Study on real-time prediction model of railway passenger flow based on big data technology

In order to solve the limitation of traditional offline forecasting application scenarios, the author uses a variety of big data open source frameworks and tools to combine with railway real-time data, and proposes a real-time prediction model of railway passenger flow. The model architecture is divided into four levels from bottom to top: data source layer, data transmission layer, prediction calculation layer and application layer. The main components of the model are data flow and prediction flow. Through message queue and ETL, the data process part realizes the synchronization of offline data and real-time data; through the big data technology frameworks such as Spark, Redis and Hive and the GBDT (Gradient Boosting Tree) algorithm, the prediction process partially realizes the real-time passenger flow of the train OD section prediction. The experimental results show that the model proposed by the author has certain practicability and accuracy both in performance and prediction accuracy.

Analyzing the Factors Which Influence the Effectiveness of Railway Passenger Transport

Railway transport makes significant contributions to the economy of every country. Approximately 30 000 people are directly employed in this sector in Bulgaria, and the added value to the GDP amounts to approximately 2% (NSI, 2019а). Railway transport is crucial for a more sustainable transport sector, stable economic development, as well as social cohesion and connectivity of citizens. The article presents a study of the technical and operational factors for the work of railway transport as well as energy consumption during freights. The goal is to outline the way these indicators affect the stable development of railway transport and what their actual influence is in regard to carrying out railway passenger transport. The speed and energy efficiency of railway passenger transport have been analysed, as they will serve as the foundation for specific suggestions on how to carry out passenger transport in Bulgaria more effectively.

Evaluation of Ride Comfort in a Railway Passenger Car Depending on a Change of Suspension Parameters

Ride comfort for passengers remains a pressing topic. The level of comfort in a vehicle can influences passengers’ preferences for a particular means of transport. The article aims to evaluate the influence of changes in suspension parameters on the ride comfort for passengers. The theoretical background includes a description of the applied method for a creating the virtual model of an investigated vehicle as well as the method of evaluating the ride comfort. The ride comfort of the vehicle is assessed based on the standard method, which involves calculating the mean comfort method, i.e., ride comfort index NMV in chosen points on a body floor. The NMV ride comfort index (Mean Comfort Standard Method) requires the input of acceleration signals in three directions. The rest of the article offers the results of simulation computations. The stiffness–damping parameters of the primary and secondary suspension systems were changed at three levels and the vehicle was run on the real track section. The ride index NMV was calculated for all three modifications of the suspension system in the chosen fifteen points of the body floor. It was found that lower values in the stiffness of the secondary suspension system lead to lower levels of ride comfort in the investigated railway passenger car; however, lower values in the stiffness–damping parameters of the primary suspension system did not decrease the levels of ride comfort as significantly.

Prediction of passenger train using fuzzy time series and percentage change methods

In the subject of railway operation, predicting railway passenger volume has always been a hot topic. Accurately forecasting railway passenger volume is the foundation for railway transportation companies to optimize transit efficiency and revenue. The goal of this research is to use a combination of the fuzzy time series approach based on the rate of change algorithm and the Holt double exponential smoothing method to forecast the number of train passengers. In contrast to prior investigations, we focus primarily on determining the next time period in this research. The fuzzy time series is employed as the forecasting basis, the rate of change is used to build the set of universes, and the Holt's double exponential smoothing method is utilized to forecast the following period in this case study. The number of railway passengers predicted for January 2020 is 38199, with a tiny average forecasting error rate of 0.89 percent and a mean square error of 131325. It can also help rail firms identify future passenger needs, which can be used to decide whether to expand train cars or run new trains, as well as how to distribute tickets.

Possibilities of Building Connection of M.R. Štefánik Airport to the ŽSR Network

The current conditions of the railway infrastructure near the M. R. Štefánik Airport is analysed as unsatisfactory. The current form of the railway infrastructure of the monitored area is not adapted to the creation of a suitable place for boarding and alighting of passengers. The point determined for boarding and alighting of passengers must be at a reasonable distance from the M. R. Štefánik Airport terminal. This distance must be able to be overcome by walking so that it is not necessary to use another mode of transport to move between these places. The article deals with the possibilities of connecting of M. R. Štefánik Airport to the ŽSR network. The basis for the proposal to connect M. R. Štefánik Airport with a suitable infrastructure ŽSR network within the framework of railway passenger transport is the determination of a suitable transfer point. One of the logical priorities is to place the transfer point as close as possible to the air transport terminal of the M. R. Štefánik Airport within the space possibilities and technical conditions.

The Mathematical Analysis of Demands for Railway Passenger Transport in Kosovo

The purpose of this paper is to analyse the railway transport of passengers in Kosovo, to determine its intensity and structure, to analyse which factors have the greatest impact on the demand for regular rail transport. Furthermore, the paper will examine which trend, which model fits best in moving this mode of transport based on data from 2011 to 2019, and then predict future trends in transport demand. The existence and strength of the dependence among the selected factors, which are assumed to have an impact on passenger rail transport will be examined by the mathematical method of regression analysis.

Increasing the mobility of University North students by improving the railway infrastructure: Case study on the Varaždin-Koprivnica route

The trend of an increasing number of student travellers from the University of the North, the University Centers of Koprivnica and Varaždin also affects the quality of their mobility. The mobility of student-passengers in rail passenger transport is directly related to the quality of service and the inevitable maximum safety aspect, but also to the appropriate railway infrastructure. According to the above, it is necessary to analyse the current state of transport infrastructure and propose activities to increase the mobility of student-passengers. This paper analyses the current status of student-passenger mobility in railway passenger transport, and also analyses the regional features of road and railway transport infrastructure, state road DC-2 and railway R202 Varaždin-Dalj, located between the cities of Varaždin and Koprivnica, with regard to route characteristics and infrastructure facilities. As part of the work, a survey was conducted through questionnaires, and questionnaires were completed by students-travellers of the University of the North.