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

Edla, Damodar Reddy; Tripathi, Diwakar Ramanuj; Kuppili, Venkatanareshbabu; Ramesh, Dharavath

doi:10.1007/s11277-019-06952-4

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…Accidents such as “derailment of passenger trains” (S4), “derailment of goods trains” (S5), and “collision at un-manned level crossings” (S7) are classified as “intolerable” or “undesirable” due to their high likelihood and severity. Derailments can have catastrophic consequences in terms of both human casualties and infrastructure damage [ 60 , 61 ], and collisions at unmanned level crossings cause significant risks due to the absence of active safety measures [ 62 , 63 ]. These types of accidents demand urgent mitigation efforts to minimize their occurrence and impact on railway safety.…”

Section: Resultsmentioning

confidence: 99%

Comprehensive risk assessment of Pakistan railway network: A semi-quantitative risk matrix approach

Khan,

Pervez,

Zhang

et al. 2024

Heliyon

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Section: Resultsmentioning

confidence: 99%

Comprehensive risk assessment of Pakistan railway network: A semi-quantitative risk matrix approach

Khan,

Pervez,

Zhang

et al. 2024

Heliyon

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“…In India, as per records of Indian railway, 66% of fatalities with deaths because of accidents at crossings have hovered around 300 for almost a decade, now with 40% of the train accidents occurring at level crossings (Edla et al , 2020). Here, level crossing collisions are more frequent and consequently more severe, because they involve injuries and death to many both rail and road users as well as property damage and transportation delays.…”

Section: Literature Reviewmentioning

confidence: 99%

Safety and risk analysis at railway crossings of north-south Addis Ababa light rail

Sekasi

Solihu

2021

SRT

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Purpose Railway-level crossings (RLCs) are the point of intersection between rail and road users and are therefore hotpots of road-rail user conflict and catastrophic collisions. The purpose of this study is to assess the risks associated with RLCs and suggest probable reduction measures. Through questionnaires and visual inspection, the authors identify the safety risks, hazards and hazardous events at some railway crossing of Addis Ababa light rail transit (AA-LRT) north-south (N-S) route. The identified risky events are then categorized based on As Low As Reasonably Practicable (ALARP) principle and generic risk ranking matrix. The authors then examine existing safety management measures at railway crossing and assess the need for additional safety management. Five major crossings on the 16.9 km (10.5 mi) N-S line, starting from Menelik II Square to Kality, were considered for the study. This study is carried out by data collection from about 145 stakeholders and the application of statistical data and risk analysis methods. The major findings of this study and the recommendations for improvement are suggested. Design/methodology/approach The research followed a case study approach. Through questionnaires and visual inspection, the authors identify the safety risks, hazards and hazardous events at some railway crossing of AA-LRT N-S route. The identified risky events are then categorized based on ALARP principle and generic risk ranking matrix. Collected data was then analyzed using SPSS to deduce relationships. Findings The study findings reveal human factors as the greatest cause of accidents, injury or death. About 22% of hazards identified by category are human factors, whereas 20% are because of technical problems. Intolerable risks stand at 42%, whereas the tolerable risks are at 36% according to risk classification results as per the ALARP model. Because the process of risk management is a long-term cycle, its importance should not be missed at any time. Research limitations/implications Because of design considerations of RLCs and the difference in generalized human behaviors for people of a given region, the results are limited to AA-LRT RLCs. This study opens a discourse for detailed evaluations, qualitative and quantitative analysis into the categorized identified hazards. There is also room for additional research into the performance of RLCs aimed at formulating standard necessary features that should be included on RLCs for proper risk control especially in emerging economies. Originality/value The research paper is original and has not been submitted for consideration to other journals.

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“…The laser beam is the first sign for the upcoming train, and the other sensors help to detect the train pass. Another study on the safety of level crossing was made by Edle et al [7]. They studied on the multilevel automated security system which aims to unmanned level crossings.…”

Section: Introductionmentioning

confidence: 99%

Vibration analyses of railway systems using proposed neural predictors

Yıldırım¹,

Sevim²,

Kalkat³

2023

NNW

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Due to travelling on railway systems; there are many gaps and problems in cross areas. Therefore; it is necessary and very important to establish intelligent crossing systems in such areas. On the other hand, it is not possible for trains to stop or brake immediately against an obstacle due to their high speed and inertia. For this reason, it is necessary to work on the safety/warning of the other main factors and necessities (pedestrians and vehicles) in level crossings. This experimental investigation is carried out by using an experimental real-time train and crossing systems. The main vibration parameters are analysed by using neural networks. First, the dynamics of the train-rail system related to level crossings are examined, and the vibrations created by the train on rails are measured at different speeds. Then three types of proposed neural networks predictors, Levenberg-Marquardt backpropagation (LMBP), scaled conjugate gradient backpropagation (SCGB) and BFGS quasi-Newton backpropagation (BFGS) are used to predict the vibration of the train-rail system. From the results, it is seen that the proposed LMBP is more suitable for analysing and predicting the vibration of the train-rail system. It is clear that the speeds of the trains approaching the level crossing can be estimated from the vibration of the trains on the rails.

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

Cited by 8 publications

References 6 publications

Comprehensive risk assessment of Pakistan railway network: A semi-quantitative risk matrix approach

Comprehensive risk assessment of Pakistan railway network: A semi-quantitative risk matrix approach

Safety and risk analysis at railway crossings of north-south Addis Ababa light rail

Vibration analyses of railway systems using proposed neural predictors

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