An Estimate of the Number of Accidents and Serious Accidents in Railway Traffic

The aim of this paper is to investigate the relationship between the number of extraordinary events and the total number of accidents and serious accidents in railway traffic. The purpose of the paper is to estimate the total number of accidents and serious accidents on the track network of Croatian Railway Infrastructure (HŽI) until 2027. The results of the research are based on secondary data that are the subject of processing using statistical methods of correlation and regression analysis. The main finding of this paper points to the existence of a strong and positive relationship between the number of extraordinary events and the total number of accidents and serious accidents in railway traffic. The estimated number of extraordinary events and total number of accidents and serious accidents until 2027 indicates a trend of their further reduction

Modelling of Diagnostics Influence on Control System Safety

If the control system besides the standard control functions also realizes the functions (known as safety functions), failures of which can influence safety of the controlled process, then the control system may be a source of risk for assets, that are within the scope of the controlled process. Early detection of these failures and subsequent negation of their effects can have a significant influence on the safety integrity level of the safety function and thus also on the elimination of risks related to the controlled process. Therefore, the diagnostics is the means which, if appropriately applied, can increase not only the availability, but also the safety of the control system. The paper deals with using the homogeneous Markov chains to influence the evaluation of on-line diagnostics on the hardware safety integrity of the safety function, depending on the application method of several simultaneously operating diagnostics mechanisms and their basic parameters - the failures diagnostic coverage coefficient and the failure diagnostics time

On analyzing the vulnerabilities of a railway network with Petri nets

Petri nets are used in this paper to estimate the indirect consequences of accidents in a railway network, which belongs to the class of the so-called transportation Critical Infrastructures (CIs), that is, those assets consisting of systems, resources and/or processes whose total or partial destruction, or even temporarily unavailability, has the effect of significantly weakening the functioning of the system. In the proposed methodology, a timed Petri ne<t represents the railway network and the trains travelling over the rail lines; such a net also includes some places and some stochastically-timed transitions that are used to model the occurrence of unexpected events (accidents, disruptions, and so on) that make some resources of the network (tracks, blocks, crossovers, overhead line, electric power supply, etc.) temporarily unavailable. The overall Petri net is a live and bounded Generalized Stochastic Petri Net (GSPN) that can be analyzed by exploiting the steady-state probabilities of a continuous-time Markov chain (CTMC) that can be derived from the reachability graph of the GSPN. The final target of such an analysis is to determine and rank the levels of criticality of transportation facilities and assess the vulnerability of the whole railway network

Model for estimating and comparing the risk of occurrence accidents and incidents on the level crossings

U radu je određen matematički model sa ciljem proračuna maksimalnog rizika i utvrđivanja pouzdanosti putno-pružnih prelaza. U definisanom inženjerskom okviru, od determinističke do stohastičke granice apstraktnog broja nesreća i nezgoda, nalazi se  proporcija za estimaciju i komparaciju rizika od nastanka nezgoda i nesreća na putno-pružnim prelazima zasnovana na realnim događajima. Moguće je utvrđivanje nivoa bezbednosti za svaki putni prelaz pojedinačno, što predstavlja originalni doprinos u istraživanjima bezbednosti na mestima ukrštaja železničkog i drumskog saobraćaja.This paper is determined a mathematical model to calculate the maximum risk and determine the reliability of level crossings. In the strongly defined engineering framework, from the deterministic to the stochastic limit of the number of theoretical accidents and incidents, there is a proportion for estimating and comparing the risk of accidents and incidents at level crossings based on real occurrences. It is possible to determine the level of safety for each railroad crossing individually, which is an original contribution to safety research at the intersections of railway and road traffi

Model-Based Diagnosis of Multi-Track Level Crossing Plants

As is witnessed by railway statistics, Level crossing (LC) safety has always been one of the major concerns for railway stakeholders. LC safety is an issue at the crossroads between technical aspects, operational procedures and human factors, making the search for effective solutions a challenging task. This paper deals with technical aspects related to LC safety. In particular, we carry out an analysis pertaining to the diagnosability of two main failure classes that can affect the protection system at automatic LCs. In the current study, a labeled Petri net behavioral model depicting the global system function, including both the normal operation and the faulty behavior, is first established. Petri net has been used as the modeling formalism mainly for its mathematical foundations and expressiveness capabilities. Using such a mathematical notation is highly recommended to deal with dependability issues in safety-critical systems, especially in railways. Based on the established model, different model-based approaches for the diagnosis of discrete event systems (DESs) will be brought into play to investigate the diagnosability of two considered failure classes, while the obtained results will be compared. In particular, a technique that we have established, which is based on on-the-fly and incremental analysis of the model state space shows interesting efficiency, making it possible to tackle the combinatorial explosion problem, which arises particularly when considering multi-track LCs. The originality of this technique w.r.t existing DES model-based diagnosis approaches is that, in general, a partial building/investigation of the state space suffices to decide diagnosability and build an online diagnoser. Findings pertaining to LC safety are drawn based on a thorough discussion of the obtained results. In particular we show how the diagnosability analysis outputs can be taken into account in the global LC risk assessment process