Metin Mutlu Aydin

This article investigates the challenge of establishing a common definition of public transport systems within the multidisciplinary framework of the BOPALiM COST project. Drawing on a comparative analysis across 11 countries, this project explores how accessibility and usability for persons with reduced mobility are addressed in law, policy, and practice. Focusing on the specific question of Public Transport System, by combining legal, technical, sociological, and rehabilitative perspectives, this article highlights the divergences and overlaps between disciplinary and institutional approaches. It concludes by proposing a shared definition that integrates accessibility, regulation, multimodality, and social participation as essential dimensions for inclusive mobility.

Traffic signal-controlled intersections are important elements of urban transport systems, where inappropriate signal control strategies can increase traffic congestion, energy consumption, and pollutant emissions. Increasing and time-varying traffic intensity reduces the efficiency of traditional fixed-cycle traffic signal control; therefore, fully traffic-actuated control solutions are increasingly being applied. This study compares the efficiency of fixed-cycle and fully traffic-actuated signal control at eight traffic signal-controlled intersections in Bursa (Turkey), including four-way intersections and signalized three-way and four-way roundabouts with different geometric characteristics. The analysis was performed using a microsimulation method and PTV Vissim software, incorporating actual peak hour traffic flows, detailed intersection geometry, and camera-based vehicle detection logic implemented through the VisVAP module. Particular attention was given to the sustainability implications of signal control by jointly considering traffic performance, fuel consumption, and traffic-related pollutant emissions. The efficiency of intersections was assessed based on average vehicle delays, the number of stops, queue length, average speed, fuel consumption, and emissions (CO, NOx, and VOC). The results show that fully traffic-actuated traffic control usually improves both operational and environmental performance, but the magnitude of the effect depends on the intersection geometry and traffic flow distribution. At four-way intersections, average delays decreased by up to 47% and queue length by up to 67%, while fuel consumption and emissions decreased by around 20–39% in some cases. These findings indicate that fully traffic-actuated control can contribute to more sustainable urban mobility by reducing congestion-related inefficiencies, unnecessary fuel use, and local pollutant emissions, although the magnitude of these benefits depends strongly on intersection geometry and traffic flow characteristics.

Traffic accidents are one of the most significant societal problems worldwide, resulting in loss of life and property. In recent years, powerful solutions for the automatic classification of traffic accidents have been offered by deep learning-based image processing methods. This study comparatively evaluated four convolutional neural network architectures (SqueezeNet, ResNet-18, ResNet-50 and AlexNet) with different depths and levels of complexity using the CADD (Car Accidents and Deformation) dataset, which consists of images of vehicle accidents. The model’s performance was examined in detail using accuracy, precision, recall, the F1 score, a confusion matrix and an ROC–AUC analysis. The ResNet-50 model significantly outperformed all others, achieving 52% validation accuracy and balanced F1-score values (~0.50–0.52). It also achieved particularly high precision (0.70), recall (0.79) and AUC (0.922) values in the Totaled class. In contrast, SqueezeNet exhibited significant class bias and struggled to learn the multi-class structure. The AlexNet and ResNet-18 models showed moderate performance, achieving limited success in terms of discriminability, particularly in the ‘Severe’ class. It should be emphasized that the analysis relies on single-frame static images and a relatively small, predefined dataset; the study is therefore intended as a preliminary comparative benchmark rather than a deployable damage-assessment system. Within this scope, the findings indicate that residual architectures such as ResNet-50 are promising candidates for future deep learning-based accident analysis tools, although further validation on larger and more diverse datasets is required prior to their real-world use in traffic safety, insurance assessment, and intelligent transportation applications.

Integration of innovative solutions into the transportation sector have led to the emergence of intelligent transportation systems (ITS) to reduce traffic congestion and accidents, provide environmentally friendly, safe and cost-effective infrastructure and increase efficiency. A key prerequisite for public institutions, local authorities and industry stakeholders to benefit from ITS is the availability of qualified technical staff. This study examined the presence of ITS courses within civil engineering departments across universities in Türkiye. The analysis revealed that only four out of 143 undergraduate programmes, 14 out of 111 master’s programmes and seven out of 69 doctoral programmes offer dedicated ITS courses. This demonstrates that only a limited proportion of civil engineering students receive ITS education. Expert interviews emphasised the urgent need to incorporate ITS courses into the civil engineering curriculum. Experts also emphasised the need to supplement theoretical content with field training and simulation studies. Survey results further indicated strong agreement among participants regarding the importance of hands-on ITS applications. Overall, the findings suggest that ITS education and awareness in Türkiye are still at an early developmental stage; however, increasing demand for qualified staff and rising interest in the field indicate strong potential for rapid advancement in the near future.

Flying cars are emerging as an innovative and sustainable means of transport. In recent years, efforts to develop flying cars have gained momentum. Flying cars, which do not consume fossil fuels thanks to their electric systems, are attracting attention due to their effective contribution to sustainable transport policies thanks to their carbon-neutral design. Furthermore, flying cars are expected to travel using air routes, which will make them a more attractive option, as they will be able to travel without being affected by traffic congestion in crowded cities. This study provides a comprehensive examination of research on flying cars, covering topics such as the emergence of the need for flying cars, flying car travel and urban life, the desirability of flying cars, and the integration of flying cars into social life.