TY - JOUR AU - Ötvös, Viktória AU - Török, Ádám TI - Measurement of Accident Risk and a Case Study from Hungary JF - PERIODICA POLYTECHNICA TRANSPORTATION ENGINEERING J2 - PERIOD POLYTECH TRANSP ENG VL - 52 PY - 2024 IS - 2 SP - 159 EP - 165 PG - 7 SN - 0303-7800 DO - 10.3311/PPtr.22731 UR - https://m2.mtmt.hu/api/publication/34763427 ID - 34763427 N1 - Export Date: 2 April 2024 CODEN: PPTED Correspondence Address: Ötvös, V.; Department of Transport Technology and Economics, Műegyetem rkp. 3., Hungary; email: otvos.viktoria@kti.hu AB - For the cost-benefit analysis of road safety measures, it is essential to estimate the national value of statistical life. By calculating the updated values, it is possible to assess the aggregate national value of statistical life for road traffic crashes, thereby also characterizing the road safety situation in the country. It is important that the values set and the methods used are compatible with the practices of the European Member States. It must be stressed that updating the values is of major importance both for the costbenefit analysis of the various road safety measures and for raising public and decision-makers' awareness of the huge losses. The full identification and use of loss figures is an important element of road safety. In this article we present possible methods for estimating the value of statistical life. © 2024 Budapest University of Technology and Economics. All rights reserved. LA - English DB - MTMT ER - TY - THES AU - Lévai, Zsolt TI - A vasúti infrastruktúra komplex védelmi célú felkészítésének innovatív módszerei PY - 2024 SP - 286 UR - https://m2.mtmt.hu/api/publication/34741141 ID - 34741141 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Bauer, Béla AU - Déri, András TI - Szabálykövetés és közlekedésbiztonsági kultúra elméletek és empíria tükrében JF - KORUNK (KOLOZSVÁR) J2 - KORUNK (KOLOZSVÁR) VL - III. folyam PY - 2024 IS - 1. szám SP - 68 EP - 81 PG - 14 SN - 1222-8338 UR - https://m2.mtmt.hu/api/publication/34555946 ID - 34555946 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Farkas, Bálint AU - Köller, László AU - Kövesdi, István TI - Issues for the Introduction of Hydrogen-Powered Rail Vehicles on Hungarian Regional Railway Lines Through an Example from Germany JF - TRANSPORTATION RESEARCH PROCEDIA J2 - TRANSP RES PROCEDIA VL - 77 PY - 2024 SP - 35 EP - 42 PG - 8 SN - 2352-1465 DO - 10.1016/j.trpro.2024.01.005 UR - https://m2.mtmt.hu/api/publication/34523517 ID - 34523517 LA - English DB - MTMT ER - TY - JOUR AU - ABDULLAH, PIRES AU - Sipos, Tibor TI - Exploring the Factors Influencing Traffic Accidents: An Analysis of Black Spots and Decision Tree for Injury Severity JF - PERIODICA POLYTECHNICA TRANSPORTATION ENGINEERING J2 - PERIOD POLYTECH TRANSP ENG VL - 52 PY - 2024 IS - 1 SP - 33 EP - 39 PG - 7 SN - 0303-7800 DO - 10.3311/PPtr.22392 UR - https://m2.mtmt.hu/api/publication/34498267 ID - 34498267 N1 - Department of Transport Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3, Budapest, H-1111, Hungary Department of Spatial Planning, College of Spatial Planning, University of Duhok, Zakho Street 38, Kurdistan Region, Duhok, 1006 AJ, Iraq Directorate for Strategy, Research & Development and Innovation, KTI Institute for Transport Sciences Non-profit Ltd., Than Károly u. 3-5, Budapest, 1119, Hungary Export Date: 12 January 2024 CODEN: PPTED Correspondence Address: Abdullah, P.; Department of Transport Technology and Economics, Műegyetem rkp. 3, Hungary; email: pires.abdullah@edu.bme.hu Funding text 1: The project presented in this article is supported by the Faculty of Transportation Engineering and Vehicle Engineering of the Budapest University of Technology and Economics, and the Department of Transport Technology and Economics supported this research. AB - This research aimed to examine the spatial distribution of road traffic accidents in Budapest, Hungary. The primary objective was to identify the factors associated with traffic accidents on the city's transportation network and to determine the locations of the most frequent accidents during peak and off-peak hours. A quantitative methodology was employed in this study, utilizing a dataset of recent accidents that occurred between 2019 and 2021, classified into peak and off-peak incidents. The data was analyzed using Python software and Quantum Geographic Information System (QGIS) tools for big data analytics. These programs enabled the creation of spatial maps of the study area and the identification of accident spots based on latitude and longitude information. A decision tree classification approach was used in the machine-learning method implemented with Python software. Additionally, the dataset file was uploaded to QGIS, which applied the heatmap (Kernel Density Estimation) algorithm to identify accident hotspots. The study findings revealed that the city center was the most common location for accidents overall, with peak and off-peak times, lanes, and days of the week investigated as potential contributing factors. The target variable was the number of accidents involving serious and minor injuries, which were found to be significantly associated with the identified accidents in this study. © 2024 Budapest University of Technology and Economics. All rights reserved. LA - English DB - MTMT ER - TY - JOUR AU - Bayagoob, Ali Ahmed Saleh AU - Gáspár, László TI - Optimizing asphalt foaming using neural network JF - POLLACK PERIODICA: AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES J2 - POLLACK PERIODICA VL - 19 PY - 2024 IS - 1 SP - 130 EP - 136 PG - 7 SN - 1788-1994 DO - 10.1556/606.2023.00896 UR - https://m2.mtmt.hu/api/publication/34288617 ID - 34288617 AB - This study uses a three-layer backpropagation neural network combined with particle swarm optimization to control the foamed bitumen in cold recycling technology. The foaming process of bitumen is non-linear and depends on dynamic temperature. By developing a neural network model, this study effectively captures the complex relationships between temperature, water content, air pressure, and the expansion ratio and half-life of foamed bitumen. The integration of particle swarm optimization enhances the accuracy and convergence of the neural network model by optimizing the initial weights. This optimization process improves the model's ability to predict and control the quality of foamed bitumen accurately. It serves as a valuable tool for the rapid development of high-quality cold asphalt design. LA - English DB - MTMT ER - TY - JOUR AU - Bauer, Béla AU - Déri, András AU - Kovács, Tamás AU - Miskolczi, Márk TI - Korszakváltás a közlekedésben? A pandémiás helyzet hatásai JF - KÖZLEKEDÉS ÉS MOBILITÁS J2 - KÖZL MOBIL VL - 2 PY - 2023 IS - 2 SP - 70 EP - 78 PG - 9 SN - 2939-7057 DO - 10.55348/KM.44 UR - https://m2.mtmt.hu/api/publication/34556478 ID - 34556478 AB - Tanulmányunk a pandémiás helyzet közlekedésre és – részben – a turizmusra gyakorolt hatásait a Közlekedéstudományi Intézet Stratégiai és Koordinációs Központjának 2020-as kvalitatív és kvantitatív, és 2021-es kvantitatív kutatásának eredményei alapján elemzi, elsősorban problémafelvető, leíró jelleggel. Bemutatjuk, hogy 2020-ban az óvatosság határozta meg leginkább a közlekedési módok választásával kapcsolatos attitűdöket, és azt, hogy a fiatalok kisebb arányban tettek le az autós közlekedésről, mint az idősek, míg a kerékpárhasználók aránya csak az idősek körében nem nőtt jelentősebben LA - Hungarian DB - MTMT ER - TY - JOUR AU - ABDULLAH, PIRES AU - Sipos, Tibor TI - Traffic Accidents Analysis Using QGIS and Binary Decision Tree JF - TRANSPORTATION RESEARCH PROCEDIA J2 - TRANSP RES PROCEDIA VL - 72 PY - 2023 SP - 1677 EP - 1684 PG - 8 SN - 2352-1465 DO - 10.1016/j.trpro.2023.11.640 UR - https://m2.mtmt.hu/api/publication/34554389 ID - 34554389 N1 - Budapest University of Technology and Economics, Department of Transport Technology and Economics, Budapest, 1111, Hungary Duhok University, College of Spatial Planning, Department of Spatial Planning, Kurdistan Region, Iraq KTI - Institute for Transport Sciences, Directorate for Strategic Research and Development, Hungary Conference code: 196032 Export Date: 2 February 2024 Funding text 1: BME - Faculty of Transportation Engineering and Vehicle Engineering and UoD - College of Spatial Planning supported the research. AB - Traffic accident data includes many factors in order to be investigated. The main aim of this study is to analyze traffic accidents in terms of the spatial location in which they have occurred. Moreover, to identify the main socioeconomic factors that lead to frequent accidents by drivers. The questionnaire included items related to the location of the accident and the number of accidents a driver has had in a 10-year period. The study took place in the city of Duhok in the Kurdistan Region of Iraq. The study's findings showed that the city's center was the main area of accidents in general, while severe crashes had different "black spots" across the city's road network. Furthermore, the Decision Tree's classification of the driver's multiple accidents placed the level of education at the top, followed by gender and age, respectively. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) LA - English DB - MTMT ER - TY - JOUR AU - Tordai, Dániel AU - Munkácsy, András AU - Andrejszki, Tamás AU - Hauger, G. TI - The real value of cycling JF - TRANSPORTATION RESEARCH PROCEDIA J2 - TRANSP RES PROCEDIA VL - 72 PY - 2023 SP - 2896 EP - 2903 PG - 8 SN - 2352-1465 DO - 10.1016/j.trpro.2023.11.835 UR - https://m2.mtmt.hu/api/publication/34554386 ID - 34554386 N1 - KTI Institute for Transport Sciences, Department for Transport Management, Than Károly street. 3-5, Budapest, 1119, Hungary Budapest University of Technology and Economics, Department of Transport Technology and Economics, Stoczek street 2, Budapest, 1111, Hungary Technischen Universität Wien, Research Unit Transportation System Planning, Erzherzog-Johann-Platz, Wien, 11040, Austria Conference code: 196032 Export Date: 2 February 2024 Correspondence Address: Tordai, D.; KTI Institute for Transport Sciences, Than Károly street. 3-5, Hungary; email: tordai.daniel@kti.hu Funding details: European Commission, EC Funding details: European Regional Development Fund, ERDF Funding text 1: In this guideline, two conditions must be fulfilled for a project to be financed by the EU: the financial net present value has to be smaller than 0, so the project must require financial support, and the economic net present value has Funding text 2: This research was conducted as part of the Danube Cycle Plans project (2020-2022), co-founded by the European Union (ERDF, IPA) Interreg Danube Transnational Programme. AB - In recent decades, there has been significant scientific effort to explore and measure the different benefits of cycling. Thanks to the research done in this field, nowadays we have extensive knowledge about the contributions of cycling to the reduction of transportation related air pollution, health related benefits and other socio-economic advantages. Despite the scientific evidence, methodologies for cost-benefit analysis (CBA) have not been updated to take into account all benefits of cycling when making decisions on the realization of bicycle infrastructure projects. By omitting these specific benefits, policy and decision-makers might underestimate the overall societal benefit of these projects. This contribution introduces an update of the CBA methodology for cycling infrastructure projects by looking at the scientific evidence on the different benefits of cycling. © 2023 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) LA - English DB - MTMT ER - TY - JOUR AU - Kún, Gergely Ottó AU - Wührl, Tibor TI - Közlekedés és a mobilkommunikáció kapcsolata JF - KÖZLEKEDÉS ÉS MOBILITÁS J2 - KÖZL MOBIL VL - 2 PY - 2023 IS - 2 SP - 98 EP - 109 PG - 12 SN - 2939-7057 DO - 10.55348/KM.43 UR - https://m2.mtmt.hu/api/publication/34528636 ID - 34528636 LA - Hungarian DB - MTMT ER -