Railway Level Crossings Research Articles

Improving the safety of distracted pedestrians with in-ground flashing lights. A railway crossing field study

Introduction: Current signage at intersections is designed for attentive pedestrians who are looking ahead. Such signage may not be sufficient when distracted by smartphones. Illuminated in-ground LED lights at crossings are an innovative solution to alert distracted pedestrians. Method: We conducted a field study at a railway crossing equipped with in-ground lights to assess whether distracted pedestrians (N = 34, Mean age 33.6 ± 8.6 years) could detect these lights and how this impacted on their visual scanning and crossing behaviour. This involved a 2 × 3 repeated measures design exploring the impact of the presence (treatment) or absence (control) of in-ground lights (treatment) at a crossing, and a distractor task presented through a mobile device (none, visual, and audio) on eye movements recorded using an eye tracker, and verbal reporting of when participants detected the lights. Results: Participants engaged in the distraction tasks as evidenced by their accuracy and reaction times in all conditions. With both the audio and visual distraction tasks, participants looked at the in-ground LEDs and detected their activation as accurately as when not distracted (95%). While most participants detected the lights at their activation, visual distraction resulted in 10% of the detections occurring as participants entered the rail corridor, suggesting effectiveness in gaining pedestrians’ attention. Further, participants were significantly less likely to check for trains when visually distracted (70%), a 10% reduction compared to the no or audio distractor conditions (80% and 78% respectively). The introduction of the in-ground lights resulted in appropriate scanning of the rail tracks (77% and 78% for the visual and auditory distractor tasks respectively) similar to that of non-distracted participants for the crossing without lights (80%). Conclusions: Our findings indicate that illuminated in-ground lights could be useful in attracting the attention of distracted pedestrians at railway level crossings, and possibly at other road intersections. Practical Applications: Illuminated in-ground lights can be installed at rail and road intersections with known pedestrian distraction as a countermeasure. Further research is necessary to understand their long-term effects.

Autopsy Death Profile Due to Railway Injury in Mangalore, A Coastal City of South Karnataka- A Retrospective Analysis

Background: Accident deaths is one of the most common types of deaths in India. In India railway relateddeaths are reported throughout the year. Fatal trains impacts cause extensive musculoskeletal injuries due tothe nature of the object as well as the amount of force transmitted during impacts. The purpose of all accidentinvestigation to take a positive step in correction of causation and to prevent such incidents in the future.Objective: The aim of this study is to assess and learn demographic details, characteristics of the incident infatal train crashes and recognize the injury profile.Methods: This is a retrospective autopsy based study. We considered 59 cases of railway track relateddeaths in three years (2016-2018) conducted at Tertiary Care Hospital, mortuary, Mangalore and analyzedthem statistically.Results: The study showed most of the victims were men between 30-40 years of age. Most victims ofincidents were pedestrians (72.9%,). The circumstance of incident in the majority was while walking on sideof railway track (39%). The highest number of fatalities 42.4 % were observed between 6 Am to 12 pm.Analysis as to cause of death in accidental circumstances revealed that multiple injuries (35.9%) followedby blunt trauma of head (33.3%) and in suicidal circumstances, death due to blunt trauma to head (40%) anddecapitation (40%) were the most prevalent.Limitations: The study needs to be done for longer duration and more detailed parameters in the railwaytrack accidents.Conclusion: The study established that majority of railway related deaths are accidental. and there is arequirement of awareness and implementing strict traffic laws to strengthen their safety for such preventabledeaths especially among the commuters of train and among the pedestrians using railway level crossings

Modelling driver decision-making at railway level crossings using the abstraction decomposition space

The objective of this paper is to cast users of railway level crossings as flexible and adaptive decision-makers, and to apply a cognitive systems engineering approach to discover new behaviour-based insights for improving safety. Collisions between trains and road vehicles at railway level crossings/grade crossings remain a global issue. It is still far from apparent why drivers undertake some of the behaviours that lead to collisions, and there remains considerable justification for continuing to explore this issue with novel methods and approaches. In this study, 220 level crossing encounters by 22 car drivers were subject to analysis. Concurrent verbal protocols provided by drivers as they drove an instrumented vehicle around a pre-defined route were subject to content analysis and mapped onto Rasmussen’s Abstraction Decomposition Space. Three key results emerged. First, when they realise they are in a crossing environment, drivers’ natural tendencies are to look for trains (even if not required), slow down (again, even if not required), and for their behaviour to be shaped by a wide variety of constraints and affordances (some, but not all, put there for that purpose by railway authorities). The second result is that expert decision-making in these situations does not describe a trajectory from high-level system purposes to low-level physical objects. Instead, drivers remain at intermediate and lower levels of system abstraction, with many loops and iterations. The final finding is that current level crossing systems are inadvertently constraining some desirable behaviours, affording undesirable ones, and that unexpected system elements are driving behaviour in ways not previously considered. Railway level crossings need to be designed to reveal their functional purpose much more effectively than at present.

3D-LIDAR Based Object Detection and Tracking on the Edge of IoT for Railway Level Crossing

Object detection is an essential technology for surveillance systems, particularly in areas with a high risk of accidents such as railway level crossings. To prevent future collisions, the system must detect and track any object that passes through the monitored area with high accuracy, and this process must be performed fulfilling real-time specifications. In this work, an edge IoT HW platform implementation capable of detecting and tracking objects in a railway level crossing scenario is proposed. The response of the system has to be calculated and sent from the proposed IoT platform to the train, so as to trigger a warning action to avoid a possible collision. The system uses a low-resolution 3D 16-channel LIDAR as a sensor that provides an accurate point cloud map with a large amount of data. The element used to process the information is a custom embedded edge platform with low computing resources and low-power consumption. This processing element is located as close as possible to the sensor, where data is generated to improve latency, privacy, and avoid bandwidth limitations, compared to performing processing in the cloud. Additionally, lightweight object detection and tracking algorithm is proposed in this work to process a large amount of information provided by the LIDAR, allowing to reach real-time specifications. The proposed method is validated quantitatively by carrying out implementation on a car road, emulating a railway level crossing.

Automatic Railway Road Crossing (RLC) Traffic Light System for Metric Gauge Railway Network in Tanzania

The verdict has been established that Railway Level Crossings (RLCs) present possible risk to roads users. Because of the ever-increasing number of vehicles on the road every day, it was determined that employing automation at level crossings can be beneficial to both road and railway users' safety. The aim is to develop an automated railway level crossing system that would reduce the likelihood of collisions between trains and road users at intersections. From the perspective of a railway level crossing, the conditions safeguards must meet is straightforward - Before a train passes, there must be a complete stop for all road users. Two RFID sensors and Ultrasonic sensors are used located at strike-in and strike-out points at the level crossing. Detection of automobiles stuck on the railroad once the train has activated the automation at the RLC is performed by the Ultrasonic sensor. Other warning measures in the system include an automated barrier, Light Emitting Diode flashing lights, and an audio alarm device. Arduino UNO and ESP32 were used as microcontrollers to perform all the logical operations and control commands. Consequently, the next train station from RLC was updated of the incoming train’s Expected Time of Arrival (ETA). The time it takes for the barriers to close will be determined by the train’s speed. In this project work, the prospective application strategy for securing railroad crossings is described in detail. It is the best feasible control of the level crossing by using the train detection system.

Acceptance of visual and audio interventions for distracted pedestrians

Distraction from mobile devices increases pedestrian risks at intersections. Innovative interventions are currently installed at road and rail intersections to alert pedestrians. These interventions will be effective only if pedestrians modify their behaviour. The Technology Acceptance Model (TAM) posits that behaviour changes as a result of behavioural intention, which is affected by perceived usefulness and perceived ease of use. However, the link between intention and actual behaviour is often overlooked. The current study aims to investigate this link and apply this theoretical framework to interventions for distracted pedestrians. We conducted a day-time field study at three railway level crossings in New Zealand with such interventions reminding pedestrians to look for trains: in-ground flashing lights located at footpath level, an audio warning message, and in-ground flashing lights combined with the audio warning message. Participants (N = 34, Mean age 33.6, SD = 8.6 years) walked through level crossings while performing a distractor task (visual and auditory distraction) or when not distracted. Actively checking for trains from both sides of the crossing was used as a measure of actual behaviour. All three interventions were perceived as useful (5.1 ± 0.4) and easy to use (5.6 ± 0.2) and resulted in positive intention to use the technology (5.8 ± 0.3). Statistical analyses confirmed that the TAM constructs - particularly perceived usefulness - affected intention, and intentions lead to behavioural change with improved crossing behaviours. This study highlights the importance of perceived usefulness and intentions to use the interventions with reducing distracted pedestrian behaviours.

An Innovative Approach to Surveying the Geometry of Visibility Triangles at Railway Level Crossings.

Railway level crossings (RLCs) in Poland are classified according to their protection systems. Category D, which is a form of passive RLC, aims to ensure safe and efficient operation. Surveying is essential to prepare and control the geometry of the visibility triangles used at RLCs. This article presents a new approach to monitoring the geometry of visibility triangles of RLCs using an electronic total station and a magnetic measuring square (MMS). Its main assumptions are presented together with the application of the innovative measuring instruments. Visibility is demonstrated taking into account the angles of intersection of the road axis with the track axis of the railway line and additional attributes related to the analysis and evaluation of general visibility conditions. The research highlights controversies that have received special attention against the background of the safety status of railway level crossings. As a case study, the RLC located on a single-track railway line in Poland is examined. The final section presents applications of the results obtained according to the proposed methodology. It is shown that the proposed approach is practical and effective. In addition to surveyors, the survey methodology can be used by road and rail traffic engineers and policy makers to further improve traffic safety at RLCs. This is an important global research task.

Understanding Why Drivers Cross the Line at Activated Railway Crossings

Congestion at urban and active railway level crossings leads to non-compliant driver behavior, and scenarios in which road users may enter into the rail corridor with the crossing nearing full closure. Previous research indicates this scenario occurs with alarming regularity during peak periods. However, limited research has investigated whether such non-compliance arises from errors or from deliberate decisions. The objective of this study was to better understand driver decisions when approaching a level crossing during activation. Vehicle movements and crossing activation were continuously recorded for 2 months at a congested active level crossing close to Melbourne, Australia. Each movement corresponding to a vehicle approach to the level crossing during onset of activation was extracted with traversals counted, and the ability to stop safely modeled with linear motion equations, using the position and speed of the vehicle at activation. The probability of entering the level crossing was then modeled with generalized linear models. Analysis revealed that much of the non-compliance was involuntary and linked to a dilemma zone in the absence of sufficient warning time for drivers to react to and safely stop before proceeding through the crossing. However, deliberate non-compliance was also an issue, and independent of the time of day. Findings are discussed in relation to the ideal grace period for road users at such crossings, and consideration is given to enforcement as a viable treatment for reducing deliberate non-compliance.

Advanced model-based risk reasoning on automatic railway level crossings

Safety is a core issue in the railway operation. In particular, as witnessed by accident/incident statistics, railway level crossing (LX) safety is one of the most critical points in railways. In the present paper, a Bayesian network (BN) based framework for causal reasoning related to risk analysis is proposed. It consists of a set of integrated stages, namely risk scenario definition, real field data collection and processing, BN model establishment and model performance validation. In particular, causal structural constraints are introduced to the framework for the purpose of combining empirical knowledge with automatic learning approaches, thus to identify effective causalities and avoid inappropriate structural connections. Then, the proposed framework is applied to risk analysis of LX accidents in France. In details, the BN risk model is established on the basis of real field data and the model performance is validated. Moreover, forward and reverse inferences based on the BN risk model are performed to predict LX accident occurrence and quantify the contribution degree of various impacting factors respectively, so as to identify the riskiest factors. Besides, influence strength and sensitivity analyses are further carried out to scrutinize the influence strength of various causal factors on the LX accident occurrence likelihood and determine which factors the LX accident occurrence is most sensitive to. The main outputs of our study attest that the proposed framework is sound and effective in terms of risk reasoning analysis and offers significant insights on exploring practical recommendations to prevent LX accidents.

Artificial Intelligence Enabled Road Vehicle-Train Collision Risk Assessment Framework for Unmanned Railway Level Crossings

The study focuses on the artificial intelligence empowered road vehicle- train collision risk prediction assessment, which may lead to the development of a road vehicle-train collision avoidance system for unmanned railway level crossings. The study delimits itself around the road vehicle-train collisions at unmanned railway level crossings on single line rail-road sections. The first objective of the study revolves around the rail-road collision risk evaluation by the development of road vehicle-train collision frequency and severity prediction model using Poisson and Gamma-log regression techniques respectively. Another study objective is the collision modification factor implementation on predicted risk factors, to reduce the road vehicle-train collision risk at the crossings. The collision risk has been predicted to be 3.52 times higher and 77% lower in one direction while in other directions it is 2.95 times higher and 80% lower than average risk at all unmanned railway level crossings. With collision modification factor application on higher risk contributing factors i.e. `crossing angle' and `train visibility, it predicts to reduce the road vehicle-train collision risk to 85% approximately.

Multilevel Automated Security System for Prevention of Accidents at Unmanned Railway Level Crossings

Developing technology to come up with viable, economic and efficient solutions for prevention of accidents at unmanned railway level crossings is an active research field. Many approaches have been proposed in this research area but none of them are efficient enough to deploy them at the unmanned level crossings and completely eliminate human presence. In this work, we have sensed the research gaps in the current technologies which try to eliminate the unmanned railway level crossings by building Road Over Bridges and Road Under Bridges or by manning them. We have come up with a cost efficient and effective multi-level automated system for prevention of accidents at the railway level crossings using sensor networks.

Marginal costs for railway level crossing accidents in Sweden

The purpose of the present study is to estimate accident risks and marginal costs for railway level crossings in Sweden. The marginal effect of train traffic on the accident risk is used to derive the marginal cost per train passage that is due to level crossing accidents. The estimations are based on Swedish data from 2000 to 2012 on level crossing accidents, train volume, and crossing characteristics. In this study we estimate the accidents risk for both motorized road traffic and vulnerable road users. As a proxy for road traffic flow we use three categories of road type, and to capture the influences of pedestrians and bicyclists we use information about the number of persons living nearby the level crossing. The results show that both protection device, road type, traffic volume of the trains, and number of persons living nearby the level crossing have significant influence on the accident probability. The marginal cost per train passage regarding motor vehicle accidents is estimated at EUR 0.15 on average in 2012 (price level of 2017). The corresponding number for accidents with vulnerable road users excluding suicides is EUR 0.08 or including suicides EUR 0.50. The cost per train passage varies substantially depending on type of protection device, road type, the traffic volume of the trains, and number of persons living nearby the crossing.

Frustration at congested railway level crossings: How long before extended closures result in risky behaviours?

Drivers’ non-compliance with rules is a prominent factor in collisions with trains at railway level crossings. Road user impatience and frustration has been identified as an underlying factor in non-compliance and can be characterised as a specific risk factor. However, research on non-compliance related to waiting times and driver inconvenience lacks in the literature. This paper, therefore, seeks to enhance the currently limited understanding of the relationship between waiting times and risky driver behaviour. An Advanced Driving Simulator was used to obtain objective measures of level crossing non-compliance. Subjective measures on driver frustration and decision-making processes were also collected. Sixty participants completed six driving tasks each, with the tasks varying in terms of traffic conditions, number of trains and associated waiting times. This study shows that increased waiting times result in higher levels of frustration and an increased likelihood of risky driving behaviour, particularly for waiting times longer than 3 min. Non-compliance included entering the activated crossing before boom gates are down, entering the crossing after the train passage but before signals are deactivated, stopping/reversing on the crossing. Subjective data revealed that participants did not comply with level crossing rules due to factors including time pressure, impatience/frustration and low perceived risk. The results suggest that, where possible, waiting times should be standardised at values lower than 3 min to reduce the likelihood of risky road user behaviour.

Automation System of Railway Level Crossings and SCADA Integration

The increasing complexity of the industrial automation equipment, through interlocking hardware and software solutions and the dynamics of upgrading facilities for providing the final products or services at competitive costs has led to the need to impose the standards of mandatory requirements for functional safety and risk reduction. Thus a complex system was developed for the production and management of the power supply voltages to ensure both the safety standards and a high degree of adaptation to the specific conditions of supervision and control for railway level crossings and SCADA integration. The data communication between the automatic control system and the SCADA system is achieved through the TCP/IP Modbus protocol and OPC-UA server. The log file of the automation process is recorded into a MySQL database server and in TDMS files. The monitoring of the automatic process through SCADA integration is improved by generating automatic reports and sending e-mails to predefined addresses if the local control unit does not function properly or if the undue presence of vehicles or people is detected in the crossing area when the barriers are lowered.

Traverses, delays and fatalities at railway level crossings in Great Britain

This paper investigates relationships between traverses, delays and fatalities to road users at railway level crossings in Great Britain. A ‘traverse’ means a passage across a level crossing by a road user, who may be a pedestrian, cyclist, or occupant of a road vehicle. The paper finds that the road users with the highest fatality rate per traverse are pedestrians at passive crossings. Their rate is about three orders of magnitude higher than that of users with the lowest risk, who are road vehicle occupants at railway-controlled crossings. The paper considers the choice between automatic and railway-controlled crossings on public roads. Railway-controlled crossings are widely used in Britain. They are about one order of magnitude safer than automatic crossings, but they impose greater delays on users. A formula is developed to give the overall delay to road users at either type of crossing in terms of the numbers of road users and trains per day, and in terms of the length of time that the crossing must be closed to the road to allow the passage of one train. It is found that automatic level crossings cause substantially less delay than railway-controlled level crossings. The official monetary values of road user delay and of preventing a fatality were used to estimate the valuations of delays and fatalities at hypothetical but representative automatic and railway-controlled crossings. These valuations were then used to explore the effect of replacing representative railway-controlled with automatic crossings or vice-versa. It is found that the valuation of the reduced delays from adopting automatic crossings typically outweighs the valuation of the losses from the increased casualties. However, in practice Britain has chosen to retain a large number of railway-controlled crossings, which implies accepting the delays in return for a good level crossing safety record. Finally, an analysis is carried out to determine the additional risk of typical car and walk journeys that involve traversing a level crossing compared with similar journeys that do not. It is found that the additional risk is small for motor vehicle journeys, but substantial for walk journeys.

Getting the Attention of Drivers Back on Passive Railway Level Crossings: Evaluation of Advanced Flashing Lights

Improving safety at railway level crossings remains a priority for the rail industry internationally, as they remain a significant hazard. A high proportion of collisions occur at passive level crossings, because of their high prevalence and their lower effectiveness at mitigating the risks that road users encounter at such crossings. The unreasonable cost required to upgrade them to incorporate active warnings implies that such crossings will remain on the road, and that alternative approaches are required. Drivers tend to make errors at such crossings, and this can be related to approaching such level crossings at speeds that are too high, exhibiting reduced scanning behaviors to look for trains, and not complying with stop signs at the crossing. An alternative approach is to upgrade the advanced signage with active flashing lights activated by road vehicles, aimed at reducing looked-but-failed-to-see errors and reinforcing the behavior expected from road users at such crossings. A field trial was conducted in New Zealand that evaluated how approach speeds and the visual scanning behavior of 27 drivers, recorded with an eye tracker, changed with such treatments. It was found that the presence of road vehicle-activated advanced signage provided a range of benefits for drivers unaware of the presence of a passive crossings, such as increasing drivers’ attention to road signs through drivers fixating on signage for longer durations and reduced (slower) approach speeds. Further research is needed to evaluate whether these benefits are sustained over time, and whether this can minimize complacency resulting from familiarity.

Identification Determinant Variables of the Injury Severity Crashes at Road-Railway Level Crossing in Indonesia

Abstract Accident between road and railway traffic at the railway level crossings (RLCs) is a significant issue in developing countries particularly in Indonesia. The Indonesia national traffic accident data (IRSMS) recorded approximately 900 accidents at RLCs between 2013 and 2016. In this study, accessed for 154 RLCs detail accident records can be completed. The number of accidents at RLCs in Indonesia are substantial high with a ratio of accidents and fatality accidents were 40.47 accidents/1,000 RLCs and 14.96 fatalities/1,000 RLCs respectively by comparison to the international standard. This paper adopts the ordered probit model for identifying the determinant variables of the injury severity crashes at various RLCs types (i.e. active and passive) and locations (i.e. urban and rural). The findings are as follows: rain will increase the risk of fatality, Power Two Wheelers have a high risk of fatalities in urban and less risk in rural passive RLCs; Fatal accident crossing at RLCs occur in the low traffic condition and dawn period. Finally, Male drivers are more likely being killed in the vehicles-train accidents in the RLCs. The recommendations are: First, to suggest the train authority to provide full length boom gate at both sides at the active RLC to reduce the chances for motorcyclists’ violate the boom gate from the other side of roads when train passing the level crossing. Second, for all passive RLCs must be equipped with a warning siren, flashing light prior train passing, and street light for improving alertness drivers/riders during day and night as well as in peak or non-peak hours.

ICT Enabled Vehicular Safe Distance Modeling at Indian Unmanned Railway Level Crossings

Indian railways have been facing a serious problem of railroad accidents at unmanned railway level crossings. The study presents the Information and Communication technology enabled modeling of safe distance for road vehicles approaching at Indian unmanned railway level crossings. The purpose of study is the computation and analysis of the speed breaker distance to provide a safer distance to road vehicles arriving towards the unmanned railway level crossings. Information and Communication Technology i.e. integrated GPS, GIS; sensor-based data collection was done from 19 unmanned railway level crossings on Shahdara-Shamli-Tapri railway route. The ‘speed breaker distance from crossing’ modeling and validation has been performed using regression analysis in IBM SPSS Statistics 24.0. The sensitivity analysis results indicated that, the perception and reaction time is the most contributing factor for speed breaker distance from crossing determination. The accidents are predicted to decrease 17% (approx.) with developed ‘speed breaker distance from crossing’ model. Therefore, the scope of the work lies in road user safety at unmanned railway level crossings.

Key considerations for automated enforcement of non-compliance with road rules at railway level crossings: The Laverton case in Victoria, Australia

In Australia, most railway level crossings in high-traffic road environments are actively protected. Despite this, crashes at these crossings account for two thirds of the costs of crashes at all level crossings. Such crashes typically arise from non-compliance with road rules. Current protections and interventions have mainly focused on reducing driver errors through increased level crossing awareness. The rail industry is now exploring the use of automated enforcement at level crossings to reduce non-compliance. However, very little research has evaluated the potential benefits of such an approach, or provided a sound scientific evidence-base for its utility within Australia. The aim of this research is to create a scientific evidence-base reflecting the size of the problem at such crossings, and to understand whether the current automated enforcement policies used on the road can be viably adapted for level crossings. A level crossing in a suburb called Laverton close to Melbourne was selected as a study site based on reported congestion issues and high rates of non-compliance to road rules. Monitoring equipment (cameras and radar) was installed for two months to obtain a baseline dataset of non-compliance with a two-day observation study conducted at the site prior to the installation in order to evaluate the reliability of these data. Over 700 separate road user non-compliance events were recorded with the equipment – such as entering the level crossing while flashing lights were activated, and stopping on the level crossing, highlighting that non-compliance at active level crossings can be commonplace. The equipment was found to be effective at detecting some non-compliance events but not very effective at detecting others, such as occurrences of vehciles stopping on the crossing. Further studies need to be conducted to determine whether such technology could modify driver behaviour at such level crossing, and reduce rates of non-compliance.

Walking the talk: Comparing pedestrian ‘activity as imagined’ with ‘activity as done’

The safety of vulnerable road users, including pedestrians, is an important issue worldwide. In line with the shift towards systems thinking in transport safety, the aim of this study was to compare the normal performance of pedestrians as they navigate the road system with that imagined by road system managers to gain insights into how safety management can be improved for this vulnerable road user group. The Event Analysis of Systemic Teamwork framework was used to compare pedestrian activity ‘as imagined’ and ‘as done’ at signalised road intersections and railway level crossings. Data regarding ‘activity as imagined’ was derived from documentation review, and data on ‘activity as done’ was derived from a semi-naturalistic study of ten participants. It is concluded that in both environments pedestrians exhibited more diversity and variability than anticipated by system managers. Insights for improving the design of the road environment for pedestrians are provided. Further, it is argued that wider changes to the processes used in the design and management of road systems are needed.