar Oviedo-Trespalacios, Associate Professor Ioni Lewis and Professor Narelle Haworth.
Complex and critical driving task handover in automated vehicles
A third project has received $176,152 to explore safety issues in automated vehicles (AV) arising during the fundamental change in drivers when transition from active controller to passive supervision.
Although plenty of research has been done in AV simulators this study, led by Dr Sébastien Demmel with Professor Sébastien Glaser, will put a human driver in the driver’s seat of one of Australia’s most advanced Level 4 AV research prototypes, ZOE2. Dr Demmel said this role transfer from driver to supervisor had associated risks of inattention, reduced situational awareness, and human error.
“This project will benefit from the experimental design and ethics approvals, data analysis tools, and technological developments already applied to the Cooperative and Highly Automated Driving (CHAD) Safety Study an iMOVE Australia, QUT and Queensland’s Department of Transport and Main Roads project,” Dr Demmel said.
“We propose to capitalise on the strong technical and research baselines established by the CHAD pilot to further investigate other dimensions of the handover task in a real AV, to improve understanding of the drivers’ performance in complex handover conditions, which remain largely unknown despite ongoing technological progress with AVs.”
The research will look at:
- handover phase duration;
- distractions before and during handover;
- surrounding traffic density;
- system transparency and the driver-machine interface including visual,
- auditive and haptic feedback.
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