Characterisation and Prevention of Vibration-Induced Drowsiness in Drivers. The present CIs have demonstrated that vibrational frequencies of 4-7 Hz entrain brainwaves associated with the onset of sleep. Our unpublished pilot data show that higher vibrational frequencies can restore alertness. Thus future vehicle design could dampen 3-8Hz vibrations while higher frequency vibrations could counteract drowsiness or stimulate alertness. This project aims to: i) develop novel equivalent drowsiness c ....Characterisation and Prevention of Vibration-Induced Drowsiness in Drivers. The present CIs have demonstrated that vibrational frequencies of 4-7 Hz entrain brainwaves associated with the onset of sleep. Our unpublished pilot data show that higher vibrational frequencies can restore alertness. Thus future vehicle design could dampen 3-8Hz vibrations while higher frequency vibrations could counteract drowsiness or stimulate alertness. This project aims to: i) develop novel equivalent drowsiness contours for the effects of physical vibration on driver drowsiness that will form the basis of a new industry standard for transportation safety; ii) develop an innovative vibration regime to improve alertness. This research will reduce transportation injuries and deaths by enabling the design of safer transport vehicles.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100372
Funder
Australian Research Council
Funding Amount
$373,536.00
Summary
Understanding the role of self-regulation in moderating distracted driving. The goal of this project is to combine naturalistic driving and simulation methods to explore the role that driver-initiated adaptive behaviour (self-regulation) can play in mitigating the effects of distraction on driving performance and safety. Driver distraction is a growing threat to road safety worldwide, contributing to approximately one-quarter of all crashes. Distraction is a complex, multifaceted phenomenon and, ....Understanding the role of self-regulation in moderating distracted driving. The goal of this project is to combine naturalistic driving and simulation methods to explore the role that driver-initiated adaptive behaviour (self-regulation) can play in mitigating the effects of distraction on driving performance and safety. Driver distraction is a growing threat to road safety worldwide, contributing to approximately one-quarter of all crashes. Distraction is a complex, multifaceted phenomenon and, despite its impact on safety, our understanding of it is far from complete. The project aims to develop and assess a set of new countermeasures designed to enhance drivers’ self-regulatory behaviour when distracted. The outcomes of the project may reduce the impact of distraction on road trauma in Australia.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210101181
Funder
Australian Research Council
Funding Amount
$403,775.00
Summary
Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multipl ....Information Fusion for Tracking Objects in Large-Scale Sensor Network. This project aims to develop a mathematical framework to combine multi-modal information coming from multiple sensors. These mobile sensors will be spatially distributed over a large-scale area for the purpose of multi-object tracking. The main application of this framework is for cooperative perception for intelligent decision making. Expected outcomes include a novel technique to integrate receiving information from multiple mobile agents (e.g. vehicle) to enhance their ability to anticipate situations in dynamic environments and to act effectively to enhance safety. This should provide benefits for the development of cooperative autonomous driving to enhance road safety.Read moreRead less
Driving Towards Greener and Safer Roads using Big Spatiotemporal Data. This project aims to design novel techniques for using big spatiotemporal data to reduce the impact of road transport on the environment and improve road safety. This project expects to address key challenges and lay scientific foundations of using the big data for developing a next-generation eco-friendly navigation system and increasing situational awareness for road transport safety. Expected outcomes of this project inclu ....Driving Towards Greener and Safer Roads using Big Spatiotemporal Data. This project aims to design novel techniques for using big spatiotemporal data to reduce the impact of road transport on the environment and improve road safety. This project expects to address key challenges and lay scientific foundations of using the big data for developing a next-generation eco-friendly navigation system and increasing situational awareness for road transport safety. Expected outcomes of this project include novel big data management and analytics techniques, and new edge computing models for vehicular networks. The success of this project should bring several key benefits including reducing greenhouse gas emissions on roads, facilitating urban planning, and improving road safety.Read moreRead less