OJS (University St. Kliment Ohridski)
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APPLICATION OF FUZZY LOGIC FOR TRAIN BRAKING DISTANCE DETERMINATION
Full text linkDetermination train braking distance or where should train stop in station represent delicate task which consist of many factors. This factors can be human and technical. In this paper we focused on external factors that mostly affect braking distance and can cause changes in its length. This factors are often imprecisely, crisp data like speed, grade, braking force and braking equipment response time, and for that purpose we use fuzzy logic. A fuzzy logic system that uses rules based on the experience and expertknowledge of a locomotive drivers and railway operators is proposed and applied to achieve train braking distance.The aim of this paper is to determine train braking distance and difference between calculated braking distance and data from the field. In this paper an attempt has been made to create model that can represent real state. This model was created and simulated using Matlab fuzzy logic toolbox. Special attention in this paper is paid on sensitivity analysis, which shown the stability of the obtained results. Sensitivity analysis was done through two phases which shown the stability of the results to a change in the types and values of membership functions and change in the defined fuzzy rules. FLS is tested for ten variants for different train categories anddifferent conditions on the field
PREDICTION OF DENSITIES BASED ON SCARCE TRAFFIC FLOW INFORMATION
Full text linkTraffic fluctuations are always evident in highways or urban arterial networks that consist of some signalized or unsignalized intersections. Traffic conditions may change as a result of changes in peak timing flows, miscellaneous incidents, variable weather etc. A constant challenge of traffic engineers and professional peoplethat are closely related to traffic control and management remains the identification of parts in which the traffic situation changes and the provision of information about traffic parameters. Prediction of density parameter in short time intervals is important in lots of traffic modelling and control strategies of freeways and urban arterials. For more, the possession of short time density values for particular parts of the freeway segment, plays an importation role on providing drivers with information about events or traffic incidents. Not always the traffic flow amounts are possible to be measured in any part of the segment we are interested in. Thus maycome due to the lack of detector coverage or detecting defects even if it exists. The purpose of this paper is twofold. First is the development of a discrete model so called Cell Transmission Model (CTM) [1,2] that is analogue with approximation of the LWR hydrodynamic model of traffic flow. The second one is the integration of the Kalman Filter [3] to the mentioned model, in order to increase the accuracy of the modeled traffic densities. A Kalman filter (KF) is a recursive algorithm that uses only the previous time-step’s prediction with the current measurement in order to make an estimate for the current state. KF does not require previous data to be stored or reprocessed with new measurements. At everyiteration, the KF minimizes the variance of the estimation error, making it an optimal estimator if linear and Gaussian conditions are satisfied. In order to highlight the difference between accuracies of the predictions of the densitiesobtained by pure CTM model and by application of the Kalman Filter on it, a short highway segment with simple composition is chosen as object of study. The segment comprises of a ramp and the number o lanes are the same during its entire length
DETERMINING THE IMPACT OF OVERLOAD ON MARKOV PROCESSES IN THE QUEUEING SYSTEM BASED ON AN ANALYSIS OF CUSTOMERS PATIENCE IN QUEUE
Full text linkThe impact of overloading the queueing system on Markov processes was based on an analysis of customers patience in queue. In this paper the regimes of the unloaded and overloaded operation of the queueing system are observed. In the case of overloading, there is a general change in Markov characteristics. Implications for patient and impatient customers are in queue with the significance. Customer patience was degraded quantitatively and qualitatively in overload mode of operation. These characteristics are confirmed on the concrete example and measurements of parameters of the queueing system - parking garage
APPLICATION OF FUZZY FAULT TREE ANALYSIS FOR DETERMINATION OF RAILWAY CROSSING RELIABILITY
Full text linkFault tree analysis (FTA) is one of the basic and most used methods for safety and reliability analysis of technical systems. This method is especially suitable for analysis system, which failures can cause serious consequences that affect on human lives and environment.Railway crossings, as places of crossroads of road and rail traffic, constitute one of the most important sources of potential conflicts and accidents in the railroad domain. The probability of occurrence of an unwanted event is increased if the participants in the traffic do not respect the rules or if a malfunction has occurred on the technical device of the railway crossing. In this paper FTA model was created in combination with fuzzy logic. Fuzzy logic in this model is used to represent imprecisely probabilities of failure of the system. By using the technique we proposed herein, values are transformed into the fuzzy numbers to give a realistic estimate of failure possibility of a basic event in FTA. The aim of this paper was to form a model which can identify scenarios and events that have the most affect on unwanted top event. This can lead to reduce number of accidents on railway crossing.Model was tested for one railway crossing in Pirot for basic top event “Passing the train by the unsecured railway crossing”. Final ranking on events by their impact on failure of system was done through fuzzy importance index
COMPETITIVENESS OF RAIL FREIGHT CORRIDORS – CASE STUDY: CORRIDORS X AND IV
Full text linkAfter almost 30 years since the first declaration of corridor network of Europe and the same amount of time spent on investments in its development with goal of creating single european transport market, it seems like the era of competitiveness of some of the corridors has begun. The term of corridor competitveness, its significance, factors of competitiveness and comparative analisys of factors for TEN-T Corridors X and IV have been reviewed in this paper. Also, paper reviews methods of evaluation of corridor competitiveness which have been used in other author’s work, followed by the method of comparative analisys. As main factors of competitiveness of these two corridors in this moment, this paper specialy marks the length of corridor, travel time - commercial speed of the train, waiting time at border crossings, level of access charges and usage of corridor capacity
DEVELOPMENT OF TRAFFIC VOLUME FORECASTING MODEL USING MULTIPLE REGRESSION AND PRINICPAL COMPONENT ANALYSIS
Full text linkThis paper is focused in development model for traffic volume forecasting in Anamorava region. Demographic and socioeconomic macro variables (independent variables) are identified at country and region level which have an impact on generation of traffic volume (dependent variable), using dataset for the period 2004-2016. Multiple Regression Analysis (MLR) method was used to build dependency between variables and model development. In order to increase forecasting capabilities of the MLR model, it was necessary to eliminate high correlation between variables (multicollinearity phenomenon). A new methodology was used, with included Principal Component Analysis (PCA) by transforming original variables in Principal Components (PCs). With the combination PCA and MLR methods are developed hybrid model as called Principal Component Regression (PCR). By employing performance indicators, it was found that the PCR model performs much better than MLR model