Periodica Polytechnica Transportation Engineering

Supplier Qualification Using FMEA in a Meat Company

Adrienn Boldizsár — 2023-09-13

The analysis of the processes between supplier and customer and the detection and handling of defects is based on objective, quantified criteria so that customer complaints can be handled as efficiently as possible, with the least possible inconvenience. One possible risk-management method is FMEA, or Failure Mode(s) and Effect(s) Analysis, which allows a team to anticipate and prevent failures from occurring anywhere. It is an analytical methodology to identify and check for potential problems when designing a product, service or process. It can be used to reduce the number of defective supplies and thus indirectly increase customer satisfaction (by more efficient purchasing, the price can be kept lower and the quality higher, and fewer customer complaints from end users can be expected). It was used in this study to assess the supplier quality of a Hungarian industrial company in the FMCG sector and to make tangible improvements in a short time to eliminate supplier defects.

Accident Prediction Modeling for Indian Metro Cities

Villuri Mahalakshmi Naidu — 2023-09-13

Road accidents are one of the biggest concerns to the road safety of developing nations. In India, around 150,000 fatal accidents occur annually. Road accident prediction models help in accessing the factors responsible for and those that contribute more to accidents. Most of the prediction models focus on the parameters like road characteristics, traffic characteristics, driver characteristics, and road geometrics. In this study, we considered socio-economic and land-use parameters as input data for accident prediction modeling. The socio-economic and land-use variables data of 20 Indian metro cities were collected. The data were collected for a period of 5 years ranging from 2016 to 2020. A multiple linear regression model was developed between the total number of accidents that happened in the 20 metro cities and the socio-economic and land-use variables. ANN model was also developed to check its applicability to this study and the results obtained are satisfactory.

Impact of Traffic Sign Diversity on Autonomous Vehicles

Ziyad N. Aldoski — 2023-09-13

Traffic sign classification is indispensable for road traffic systems, including automated ones. There is a fundamental difference in the visual appearance of traffic signs from one country to another. Each dataset has its design standards and regulations based on shape, color, and information content, making implementing classification and recognition techniques more difficult. This paper aims to assess the influence of traffic sign diversity on autonomous vehicles (AVs) by reviewing several previous studies, comparing, summarizing their results, and focusing on classifying and detecting traffic sign datasets based on color, shape, and deep learning spaces using various methods and applications. Furthermore, it covers the main challenges facing road designers and planners considering changes to road safety infrastructure. It will be argued that compiling and standardizing a comprehensive global database of traffic signs is very difficult because it is costly and complex in application. However, it is still one of the possible solutions for the coming decades. Recommendations for future developments are also presented in this study.

The Influence of Pandemic COVID-19 on the Quality of Public Railway Transport in South Bohemia

Martin Telecký — 2023-09-13

The way the pandemic COVID-19 affecting the public railway transport in the South Bohemia currently is a much-debated issue. On both a theoretical and practical level, this paper aims to determine whether the pandemic COVID-19 influenced the quality of public railway transport in South Bohemia between the years 2020 and 2021. The results of the paper provide the unambiguous arguments which could have been foreseen. There is, however, dissatisfaction among individual groups of passengers as well as on the part of the state. The surveys point to the slowly improving state of the quality of public railway transport in the coming years. Statistical and mathematical methods confirm the overall weaker efficiency and stability of passenger transportation. The reason is the psychological and economic aspects due to the COVID-19 pandemic.

Benchmarking Travel Time and Demand Prediction Methods Using Large-scale Metro Smart Card Data

Iyad Zimmo — 2023-09-13

Urban mass transit systems generate large volumes of data via automated systems established for ticketing, signalling, and other operational processes. This study is motivated by the observation that despite the availability of sophisticated quantitative methods, most public transport operators are constrained in exploiting the information their datasets contain. This paper intends to address this gap in the context of real-time demand and travel time prediction with smart card data. We comparatively benchmark the predictive performance of four quantitative prediction methods: multivariate linear regression (MVLR) and semiparametric regression (SPR) widely used in the econometric literature, and random forest regression (RFR) and support vector machine regression (SVMR) from machine learning. We find that the SVMR and RFR methods are the most accurate in travel flow and travel time prediction, respectively. However, we also find that the SPR technique offers lower computation time at the expense of minor inefficiency in predictive power in comparison with the two machine learning methods.

Intermodal Passenger Transport after COVID-19 Pandemic Breakout

Maria Morfoulaki — 2023-09-13

The current paper is based on data collected within the framework of the Inter-Connect PLUS project, with a focus on incorporating new norms before, during, and after the COVID-19 pandemic. A questionnaire was conducted in four countries of the Adriatic-Ionian (ADRION) Region: Italy, Slovenia, Croatia, and Albania. The collected data from the survey was analyzed to draw conclusions about the travel modes citizens used before, during, and are willing to use after the pandemic. The paper closes with recommendations, in the form of a Roadmap, highlighting the potential positive impact of the pandemic on the future of sustainable mobility.

Automated System for Freight Transportation Optimization on the Transport Network

Mykola Dekhtyaruk — 2023-09-13

An automated system for freight traffic optimization on a transport network has been developed, which is realized in the form of a complex computer program with application of the visual design environment of Embarcadero RAD Studio. The program complex consists of the main form from which two subprograms are loaded. The search of optimum routes performed by the routing optimization subprogram is used at transportations of freight on the set transport network based on different schemes (from one vertex (the supplier) to all other vertices (consumers), serially – from each vertex to all other vertices, and from two (or several) set of vertices to all other vertices). Freight delivery between the supply and consumption points was optimized by means of the freight transportation optimization subprogram, taking into account the restrictions on the volume of freight at the points of departure and destination.

Determination of Urban Public Transport Demand by Processing Electronic Travel Ticket Data

Aleksandr I. Fadeev — 2023-09-13

Determination of transport demand is one of the key factors to solve many transportation problems. Existing methods for obtaining information about passenger mobility have significant shortcomings; currently, methods based on the collection, integration and analysis of big data (Urban computing, big data) are being increasingly used.
Within the framework of this approach, a methodology has been developed for determining the passenger traffic by public transport from the operations of validating electronic travel tickets: smart cards, transport cards, magnetic cards, mobile phones or other electronic devices (Electronic Gadgets), their details are recorded in the Automated Fare Collection (AFC).
In this work we have taken into account that the passenger can travel one, two or more segments before paying for the trip. On some routes, payment is made at the end of the trip.
The article presents a methodology based on defining and evaluating the set of acceptable variants of the connectedness of the passenger trips' sequence, which takes into account many factors that influence the choice of travel routes by the passenger. For example, unlike existing solutions, the possibility of paying for travel at any point of the route is taken into account, not necessarily immediately after boarding the vehicle.
Approbation of the considered methodology was carried out on the data of the Krasnoyarsk public transport system for April 2019. It has been proved that passenger traffic from the validation of electronic travel tickets allows us to estimate the parameters of public transport demand within the limits of acceptable statistical errors.

Integrating Multi-agent System and Microsimulation for Dynamic Modeling of Urban Freight Transport

Cristian G. Gómez-Marín — 2023-09-13

This work aims to apply an integration between a multi-agent system and microsimulation to take advantage of the large amount of data generated in urban freight transport to improve the overall performance of the urban supply chain without forgetting the principles of autonomy that govern each of its actors, responding to the different dynamic scenarios that may arise in the operational context. The integration framework produces a satisfactory communication process in those modeling methods measured by two indexes: throughput and latency. The results of this integration show a robust response to dynamic scenarios and allow reacting to the different quantity of changes without dismissing the search for optimum solutions.

Modeling of Passenger Flows in Agglomerations of Large Developing Cities (on the Example of Kyiv)

Dmitry Prusov — 2023-09-13

Based on the analysis of the fundamental impact of transport infrastructure, the city and the agglomeration are increasingly interpreted as a set of historically composed residential and industrial districts formed in the areas of interchanges of different modes of transport. On the example of the City of Kyiv, the modeling of passenger flows in agglomerations of large developing cities is considered, in order to implement the provisions of a modern urban environment, based on transport analysis of the urban area, with further forecasting of passenger flows on the street-road network and choice of main types of citywide passenger transport in the city. Based on the calculation of the population and passenger formation of transport areas, a model of the city's transport infrastructure is represented, the distribution of passenger traffic by modes of transport is estimated. The results of experimental studies of the intensity of existing passenger flows and models of their definition in the agglomeration of the most valuable city are determined. And the ways to solve the problems of conflict between the city and transport are proposed.

Forecasting the Number of Road Accidents in Poland Depending on the Day of the Week Using Neural Networks

Piotr Gorzelanczyk — 2023-09-13

A very large number of people are killed on the roads. Although the value is decreasing from year to year and the pandemic has reduced the number of traffic accidents even further, the number is still very high. For this reason, it is necessary to find out on which days of the week the highest number of traffic accidents occur, and to know the accident forecast for the coming years, so that we can do everything possible to minimize the analyzed value.
The aim of the article is to develop a forecast of the number of road accidents in Poland depending on the days of the week. For this purpose, monthly data on the number of road accidents in Poland by days of the week were analyzed on the basis of Police data. Based on this data, a forecast of the number of road accidents for 2022-2024 was made in Statistica software. Selected neural network models were used to forecast the number of road accidents. The results show that we can still expect a reduction in the number of road accidents on Polish roads, but the prevailing pandemic disturbs the results obtained. The choice of the number of random samples (learning, testing and validation) affects the obtained results.

A Modified Weighted Connectivity Ratio for Measuring a Low-cost Carrier's Connectivity at its Major Airports

Pino Rachmandika — 2023-09-13

This study aims to analyze how good and efficient the low-cost carriers' connectivity is at their major airports by studying one of the largest low-cost carriers in the world, AirAsia Group. Weighted Connectivity Ratio is used in the calculation, applied with slight modifications to suit the operations of low-cost carriers at their airports. The results reveal that some airlines have very good connectivity, even when it is compared to the connectivity of several big full-service carriers in Europe. This research brings a novelty in the form of an analysis of connectivity of low-cost carriers, considering that most of the previous research only focused on the connectivity of full-service carriers that implement a hub-and-spoke strategy. This is important because low-cost carriers are currently present with a very rapid growth as an alternative flight option that is more affordable for passengers in addition to full-service carriers that have previously dominated the aviation market.