Promet - Traffic & Transportation Journal
Pioneering the future of mobility
Welcome to the world of Promet - Traffic&Transportation, where we delve into shaping the future of traffic and transportation through innovation and research. Our platform is dedicated to uncovering the latest insights, trends, and technological advancements impacting transportation systems worldwide.
Through an interdisciplinary approach, we explore how intelligent technologies, sustainable solutions, and transportation planning collectively shape the path towards safer, more efficient, and sustainable traffic and transportation systems.
Welcome to Promet - Traffic&Transportation, where we explore shaping the future of traffic and transportation through innovation and research. Discover the latest insights and technological advancements influencing transportation systems worldwide, aiming for safer, more efficient, and sustainable solutions.
Open Access
We truly believe in knowledge without boundaries!
Journal's metrics
WoS: IF 0.8
Scopus: Citescore 2023 1.9
SJR: Q3 (Engineering)
Latest Issue
Browse through the selection of our newest research
Prachiti SHINDE, Marin MARINOV
The rapid expansion of the metro network, driven by urbanisation and a heightened focus on environmental sustainability, underscores the need for efficient and sustainable public transportation systems. This study utilises the West Midlands Metro system as a case study to investigate operational efficiency and utilisation challenges that are common across metro networks globally. Employing advanced simulation modelling with SIMUL8, this research evaluates the existing timetables and utilisation rates of the West Midlands Metro to uncover inefficiencies and untapped potential. Various scenarios, including increased service frequencies and disruptions at high-traffic stations, were simulated to provide actionable insights for optimising metro operations. Findings revealed that increasing service frequency from every 10 minutes to every 5 minutes enhanced utilisation levels and boosted the total number of completed services. Meanwhile, disruptions at major stops resulted in a reduction in utilisation in a negligible range. These results demonstrate that improved service frequency significantly bolsters operational efficiency and showcases resilience to disruptions with minimal impact on overall performance. As to future research, the study suggests that implementing adaptive scheduling through AI-driven maintenance and infrastructure improvements can further elevate the efficiency and passenger experience of metro operations.
2025 (Vol 37), Issue 2
Patricija BAJEC, Eva PODOVŠOVNIK
Crowdshipping has garnered increasing interest due to its potential benefits for various stakeholders. However, despite challenges in attracting crowdshippers, limited research explores their preferences, including socio-demographic factors and the practical challenges providers face when testing or implementing crowdshipping. This study aims to identify key factors influencing willingness-to-work (WTW) among potential crowdshippers, both in general and within business-to-business (B2B) and business-to-customer (B2C) contexts. Based on the literature review, this paper identifies 19 barriers influencing WTW and develops 22 corresponding enablers to address these barriers. Using a survey of 432 participants from Slovenia, the overall significance of these factors without differentiating business models was first assessed. Then, chi-squared automatic interaction detection analysis was applied to predict WTW in B2B and B2C contexts, identifying variations across these models. The disclosure of a mobile number emerged as the most influential predictor in both settings. Other notable differences in enablers and barriers were observed depending on the business model. These findings emphasise the need to consider business models in future preference analyses and provide a foundation for targeted recruitment strategies for crowdshippers.
2025 (Vol 37), Issue 2
Zhenbao WANG, Yanfang HE, Xueqiao ZHAO, Yuqi LIANG, Shihao LI
Previous studies have primarily focused on the effect of the built environment on ridership during weekdays and weekends. This paper aims to investigate the spatial heterogeneity of the effect of built environment factors on ridership at metro stations during National Day holidays. Beijing is divided into three zones from inner to outer areas. Taking metro station boarding and alighting ridership during National Dayholidays as the dependent variable, 13 built environment factors were selected as independent variables according to the “7D” dimension of the built environment. The recommended pedestrian catchments (PCA) combinations for the three zones in Beijing are 400 m_500 m_400 m by using the Multi-Scale Geographically Weighted Regression (MGWR) model. We investigated the effect of built environment factors on metro ridership and spatial heterogeneity. The influencing factors that have significant effects on both boarding and alighting ridership are building density, number of commercial facilities, bus lines density, number of entrance and exit, number of office facilities, mixed utilization of land and road density. The MGWR model results are helpful to propose targeted strategies for revitalising the built environment around metro stations.
2025 (Vol 37), Issue 2
Xiaoyu CAI, Zimu LI, Wufeng QIAO, Xiling CHENG, Bo PENG, Dong ZHANG
2025 (Vol 37), Issue 2
Meiling HE, Guangrong MENG, Xiaohui WU, Xun HAN, Jiangyang FAN
With the acceleration of urbanisation and the rapid increase in road traffic volume, the scientific prediction of traffic accidents has become crucial for improving road safety and enhancing traffic efficiency. However, traffic accident prediction is a complex and multifaceted problem that requires the comprehensive consideration of multiple factors, including people, vehicles, roads and the environment. This paper provides a detailed analysis of traffic accident prediction based on multi-source data. By thoroughly considering data sources, data processing and prediction methods, this paper introduces the various aspects of traffic accident prediction from different perspectives. It helps readers understand the characteristics of different data and methods, the process of accident prediction and the key technologies involved. At the end of the paper, the main challenges and future directions in road crash prediction research are summarised. For example, the lack of efficient data sharing between different departments and fields poses significant challenges to the integration of multi-source data. In the future, combining deep learning models with time-sensitive data, such as social media and vehicle network data, could effectively improve the accuracy of real-time accident prediction.
2025 (Vol 37), Issue 2
Yanhong YIN, Zihao YE, Qiuyan HAN, Li'ao HUANG
This study focuses on understanding the effects of shared mobility on travel behaviours and transport energy in the university campus. Using survey data collected from college students in Ningbo, China, a substitution model was developed to identify changes in travel modes with the introduction of shared mobility on college campuses and to quantify its impact on net energy saving. Considering the average time travelled and the life cycle energy unit of the trip, the before-and-after analysis was conducted to determine the travel behaviours and related transport energy of college students in 2016 and 2019. Compared with the data of 2016 when no shared mobility was introduced, 2019 data revealed three changes in travel behaviours. First, although the total number of trips per person decreased slightly, the trip distance increased in 2019. Second, the energy for trips by each student increased by 25% from 19,809 KJ in 2016 to 24,897 KJ in 2019. Third, the overall energy efficiency of the trips decreased. In conclusion, the effect of shared mobility introduced in the university campus on reducing the transport energy of college students has not been satisfactory.
2025 (Vol 37), Issue 2
Current Special Issue Call
Rethinking the European Railway System
Guest Editors: Armando Carrillo Zanuy, PhD; Juan de Dios Sanz Bobi, PhD
Editor: Borna Abramović, PhD
Deadline: September 10, 2025
The European railway system has played a pivotal role in shaping the continent’s economic integration, cultural exchange, and sustainable mobility solutions. However, this system now faces unprecedented challenges, including climate change imperatives, digital transformation, and the need for revitalised cross-border connectivity.
Addressing funding mechanisms and harmonising regulatory and operational standards are equally vital to achieving seamless cross-border mobility. The current lack of coordination among national rail systems creates significant barriers to forming an interconnected seamless European rail network, underscoring the urgency of developing solutions for improved interoperability, technical standardisation, increased safety, passenger experiences, active participation in supply chain management, unified organisation, and aligned policy frameworks.
This call for papers seeks innovative approaches to rethinking European railways' governance, technology, and infrastructure in the context of 21st-century demands. Original research papers and reviews are welcome.
Stay Focused
Read about the latest news in the T&T landscape

16th International Scientific Conference TRANSBALTICA 2025: Transportation Science and Technology
Vilnius Gediminas Technical University – VILNIUS TECH (Vilnius, Lithuania) has the pleasure of inviting You to join the 16th International Scientific Conference TRANSBALTICA 2025: Transportation Science and Technology.
The Conference will be held on September 18–19, 2025. The Conference aims to overview relevant issues of the transport system, present research results and exchange scientific expertise.
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10th International Ergonomics Conference - ERGONOMICS 2024
It is with great pleasure that we invite you to participate in the 10th International Ergonomics Conference - ERGONOMICS 2024, which will be held from December 5th to 6th, 2024 in Zagreb, Hotel International.
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Workshop - improving the publication process and developing the support system for the journal
Editorial Board meeting of the Promet – Traffic&Transportation journal took place on May 16th, 2023 as a workshop aimed at improving the publication process and developing the support system for the journal under the leadership of the Editor-in-Chief, Assoc. Prof. Ivona Bajor, PhD.
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Cooperation between Faculty of Transportation Engineering and Vehicle Engineering, Budapest and journal Promet – Traffic & Transportation
On March 9, 2023, Editor-in-Chief Ivona Bajor and Assistant Editor-in-Chief, Luka Novačko met with long-term partners of the scientific journal Promet – Traffic & Transportation, representatives of the Budapest University of Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Vice-Dean for science and international cooperation Dr. Adam Torok and Dr. Tibor Šipoš.
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Faculty of Logistics signed a co-publishing agreement
On December 21, 2022, the Faculty of Transport and Traffic Sciences, as the publisher of the scientific journal Promet-Traffic&Transportation and the University of Maribor, Faculty of Logistics signed a co-publishing agreement
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Suradnja vezana uz izdavanje međunarodnog časopisa Promet – Traffic&Transportation
Prošlog tjedna održao se sastanak u Celju kojem su prisustvovali glavna urednica časopisa Promet – Traffic and Transportation, doc. dr. sc. Ivona Bajor i zamjenik glavne urednice izv. prof. dr. sc. Luka Novačko sa predstavnicima Univerze v Mariboru, Fakulteta za logistiko, dekanicom Majom Fošner i prodekanom za financije Andrejem Lisecom.
Read moreEditor's Choice Papers
Explore the selection of scientific papers handpicked by the editor

Pavle Bugarčić, Nenad Jevtić, Marija Malnar
Vehicular and flying ad hoc networks (VANETs and FANETs) are becoming increasingly important with the development of smart cities and intelligent transportation systems (ITSs). The high mobility of nodes in these networks leads to frequent link breaks, which complicates the discovery of optimal route from source to destination and degrades network performance. One way to overcome this problem is to use machine learning (ML) in the routing process, and the most promising among different ML types is reinforcement learning (RL). Although there are several surveys on RL-based routing protocols for VANETs and FANETs, an important issue of integrating RL with well-established modern technologies, such as software-defined networking (SDN) or blockchain, has not been adequately addressed, especially when used in complex ITSs. In this paper, we focus on performing a comprehensive categorisation of RL-based routing protocols for both network types, having in mind their simultaneous use and the inclusion with other technologies. A detailed comparative analysis of protocols is carried out based on different factors that influence the reward function in RL and the consequences they have on network performance. Also, the key advantages and limitations of RL-based routing are discussed in detail.
2022 (Vol 34), Issue 6
Junzhuo Li, Wenyong Li, Guan Lian
Data-driven forecasting methods have the problems of complex calculations, poor portability and need a large amount of training data, which limits the application of data-driven methods in small cities. This paper proposes a traffic flow forecasting method using a Nonlinear AutoRegressive model with eXogenous variables (NARX model), which uses a dynamic neural network Focused Time-Delay Neural Network (FTDNN) with a Tapped Delay Line (TDL) structure as a nonlinear function. The TDL structure enables the FTDNN to have short-term memory capabilities. At the same time, before the data is input into the FTDNN, the use of trend decomposition or differential calculation on the traffic data sequence can make the NARX model maintain long-term predictive capabilities. Compared with common nonlinear models, the FTDNN has structural advantages. It uses a simple TDL structure without the memory mechanism and the gated structure, which can reduce the parameters of the model and reduce the scale of data. Through the four-day data of Guilin City, the traffic volume forecast for five minutes is verified, and the performance of the NARX model is better than that of the SARIMA model and the Holt-Winters model.
2022 (Vol 34), Issue 6
Ying Chen, Zhigang Du, Zehao Jiang, Congjian Liu, Xuefeng Chen
For urban extra-long underwater tunnels, the obstacle space formed by the tunnel walls on both sides has an impact on the driver's driving. The aim of this study is to investigate the shy away characteristics of drivers in urban extra-long underwater tunnels. Using trajectory offset and speed data obtained from real vehicle tests, the driving behaviour at different lanes of an urban extra-long underwater tunnel was investigated, and a theory of shy away effects and indicators of sidewall shy away deviation for quantitative analysis were proposed. The results show that the left-hand lane has the largest offset and driving speed from the sidewall compared to the other two lanes. In the centre lane there is a large fluctuation in the amount of deflection per 50 seconds of driving, increasing the risk of two-lane collisions. When the lateral clearances are increased from 0.5 m to 2.19 m on the left and 1.29 m on the right, the safety needs of drivers can be better met. The results of this study have implications for improving traffic safety in urban extra-long underwater tunnels and for the improvement of tunnel traffic safety facilities.
2023 (Vol 35), Issue 4
Ahmed Jaber, Bálint Csonka
The purpose of this research is to investigate the effect of land use, built environment and public transportation facilities’ locations on destinations of bike-sharing trips in an urban setting. Several methods have been applied to determine the relationship between predicting variables and trip destinations, such as ordinary least squares regression, spatial regression and geographically weighted regression. Additionally, a comparison between the proposed models, count models and random forest has been conducted. The data were collected in Budapest, Hungary. It has been found that touristic points of interest, and healthcare and educational points have a positive impact on bike-sharing destinations. Public transportation stops for buses, trains and trams attract bike-sharing users, which has a potential for the bike-and-ride system. Land use has different effects on bike-sharing trip destinations; mostly as a circular shape variation within the urban structure of the city, such as residential, industrial, commercial and educational zones. Other variables, such as road length and water areas, form as constraints to bike-sharing trip destinations. Geographically weighted and spatial regression performs better than count models and random forest. This study helps decision-makers in predicting the origin-destination matrix of bike-sharing trips based on the transportation network and land use.
2023 (Vol 35), Issue 1
Emma Strömblad, Lena Winslott Hiselius, Lena Smidfelt Rosqvist, Helena Svensson
In search for measures to reduce greenhouse gas emissions from transport, insights into the characteristics of all sorts of trips and specifically trips by car are needed. This paper focuses on everyday leisure trips for social and recreational purposes. Travel behaviour for these purposes is analysed considering individual and household factors as well as properties of the trip, based on Swedish national travel survey data. The analysis reveals that everyday leisure trips are often of joint character and that the average distance travelled per person and day increases with, for example, income, cohabitation, children in the household and residence in rural areas. The result also shows that the studied characteristics vary between studied trip purposes, influencing the sustainability potential of a reduction in car use and suggested measures. For instance, the largest share of passenger mileage comes from social trips, whereas trips for exercise and outdoor life have the largest share of car trips below 5 km. Several characteristics indicate difficulties in transferring trips by car to, for example, bicycle or public transport due to convenience, economy, start times, company etc. The study indicates that there is a need to take a broader view of the effective potential.
2022 (Vol 34), Issue 4
Laura Eboli, Maria Grazia Bellizzi, Gabriella Mazzulla
Evaluating air transport service quality is fundamen-tal to ensure acceptable quality standards for users and improve the services offered to passengers and tourists. In the transportation literature there is a wide range of studies about the evaluation of public transport service quality based on passengers’ perceptions; however, more recently, the evaluation of air transport service quality is becoming a relevant issue. Evaluating service quality in air transport sector represents a more stimulating chal-lenge, given the complexity of air transport system in re-gards to the other systems; in fact, air transport service is characterised by a great variety of service aspects relat-ing to services offered by the airlines and provided by the companies managing airports. The complexity of such a service requires a deep investigation on the methods adopted for collecting and analysing the data regarding passengers’ perceptions. We propose this paper just for treating these interesting aspects and to provide an ex-haustive literature review of the studies analysing ser-vice quality from the passengers’ point of view, where the opinions of the passengers are collected by the Customer Satisfaction Surveys (CSS). We decided to select papers published within the last decade (2010–2020) in journals indexed in important databases such as Scopus and WoS.
2022 (Vol 34), Issue 2