Collecting evidence from distributed sources to evaluate railway suicide and trespass prevention measures

It can be difficult to select from available safety preventative measures, especially where there is limited evidence of effectiveness in different contexts. This paper describes application of a method to identify and evaluate wide-ranging preventative measures for rail suicide and trespass fatalities. Evidence from literature and industry sources was collated and reviewed in a two stage process to achieve consensus among experts on the likely effects of the measures and factors influencing their implementation. Multiple evaluation criteria were used to examine the measures from different perspectives. Fencing, awareness campaigns and different types of organisational initiatives were recommended for further testing. This is the first time evidence has been collected internationally across such a range of preventative measures. Commentary is provided on using this type of approach to select safety measures from a pool of prevention options, including how re-framing the scope of the exercise could identify alternative options for prevention. Practitioner summary: The findings give insight to how different measures work in different ways and how industry can consider this in strategic initiatives. The method could be used in future studies with different frames of reference (e.g. different timescales, level of ambition and safety context e.g. railway crossings or highway fatalities)

Cognitive Biases, Risk Perception, and Risky Driving Behaviour

This study evaluated the relationship between drivers’ cognitive biases (i.e., optimism bias, illusion of control) and risky driving behaviour. It also investigated the mediational role of risk perception in the relationship between cognitive biases and self-reported risky driving. The sample included 366 drivers (Mage = 39.13, SD = 13.63 years) who completed scales measuring optimism bias, illusion of control, risk perception, and risky driving behaviour, as well as demographic information. The results showed that risky driving behaviour was negatively predicted by optimism bias and positively predicted by the illusion of control. Further, risk perception negatively correlated with risky behaviour and also mediated the relation between both optimism bias and illusion of control with risky driving. The practical implications of these results for traffic safety and future research are discussed

Human Factor at Level Crossings: Towards a design for self‐explaining and forgiving infrastructure

(1) Human factors vision in SAFER-LC - Rationale and approach (2) Analyzing the effect of countermeasures on human behaviour and safety - Application of a Human Factor Methodological Framework (3) Human-centered cost-effective measures – From design to evaluation (4) Discussio

Human factors and automation in future railway systems

This special issue contributes to the achievement of challenges related to human factors and automation dedicated to future railway systems. It includes transverse research topics by considering several emerging trends as the design of learning systems, of grades of automation, of cooperative system, or of analysis approaches about feedback of experience. To do so, contributions are detailed in different railway organization levels as training, design, operation, or maintenance. There are based on field studies, on simulation environments or on accident reports. They reveal the value of taking the human into account in the control and supervisory loop for the design, the analysis and the evaluation of future railway systems. Human-centered automation can indeed make system more resilient to various risks and threats by including human contributions through different degrees of automation and modalities of human–machine interaction

November 2015 Paris Terrorist Attacks and Social Media Use: Preliminary Findings From Authorities, Critical Infrastructure Operators and Journalists

Crisis communication is a key component of an effective emergency response. Social media has evolved as a prominent crisis communication tool. This paper reports how social media was used by authorities, critical infrastructure operators and journalists during the terrorist attacks that hit Paris on 13th November 2015. A qualitative study was conducted between January and February 2017 employing semi-structured interviews with seven relevant stakeholders involved in this communication process. The preliminary critical thematic analysis revealed four main themes which are reported in the results section: (1) social media is used in crisis times; (2) authorities gained situational awareness via social media; (3) citizens used social media to help one another; and (4) communication procedures changed after these critical events. In conclusion, authorities, citizens and journalists all turned to social media during the attack, both for crisis communication and for increasing situational awareness

Definition of new human-centred low-cost countermeasures. Deliverable D2.3 of the SAFER-LC project

This deliverable describes the methods applied and the results achieved during the first phase of Task 2.3 within the SAFER-LC project: the design of new human-centred low-cost measures to improve safety at level crossings (LCs). The European project SAFER-LC Safer level crossing by integrating and optimizing road-rail infrastructure management and design aims to improve safety in road and rail transport by minimising the risk of LC accidents, focusing on both technical solutions and human processes. Within the project, the objective of Work Package 2 (WP2) is to enhance the safety performance of level crossing infrastructures from a human factors perspective, making them more self-explaining and forgiving. Task 2.3 specifically aims to design concepts of human-centred low-cost countermeasures to enhance the safety of current LC infrastructures and, in a later step, to evaluate these countermeasure designs from a human factors perspective. A two-stage process, consisting of a collection phase and a selection phase, was adopted to define the countermeasure concepts presented in this report. In the first phase, a large pool of design ideas was collected from three different sources: (1) a comprehensive review of the research literature, (2) an analysis and selection of theoretical models relevant to explaining and predicting road user behaviour at level crossings, and (3) a design workshop with road and rail experts. In the second phase, three steps were undertaken in order to systemize and prioritize the measures collected: (1) an elimination of measures based on redundancy, feasibility, and expert ratings of their effectiveness and cost, (2) a classification of the remaining measures with respect to their applicability to different LCs and road user types, and their effect mechanism, and (3) a ranking of the measures based on their prospects for accident risk reduction and the need for further research. The design process was based on operational descriptions of different types of road user behaviours observed at LCs that challenge safety and hence need to be defined as the target of safety measures. The presence or absence of active controls and barriers at LCs was identified as a particularly significant factor with regard to what types of behaviour need to be supported or prevented. Therefore, the design thinking process and organization of measures drew upon the basic distinction between passive and active LCs. Measures for passive LCs were mainly to address the problems of road users insufficiently scanning the tracks for trains, insufficiently adapting their approach speed to the need of scanning and the potential need to stop, and road users getting stuck on the rails. Measures for active LCs were mainly to prevent road users from circumventing closed barriers (climbing over / below; swerving around half-barriers), passing the LC in spite of active light signals (e.g. flashing red light), passing the LC after pre-signalling has begun or while barriers are closing, and, again, getting stuck on the rails. Apart from the differences, a range of common possibilities to support safe road user behaviour at both active and passive LCs was identified (e.g. by improving LC conspicuity, using common means of conveying behavioural recommendations adapted to the respective LC type, and helping road users not to enter the tracks when they cannot be sure to leave in good time). In all cases, design considerations included vulnerable (VRU) as well as motorized road users (MRU). The process resulted in a list of 89 design solutions that can be applied in LC design. The complete list is given in Annex A of this report. The ten measures achieving the best ranks in each of the aforementioned use cases were: Passive LCs: Active inverted speed bumps, laser illumination of the crossing, image process warning, blinking peripheral lights drawing driver attention, light markings in the road to highlight the waiting line, speed bumps on approach to the LC, on-road flashing markers, road swivelling, LC attention device, and coloured marking of the danger zone. LCs with barriers: Adapting the timing of LC closure to the actual speed of the passing train, camera based enforcement (prosecution of violations), additional display "Two Trains", second chance zone, sound warning indicating an approaching train, lane separation in front of half barriers, increasing the length of the barrier, audible signal while in the danger zone, information countdown to closing the barrier and complete open / close cycle. All types of LCs: Proximity message via connected device (in- vehicle display, satnav, mobile device), improving train visibility using lights, audible warnings about LC, extended "no stop" zone, message on smartphone / -watch to warn on approaching train (VRU), coloured pavement markings to mark the danger zone (MRU), satnav intelligence, countdown to train arrival, LED enhanced traffic signs and warning sign to avoid blocking back. The next steps within the SAFER-LC project will be to conduct empirical tests on selected measures to evaluate their effects on road user behaviour and LC safety, and to integrate the projects practical results and recommendations in a toolbox to be accessed through a user-friendly interface to support rail and road stakeholders in improving safety at LCs. Document type: Boo

Evaluation of new human-centred low-cost measures. Deliverable D2.4 of the SAFER-LC project

This deliverable describes the methods applied and the results achieved during the second phase of Task 2.3 in the SAFER-LC project: the evaluation of new human-centred low-cost measures to improve safety at level crossings (LCs). The European project SAFER-LC – Safer level crossing by integrating and optimizing road-rail infrastructure management and design – aimed to improve safety in road and rail transport by minimising the risk of LC accidents, focusing on both technical solutions and human processes. Within the project, the objective of Work Package 2 (WP2) was to enhance the safety performance of level crossing infrastructures from a human-factors perspective, making them more self-explaining and forgiving. Task 2.3 specifically aimed to design human-centred low-cost countermeasures to enhance the safety of current LC infrastructures and, in a later step, to evaluate these countermeasure designs from a human-factors perspective. This objective was driven by the insights of the major role that road user behavior plays in accidents at level crossings and the need for safety measures to be affordable to enable their application to a large number of crossings and the achievement of tangible safety effects. The activities in the design of countermeasures were performed in the first phase of task 2.3 from May 2017 to October 2018. They resulted in a list of 89 reviewed LC safety measures, of which 36 measures were for use at passive LCs, 29 for LCs with barriers, and 24 for use at all kinds of LCs. For the purpose of evaluation, Task 2.3 referred to two main inputs from other tasks within SAFER-LC: the human factors methodological framework developed in Task 2.2 and the pilot tests of innovative LC safety measures performed in Work Package 4 (WP4). The human factors methodological framework was developed to define what aspects of human behavior should be considered when trying to assess the suitability of a LC safety measure. It also defined important context variables that influence this suitability, including environmental factors such as LC type, layout, weather, traffic etc. as well as the issue of acceptance by different stakeholders. The methodological framework is based on sociotechnical systems theory, relevant models of human cognition and behavior, and analytical tools and empirical approaches from related research projects. Its development resulted in the definition of three sets of criteria important to the human factors assessment of a given LC safety measure. To facilitate and structure the application of the framework, a human factors assessment tool (HFAT) was developed. Its core is a survey comprising checklists and forms to assess the three sets of criteria defined. The tool helps to collect and systemize relevant information on a given LC safety measure in order to enable a reasoned estimation of its effects in road user behavior, user experience and social perception. The pilot tests in WP4 involved two kinds of tests. One kind focused on demonstrating the feasibility of technical solutions to improve LC safety. The other one was concerned with the effects of LC safety measures on road user behavior. This included two simulator studies of infrastructural safety measures, an online survey based on videos of a train-mounted countermeasure in a real rail environment, a field test of an in-vehicle LC proximity warning, and a field test of two infrastructural measures. Based on the results of these tests, the pilot site leaders used the HFAT to assess the piloted measures from a human-factors perspective. Using the HFAT enabled the presentation of the results in a common format, although the input studies used different methods and measured different indicators. The LC safety measures evaluated in this way were: blinking lights for the locomotive front, coloured road markings on approach to the LC, in-vehicle proximity warning, rings upstream of the LC, traffic light, blinking amber light with train symbol, funnel effect pylons, message , “” written on road, peripheral blinking lights, rumble strips, sign “”, and speed bump and flashing posts. The four measures assessed to most facilitate safe road user behavior in the HFAT evaluation were the blinking lights for the locomotive front, the two in-vehicle proximity warnings, and the peripheral blinking lights. Minding the evidence collected in the HFAT, this assessment is rather certain for the two measures involving blinking lights, and more tentative for the in-vehicle proximity warnings. Stakeholder acceptance and user trust are expected to be sufficient to allow for successful implementation of these measures, minding the principles of stakeholder participation and user-friendly design. Two measures scored particularly low on the assessment of behavioral safety effects: the funnel effect pylons and the message “” on the road. Both assessments are tentative, as the findings from the pilot are the only evidence available by now. Due to the low expected efficacy, acceptance and trust values were not considered in these cases. The seven remaining measures were attested a medium effectivity on the facilitation of safe behavior. These assessments are more certain for the rumble strips and the sign “”, and remain tentative for the coloured road markings on approach to LC, the rings upstream of the LC, the traffic light, the blinking amber light with a train symbol, and the speed bumps and flashing posts due to the limited availability of evidence. Based on the acceptance and trust values obtained with the HFAT, successful implementation appears possible for most of these measures. Some difficulty in implementation is expected based on the acceptance assessment for the coloured road markings on approach to LC, the rings upstream of the LC, and the funnel effect pylons. Beyond its use as a tool to guide and evaluate empirical research on LC safety, the HFAT can also be used by road and railway transport stakeholders as a checklist to support the consideration of human factors aspects in the evaluation of LC safety measures. Using the HFAT in this function can help to assess the suitability of a LC safety measure to different railway environments and user requirements and to avoid efficacy barriers, by considering the important issues of acceptance and social perception of road users and other stakeholders. The results obtained in SAFER-LC Task 2.3, the design and evaluation of human-centered low-cost measures to improve LC safety, will be used as one main input in the implementation of the SAFER-LC toolbox, a web-based tool for anyone concerned with LC safety. The toolbox is conceived to be a guide to best practice that integrates all the recommendations, promising interventions, and specifications developed during the project with the empirical evidence collected from the scientific literature and the pilot tests. The toolbox will be accessible free of charge at the end of the project and will continue to be maintained, updated and improved by the International Union of Railways (UIC) for the benefit of the road- and railway-safety community

Human factors approach to study border control automation impacts and needs:Methodology and preliminary results of field studies

International audiencePassenger flows are continuously increasing in Europe and the number of border guards does not increase as quickly as it needs. The use of automatic systems such as e-gates and kiosks is envisaged to enhance security and to facilitate the border crossing. Border control activity should be thoroughly studied in order to understand in which ways it would be impacted by the introduction of more technological systems. The purpose of this study is to analyze the current border guards’ activities from a human factor point of view and to provide recommendations and requirements regarding the introduction of the future regulation and the use of automatic systems. The paper introduces the methodology used to investigate human factors at four types of borders based on a systemic human factors approach, organizational factors, technical tools and environmental aspects