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
Establishing safe driving practice: Improving young learner driver training. This project plans to develop a best-practice model to enable professional instructors to teach essential higher-order skills (e.g. hazard perception) to young learner drivers to establish safe driving behaviours. Australian young drivers aged 17–25 years comprise 13 per cent of the population but 22 per cent of road deaths. More effective teaching models are expected to reduce young drivers’ crash risk when they drive ....Establishing safe driving practice: Improving young learner driver training. This project plans to develop a best-practice model to enable professional instructors to teach essential higher-order skills (e.g. hazard perception) to young learner drivers to establish safe driving behaviours. Australian young drivers aged 17–25 years comprise 13 per cent of the population but 22 per cent of road deaths. More effective teaching models are expected to reduce young drivers’ crash risk when they drive unsupervised. The project aims to develop and assess the effectiveness of the model including the impact on instructor teaching practices, and changes in young driver skills, attitudes, and driving behaviours including crashes and offences. It also aims to assess instructor and young driver perceptions of the model.Read moreRead less