King of the castle: organisational influences on authority gradients between network controllers and other team members

The rail system relies on the effective coordination of multiple disciplines and teams situated within an operational hierarchy to meet a single operational objective-the safe and timely movement of rail traffic. Power and status dispersals across these teams and the various roles within them impact interaction and communication. This study drew on the perceptions of network controllers, to identify organisational factors influencing power imbalances that generate authority gradients between network controllers and other team members. Network controllers (N = 55) across eight Australasian organisations engaged in interviews using the Scenario Invention Task Technique to explore perceptions of risk. Thematic analysis revealed relationships between teams were affected by: (1) the accountability mechanisms adopted by organisations; (2) the way power was vested in roles; and (3) the status attached to roles. This insight into organisational power hierarchies and the generation of authority gradients provides opportunities for understanding teamwork error.Practitioner summary: Communication is impaired by authority gradients across teams in rail and is a contributing factor in incidents occurring on the network. This paper explores the organisational influences on power hierarchies across teams from the perspective of the network controller, pointing to an adversarial culture, resulting in tribalism impeding team interactions.

Will transit recover? A retrospective study of nationwide ridership in the United States during the COVID-19 pandemic

Although the COVID-19 pandemic highly impacted transit ridership as people reduced or stopped travel, these changes occurred at different rates in different regions across the United States. This study explores the impacts of COVID-19 on ridership and recovery trends for all federally funded transit agencies in the United States from January 2020 to June 2022. The findings of this analysis show that overall transit ridership hit a 100-year low in 2020. Changepoint analysis revealed that June 2021 marked the beginning of the recovery for transit ridership in the United States. However, even by June 2022, rail and bus ridership were only about two-thirds of the pre-pandemic levels in most metropolitan statistical areas (MSAs). Only in a handful of MSAs like Tampa and Tucson did rail ridership reach or exceed 2019 ridership. This retrospective study concludes with a discussion of some longer-term changes likely to continue to impact ridership, such as increased telecommuting and operator shortages, as well as some opportunities, such as free fares and increased availability of bus lanes. The findings of this study can help inform agencies about their performance compared to their peers and highlight general challenges facing the transit industry.

The impact of coal trains on PM2.5 in the San Francisco Bay area

Exposure to fine particulate matter (PM2.5) is associated with adverse health effects, including mortality, even at low concentrations. Rail conveyance of coal, accounting for one-third of American rail freight tonnage, is a source of PM2.5. However, there are limited studies of its contribution to PM2.5, especially in urban settings where residents experience higher exposure and vulnerability to air pollution. We developed a novel artificial intelligence-driven monitoring system to quantify average and maximum PM2.5 concentrations of full and empty (unloaded) coal trains compared to freight and passenger trains. The monitor was close to the train tracks in Richmond, California, a city with a racially diverse population of 115,000 and high rates of asthma and heart disease. We used multiple linear regression models controlling for diurnal patterns and meteorology. The results indicate coal trains add on average 8.32 µg/m3 (95% CI = 6.37, 10.28; p < 0.01) to ambient PM2.5, while sensitivity analysis produced midpoints ranging from 5 to 12 µg/m3. Coal trains contributed 2 to 3 µg/m3 more of PM2.5 than freight trains, and 7 µg/m3 more under calm wind conditions, suggesting our study underestimates emissions and subsequent concentrations of coal train dust. Empty coal cars tended to add 2 µg/m3. Regarding peak concentrations of PM2.5, our models suggest an increase of 17.4 µg/m3 (95% CI = 6.2, 28.5; p < 0.01) from coal trains, about 3 µg/m3 more than freight trains. Given rail shipment of coal occurs globally, including in populous areas, it is likely to have adverse effects on health and environmental justice.

Survey evidence on COVID-19 and its impact on rail commuting patterns in Great Britain

The COVID-19 pandemic saw a large proportion of the working population in the United Kingdom working from home for an extend period of time. In September 2021, a substantial number continued to work from home on a regular basis, a stark contrast to the situation pre-pandemic. Prior to 2020, although there was a growing trend for increased home working, this was still not a widespread practice across UK businesses, with the majority of staff working full-time from the employment location. The aim of this paper is to report the main changes in commuting and working patterns among commuters in Great Britain (GB) brought about by the COVID-19 pandemic with a special emphasis on the rail commuting market. The paper is informed by a panel survey of 3,892 GB respondents who commuted regularly to work prior to the pandemic in two waves. The first wave was conducted in Summer 2020 and focused on respondents' pre-pandemic travel patterns. The second wave was conducted in the Autumn 2021 and asked respondents about their current travel patterns. Although the focus was on rail travel, many of the conclusions of this paper are applicable to all modes of transport. Although a majority of pre-pandemic commuters have returned to commuting at least once per week to their place of work, there is a significant share of pre-pandemic commuters who are still working from home full-time. The return to the workplace has been slower among individuals who used to commute by rail compared to other modes. This is partially explained by current workplace arrangements being strongly linked with an individual's occupation and mode of transport. Individuals in office-based occupations are much more likely to work from home compared to those who work in other occupations. The pandemic has brought additional challenges to transport systems in addition to the reduced ridership level. Some of the emerging issues include managing post-pandemic peak travel volumes across a curtailed working week and the associated funding for peak capacity. Nonetheless, the research has highlighted some potential strategies to boost a faster recovery for travel demand.

Rail Intermodal Freight during the Covid-19 Pandemic

The rapid onset of the COVID-19 pandemic in March 2020 marked a challenging time for the US and its freight industry. Manufacturing slowed, consumer purchasing patterns changed, and for many, shopping moved online. The freight industry suffered a sharp decline in shipments, followed by a surprisingly quick rebound. The industry had to adapt quickly to meet fast-changing demand and supply patterns upended by global supply chain disruptions. This paper uses U.S. intermodal activity data, supported by in-depth interviews with leaders of railroads, intermodal carriers, equipment manufacturers, car leasing companies, shippers, and e-commerce players to characterize and assess how the rail industry met the challenge of this demand whiplash and other performance impediments. What emerges is a rich picture of the multi-actor intermodal supply chain, the impacts of COVID-19 on it, the performance of the logistics system in general, and railroads in particular during the pandemic. Industry interviews revealed that a handful of choke points, many of which were outside the rail industry, complicated supply chain responses to COVID-19. The paper shows how the rail industry was an essential component of pandemic resilience, demonstrating a high level of adaptability to meet consumer and business demands. Through the use of depth interviews it reveals the complexity of the intermodal supply chain, and it accurately foretells the subsequent disruptions that continued to plague that supply chain long after the initial impacts of the pandemic.

Injury by design: A thematic networks and system dynamics analysis of work-related musculoskeletal disorders in tram drivers

Tram driving is a safety critical task where work-related musculoskeletal disorders (WRMSDs) and injuries are associated with interacting occupational design factors over time. These interactions then carry implications for workforce retention, public safety, workplace relations and supports. To better understand such interactions, this study used thematic networks and system dynamics (causal loop diagrams) analysis with the aim to unearth a global theme underscoring occurrence of WRMSDs, and describe the factors influencing the system dynamics of WRMSD occurrence in tram drivers. Building on earlier work focused on occupational participation, secondary analysis of driver interviews (n = 13) and driving observations (n = 11) produced thematic network and causal loop models of risk factors that highlighted an Injury by Design problem structure as a global theme. Research targeting organisational culture, human factors, and design standards is needed to minimise WRMSDs risk in tram drivers.

Prevalence and dynamics of distracted pedestrian behaviour at railway level crossings: Emerging issues

Recent increases in pedestrian collisions have led to several studies investigating the effects of distraction on pedestrian behaviour at road intersections. Although distraction has been identified as a contributing factor to pedestrian crashes at railway crossings, only limited research is available regarding the prevalence of this behaviour occurring at railway level crossings. It is, therefore, essential to better understand distraction prevalence at railway crossings to support the use of countermeasures to improve safety outcomes. We conducted field observations at a railway crossing in Brisbane, Australia and its adjacent road intersection to gauge the prevalence of distracted pedestrians. Overall, 585 pedestrians were observed and video recorded during the daytime. The video recordings were coded to estimate the prevalence of distraction behaviour that road users engaged in, factors that affected these proportions, and dynamic changes in behaviour. Compliance with signals was also analysed. We found distraction behaviours such as talking and looking at the mobile screen (41.9%) while walking to be prevalent and affected by age. Highly distractive tasks were found to be less commonplace at the railway crossing, accounting for 3% of the observations. Still, pedestrians at the railway crossing engaged in these highly distractive tasks on their phones for a much longer period of time. While most non-compliances (with traffic lights) occurred among attentive pedestrians and are likely to be intentional, non-compliances by distracted pedestrians were also observed, highlighting that distraction can lead to unsafe decisions or lack of decisions that result in unsafe behaviours. Finally, distraction was found to be a dynamic phenomenon as a few pedestrians stopped engaging in distractive tasks once they reached the crossing, while others engaged in more distractive tasks once they were on the road or crossing. Our study shows that pedestrian distraction is a prevalent issue at railway crossings and future research is required to further understand and mitigate this changing behaviour.

Train driver experience: A big data analysis of learning and retaining the new ERTMS system

Now and in the coming years a new European Rail Traffic Management System (ERTMS) is being deployed on a larger scale. In the system level chosen in the Netherlands (Level 2) lineside signals will disappear and the train driver will receive all information needed for safe and efficient train operation through an interface inside the train cab. Furthermore, procedures, driving skills and communication will alter. Many train drivers will thus need to be trained in driving with ERTMS. Train operating companies (TOC) have to decide on efficient and effective strategies to organise this extensive training volume and to reassure that drivers become and remain proficient after training when roll-out of ERTMS may not have been fully completed. In this paper the central questions to be answered are: How many hours/duties does a driver have to do during a certain period of time on an ERTMS track section to become proficient with ERTMS (learning period), and to stay proficient (retaining period)? The approach taken is unique for rail industry (to the authors' knowledge) and is based on big data analyses. In this study, we were able to study the collective performance of train drivers, by big data analysis while at the same time maintaining privacy through pseudonymisation of the train driver database and their individual performances, characteristics and other potential privacy sensitive data. Databases containing detailed information on all planned and accomplished train service times/positions of the last three years (2015-2017) of a large TOC were combined with personal data from HR databases (age, experience, ERTMS training history, job assessment results, etcetera). From the data, delays caused by rolling stock and train operating related issues were identified. The amount and duration of these delays were correlated with the personal data to test research hypotheses. Again, at the same time we maintained privacy of the individuals' personal data. Although the research has some limitations due to the small amount of existing ERTMS lines, and associated rolling stock, the results show some clear correlations. Thus, quantifiable directions to the minimum amount of ERTMS driving per 3 months during the first year and in the years after are presented. The results are now being translated into models for training and rostering related to the phase of ERTMS roll-out.

Loud and clear? Train horn practice at railway level crossings in Australia

The road environment has changed markedly over the years. Train horns are ostensibly used to alert road users and are typically mandatory on approach to railway level crossings. However, they have increasingly been seen as a nuisance. Beyond their negative aspects, a study has yet to comprehensively evaluate train horn effectiveness and understand if they remain beneficial and relevant in the contemporary environment. Hence, this study aimed to provide evidence on the actual use of train horns. Field observations were conducted at 54 railway crossings across four Australian States. The effects of level crossing type, location, and environmental conditions were investigated in relation to train horn loudness as objectively measured at the crossing. Results revealed that train horns were not always used, presenting an issue for passive level crossings. However, when sounded, train horn use was redundant and insufficiently loud at level crossings equipped with bells. Taken together, current train horn practice was found to be highly variable and dependent on crossing type, remoteness, and individual train drivers, thus resulting in inconsistent warnings and raising important implications for standardisation.

Climate effects on US infrastructure: the economics of adaptation for rail, roads, and coastal development

Changes in temperature, precipitation, sea level, and coastal storms will likely increase the vulnerability of infrastructure across the USA. Using models that analyze vulnerability, impacts, and adaptation, this paper estimates impacts to railroad, roads, and coastal properties under three infrastructure management response scenarios: No Adaptation; Reactive Adaptation, and Proactive Adaptation. Comparing damages under each of these potential responses provides strong support for facilitating effective adaptation in these three sectors. Under a high greenhouse gas emissions scenario and without adaptation, overall costs are projected to range in the $100s of billions annually by the end of this century. The first (reactive) tier of adaptation action, however, reduces costs by a factor of 10, and the second (proactive) tier reduces total costs across all three sectors to the low $10s of billions annually. For the rail and road sectors, estimated costs for Reactive and Proactive Adaptation scenarios capture a broader share of potential impacts, including selected indirect costs to rail and road users, and so are consistently about a factor of 2 higher than prior estimates. The results highlight the importance of considering climate risks in infrastructure planning and management.

Safe trip: Factors contributing to slip, trip and fall risk at train stations

Public transport systems are vital services in urban environments. The design of these complex socio-technical systems is continuously evolving to accommodate larger populations, and their adaptation is essential in supporting the successful and sustainable development of cities and regions. An essential part of this adaptation includes working to increase passenger safety and to minimise their risk of injury. With this focus, key objectives of the current study were to identify the causes of slip, trip and fall (STF) incidents attributable to the rail user and to train and station characteristics. An investigation of historical STF records of 1247 train and station incidents in two Australian jurisdictions was conducted. Various contributing factors to STF events were identified, including locations such as stairs, ramps, escalators, the train's entry and exit step, doorway areas, and passenger running or rushing. A mixed-method field study was then conducted at three train stations and on trains. To further investigate the contributing factors, participants (N = 40) wore an eye tracker as they navigated the stations and trains. The research illustrates that their continuous search for information, and a disconnect between the information needed and the information provided, might be a cause of passenger distraction and an increase in their risky behaviour. Therefore, we suggest that improvements in information design to reduce the high visual workload for passengers might also reduce the incidence of STFs.

Transport safety and human factors in the era of automation: What can transport modes learn from each other?

One of the main aims of introducing automation in transport is to improve safety by reducing or eliminating human errors; it is often argued however that this may induce new types of errors. There is different level of maturity with automation in different transport modes (road, aviation, maritime and rail), however no systematic research has been conducted on the lessons learned in different sectors, so that they can be exploited for the design of safer automated systems. The aim of this paper is to review the impact of key human factors on the safety of automated transport systems, with focus on relevant experiences from different transport sectors. A systematic literature review is carried out on the following topics: the level of trust in automation - in particular the impact of mis-aligned trust, i.e. mistrust vs overreliance, the resulting impact on operator situation awareness (SA), the implications for takeover control from machine to human, and the role of experience and training on using automated transport systems. The results revealed several areas where experiences from the aviation and road domain can be transferable to other sectors. Experiences from maritime and rail transport, although limited, tend to confirm the general patterns. Remarkably, in the road sector where higher levels of automation are only recently introduced, there are clearer and more quantitative approaches to human factors, while other sectors focus only on mental modes. Other sectors could use similar approaches to define their own context-specific metrics. The paper makes a synthesis of key messages on automation safety in different transport sectors, and presents an assessment of their transferability.

On the Identification of Elastic Moduli of In-Service Rail by Ultrasonic Guided Waves

Non-destructive rail testing and evaluation based on guided waves need accurate information about the mode propagation characteristics, which can be obtained numerically with the exact material properties of the rails. However, for rails in service, it is difficult to accurately obtain their material properties due to temperature fluctuation, material degradation and rail profile changes caused by wear and grinding. In this study, an inverse method is proposed to identify the material elastic constants of in-service rails by minimizing the discrepancy between the phase velocities predicted by a semi-analytical finite element model and those measured using array transducers attached to the rail. By selecting guided wave modes that are sensitive to moduli but not to rail profile changes, the proposed method can make stable estimations for worn rails. Numerical experiments using a three-dimensional finite element model in ABAQUS/Explicit demonstrate that reconstruction accuracies of 0.36% for Young's modulus and 0.87% for shear modulus can be achieved.

Estimation of rail properties using semi-analytical finite element models and guided wave ultrasound measurements

Guided wave based monitoring systems require accurate knowledge of mode propagation characteristics such as wavenumber and group velocity dispersion curves. These characteristics may be computed numerically for a rail provided that the material and geometric properties of the rail are known. Generally, the rail properties are not known with sufficient accuracy and these properties also change due to temperature, rail wear and rail grinding. An automated procedure is proposed to estimate material and geometric properties of a rail by finding the properties which, when input into a Semi-Analytical Finite Element (SAFE) model, accurately reproduce measured dispersion characteristics. Pulse-echo measurements were performed and spectrograms show the reflections from aluminothermic welds of three modes of propagation. The SAFE method was used to solve the forward problem of predicting the dispersion characteristics for specified rail properties. Dispersion curves are computed for different combinations of Poisson's ratio and three geometric parameters. These dispersion curves are scaled to cover a range of longitudinal speeds of sound of the rail material. A technique is developed to determine which SAFE model provided the best fit to the experimental measurements. The technique does not require knowledge of the distances to the reflectors; rather these distances are estimated as part of the proposed procedure. A SAFE model with the estimated rail parameters produced dispersion curves and distances in very good agreement with the measured spectrograms. In addition, the estimated mean geometric parameters agreed with the measured profile of the rail head.

Simultaneous lead traction from above and below: A novel technique to reduce the risk of superior vena cava injury during transvenous lead extraction

BACKGROUND

Superior vena cava (SVC) injury is a rare but dreaded complication during percutaneous transvenous lead extraction (TLE) that carries high morbidity and mortality. Despite technological advances and improved efficacy, complication rates remain unchanged.

OBJECTIVE

We sought to develop and test a novel technique that could reduce the risk of SVC injury during TLE.

METHODS

Fifteen patients referred for TLE of an implantable cardioverter-defibrillator lead were included. Patients underwent fluoroscopic and intracardiac echocardiographic (ICE) imaging of the lead-SVC interface with traction from above, below, and simultaneously. Clinical characteristics, fluoroscopic and ICE findings, and procedural outcomes were collected and analyzed.

RESULTS

Fourteen of 15 patients were men (93%) with a mean age of 58 years. The mean lead dwell time was 8.09 ± 3.97 years (range 1.08-16.25 years), and 12 of 15 leads (80%) were dual-coil. Acceptable ICE imaging was not possible in 3 of 15 patients (20%). Simultaneous traction showed greater leftward fluoroscopic shift compared with traction from above (24.96 ± 8.82 mm vs 13.68 ± 6.86 mm; P < .01), created greater separation between the lead and the SVC wall upon ICE imaging (2.0 ± 0.52 mm vs 1.24 ± 0.38 mm; P < .01), and maintained a more parallel relationship of the lead with the SVC wall (24.41° ± 4.14° vs 27.91° ± 4.92°; P < .05).

CONCLUSION

In patients presenting for TLE, simultaneous traction results in increased separation and a more parallel alignment of the lead and SVC wall, allowing the sheath to be better oriented in the desired cleavage plane. This improved sheath alignment is particularly critical when powered sheaths are to be used.

Application of Human Factors Analysis and Classification System (HFACS) to UK rail safety of the line incidents

Minor safety incidents on the railway cause disruption, and may be indicators of more serious safety risks. The following paper aimed to gain an understanding of the relationship between active and latent factors, and particular causal paths for these types of incidents by using the Human Factors Analysis and Classification System (HFACS) to examine rail industry incident reports investigating such events. 78 reports across 5 types of incident were reviewed by two authors and cross-referenced for interrater reliability using the index of concordance. The results indicate that the reports were strongly focused on active failures, particularly those associated with work-related distraction and environmental factors. Few latent factors were presented in the reports. Different causal pathways emerged for memory failures for events such a failure to call at stations, and attentional failures which were more often associated with signals passed at danger. The study highlights a need for the rail industry to look more closely at latent factors at the supervisory and organisational levels when investigating minor safety of the line incidents. The results also strongly suggest the importance of a new factor - operational environment - that captures unexpected and non-routine operating conditions which have a risk of distracting the driver. Finally, the study provides further demonstration of the utility of HFACS to the rail industry, and of the usefulness of the index of concordance measure of interrater reliability.

A practical approach to glare assessment for train cabs

The assessment of glare is a key consideration in the design of a railway driver's cab. However, unlike assessment of other factors, such as forward visibility, there are no standardised approaches for performing assessments of glare. This paper describes an approach for assessing the impact of glare in a full size mock-up of a railway cab. While it is unrealistic to evaluate every possible lighting condition that may potentially occur in the vehicle cab in service, a pragmatic and practical approach is taken to provide a good level of indicative information about the cab design's likely glare performance. This involves assessing internal light sources, such as internal lights and illuminated controls, and simulating external light sources (e.g. the sun, other trains' headlights) by illuminating the cab mock up windscreen, side and door windows with a single light source manually located in a sequence of discrete positions and orientations and assessing the resulting glare impacts. The paper describes a structured process for assessing and recording the impact of glare and recommending mitigations.

Management of personal safety risk for lever operation in mechanical railway signal boxes

Despite increased implementation of computer control systems in managing and regulating rail networks, mechanical signal boxes using lever operation will be in place for years to come. A rolling risk assessment programme identified a number of levers in mechanical signal boxes within the UK rail network which potentially presented unacceptable personal safety risk to signallers. These levers operate both points and signals and the risk is primarily the weights which have to be moved when pulling and pushing the levers. Operating difficulties are often compounded by the design and condition of lever frames, the linkages to the points/signals, maintenance regimes, the workspace and the postures and strategies adopted by signallers. Lever weights were measured as from 15 kg to 180 kg at over 160 boxes, using a specially designed and constructed device. Taken together with examination of injury and sickness absence data, interviews and field observations, and biomechanical computer modelling, the measurement programme confirmed the potential risks. A risk management programme has been implemented, comprising lever weight measurement, training of operations staff, a structured maintenance regime and renewal or redesign for boxes/levers where, after maintenance, a criterion weight level is still exceeded. For a feasible management programme, the first alert (or 1st action) value for further assessment is 55 kg, a second action level requiring specified maintenance is 80-99 kg, and a third action level requiring the lever to be signed out of use is 100 kg.

freight-train derailment severity using zero-truncated negative binomial regression and quantile regression

Derailments are the most common type of freight-train accidents in the United States. Derailments cause damage to infrastructure and rolling stock, disrupt services, and may cause casualties and harm the environment. Accordingly, derailment analysis and prevention has long been a high priority in the rail industry and government. Despite the low probability of a train derailment, the potential for severe consequences justify the need to better understand the factors influencing train derailment severity. In this paper, a zero-truncated negative binomial (ZTNB) regression model is developed to estimate the conditional mean of train derailment severity. Recognizing that the mean is not the only statistic describing data distribution, a quantile regression (QR) model is also developed to estimate derailment severity at different quantiles. The two regression models together provide a better understanding of train derailment severity distribution. Results of this work can be used to estimate train derailment severity under various operational conditions and by different accident causes. This research is intended to provide insights regarding development of cost-efficient train safety policies.