Railway accident causation analysis: Current approaches, challenges and potential solutions.

Railway accident causation analysis is fundamental to understanding the nature of railway safety. Although a considerable number of prior studies have investigated this context, many of them suffer from the need to deal with a large amount of textual data given that most railway safety-related information is recorded and stored in the form of text. To gain a better understanding of the limitations imposed by overreliance on textual analysis, a scoping review of the academic literature on how railway accident causation analysis is addressed has been conducted. The results confirm the high frequency of using textual data, a single case study, and in-depth analysis frameworks. While the value of exploring causational factors is clear, the high level of human intervention and the labour-intensive analysis processes based on a large volume of textual data hinder researchers from understanding the complex nature of the rail safety system. Recently, growing attention has been given to the application of Natural Language Processing (NLP) to aid the practice of analysing a large corpus of textual data, but only limited studies to date in railway safety use such techniques and none address railway accident causation analysis. To fill this gap, a supplementary review is conducted to identify opportunities, challenges, boundaries and limitations in the application of NLP approaches to railway accident causation analysis. Findings indicate that novel techniques using off-the-shelf tools have strong potential to overcome the limitations of overreliance on manual analysis in practice and theory, but the absence of shared railway safety-related benchmark corpora restricts implementation. This study sheds light on a new approach to railway accident causation analysis and clarifies future applicable utilisations for further research.

The relation of visual perception of speed limits and the implementation of cycle lanes - a cross-country comparison.

Speed plays a key role in road safety research. Recent studies have indicated an association between speed limits and driving behaviour. However, less attention has been paid to the role of context in the perception of speed limits, and the way cycle lanes influence this perception. This study examines how respondents in different countries of residence perceive speed limits, and how cycle lanes influence their perception of speed limits. An online survey provided quantitative data for a cross-country comparison from 1591 respondents in Australia, the Netherlands, and the United Kingdom. The findings show that country of residence influences the way speed limits are perceived, and cycle lanes are interpreted distinctly. In locations where cycle lanes are common, they act as indicators of either lower or higher speed limits, while in countries with less familiarity with cycle lanes respondents associate cycle lanes only with lower speed limits. Suggesting a safer and broader understanding of cycle lanes where they are familiar (the Netherlands) and a narrower understanding where cycle lanes are not common (Australia and the United Kingdom), this study provides evidence for policymakers explaining resistance to implementing cycle lanes and implies that implementing lower speed limits and cycle lanes are a road safety measure. Suggestions are identified for future research.