Gemma Read

Cyclist incidents remain a persistent road safety issue. Existing data on cyclist incidents are limited; consequently, there is a knowledge gap around effective cyclist safety interventions. A mechanism for improved incident data collection—a cyclist incident reporting and learning system (Cyclist Reporting of Incidents Tool; CRIT)—was developed and trialed over a 12-month period across Australia. This study analysed the cyclist incidents submitted to CRIT during the trial. A total of 347 cyclists participated in the study, reporting 135 cyclist incidents from 1,962 hours cycled. The overall incident rate was 68.8 per 1,000 hours cycled, with a crash rate of 11.2 and near miss rate of57.6 per 1,000 hours cycled. Factors relating to driver behaviour (e.g., non-compliance with road rules) and poor infrastructure (e.g., bicycle lane) were frequently reported to have contributed to cyclist incidents. The findings highlight the utility of self-reported cyclist incident data in understanding and enhancing cyclist safety.

There have been previous calls for a ‘many model’ approach to solving complex challenges in ergonomics (Salmon and Read, 2018). In this work, we demonstrate how the combination of three systems ergonomics methods can provide different, yet compatible insights into the emerging challenge of the successful (safe and effective) introduction of advanced automated vehicles. Specifically, we applied ActorMap, Hierarchical Task Analysis, and the abstraction hierarchy from the Cognitive Work Analysis framework. Each model provides detailed descriptions of the road transport system that can be used as a basis to explore the issues surrounding the introduction of automated vehicles. Importantly, they provide a series of compatible insights from different perspectives regarding the future road transport system that can inform policy response and other initiatives to support the successful introduction of advanced automated vehicles. It is concluded that the application of multiple methods is beneficial to gain more insight than would be available from a single method used in isolation.

Objectives: There have been recent calls for the application of the 'complex systems approach' in sports injury research. However, beyond theoretical description and static models of complexity, little progress has been made towards formalising this approach in way that is practical to sports injury scientists and clinicians. The objective of this study was to use a computational systems science modelling method and develop a dynamic simulation in sports injury research. Methods: Agent-Based Modelling (ABM) was applied in the context of distance running-related injury (RRI). The primary aim of the model was to demonstrate the method and simulate the dynamic relationship between weekly running distances and RRI through the manipulation of various 'athlete management tools'. The ABM was developed based on sports injury and RRI causal theory, and incorporates evidence gathered from studies using the acute: chronic workload ratio (ACWR). Results: Building weekly running distances over time, even within the reported ACWR 'sweet spot', will eventually result in RRI as athletes reach and surpass their individual physical workload limits. Introducing training-related error into the simulation and the modelling of a hard ceiling dynamic resulted in a higher RRI incidence proportion across the population at higher absolute workloads. Discussion: Whilst this simulation was modelled on understanding RRI occurrence in a general population, the implications of this dynamic indicated fragility at the extremities of performance for the more serious runner who might aim to participate in competitive events. Athletes, running coaches, and healthcare practitioners are reminded that although it is necessary to progressively and systematically increase external workloads over time, it is as equally important to continuously monitor and measure internal physiological and psychological responses to that load. Importantly, the presented simulation offers a practical starting point to further apply more sophisticated computational models that can account for the complex nature of sports injury aetiology. Alongside traditional forms of scientific inquiry, the use of ABM (and other simulation-based techniques) could be considered as a complementary and alternative methodological approach in sports injury research.

Fatigued driving is a well-known road safety issue. While fatigued driving is usually investigated from an individual perspective, this study used a novel approach to identify the system-wide factors influencing this issue. An online survey methodology was used to gather the perceptions of 150 Queensland drivers about the factors that contribute to fatigued driving, and recommendations for reducing its prevalence. The results suggested that drivers perceive individual factors to be the predominant cause of fatigued driving. However, some wider system-level factors and recommendations were identified. Implications for practical countermeasures to reduce the incidence of fatigued driving are discussed.

Efforts to improve rail level crossing (RLX) safety are hampered in part by the sheer number of RLXs; approximately 10,500 in Australia, with diverse characteristics. The plethora of RLX environments means a single standard RLX design may not be appropriate, since the same infrastructure could generate distinct interactions depending on its surrounding context. Using instrumented vehicles, we compared drivers' perceptions and interactions with boom-controlled active RLXs in two vastly different on-road environments: urban and rural. Results suggest that although urban RLX environments are more complex and demanding, drivers in rural areas are more likely to perceive RLXs as hazardous.