A human factors investigation into the effectiveness of traffic incident management

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Traffic incident management aims to maximise outcomes for road crash casualties and the safety of responders working at the scene, as well as optimising traffic flow past the incident and prompt restoration of full traffic capacity. Apart from improving road crash casualty outcomes, traffic incident management is also an important aspect of road safety because 14%–18% of all traffic incidents are secondary incidents occurring subsequent to a primary incident.Despite this, traffic incident management is relatively unexplored in research terms. The overall objective of this thesis was, therefore, to use an explorative approach to identify ways to improve traffic incident management.The first study aimed to better understand the primary safety concerns of responders at incidents. The study used interviews, focus groups, observations and surveys to explore operator perceptions of the safety and performance of their work environment. Results indicated that there were non-optimal technical issues at incidents for both responders and motorists. Non-technical issues in the work environment were also apparent and overall, responder perceptions of safety at traffic incidents was low. The findings from the first study guided further investigation of safety and performance issues at traffic incidents.In study two, a survey of 720 emergency responders was conducted to better understand the types of issues within traffic incident precincts. Technical issues identified through the survey were agency specific. Non-technical issues were consistent across all agencies and included poor inter-agency communication and poor understanding of the priorities and requirements of other agencies at incidents. The uniformity of non-technical issues across all agencies in study two directed the focus of the subsequent studies and also identified Naturalistic Decision Making as the most appropriate theory on which to base the remainder of the thesis.In the third study, the Critical Decision Method, decision ladder template and the Recognition-Primed Decision model were used to extract and map decisions made at incidents. The objectives of this study were to firstly extend these human factors tools into the traffic incident management domain; secondly, to identify system issues in the work environment; and thirdly to identify possible solutions to any identified system issues. The study identified that the Critical Decision Method was an effective knowledge elicitation tool for the analysis of responder decisions at traffic incidents, and that both the decision ladder template and Recognition-Primed Decision model effectively identified system issues and corresponding solutions. Key issues identified at the scene related to inadequate technology, training and processes. The key recommendations to improve traffic incident management safety and performance included a requirement to develop an incident communication ability for all responders at the scene of large incidents, developing policies to support novice responders at their first fatal incidents, reviewing policies related to perimeter vehicle lights at incidents, developing a process requiring all responders to receive an incident debrief at the scene when they won’t return to the same station following incident clearance and investigating QPS communication at police borders.One of the limitations identified in the third study was that the analyses were conducted with individuals, while traffic incidents are managed by inter-agency teams. To address this limitation, the final study in the thesis used a desk-top exercise to conduct a group analysis of a complex traffic incident. The tools used for this study were modifications of the Critical Decision Method and the Cognitive Work Analysis framework. The Critical Decision Method was found to be an effective knowledge elicitation tool in the group setting. Cognitive Work Analysis was also shown to be an effective framework for analysing traffic incident management systems. There were numerous findings from this process. The current structure of communication teams within agencies was found to be non-optimal, with little collaboration and coordination between teams despite the overlap of functions and priorities. A training requirement between agencies to improve inter-agency understanding of all emergency response functions at the scene was identified. Training is also required between agencies with joint functions at the scene and the work highlighted that agency policies need to be flexible and account for other agency functions at the scene.In conclusion, the thesis identified technical and non-technical issues in the traffic incident management work environment. Technical issues were found to be agency specific and nontechnical issues were consistent across the participant agencies. Cognitive Work Analysis, the Critical Decision Method and Recognition-Primed Decision model were used to investigate non-technical issues across agencies at traffic incidents. The tools extracted information about decisions made at the scene, and analysed decisions to determine system issues and system support requirements. The data gathering and analysis process also helped generate innovative solutions to the identified issues. The combined studies provide insight and direction to improve traffic incident management training, policies and practices, and contributed significantly to the heretofore limited body of work within the traffic incident management domain.