The Safer Scooting Study. E-scooters are a new transport option experiencing rapid uptake, but many people are concerned about their safety. This project aims to provide an understanding of how and why people use e-scooters and how rider behaviour and safety outcomes change with experience. The anticipated goal of this project is to harness the potential benefits of e-scooters as an efficient replacement for short car trips and a way of improving access to public transport, while minimising the ....The Safer Scooting Study. E-scooters are a new transport option experiencing rapid uptake, but many people are concerned about their safety. This project aims to provide an understanding of how and why people use e-scooters and how rider behaviour and safety outcomes change with experience. The anticipated goal of this project is to harness the potential benefits of e-scooters as an efficient replacement for short car trips and a way of improving access to public transport, while minimising the dangers to riders and pedestrians. This knowledge is expected to inform governments at all levels, industry and riders on how to optimise e-scooter design, use and regulation to contribute to improvements in transport, health and environmental outcomes for all Australians.Read moreRead less
Predictive Analytics and Real-time Traffic Control for Urban Corridors. This project aims to develop predictive data analytics and real-time traffic control and safety models for multimodal management of urban corridors, serving two salient objectives: (1) optimising person-throughput of multimodal traffic; while (2) minimising safety risks for all modes. The outcome will be an automated, sensor-based platform to monitor traffic flows from all modes and make proactive and coordinated control dec ....Predictive Analytics and Real-time Traffic Control for Urban Corridors. This project aims to develop predictive data analytics and real-time traffic control and safety models for multimodal management of urban corridors, serving two salient objectives: (1) optimising person-throughput of multimodal traffic; while (2) minimising safety risks for all modes. The outcome will be an automated, sensor-based platform to monitor traffic flows from all modes and make proactive and coordinated control decisions in real-time. The expected benefits are profound; the developed algorithms and platform will significantly reduce traffic congestion, travel delays and safety risks for all modes of transport, especially for vulnerable road users (e.g. pedestrians and cyclists).Read moreRead less
A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driv ....A safety-preserving ecosystem for autonomous driving. In this project, Macquarie University will collaborate with UTS and SilverQuest to develop an innovative safety-preserving ecosystem for autonomous driving. This system will not only be adopted by SilverQuest’s customers (automotive companies) to secure their latest autonomous driving models, but also be commercialised as a toolset that can be plugged into existing autonomous vehicles to detect and prevent malicious attacks on autonomous driving models. The project will lead to two innovations: in theory design an attack detection and prevention ecosystem for autonomous driving and in application implement a safety analysis toolset for industry-scale autonomous systems.Read moreRead less