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Train driving is primarily a visual task; train drivers are required to monitor the dynamic scene visually both outside and inside the train cab. Poor performance on this visual task may lead to errors, such as signals passed at danger. It is therefore important to understand the visual strategies that train drivers employ when monitoring and searching the visual scene for key items, such as signals. Prior to this investigation, a pilot study had already been carried out using an eye tracking technique to investigate train drivers' visual behaviour and to collect data on driver monitoring of the visual environment, Groeger et al. (2003) Pilot study of train drivers' eye movements, University of Surrey. However, a larger set of data was needed in order to understand more fully train driver visual behaviour and strategies. In light of this need, the Transport Research Laboratory produced a methodology for the assessment of UK train driver visual strategies, on behalf of the Rail Safety and Standards Board and applied this methodology to conduct a large-scale trial. The study collected a wealth of data on train drivers' visual behaviour with the aim of providing a greater understanding of the strategies adopted. The corneal dark-eye tracking system chosen for these trials tracks human visual search and scanning patterns, and was fitted to 86 drivers whilst driving in-service trains. Data collected include the duration and frequency of glances made towards different elements of the visual scene. In addition, the train drivers were interviewed after driving the routes, to try and understand the thought processes behind the behaviour observed. Statistical analysis of over 600 signal approaches was conducted. This analysis revealed that signal aspect, preceding signal aspect, signal type and signal complexity are important factors, which affect the visual behaviour of train drivers. Train driver interview data revealed that driver expectation also plays a significant role in train driving. The findings of this study have implications for the rail industry in terms of infrastructure design, design of the driving task and driver training. However, train driving is extremely complex and the data from this study only begin to describe and explain train driver visual strategies in the specific context of signal approaches. This study has provided a wealth of data and further analysis of it is needed to investigate the role of other factors and the complex relationships between factors during signal approaches and other driving situations systematically. Finally, there are important aspects of visual behaviour that cannot be examined using these data or this method. Investigation of other aspects of visual behaviour, such as peripheral vision, will require other methods such as simulation.

The critical examination of driver cognition and information processing is vital to ensuring an effective signal passed at danger (SPAD) prevention strategy. Although this need was identified in KiwiRail's organisational strategy to reduce signal passed at danger risk, the why and how factors were not clearly described and robustly linked to deliver the necessary effects. With risk-triggered commentary driving programmes gaining recognition as valuable components and activities within the driver competency model, an opportunity to couple risk-triggered commentary driving with stabilised approach methodologies and procedures, adopted from aviation and modified for use on New Zealand's railway network was subsequently identified. A driver subject matter expert group was formed, a literature review completed, guidance developed and new procedures trialled. This activity provided new opportunities to introduce error-tolerant system design, increase accuracy of driver signal action response and reduce signal passed at danger risk on New Zealand's National Rail System by adopting and designing bespoke methodologies that support enhanced driver cognition and safe system design.

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