Probing deeper into the risks of slips, trips and falls for an ageing rail passenger population: applying a systems approach

In this study, the authors report the findings from a study of the contributory factors leading to slips, trips and falls (STFs) amongst elderly passengers at train stations and how these are likely to change in the future over the medium to long term (the period 2035–2050). Their data draws on: stakeholder interviews with rail personnel and elderly passengers; a set of station observations carried out across the UK; and, a survey of the views of station managers. The findings point to a set of 22 contributory factors covering aspects of organisational, station environment and passenger (individual) influence on STFs. Amongst the factors which most concern station managers at the present and over the next few decades are: rushing behaviour on train platforms; the consumption of alcohol by passengers; aspects of station design (e.g. flooring); and, training for station staff as regard the risks of STFs. The authors summarise their findings in the form of a systems model which highlights priorities with regard to STFs in terms of all of the stakeholders taking part in the study. A final section discusses a set of issues which might form the basis for a future agenda for research and practice in this area

Learning and acquiring display-based skills

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Evaluation of the London driver information system: results from the CLEOPATRA study

CLEOPATRA was a project in the European Union Fourth Framework Programme. It was concerned with scientific techniques (algorithms, models and strategies) to support driver information and guidance systems. It evaluated techniques in six collaborating cities. In London, the work included evaluation of the variable message sign (VMS) installations operated by the Metropolitan Police from New Scotland Yard. The CLEOPATRA study attempted to identify the impacts of VMS in London through driver surveys, network modelling and traffic monitoring. Driver surveys were conducted to examine attitudes and responses to VMS. Impacts of VMS were then modelled to predict flow patterns and network performance under incident conditions with and without information present. Finally, a field survey was conducted with messages activated on one of the VMS signs and driver responses measured. This paper summarises the results of the study and discusses its implication