Carbon emissions generated by the transportation sector represent a large part of total greenhouse gas emissions and are thus subject to various policies and initiatives for emission reduction and the development of sustainable transportation networks. Furthermore, passenger transportation generates a significant amount of emissions within this sector, especially in those countries with large and developed tourist sectors. Examples of such countries are Italy and Croatia, located in the Adriatic region, with a large portion of passengers between them being transported utilizing mainly maritime and/or road transportation modes. A proper analysis of the impact of these transportation mode choices on carbon emissions is essential to enable the selection of the optimal transportation mode for the particular transportation route with respect to the generated emissions. Therefore, this study determines the carbon emissions of the maritime and/or road transportation modes on the existing cross-border passenger transportation routes between Italy and Croatia. For the analysis, the Adriatic region was divided into three sections—the Northern, Middle, and Southern regions—each characterized by specific transportation routes defined by geographical features and distances. The results obtained from this research are presented as total carbon emissions for each transportation mode separately, based on each of three chosen routes in different regions. In addition, a carbon emission comparison between each transportation mode in regard to occupancy rate is performed and presented separately for each chosen route based on its specific distances, transportation means, and features. Finally, by providing an analysis of the existing state, this study can serve as a basis for Italy–Croatia cross-border passenger mobility network modernization and the introduction of new, sustainable, and multimodal transportation routes.

The development of light detection and ranging (lidar) technology began in the 1960s, following the invention of the laser, which represents the central component of this system, integrating laser scanning with an inertial measurement unit (IMU) and Global Positioning System (GPS). Lidar technology is spreading to many different areas of application, from those in autonomous vehicles for road detection and object recognition, to those in the maritime sector, including object detection for autonomous navigation, monitoring ocean ecosystems, mapping coastal areas, and other diverse applications. This paper presents lidar system technology and reviews its application in the modern road transportation and maritime sector. Some of the better-known lidar systems for practical applications, on which current commercial models are based, are presented, and their advantages and disadvantages are described and analyzed. Moreover, current challenges and future trends of application are discussed. This paper also provides a systematic review of recent scientific research on the application of lidar system technology and the corresponding computational algorithms for data analysis, mainly focusing on deep learning algorithms, in the modern road transportation and maritime sector, based on an extensive analysis of the available scientific literature.

The optimization of seaside operations at container terminals includes solving standard berth and crane allocation problems. The question arises about the efficiency of such optimizations in small and medium-sized container terminals, with different quay designs or different terminal layouts. This paper focuses on developing an integrated model that would apply to medium-sized terminals with a multi-quay layout. The main objectives are determining the shortest possible vessel stay at the port and providing a high-reliability service to ship operators. The developed integrated model includes the optimization process in three stages: initiation, assignment, and adjustment. The model’s main feature is generating operational scenarios based on the cargo distribution onboard and integrated berth and crane allocation. The aim is to choose the most favorable option to optimize ships’ overall processing time in the planning horizon. The experiment was conducted to test the model’s functionality and justify the results by comparing the results obtained by the integrated model with the classical approach of berth and crane allocation in a multi-quay environment. The results show significant improvements in peak periods when ships’ arrivals are concentrated in smaller time intervals by applying the integrated model.

The optimization of the goods delivery to Rijeka’s city center presents a complex organizational framework where many parameters must be taken into account and a diverse multi-methodological approach, needs to be utilized. The building of a distribution center is asserted here to be one notable way to improve the existing delivery service. The grouping of freight in a distribution center would result in a reduction of transport costs due to a smaller number of vehicles entering the city center, in turn reducing the traffic burden incumbent on the city’s transport network. In this paper, two of the many possible methods related to the optimization of goods delivery in city centers, have been used. Based on the data collected through the study’s questionnaire, conducted in the area of the city of Rijeka, the method of gravity center has been used to determine the location of the distribution center. Then, based on the tentative location of the distribution center, the method of optimization of the transport process has been applied by resorting to transport problem-solving methods, including several different implementation scenarios. From the proposed solutions, and based on the results detailed, the solution that was found to be the most credible was arguably the best match with the default criterion.

The growth of container transport places increasing demand on traffic, especially in situations where container terminals are located near the city centers. The main problem is traffic congestion on networks caused by the integration of Heavy-Duty Vehicles and urban traffic flows. The main objective is to identify the critical traffic parameters which cause negative organizational and environmental impacts on the existing and future traffic demand. A micro-level traffic simulation model was implemented for the testing of the proposed framework-based supply, demand, and control layers. The model was generated and calibrated based on the example of a mid-size Container Terminal “Brajdica” and the City of Rijeka, Croatia. The results indicate that the critical parameters are Queue Length on the approach road to the Container Terminal and the Stop Delay on the main city corridor. High values of these parameters cause negative effects on the environment because of increased fuel consumption and the generation of extra pollution. Due to this problem, a sensitivity analysis of the traffic system performance has been conducted, with a decrement of Terminal Gate Time distribution by 10%. After re-running simulations, the results indicate the impact of subsequent variation in Terminal Gate Time on the decrease of critical parameters, fuel consumption, and vehicle pollution.

The growing demand for private and public transport services in urban areas requires sophisticated approaches to achieve satisfactory mobility standards in urban areas. Some of the main problems in urban areas today are road congestions and consequently vehicle emissions. The aim of this paper is to propose a methodological approach for the estimation of vehicle emissions. The proposed methodology is based on two interrelated models. The first model is a microscopic simulation SUMO model which can be used to identify the most congested urban areas and roads with critical values of traffic parameters. The second model is the COPERT Street Level for estimating vehicle emissions. The proposed models were tested on the urban area of Rijeka. The results of the microscopic SUMO simulation model indicate six urban roads with the critical traffic flow parameters. On the basis of the six identified urban roads, an estimation of vehicle emissions was carried out for specific time periods: 2017, 2020, 2025, and 2030. According to the results of the second model, the urban road R20-21 was identified as the most polluted road in the urban district of Rijeka. The results indicate that over the period 2017–2030, CO emissions will be reduced on average by 57% on all observed urban roads, CO2 emissions by 20%, and PM emissions by 58%, while the largest reduction of 65% will be in NOx emissions.

The study presents an analysis of the impact produced by the construction and modernization of road connections on the improvement and development of the port of Rijeka container terminal and on the growth of its competitiveness on the northern Adriatic traffic route. The paper focuses on the smoothing technique implementation as a quantitative prognostic method for road traffic. Considering the importance of container traffic within the total freight traffic in the port of Rijeka, prognostics is presented for lorry traffic on State road D – 404, which connects the container terminal of Brajdica to the expressway network to the hinterland. Thereby, the potential substratum gravitating to the container terminal and to the pertaining traffic route has been evaluated. Following description of the geographical, traffic-related and logistic situation of the port of Rijeka, the paper continues with technical and technological features of the container terminal of Brajdica and, in addition, with the significance of State road D – 404 for development of the container terminal of Brajdica and an analysis of lorry traffic trends on State road D – 404. Whereas there are confirmed assertions that there are significant differences found quite often between projected values and those ones actually obtained, the expected traffic trend values obtained by applying the smoothing technique using the moving averages method for 2017 have been assessed as satisfactory.

Maritime transport is the backbone of international trade of goods. Therefore, seaports are of great importance for maritime transport. Container transport plays an important role in maritime transport and is increasing year by year. Containers transported to a container terminal are stored in container yards side by side and on top of each other, forming blocks. If a container that is not on top of the block has to be retrieved, the containers that are above the required container must be relocated before the required container is retrieved. These additional container relocations, which block the retrieval of the required container, slow down the entire retrieval process. The container relocation problem, also known as the block relocation problem, is an optimization problem that involves finding an optimal sequence of operations for retrieving blocks (containers) from a container yard in a given order, minimizing additional relocations of blocking containers. In this paper, the focus is on the two-dimensional, static, offline and the restricted container relocation problem of real-size yard container bays. A new method for resolving the container relocation problem that uses a genetic algorithm is proposed to minimize the number of relocations within the bay. The method is evaluated on well-known test instances, and the obtained results are compared with the results of various relevant models for resolving the container relocation problem. The results show that the proposed method achieves the best or the second-best result for each test instance within the test set.