Suchergebnisse

Pedestrian safety at rail level crossings (RLXs) is a concern for government, the transport industry and the community. Collisions between trains and pedestrians are traditionally viewed as the result of errors or violations committed by pedestrians. However, as RLXs are complex sociotechnical systems, collisions are better understood as emergent properties of interactions amongst and between human and technical components within the system. Cognitive work analysis (CWA) is a powerful analytical framework that offers a sophisticated understanding of the functioning of RLXs as relevant to pedestrian safety, through identifying the constraints on pedestrian behaviour in this context. It does not, however, provide its users with guidance about how the findings of the analysis can be used to improve sociotechnical system functioning. Accordingly, the aim of this research was the development and evaluation of a CWA-based approach to support the design of complex sociotechnical systems, and the application of this approach to provide recommendations for RLX design to improve pedestrian safety. A secondary aim of the research was to investigate pedestrian behaviour within the RLX system using CWA. Drawing on systems theory, and more specifically, sociotechnical systems theory, the outcome of this research is a CWA design toolkit (the CWA-DT). The development and refinement of the CWA-DT is illustrated through a proof of concept application in the domain of public transport ticketing. Positive evaluation results were obtained and necessary refinements to the toolkit were implemented in the second version. A full evaluation of the toolkit was then undertaken within the complex, safety critical domain of RLXs. This evaluation found that while the CWA-DT could be considered a useful method, its application did not lead to the creation of design concepts that fully aligned with sociotechnical systems theory. The application did, however, lead to designs that were rated by human factors experts as more effective than the existing system design. These findings suggest that the sociotechnical systems theory approach may not provide an appropriate design philosophy in a public safety context. However, merging ideas and concepts from sociotechnical systems theory with existing paradigms such as safety management can lead to innovation and has the potential to improve safety performance. ; Awards: Winner of the Mollie Holman Doctoral Medal for Excellence, Monash Injury Research Institute, 2015.

The rail industry, as with all sectors worldwide, has faced disruptions due to the global COVID‐19 pandemic. This commentary considers how rail organizations in Australia have engaged within the early stages of the crisis, outlining the challenges faced and how they were addressed. Relying on our observations, and anecdotes obtained from others across the Australian rail industry, we identified a range of impacts including determining service delivery levels (and the associated running of "ghost trains"), implementing hygiene measures and social distancing, managing training and medical assessments, and changes in the behavior of passengers and members of the public (including aggression toward staff and increased instances of trespass). Within rail organizations, we saw changes to communication and control structures, new challenges related to balancing priorities (managing risk of rail accidents vs. virus transmission risk), and negative impacts on job design offset by increased informal support for frontline workers. Importantly, from the crisis, we gained new insights about culture. Finally, we provide recommendations regarding how the Human Factors and Ergonomics discipline can support safe and effective rail operations in the context of both widespread crises such as pandemics as well as the less dramatic, but ever present, shifts in the physical, social, economic, and political environments in which rail organizations operate.

Objective This paper presents the Binary-Based Model (BBM), a new approach to Human Factors (HF) method selection. The BBM helps practitioners select the most appropriate HF methodology in relation to the complexity within the target system. Background There are over 200 HF methods available to the practitioner and little guidance to help choose between them. Method The BBM defines a HF "problem space" comprising three complexity attributes. HF problems can be rated against these attributes and located in the "problem space." In addition, a similar HF "approach space" in which 66 predictive methods are rated according to their ability to confront those attributes is defined. These spaces are combined into a "utility space" in which problems and methods coexist. In the utility space, the match between HF problems and methods can be formally assessed. Results The method space is split into octants to establish broad groupings of methods distributed throughout the space. About 77% of the methods reside in Octant 1 which corresponds to problems with low levels of complexity. This demonstrates that most HF methods are suited to problems in low-complexity systems. Conclusion The location of 77% of the rated methods in Octant 1 indicates that HF practitioners are underserved with methods for analysis of HF problems exhibiting high complexity. Application The BBM can be used by multidisciplinary teams to select the most appropriate HF methodology for the problem under analysis. All the materials and analysis are placed in the public domain for modification and consensus building by the wider HF community.

Introduction: There is a need for an ecological and complex systems approach for better understanding the development and prevention of running-related injury (RRI). In a previous article, we proposed a prototype model of the Australian recreational distance running system which was based on the Systems Theoretic Accident Mapping and Processes (STAMP) method. That model included the influence of political, organisational, managerial, and sociocultural determinants alongside individual-level factors in relation to RRI development. The purpose of this study was to validate that prototype model by drawing on the expertise of both systems thinking and distance running experts. Materials and methods: This study used a modified Delphi technique involving a series of online surveys (December 2016- March 2017). The initial survey was divided into four sections containing a total of seven questions pertaining to different features associated with the prototype model. Consensus in opinion about the validity of the prototype model was reached when the number of experts who agreed or disagreed with survey statement was ≥75% of the total number of respondents. Results: A total of two Delphi rounds was needed to validate the prototype model. Out of a total of 51 experts who were initially contacted, 50.9% (n = 26) completed the first round of the Delphi, and 92.3% (n = 24) of those in the first round participated in the second. Most of the 24 full participants considered themselves to be a running expert (66.7%), and approximately a third indicated their expertise as a systems thinker (33.3%). After the second round, 91.7% of the experts agreed that the prototype model was a valid description of the Australian distance running system. Conclusion: This is the first study to formally examine the development and prevention of RRI from an ecological and complex systems perspective. The validated model of the Australian distance running system facilitates theoretical advancement in terms of identifying practical system-wide opportunities for the implementation of sustainable RRI prevention interventions. This 'big picture' perspective represents the first step required when thinking about the range of contributory causal factors that affect other system elements, as well as runners' behaviours in relation to RRI risk.