Young drivers at railway crossings: an exploration of risk perception and target behaviours for intervention

Effectiveness of signs for pedestrian-railroad crossings: Colors, shapes, and messaging strategies

INTRODUCTION

Train-pedestrian conflicts result in a substantial number of serious and fatal injuries annually. Signs indicating safe and permissible behaviors near railroad rights of way are commonly relied upon to mitigate collisions. However, the effectiveness of these signs in preventing accidents often depends on clarity and interpretation of the sign. The objective of this study was to evaluate the (1) effectiveness of sign messaging strategies and designs at pedestrian-railroad crossings, and (2) effects of context and risk-taking propensity on decisions to cross tracks.

METHOD

A survey study (N = 1011) was conducted comparing likeliness to cross for a variety of pedestrian-railroad scenarios. The DOSPERT scale was included to estimate an individuals' risk-taking.

RESULTS

Findings reveal that action-conveying and emotionally-motivated signs are more effective in discouraging railroad crossing in high-risk situations (i.e., train present, crossing gates down, or warning lights flashing), compared to information-only signs. However, decisions to cross are primarily influenced by the presence of a train and crossing gates' status, followed by sign type. MaxDiff analysis show that yellow signs with black symbols and square shaped signs are perceived as the clearest in conveying safety information, compared to black on white, red on white, and circular signs. Additionally, individuals who cross railroad tracks as pedestrians more frequently exhibit higher risk-taking tendencies, while there is no relationship between driving across tracks and risk-taking propensity. Males and younger individuals also have higher risk-taking tendencies.

CONCLUSIONS AND PRACTICAL APPLICATIONS

These findings have implications for policy and practice, such as revising manuals to incorporate more effective sign designs and targeted educational campaigns for high-risk groups. It is also crucial to conduct ongoing monitoring of implemented interventions, which could follow the framework presented in this paper. The study emphasizes collaboration across sectors to improve overall safety at pedestrian-railroad crossings, contributing to safer transportation infrastructure for all.

Factors associated with self-reported inattentive driving at highway-rail grade crossings

This research identified factors associated with inattentive driving at Highway-Rail Grade Crossings (HRGCs) by investigating drivers' self-reported inattentive driving experiences and factors pertaining to their socioeconomic, personality, attitudinal, and other characteristics. A random selection of 2500 households in Nebraska received a survey questionnaire designed for licensed motor vehicle drivers; respondents returned 980 questionnaires. Factor analysis identified latent variables evaluating drivers' patience and inclination to wait for trains, attitudes toward new technology, law enforcement or education regarding HRGC safety, and the propensity to commit serious traffic violations at HRGCs. The investigation utilized a structural equation model for analysis. This model indicated that drivers with a higher risk of inattentive driving at HRGCs were: female, younger in age, from households with higher incomes, with shorter tenure (in years) in their current city of residence, more frequently used HRGCs, received less information on safety at HRGCs, had less patience to wait for trains to pass and had less interest in safety improvement technology, law enforcement or safety education at HRGCs. These research findings provide useful information for future research and to policy makers for improving public safety. Additionally, the results are useful for safety educational program providers for targeted program delivery to drivers that are more vulnerable to distracted driving at HRGCs.

To stop or not to stop: Contrasting compliant and non-compliant driver behaviour at rural rail level crossings

Many rail level crossings (RLXs) have only passive protection, such as static signs instructing road users to stop, yield, or look for trains. Stop signs have been suggested as a low-cost option to improve safety at passive RLXs, as requiring drivers to stop should encourage safe behaviour. However, field observations have noted high rates of non-compliance at stop-controlled RLXs. To explore this further, we conducted an on-road study to identify factors that influence compliance at stop-controlled RLXs. Twenty-two drivers drove a 30.5km route in rural Australia, encompassing three stop-controlled RLXs. In over half of all cases (59%) drivers stopped completely at the RLX; on 27% of crossings drivers executed a rolling stop, and on 14% of crossings drivers violated the stop controls. Rolling stops were defined as a continuous deceleration to <10km/h, but remaining above 0km/h, before accelerating to >10km/h. Behavioural patterns, including visual checks and decision-making, were similar when comparing drivers who made complete versus rolling stops. Non-compliant drivers did not differ from compliant drivers in approach speeds, but spent less time visually checking for trains. Post-drive interviews revealed some drivers wilfully disregarded the stop sign, whereas others did not notice the stop sign. Those who intentionally violated noted trains were infrequent and suggested sight distance was good enough (even though all crossings had been formally assessed as having inadequate sight distance). Overall the results suggest most drivers exhibit safe behaviour at passive RLXs, but a notable minority disregard or fail to notice signs. Potential avenues for redesigning passive RLXs to improve safety are discussed.

Walking the line: Understanding pedestrian behaviour and risk at rail level crossings with cognitive work analysis

Pedestrian fatalities at rail level crossings (RLXs) are a public safety concern for governments worldwide. There is little literature examining pedestrian behaviour at RLXs and no previous studies have adopted a formative approach to understanding behaviour in this context. In this article, cognitive work analysis is applied to understand the constraints that shape pedestrian behaviour at RLXs in Melbourne, Australia. The five phases of cognitive work analysis were developed using data gathered via document analysis, behavioural observation, walk-throughs and critical decision method interviews. The analysis demonstrates the complex nature of pedestrian decision making at RLXs and the findings are synthesised to provide a model illustrating the influences on pedestrian decision making in this context (i.e. time, effort and social pressures). Further, the CWA outputs are used to inform an analysis of the risks to safety associated with pedestrian behaviour at RLXs and the identification of potential interventions to reduce risk.

Where do novice and experienced drivers direct their attention on approach to urban rail level crossings?

Crashes at rail level crossings (RLXs) remain a persistent but ill-defined safety issue. In urban areas, RLXs are typically located in areas of high workload and visual clutter, such as busy shopping strips. Despite this, the impact of such environments on driver behaviour and compliance with RLX controls is not well understood. This study sought to examine where drivers direct their attention on approach to urban RLXs located in busy shopping strip areas, and whether this differs between novice and experienced drivers. Participants drove an instrumented vehicle around a pre-defined urban route containing several active (flashing light with boom barriers) RLXs. Drivers' visual scanning behaviour and cognitive processes were examined on approach to RLXs. The results suggest that RLXs were not a key focus of drivers' attention. Further, rather than actively scanning, participants were over-reliant on RLX warning signals and the behaviour of surrounding vehicles to alert them to the presence of both trains and RLXs. This study provides important insights into drivers' visual and cognitive behaviour on approach to urban RLXs located in areas of high visual demand.

A mathematical modeling approach to resource allocation for railroad-highway crossing safety upgrades

State Departments of Transportation (S-DOT's) periodically allocate budget for safety upgrades at railroad-highway crossings. Efficient resource allocation is crucial for reducing accidents at railroad-highway crossings and increasing railroad as well as highway transportation safety. While a specific method is not restricted to S-DOT's, sorting type of procedures are recommended by the Federal Railroad Administration (FRA), United States Department of Transportation for the resource allocation problem. In this study, a generic mathematical model is proposed for the resource allocation problem for railroad-highway crossing safety upgrades. The proposed approach is compared to sorting based methods for safety upgrades of public at-grade railroad-highway crossings in Tennessee. The comparison shows that the proposed mathematical modeling approach is more efficient than sorting methods in reducing accidents and severity.