Level Crossings Research Articles

AUTOMATIC RAILWAY GATE CONTROL

In place of the current system, which requires a human to operate the gates at level crossings, this study proposes an automated system that can identify when a train is halted, send out an alarm, and open or close the gate accordingly. A railway gate controller, an alarm module, a signal light module, a stuck detection module, a train detection module, and a controller module are all developed to give a solution. While the stuck detection module has one ultrasonic sensor, the train detection module only has four. The train detection and stuck detection modules use ultrasonic sensors to send out high-frequency signals; when these signals are reflected back to the sensors, they indicate the presence of an item. The controller unit then presses the appropriate buttons to activate the gate, alarm generator, and signal lights based on whether the obstruction is a train or stuck. The results of the experimental experiments demonstrate that compared to the current dominating work, the suggested technique produces a railway gate controller that is more cost-effective, dependable, and straightforward. A level crossing alarm system that uses ultrasonic sensors to detect trains and other obstacles.

Rationalization of Selected Crossing Security Devices on Czech Railways Line 201 Tábor – Ražice

The paper focuses on improving the safety of selected railway crossings on the Tábor – Ražice line of the Czech Railways. The main goal is to rationalize existing safety measures and propose alternative modifications to increase the safety of crossings. These include, for example, the use of horizontal markings and the use of lockable barriers. The work also deals with the elimination of the possibility of some crossings with the aim of minimizing the risks of traffic accidents and thus improving overall safety on the track. The results provide practical recommendations for increasing crossing safety.

Analysis and Optimization of the Causes of Cracks in the Pavement of Highway and Railway Intersections

Firstly, an in-depth analysis is conducted on the principle of crack formation in the pavement panel of highway and railway level crossings and the reasons for cracks under load. Then, based on the characteristics of crack formation in the pavement panel, structural optimization design is carried out on the pavement panel, and finite element analysis is conducted on the optimized structure to verify whether the optimization is reasonable, reduce the occurrence of cracks in the pavement panel of highway and railway level crossings, and extend the service life of the pavement panel.

Automatic Signal and Gate System

Abstract: The "Automatic Signal and Gate System" project is a hardware setup aimed at improving safety on roads, particularly in hilly areas and railway crossings. By utilizing an Arduino UNO and an IR sensor module, the system focuses on signaling in challenging terrains, emphasizing the Automatic Rail Gate Signaling System to prevent rail crossing accidents. This project addresses the pressing issue of accidents and interruptions in rail tracks, which are prevalent in India, a densely populated country. Through the implementation of IR sensors, the system detects the presence of trains and transmits signals to the Arduino. The Arduino, in turn, controls the gate and signals using a servo motor, effectively enhancing safety measures at rail crossings. With a strong emphasis on this specific concept, the project aims to minimize rail crossing accidents and optimize the efficiency of rail gates and crossings. By concentrating efforts on this critical aspect, the system strives to mitigate accidents, reducing unnecessary interruptions in rail track operations and maximizing safety for commuters and railway personnel alike

Design and development of artificial intelligence assisted railway gate controlling system using internet of things

A improvised solution for the Indian Railways' human level crossing controls and the attendant reliability issues they cause. In our nation, level crossings have been the scene of several train accidents. So far, there have been zero productive actions. Using an infrared (IR) detector and an audible alert, the proposed system automatically opens and closes level crossing gates based on when trains approach or depart from the crossing. However, it's possible that a car may become stuck between the pedestrian crossing barriers if they're automated. Here, an ultrasonic sensor may identify the obstruction between the crossing gates, and an Internet of Things (IoT) module would inform the train of the situation. When a train approaches or departs from a railroad crossing, infrared sensors detect its presence and alert an Arduino-UNO, which then commands the gates to open or close using a little servomotor stationed nearby. Using the Node MCU and GPS navigational technology, this system also aims to reduce latency in detecting combustion attacks within the compartment. The resulting section of this paper proves the proposed work efficiency by means of graphically illustrates the following metrics such as: human detection accuracy, gate closing efficiency, alerting system efficiency and data storage efficiency.

Feasibility Analysis for Economic Flyover in Bojonegoro District

The traffic jam that occurred in the city of Bojonegoro on the Rajekwesi – MT road section. Haryono, the leading cause of problems in the area, is at intersections and meetings with railroad tracks. Building a flyover is one solution to congestion that occurs at railroad crossings. An economic feasibility study must be carried out to assess the characteristics of a development project. This study aims to determine how much profit and costs are obtained and the extent of its economic feasibility. The project that will be examined in this study is the construction of a flyover in Bojonegoro district. Then, the feasibility of the Flyover construction project is based on the calculation of Net Present Value (NPV), Benefit Cost Ratio (BCR), and Internal Rate of Return (IRR). The results of this economic feasibility analysis There are three alternative route selection that are associated with economic feasibility where the first alternative with NPV: 2,121,743,718,000, BCR: 12.7499 and IRR: 57 then the second alternative with NPV value: 1,733,795,057,000, BCR: 10.3771, IRR: 50% and the third alternative with an NPV value: 1,395,424,941,000, BCR: 6,978 and IRR: 37%. Based on the economic feasibility analysis using process hierarchy analysis, the first alternative was chosen with a score of 0.571. With the construction of the flyover, it is hoped that it can break up the flow of traffic on the Bojonegoro - Cepu - Nganjuk section to encourage economic growth, trade, and regional development in the Bojonegoro district.

Machine Learning Approach to Enhance Highway Railroad Grade Crossing Safety by Analyzing Crash Data and Identifying Hotspot Crash Locations

Safe railway operation is vital for public safety, the environment, and property. Concurrent with climbing amounts of rail traffic on the Canadian rail network are increases in the last decade in the annual crash counts for derailment, collision, and highway railroad grade crossings (HRGCs). HRGCs are important spatial areas of the rail network, and the development of community areas near railway tracks increases the risk of HRGC crashes between highway vehicles and moving trains, resulting in consequences varying from property damage to injuries and fatalities. This research aims to identify major factors that cause HRGC crashes and affect the severity of associated casualties. Using these causal factors and ensemble algorithms, machine learning models were developed to analyze HRGC crashes and the severity of associated casualties between 2001 and 2022 in Canada. Furthermore, spatial autocorrelation and optimized hotspot analysis tools from ArcGIS software were used to identify hotspot locations of HRGC crashes. The optimized hotspot analysis shows the clustering of HRGC crashes around major Canadian cities. The analysis of cluster characteristics supports the results obtained for causal factors of HRGC crashes. These research outcomes help one to better understand the major causal factors and hotspot locations of HRGC crashes and assist authorities in implementing countermeasures to improve the safety of HRGCs across the rail network.

Entrapment and extraction of wheelchairs at flange gaps with and without flange gap fillers at pedestrian railway crossings

Purpose Where pedestrian crossings meet rail tracks, a flange gap allows the train wheel flanges to pass. This gap can be hazardous for wheelchair users as castor wheels may become trapped. While compressible gap fillers can eliminate the flange gap, fillers are subject to wear, pose a derailment hazard to light rail vehicles and can strip grease from passing wheels. These issues could be mitigated by partially filling the flange gap with a compressible filler. The aim was to investigate the risk of entrapment and ease of extraction of wheelchair castors from flange gaps fully and partially filled with compressible fillers, and assess ride quality. Materials and methods Entrapment risk and ease of extraction for four wheelchairs were tested at various crossing angles with flange gap fillers. Twelve wheelchair users tested ease of extraction and ride quality for partially and fully filled flange gaps. Results It was found that risk of entrapment is low if a standards-compliant crossing with open flange gaps is traversed in a straight line. However, castors can become trapped if the user alters direction to avoid an obstacle or if the crossing surface is uneven. Once trapped, castors are extremely difficult to remove without external assistance. Conclusions Flange gap fillers that reduce the gap to 10 mm or less eliminate entrapment while retaining acceptable ride quality. Filling flange gaps or leaving a residual gap depth of less than 10 mm is the best option to eliminate risk of entrapment and ensure good ride quality for wheelchair users. IMPLICATIONS FOR REHABILITATION Rail crossings flange gaps pose an entrapment hazard for wheelchair users Partial or complete flange gap fillers may reduce entrapment but require research Rehabilitation professionals need to educate wheelchair users on techniques to cross flange gaps safely Consumers and health professionals can consult rail operators to partially fill flange gaps

Understanding the behaviour of magnetic field distribution of railgun under transient conditions using finite element method

The magnetic field distribution in the rails is a crucial factor in comprehending railgun behaviour. The projectile's rapid movement has a significant impact on the magnetic field. If the dispersion of the magnetic field conclusions regarding the conductors are known suitable methods can be used to sketch the magnetic field distribution. The railgun operates on the premise that a high current flow through the rails and armature will create a strong magnetic field. As a result, before designing magnetic shielding, it is necessary to study the features of the magnetic field distribution. The shape of rail and armature cross section is very essential in rail gun design as it determines the magnetic field distribution over rail and armature. The rail gun geometries with rectangular, convex and concave rail cross-sections are compared and simulated using finite element method (FEM). This method is used to determine the magnetic field distribution over rail and armature by sweeping armature position for different rail cross sections. It is observed that for the different rail/armature shapes like rectangular, convex and concave shapes, the C shaped convex armature possesses strong magnetic fields with minimum current density concentration at the throat and trailing end of the armature. From simulation, it can be shown that the magnetic flux density is a descending function of the central angle. The electromagnetic (EM) rail gun launching mechanism was therefore proven to be compatible with the circular concave armature.

Crash Contributing Factors and Patterns Associated with Fatal Truck-Involved Crashes in Bangladesh: Findings from the Text Mining Approach

Despite extensive research on traffic injury severities, relatively little is known about the factors contributing to truck-involved crashes in developing countries, especially in the context of Bangladesh. Because of the unavailability of authentic crash data sources, this study collected data from alternative sources such as online English news media reports. The current study prepared a database of 144 truck-involved fatal crash reports during the period of 12 months (January 2021 to December 2021). The crash reports contain a bag of 15,300 words. Several state-of-the-art text mining tools were utilized to identify crash patterns, including word cloud analysis, word frequency analysis, word co-occurrence network analysis, rapid automatic keyword extraction, and topic modeling. The analysis revealed several important crash contributing factors, such as the type of vehicle involved (auto-rickshaw, bus, van, motorcycle), the manner of collision (head-on), the time of the day (morning, night), driver behavior (speeding, overtaking, wrong-way driving), and environmental factors (dense fog). In addition, “coming from opposite direction” and “head-on collision” are two important sequences of events in truck-involved crashes. Truck drivers are also involved in crashes with trains at rail crossings. The findings of this research can assist policymakers in identifying crash avoidance strategies to lower truck-related crashes in Bangladesh.

Multi-hazard risk assessment of rail infrastructure in India under local vulnerabilities towards adaptive pathways for disaster resilient infrastructure planning

“Lifeline of the nation” is the motto of Indian Railways as it connects through a common thread, billion plus population in one way or the other. The National Rail Plan for India – 2030 focuses on creating a ‘future ready’ Railway system by 2030 by suitably integrating new railway systems like high-speed rails. However, rail infrastructure is exposed to multi-hazards and disasters sometimes disrupt safe rail operations. This study explores rail infrastructure risk assessment at a national scale utilizing the UNDRR framework and synthesized application of geospatial technologies with a focus on disentanglement of local vulnerabilities of the rail infrastructure assets utilizing factors of health of bridges, visibility obstruction to level crossings, labour wages & their regions and GSDP under multi-hazard scenarios. The results revealed that the NR and NFR were identified as high-risk routes under the risk analysis of physical and social vulnerability scenarios, followed by CR Railways. The average annual frequencies of emergency cases in each zone show a correlation r (17) = 0.4758 with the combined mean risk ranks for each zone. In comparison to socioeconomic factors, which contribute to indirect losses, physical factors directly affect safety and contribute to direct losses. Further, outcomes depict more accidents on Indian Railways during the monsoon (nearly 50%) and cold weather (29%) seasons. The study suggests that with the participation of key stakeholders, including urban and transport planners, an integrated approach is helpful in identifying critical rail routes towards risk-informed adaptive disaster-resilient infrastructure planning for providing safety, continuity and reliability of essential rail services.

Difficulty of Identification of Official Tactile Walking Surface Indicators Using the Foot in Japan

In Japan, following an accident wherein a visually impaired was hit by a train inside a railroad crossing, the installation of tactile walking surface indicators (TWSIs) at railroad crossings have become widespread. Attention and guiding patterns as well as escort patterns have been installed in front and inside railroad crossings, respectively. However, the extent to which the latter is more discriminable than the former has not been verified. This study determined the ease of identifying the Japanese official TWSIs and both patterns using the soles of the feet. Twenty blindfolded participants used TWSIs, scanned the raised surfaces with their soles, and responded to the type of TWSIs using three-alternative forced-choice. Compared with attention and guiding, escort patterns were misidentified with subjective sureness and long identification times. In about 90% of times that attention and guiding patterns were incorrectly identified, they were misidentified as escort patterns. The escort patterns were misidentified as attention patterns in about 70% of the times in which they were misidentified. Trials with misidentification had significantly longer identification times and lower sureness (but moderate sureness) than trials with correct identification. Approach angles to TWSIs had practically no effect on the identification. When escort patterns are installed inside the railroad crossings and attention and guiding patterns are installed outside, the visually impaired may misidentify them and accidentally enter or stay at the railroad crossing. Therefore, new installation methods to effectively identify all TWSIs, especially escort patterns, or develop new TWSIs with superior ease of identification should be verified.

Modelling tamping effectiveness for track geometry longitudinal levelling defects

The geometric recovery achieved with tamping is affected by several factors, including maintenance history, ballast condition, type of tamping, age and configuration of track components, operational speeds, and human factors. In this paper, data from 2,819 defects of longitudinal levelling are analysed considering 66,892 km of inspections carried out on 19 lines of the Portuguese railway network over 10 years. The influence of infrastructure clusters, defect level, ballast age, degradation rate before tamping, and the still little-studied shape of defects on geometry recovery is firstly investigated by analysing relationships between the raw data (scatterplots). A multiple linear regression model is then developed to predict the defect level after tamping, taking into account both the defect level before tamping and its shape, which is modelled through a proxy parameter. It is concluded that track sections where there are singularities (underpasses, culverts, level crossings, bridges, tunnels and viaducts) usually have much shorter maintenance cycles (median values up to 60% lower). Ballast age and degradation rate before tamping did not prove to have a marked influence on geometry recovery. Although the defect level before tamping is found to be the factor that most conditions geometry recovery, thus corroborating the critical importance of timely intervention, its shape also proves to have a significant influence, giving rise to differences in geometry recovery of up to 20% of the defect level before tamping.

ADEROS: Artificial Intelligence-Based Detection System of Critical Events for Road Security

The deployment of artificial intelligence (AI) in Intelligent Transportation Systems (ITS), especially in the field of Intelligent Transportation Cyber-Physical Systems (ITCPS) has a strong potential to achieve higher efficiency, reliability, and increased safety in both transportation and traffic. This work focuses on the real-world implementation of ITCPS, in which structure and elements in combination with advanced image processing methods increase safety and fluidity of road traffic at crossroads and railway crossings. In this work, we present a novel system called Artificial Intelligence-based Detection System for Road Security (ADEROS), which combines elements of CPS systems, object detection, and classification, computer vision (CV) which analyzes vehicle trajectory tracking, vehicle and pedestrian presence, light signaling systems, railway barriers at railway crossings, and railway warnings. The presented system is based on a camera module that is suitably positioned to capture the entire scene. The module uses graphics processing units (GPU) for accelerated image processing techniques and the YOLOv4 deep neural network model to detect traffic participants and then dangerous situations in various crossroads and railway crossings. Our improved unique detector can distinguish between individual types of road users and the status of several safety devices at crossroads and railway crossings (for example, the state of traffic lights (TL) or rail barriers). Furthermore, we present experimental implementation details of the ADEROS system, which includes a central server web interface for live traffic situation monitoring, various communication channels for the camera module, and a central server based on.NET core, Cassandra DB, and different security protocols. All data from risky situations are evaluated and transferred to the central server securely without human intervention. The central server aggregates and archives all risky situational data from connected cameras. Finally, we present our experimental results from a real-world pilot project that consists of a camera module prototype deployed in a real crossroad and an operational central web server.

Next-Generation Railway Safety: Designing an Automatic Gate System with Voice-Activated Alarms

Railway crossings are high-risk areas that demand constant vigilance and attention to ensure the safety of passengers and other road users. Automatic gate systems have been widely used to mitigate these risks, but their effectiveness is limited by the reliance on visual cues and their inability to alert drivers or pedestrians who are deaf or hard of hearing. To address this limitation, we propose a voice-activated automatic gate railway system that uses voice commands to control the gates and employs an audio alarm to alert road users of the approaching train and will give also alarm who walk on the railway. Our system consists of a voice recognition module, a control unit, and a network of sensors that detect the presence of trains and road users. When a train is detected, the gate closes automatically, and the system generates a voice alarm to alert nearby road users. The voice recognition module ensures that the system can be operated hands-free, making it convenient for drivers and pedestrians. Moreover, the audio alarm feature ensures that people with hearing impairments are alerted to the approaching train. We evaluated the performance of the proposed system using a prototype installed at a railway crossing in a high-traffic area. Our results demonstrate that the system is reliable and effective, with a high degree of accuracy in voice recognition and a low false positive rate. Our findings suggest that the voice-activated automatic gate railway system with an audio alarm is a promising solution to enhance the safety and security of railway crossings.

Next-Generation Railway Safety: Designing an Automatic Gate System with Voice-Activated Alarms

Railway crossings are high-risk areas that demand constant vigilance and attention to ensure the safety of passengers and other road users. Automatic gate systems have been widely used to mitigate these risks, but their effectiveness is limited by the reliance on visual cues and their inability to alert drivers or pedestrians who are deaf or hard of hearing. To address this limitation, we propose a voice-activated automatic gate railway system that uses voice commands to control the gates and employs an audio alarm to alert road users of the approaching train and will give also alarm who walk on the railway. Our system consists of a voice recognition module, a control unit, and a network of sensors that detect the presence of trains and road users. When a train is detected, the gate closes automatically, and the system generates a voice alarm to alert nearby road users. The voice recognition module ensures that the system can be operated hands-free, making it convenient for drivers and pedestrians. Moreover, the audio alarm feature ensures that people with hearing impairments are alerted to the approaching train. We evaluated the performance of the proposed system using a prototype installed at a railway crossing in a high-traffic area. Our results demonstrate that the system is reliable and effective, with a high degree of accuracy in voice recognition and a low false positive rate. Our findings suggest that the voice-activated automatic gate railway system with an audio alarm is a promising solution to enhance the safety and security of railway crossings.

Next-Generation Railway Safety: Designing an Automatic Gate System with Voice-Activated Alarms

Railway crossings are high-risk areas that demand constant vigilance and attention to ensure the safety of passengers and other road users. Automatic gate systems have been widely used to mitigate these risks, but their effectiveness is limited by the reliance on visual cues and their inability to alert drivers or pedestrians who are deaf or hard of hearing. To address this limitation, we propose a voice-activated automatic gate railway system that uses voice commands to control the gates and employs an audio alarm to alert road users of the approaching train and will give also alarm who walk on the railway. Our system consists of a voice recognition module, a control unit, and a network of sensors that detect the presence of trains and road users. When a train is detected, the gate closes automatically, and the system generates a voice alarm to alert nearby road users. The voice recognition module ensures that the system can be operated hands-free, making it convenient for drivers and pedestrians. Moreover, the audio alarm feature ensures that people with hearing impairments are alerted to the approaching train. We evaluated the performance of the proposed system using a prototype installed at a railway crossing in a high-traffic area. Our results demonstrate that the system is reliable and effective, with a high degree of accuracy in voice recognition and a low false positive rate. Our findings suggest that the voice-activated automatic gate railway system with an audio alarm is a promising solution to enhance the safety and security of railway crossings.

Exploring the need to model severity of single- and multi-occupant vehicles crashes separately: A case of crashes at highway-rail grade crossings

Exploring the need to model severity of single- and multi-occupant vehicles crashes separately: A case of crashes at highway-rail grade crossings

Photon-dark photon conversion with multiple level crossings

Photon-dark photon conversion with multiple level crossings

Motor Vehicle Drivers’ Knowledge of Safely Traversing Highway-Rail Grade Crossings

This study investigates motor vehicle drivers’ socioeconomic, personality, and attitudinal factors associated with their knowledge of safely traversing highway-rail grade crossings (HRGCs). A three-step mail-based survey of randomly selected Nebraska households solicited responses from licensed drivers ( N = 980, response rate = 39%). Of the total 31 questions on the questionnaire, nine pertained to respondents’ knowledge of safely navigating HRGCs (e.g., what does a crossbuck sign require a driver to do when approaching a rail crossing?). Correct answers to the questions provided a measure of respondents’ knowledge of safely traversing HRGCs and led to their classification in five ordered categories. A random parameter probit model then assessed associations among respondents’ socioeconomic, personality, and attitudinal characteristics and the five ordered categories of their HRGCs negotiation knowledge. The estimated model revealed that drivers with negative or indifferent attitudes toward HRGCs, who were unemployed, or engaged in risky driving behavior around HRGCs were likely to be less informed about safe HRGCs navigation. Similarly, drivers that disliked waiting at HRGCs and those who did not receive information on HRGCs safety had lower levels of knowledge of safely negotiating HRGCs. Attentive drivers at HRGCs and those who routinely stopped in response to active train warning devices were associated with higher levels of knowledge. Drivers with negative or indifferent attitudes toward HRGCs were less knowledgeable about safe HRGCs navigation. The research findings are useful for targeted driver education and traffic safety programs, safety professionals, and policymakers engaged in HRGCs safety.