This project aims to balance road safety and efficiency as conflicting goals of transport systems mixed with connected and automated vehicles (CAVs). This project is expected to generate fundamental knowledge on operational algorithms and analytics for CAVs and develop innovative tools for operating them. Expected outcomes include ground-breaking models capable of the co-estimation of efficiency and safety impacts of CAVs, and control strategies to safely and efficiently integrate CAVs into existing transport systems. While this project is led by the University of Queensland (UQ), STSR-Lab is leading the traffic safety component of this project, in which a new traffic safety model for connected and automated vehicles will be developed.

Road traffic crashes are responsible for hundreds of lives and thousands of injuries on Australian roadways each year. A significant research opportunity exists to fundamentally rethink how the profession quantitatively identifies black spots on the transport network. This project aims to develop, test, and validate an evidence-based methodology to proactively detect motor vehicle crash black spots by decomposing (statistically) observed crashes at a site into their engineering, behavioural, and unobserved spatial components. The new methods combined provide novel insights and knowledge regarding transport network safety management.

This project aims to balance road safety and efficiency as conflicting goals of transport systems mixed with connected and automated vehicles (CAVs). This project is expected to generate fundamental knowledge on operational algorithms and analytics for CAVs and develop innovative tools for operating them. Expected outcomes include ground-breaking models capable of the co-estimation of efficiency and safety impacts of CAVs, and control strategies to safely and efficiently integrate CAVs into existing transport systems. While this project is led by the University of Queensland (UQ), STSR-Lab is leading the traffic safety component of this project, in which a new traffic safety model for connected and automated vehicles will be developed.

This project sought to undertake and deliver a field trial utilising video-based traffic conflict analysis (video analytics trial) at four sites identified in collaboration with the Queensland Department of Transport and Main Roads (TMR). In particular, this project applied advanced video analysis technology to assess intersection safety performance, with the aim of demonstrating to TMR the value of this technology and corresponding analytical evaluation. This proof-of-concept project for the Queensland Transport and Main Roads successfully demonstrated a number of important utilities of advanced video analytics tools, including

This project aims to develop a new motorcycle-specific safety assessment methodology using the Instrumented Motorcycle. This project develops a guide detailing the motorcycle-specific road safety audit methodology, risk assessment method including Benefit Cost Ratio (BCR) estimation, instrumented motorcycle data analysis and reporting of motorcycle risk. This step-by-step guide will be used to identify risks to motorcyclists. It is expected that the findings of Road Safety Audits using the instrumented motorcycle would help to identify and treat high-risk motorcycle locations.

The aim of this project is to evaluate the effectiveness of treatments to sections of the Bruce Highway that are scheduled to be constructed as part of the Bruce Highway Safety Package – Tranche 1 (BHSP-Tranche 1), minor safety works that were recommended by route safety reviews of the BHSP-Tranche 1, and projects under the Bruce Highway Upgrade Program (BHUP) that may have foreseeable safety benefits, in terms of reducing the number of crashes, injury severities and cost of crashes at the treated sites. To evaluate the effectiveness of engineering treatments, this project applies the state-of-the-practice before-after evaluation methodology. In particular, the Empirical Bayes (EB) method is applied to evaluate the effectiveness of engineering safety treatments (e.g. wide centre line treatments, shoulder widening, delineation, etc.) along Bruce Highway. The effectiveness of treatments is measured in terms of total crashes, target crashes and injury severity of crashes.

This research aims to develop a new real-time risk assessment system that proactively and efficiently assesses and mitigates crash risks of vulnerable road users (VRUs) by applying traffic conflict techniques and artificial intelligence-based video analytics. This research utilises the power of artificial intelligence technologies in the emerging field of conflict-based safety assessment in an unprecedented effort to develop new technology for the real-time risk management system of VRUs. The proposed real-time safety assessment system for VRUs will contribute to reducing road fatalities and injuries in Australia.

This project aims to undertake a comprehensive safety evaluation of permissive to part-time protected right-turn signals at intersections by utilizing advanced video-based traffic conflict analysis (video data) at a number of sites identified in collaboration with the Department of Transport and Main Roads (TMR). The advanced video analysis technology shall be applied to assess safety issues around permissive (and part-time protected) right-turn signals. As an overarching goal of the project, the relationship between traffic conflicts and historical (annual) crash records at these sites shall be developed to assess the safety and provide recommendations thereafter. The project team shall produce a detailed report describing the results of the automated video analysis of selected sites, revealing potential conflict zones, conflict, violation issues, and the relationship between traffic conflict measures and historical crash records. In addition, this project also aims to study the effects of part-time protected right-turn signals on the queue length of treated approaches.

The aim of this project was to evaluate the road safety performance of projects delivered as part of the Targeted Road Safety Program (TRSP) for the years 2005/2006 to 2011/2012. Specifically, this project aimed to evaluate the effectiveness of the TRSP 2005/2006-2011/2012 in reducing casualty crashes and, more specifically, fatal and serious injury (FSI) crashes. From the evaluation of safety effectiveness for the verified TRSP projects, it was concluded that the 357 TRSP projects under consideration for evaluation had an overall statistically significant positive impact on the average number of crash reductions per year, both in terms of total injury and FSI crash types. This project was led by CARRS-Q. STSR-Lab was responsible for developing the methodological frameworks for road safety program evaluation.