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
2024 (Vol 36), Issue 6
Unbalanced urban development causes complex and diverse urban traffic conditions, which complicates microcirculation traffic network planning. To address this, a method based on fast search random tree algorithm is proposed. An urban microcirculation traffic network is constructed using directed graphs, and road network interference intensity and capacity are calculated. The interpolation collision detection method is used to determine the shortest path while considering constraint conditions. By incorporating target gravity into the RRT algorithm, a growth guidance function is obtained, optimising the planned path and completing urban microcirculation traffic network planning. Experimental results demonstrate accurate shortest path calculation with up to 11% delay reduction compared to existing methods. Energy consumption during planning is lower than 10 kJ, ensuring fair resource distribution within the urban microcirculation transportation network. These advantages highlight the practicality and effectiveness of this research method.
2024 (Vol 36), Issue 6
With the escalating global climate change, the cost of carbon emissions has become a crucial metric for evaluating the sustainability of logistics systems. This study addresses the optimisation of cold chain logistics routes in a time-varying network environment, considering the carbon emission cost factor, and proposes an enhanced particle swarm optimisation algorithm to solve this optimisation problem. Firstly, we establish a cold chain logistics optimisation model that incorporates the time-varying network, integrating logistics route planning with carbon emission costs. Subsequently, we design an improved particle swarm optimisation algorithm suitable for time-varying networks. This algorithm optimises vehicle routes and adjusts delivery times to minimise the total cost incurred during distribution. Finally, through simulation experiments, we analyse the impact of vehicle speeds and carbon trading mechanisms on optimisation outcomes. The results demonstrate that this method effectively optimises cold chain logistics routes, considering real network conditions and environmental factors, thereby reducing delivery costs and carbon emissions.
2024 (Vol 36), Issue 6
This paper attempts to determine the role of street lighting in the spatial clustering of night-time crashes involving pedestrians in the Republic of Croatia. Five-year (2018–2022) night-time pedestrian crash data were used in conditions with and without street lighting. First, distance-based statistical methods were used to assess the spatial clustering and deviations from complete spatial randomness (CRS) of the crash patterns. Second, the global Moran’s I analysis was conducted to investigate a degree of spatial autocorrelation of the annual crash counts aggregated in 21 counties of Croatia. Finally, the local indicators of spatial association (LISA) were used to identify the locations of the crash count hotspots. The results of the ANND analysis confirm a significant clustering of crashes for both street lighting conditions. However, different global Moran’s I values for both conditions were obtained with a high and statistically significant positive value for the crash counts without street lighting. Local Moran's I analysis reveals that the High-High (H-H) county clusters are located in coastal regions of Croatia, while the Low-Low (L-L) county clusters appear in the East continental part, next to Slavonia. The results suggest that inadequate lighting conditions have an impact on the clustering of pedestrian crashes at night.
2024 (Vol 36), Issue 6
Vessel trajectory prediction is important in maritime traffic safety and emergency management. Vessel trajectory prediction using vessel automatic identification system (AIS) data has attracted wide attention. Deep learning techniques have been widely applied to vessel trajectory prediction tasks due to their advantages in fine-grained feature learning and time series modelling. However, most deep learning-based methods use a unified approach for modelling AIS data, ignoring the diversity of AIS data and the impact of noise on prediction performance due to environmental factors. To address this issue, this study introduces a method consisting of temporal convolutional network (TCN), convolutional neural network (CNN) and convolutional long short-term memory (ConvLSTM) to predict vessel trajectories, called TCC. The model employs TCN to capture the complex correlation of the time series, utilises CNN to capture the fine-grained covariate features and then captures the dynamics and complexity of the trajectory sequences through ConvLSTM to predict vessel trajectories. Experiments are conducted on real public datasets, and the results show that the TCC model proposed in this paper outperforms the existing baseline algorithms with high accuracy and robustness in vessel trajectory prediction.
2024 (Vol 36), Issue 6
As a critical component of urban transportation, metro systems demand rigorous passenger flow safety management. This study proposes a comprehensive decision-making analysis method for metro station passenger flow safety management by integrating the entropy weight and TOPSIS methods. It aims to develop an evaluation model that accurately assesses and ranks the safety management practices of metro stations. To achieve this, 17 indicators related to station scale, safety management equipment, safety or security measures, investment in safety management and the effects of passenger flow management are selected to form an evaluation indicator system. The entropy weight method is employed to allocate weights to these indicators, reflecting their interrelatedness and importance. Subsequently, the TOPSIS method is used to establish a decision model that calculates the closeness of each station’s management practice to an optimal plan, allowing for the ranking of different stations’ safety management practices. The algorithms are developed and optimised using MATLAB, enabling efficient calculation and analysis. A case study involving real metro stations is conducted to validate the feasibility and effectiveness of the proposed evaluation method. The results demonstrate that this model provides an accurate assessment of metro station passenger safety management and offers decision-makers clear directions for improvement.
2024 (Vol 36), Issue 6
Special Issue Is Out
We invite you to contribute to our special issue
Innovation and New Technologies in Transport and Logistics
Guest Editor: Eleonora Papadimitriou, PhD
Editors: Marko Matulin, PhD, Dario Babić, PhD, Marko Ševrović, PhD
Transport and logistics, essential components of today's interconnected and globalized world, serve as the backbone of economies worldwide. They facilitate the seamless movement of goods and people, driving trade, commerce, and societal development. However, amidst their significance, contemporary transport and logistics sectors face multifaceted challenges that demand innovative solutions.
Ensuring accessibility of transportation services in both urban and rural areas remains a pressing concern. Additionally, environmental sustainability and the imperative for eco-friendly transportation and logistics solutions are paramount. Crafting responsive transport services that adapt to evolving demands and integrating diverse transport modes within the same infrastructure poses significant challenges. The precision and reliability of transportation providers are also critical factors in meeting modern logistics demands.
Stay Focused
Read about the latest news in the T&T landscape

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.
Read more
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.
Read more
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.
Read more
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
Read more
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

Meixian Jiang, Guoxing Wu, Jianpeng Zheng, Guanghua Wu
This paper constructs a berth-quay crane capacity planning model with the lowest average daily cost in the container terminal, and analyzes the influence of the number of berths and quay cranes on the terminal operation. The object of berth-quay crane capacity planning is to optimize the number of berths and quay cranes to maximize the benefits of the container terminal. A steady state probability transfer model based on Markov chain for container terminal is constructed by the historical time series of the queuing process. The current minimum time operation principle (MTOP) strategy is proposed to correct the state transition probability of the Markov chain due to the characteristics of the quay crane movement to change the service capacity of a single berth. The solution error is reduced from 7.03% to 0.65% compared to the queuing theory without considering the quay crane movement, which provides a basis for the accurate solution of the berth-quay crane capacity planning model. The proposed berth-quay crane capacity planning model is validated by two container terminal examples, and the results show that the model can greatly guide the container terminal berth-quay crane planning.
2021 (Vol 33), Issue 2
Marko Orošnjak, Mitar Jocanović, Branka Gvozdenac-Urošević, Dragoljub Šević, Ljubica Duđak, Velibor Karanović
The research on Bus Fleet Management (BFM) has undergone significant changes. It is unclear whether these changes are accepted as technological change or as a paradigm shift. Perhaps unintentionally, BFM is still perceived as routing and scheduling by some, and by others as maintenance and replacement strategy. Therefore, the authors conducted a Systematic Literature Review (SLR) to overview the existing concepts and school of thoughts about how stakeholders perceive the BFM. The SLR post-study exposed that BFM should be acknowledged as a multi-realm system rather than a uniform dimension of fulfilling timely service. Nonetheless, the work encapsulates BFM evolution which shows the need for the multi-realm research abstracted as "Bus Fleet Mobility Management" and "Bus Fleet Asset Management". The difficulties of transport agencies and their ability to switch from conventional to Zero-Emission Buses (ZEBs) illustrates why we propose such an agenda, by which the research is validated through needs both in academia and in practice.
2020 (Vol 32), Issue 6
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
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
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
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