The transportation of dangerous goods (TDG) is a critical component of economic systems, especially in regions such as the Western Balkans (WB), where infrastructure and regulatory frameworks face significant challenges. This study assesses the current state of transportation of dangerous goods in Albania, Montenegro, Bosnia and Herzegovina, and Kosovo*, focusing on the alignment of national regulations with international standards such as the ADR agreement. Using a structured questionnaire distributed to 847 stakeholders, key barriers are identified, including inadequate infrastructure, insufficient training, limited oversight and low public awareness. Statistical analyses, including paired t-tests, reveal significant differences in perceptions across the countries surveyed, indicating inequalities in implementation and enforcement. Despite these challenges, there are opportunities to close gaps through targeted investments in infrastructure, increased training programs, stricter compliance and regional cooperation. The findings underscore the need for comprehensive data collection systems and advanced risk assessment tools to improve safety and efficiency. This study contributes to a deeper understanding of TDG issues in the WB countries and provides actionable recommendations for policy makers and practitioners to promote safer and more sustainable practices. The region can improve its TDG framework by addressing these challenges and ensuring economic growth and public safety while minimizing environmental risks.

This research aims to enhance airport infrastructure development in Croatia by focusing on the establishment of a training and school airport near Šibenik, integrating modern design principles and addressing functional needs to support aviation education and training while promoting regional economic growth. This chapter focuses on the theoretical characteristics of project management throughout the project cycle, emphasizing their relevance to the sustainable development of airport infrastructure within the context of transport economics. The case study of an airport near Sibenik serves as a critical foundation for proposing a universal model that integrates airport infrastructure, project management, and metrological steps for integration. Key elements such as legal frameworks governing air transport development are evaluated to ensure the model's applicability and effectiveness within the Croatian air transport system, demonstrating its potential as a viable approach for enhancing sustainable airport operations.

Sustainable development is a crucial concept that emphasizes the need for growth that meets present needs without compromising the ability of future generations to meet their own, integrating societal, economic, and political dimensions. The importance of this approach is underscored by the need for environmental valuation and assessment, particularly in sectors like air traffic, where infrastructure development can significantly impact sustainability. Existing literature in transport economics, especially concerning optimal airport infrastructure development, is limited, highlighting the necessity for comprehensive research in this area. This doctoral dissertation aims to fill this gap by exploring sustainable practices and innovative models that can guide the development of air traffic infrastructure within the framework of sustainable development principles.

Traffic engineering is experiencing a significant transformation with the integration of Artificial Intelligence. AI-driven systems provide real-time traffic and transport monitoring, predictive analytics, and autonomous control, improving efficiency, safety, and sustainability. However, human intelligence remains essential for supervision, regulation, and ethical considerations. The coexistence and integration of AI and human intelligence in traffic engineering create a hybrid approach that maximizes strengths while minimizing weaknesses. A balanced coexistence between AI and human expertise should lead to smarter, safer, more sustainable, and more adaptable traffic systems. This paper explores the coexistence of AI in traffic engineering and the role of human engineers guided by artificial intelligence.

Logistic, transport and mobility is an important human need. To meet these mobility needs, our driving and movements must be safe, i.e. without consequences and injuries. Traffic safety can result in significant human and economic losses. As road traffic fatalities remain a global societal problem, finding effective solutions has become a top priority. Leveraging artificial intelligence (AI) presents a promising avenue for improving traffic safety through innovative approaches and applications. Improving traffic safety using artificial intelligence involves various applications and strategies aimed at enhancing road safety through advanced technological means. Improving traffic safety using artificial intelligence can be through next approaches: Intelligent traffic management systems; Predictive maintenance; Autonomous vehicles; Accident prediction and prevention; Driver assistance systems. By integrating artificial intelligence into traffic safety measures,we make transportation safer for everyone.

These plans aim to strike a balance between the prevalent use of private cars and alternative modes of transport. A pivotal aspect of SUMP formulation lies in the identification of indicators, serving as tools for cities to assess their mobility systems and strategically address strengths and weaknesses. The European Commission provides a set of reliable indicators for standardized assessments, ensuring uniform data collection. Despite the importance of SUMPs, cities often lack consistent political and institutional support for their integration into urban development plans. Additionally, disparities exist in the application of methodologies for data collection in defining SUMP indicators. This paper thoroughly analyzes the indicator identification process within the SUMP creation framework. It highlights the need for continuous political backing and institutional support for SUMP projects within urban development plans. Furthermore, the paper addresses the variations in applying methodologies for data collection, emphasizing the importance of standardization. The focus is on the European Commission's indicators, providing practical insights into their application for a more uniform assessment of mobility systems. The research contributes by presenting a refined method for data collection, encompassing both basic and additional SUMP indicators. The study also introduces an in-depth analysis of modal distribution, offering a valuable resource for cities interested in formulating new SUMPs. By enhancing our understanding of these critical aspects, this paper contributes to the ongoing discourse on sustainable urban mobility and supports the development of more effective and harmonized transportation planning strategies.

In the structure of factors on which traffic safety depends, road and road elements occupy an important place in the traffic safety management system. The elements of the road create the conditions for the danger caused by other elements to turn into a traffic accident. Road elements can affect the occurrence of traffic accidents, but in particular, they can affect the "weight", i.e. the result of a traffic accident. This statement is supported by the fact that there are a number of influential elements of the road that can be direct or indirect causes of traffic accidents. The condition and quality of the roadway affect the safety of the traffic as a direct factor. The paper emphasizes the quality of the carriageway curtain and the analysis of the impact of the same on the value of the adhesion coefficient. The value of the adhesion coefficient is determined by practical measurement with a pendulum (Skid Resistance Taster) on parts of a high-risk section of the main road, in order to achieve its satisfactory quality, i.e. satisfactory grip coefficient.

The UN Sustainable Development Goals (SDGs) are a global call for action to end poverty, protect our planet's environment and climate, and provide opportunities for all people to enjoy peace and prosperity. Decarbonizing the transport sector is key to achieving the UN and EU climate goals. Under the Paris Agreement, EU countries have committed to making the EU climate-neutral by 2050. To achieve the goal of net neutrality, EU countries have set a goal to reduce net greenhouse gas emissions in all sectors (especially transport) by at least 55% by 2030 compared to 1990 levels and to continue to gradually reduce emissions by 2050, when there should be zero greenhouse gas emissions from all sectors. The Regional Development Strategy, i.e. the Green Agenda for the Western Balkans, aims to respond to the challenges of climate change and green transition and to help the countries of the Western Balkans harmonize environmental regulations with European standards and norms. Electric mobility and management of E mobility is becoming a decisive element in the smart and sustainable development of cities and local communities as one of the UN Sustainable Development Goals. The transition to electric mobility (e-mobility) in urban areas requires a combination of infrastructure, smart grid technologies, vehicle advances, and digital platforms to ensure efficiency, accessibility, and sustainability. Several cities around the world have successfully integrated e-mobility technologies into their urban transport systems. The paper analyses cities that showcase different aspects of electric mobility transformation, with a detailed analysis of the financial investments and economic benefits associated with e-mobility projects in each of the selected cities. Western Balkan cities are gradually adopting e-mobility solutions through subsidies for electric vehicles, expansion of charging infrastructure, electrification of public transport, and integration of micro-mobility. This paper analyses cities in Southeast Europe and the Western Balkans, the challenges in fully adopting e-mobility, and their efforts to implement smart and sustainable urban transport solutions.

Planning as sustainable mobility function requires new approaches and new planning concepts that encourage the transition to cleaner and more sustainable transport modes such as walking, cycling, public transport, new patterns of car use and ownership, and the adoption and use of new technologies as indispensable support for sustainable mobility development. This approach aims to satisfy the mobility needs with a healthier environment and a better quality of life, since healthy and ecologically clean environments are becoming more attractive, both for the local population and for tourists, which can be especially important for those local communities with special tourist potential and developed tourist offer. Given the fact that electric mobility contributes significantly to the climate change mitigation through the reduction of pollutant emissions using different types of electric vehicles, it is necessary to consider the possibility of using e-mobility in order to strengthen the offer of tourist destinations while simultaneously protecting these areas from excessive noise, pollution, usurpation and deterioration of the quality and appearance of tourist areas. Considering that the city of East Sarajevo, as one of the tourist attractive local communities in terms of the diversity of the tourist offer with a scattered concentration of tourist destinations on predominantly hilly terrain, this paper will present the concept of introducing a bike-sharing system, an electric bus and an eco-taxi vehicle in the function of tourists transportation system with supporting infrastructure development plan, all based on tourist demand data analysis.

This research aims to examine the traffic noise levels and to improve the performances of the Calculation of Road Traffic Noise model (C.R.T.N.) by applying the statistical multiple linear regression approach. Research methods included traffic noise level measurements with a noise measuring device in an urban area, using a sampling method in different periods. An evaluation of the measured data and prediction results was performed. Based on the predicted values of the C.R.T.N. model and coefficient of determination (R2), multi-linear regression was carried out to determine statistically significant parameters. The obtained multi-linear regression equation defined a new form of C.R.T.N. model. When applying the new improved version based on the C.R.T.N. model, higher accuracy of prediction is achievable. It can be seen that by applying multi-linear regression, the obtained prediction values are acceptably equated with field measurements in the chosen research environment. So, in this way, the differences between the predicted values of the noise level and the values measured in the field were minimized. Finally it can be concluded that when applying the new improved version based on the C.R.T.N. model, higher accuracy of prediction is achievable.