GEOBASE

The level of technological innovation and the efficiency of transport logistics in enterprises principally depend on the resources that are used. The authors aim to develop a new approach to assess the interface between railway innovation implementation and the competencies of logistics specialists. The application of advanced technologies, such as digitisation and automation, substantially improves key performance indicators while simultaneously lowering operational costs for railway undertakings. There are notable advancements in technology within railway transport, with a particular emphasis on digitalisation. Analysis and research to determine specific engineering competencies of logistics specialists are highly anticipated and needed. This research focuses on the analysis and assessment of the interconnection between technological innovations in railway transport and the engineering competencies of logistics specialists. An analytic hierarchy process (AHP) method is used to assess the impact of technological innovations on the engineering competencies of logistics specialists, aiming to establish the presumed link between social psychological and technological factors. A new approach for assessing the competencies of logistics specialists in the railway sector has been developed. It is proven that the implementation of technological innovations within railway companies serves as the decisive factor driving the improvement of engineering competencies for logistics specialists.

Micromobility has emerged as a major global trend in urban transportation. However, it has also led to a rise in accidents, largely attributed to improper usage and inadequate safety precautions. This paper presents a model developed for the dynamic analysis of an in-wheel suspension system for micromobility vehicles, along with proposals for its improvement. The model accounts for challenges related to urban infrastructure, particularly variation in various obstacle types and heights on cycle road pavement, using the city of Vilnius (Lithuania) as a case study. The research paper additionally evaluates factors affecting rider safety and risk, with a primary focus on in-plane dynamics. The dynamic analysis demonstrates that the in-wheel suspension system enhances riding safety across simulated variations. These findings help identify critical vertical dynamic risks for micromobility in urban area and offer insights for future city’s road infrastructure planning.

Engineered wood is increasingly valued for its use of renewable raw materials, low environmental impact, and good performance characteristics. The wide variety of raw materials used to produce engineered wood requires detailed research to select rational technological production parameters. This paper examines engineered wood produced from furniture-recycling waste and different polyurethane compositions. The factors under analysis include mixture pressure level, binder type, and filler preparation. The effect of the mixture’s pressure level on density, structure, strength, and moisture indicators was evaluated. The pressure levels were 1.5, 2.0, 2.5, 3.0, and 3.5 MPa. Tests have shown that the mixture pressure level significantly affects compressive strength, absorption, swelling, and structure formation. A rational pressure level of 3.0 MPa was determined. When using this level, there are no voids in the samples. Depending on the binder composition, the resulting compressive strength ranges from 20.5 to 25.6 MPa, water absorption from 7.62 to 10.3 kg/m2, and swelling from 8.65 to 12.6%. At a pressure of 3.5 MPa, the properties of engineered wood improve further, but the binder begins to separate from the mixture. A significant influence of the binder on compressive strength, absorption, and swelling was observed. A detailed kinetic analysis was performed to evaluate changes in sample strength following production. The tests showed that the compressive strength increased markedly 14 days after sample preparation.

This paper analyses road safety issues related to the operation of right-hand drive vehicles in right-side operated traffic conditions. The problem is statistically valid, especially in regions where the states border with road traffic organised on different sides, or due to economic considerations, when it is much cheaper to purchase a vehicle adapted to the traffic of the other side. This article focuses on visibility issues of different driving positions in the case of the most dangerous overtaking manoeuvre by geometrically based situation analysis and safe distance to opposite obstacle evaluation. An additional part of the study is the functional testing of special indirect vision equipment in real traffic conditions. This is related to the technical regulations in force in the European Union Member States for vehicles adapted to the traffic in the other direction when constantly participating in traffic. An overview of these technical requirements, as well as the existing requirements not to restrict the free market of vehicles, is also covered in the paper.

Energy storage investments are essential for achieving sustainable development goals; however, their high costs and long-term returns create significant uncertainty for investors. As a result, investment decisions are shaped not only by rational evaluations but also by psychological and emotional factors. Despite this reality, behavioral economics-based variables remain largely underexplored in the energy storage literature. To address this gap, this study identifies the most critical behavioral determinants influencing the performance of energy storage investments. A novel decision support system is developed for G7 countries by integrating z-scoring, criteria impact multiplicative assessment (CIMAS), interval-valued spherical fuzzy numbers, and the ranking of alternatives through functional mapping of criterion sub-intervals into a single interval (RAFSI). The proposed framework enhances the representation of uncertainty and reduces individual biases through statistically derived expert weighting. The results indicate that risk perception and overconfidence are the most influential behavioral factors, while Germany and the United States exhibit the strongest behavioral economics-based performance in energy storage investments.

This research focuses on vehicle Advanced Driver Assistance Systems (ADAS), with particular emphasis on Lane Keeping Assist (LKA) systems which is designed to help drivers keep a vehicle centered within its lane and reduce the risk of unintentional lane departures. These kinds of systems detect lane boundaries using computer vision algorithms applied to video data captured by a forward-facing camera and interpret this visual information to provide corrective steering inputs or driver alerts. The research investigates the performance, reliability, sustainability, and limitations of LKA systems under adverse road and environmental conditions, such as wet pavement and in the presence of degraded, partially visible, or missing horizontal road markings. Improving the reliability of lane detection and keeping systems enhances road safety, reducing traffic accidents caused by lane departures, which directly supports social sustainability. For the theoretical test, a modified road model using MATLAB software was used to simulate poor road markings and to investigate possible test outcomes. A series of field tests were conducted on multiple passenger vehicles equipped with LKA technologies to evaluate their response in real-world scenarios. The results show that it is very important to ensure high quality horizontal road markings as specified in UNECE Regulation No. 130, as lane keeping aids are not uniformly effective. Furthermore, the study highlights the need to develop more robust line detection algorithms capable of adapting to diverse road and weather conditions, thereby enhancing overall driving safety and system reliability. LKA system research supports sustainable mobility strategies promoted by international organizations—aiming to transition to safer, smarter, and less polluting transportation systems.

With the swift pace of urbanization and industrialization, air pollution has emerged as a critical issue, severely impacting public health and impeding the progress toward sustainable development. This study delves into the nexus between Financial Inclusion (FI) and Air Pollution Reduction (APR), employing a balanced panel dataset that encompasses 255 Chinese prefecture‐level cities from 2011 to 2022. Through the application of econometric models and a series of robustness tests, we uncover an inverse U‐shaped dynamic between the advancement of FI and APR. Our findings indicate that during the nascent stages of FI, there is a positive impact on APR. However, this beneficial effect plateaus and potentially reverses when FI progresses beyond an optimal threshold. Further analysis elucidates three primary economic channels through which FI may influence APR: alleviation of energy poverty, stimulation of innovation, and household consumption. Notably, these mechanisms exhibit distinct patterns of influence across cities with varying levels of economic development and geographical locations. The findings hold significant implications for policy‐making, suggesting that the Chinese government must balance the acceleration of FI with a keen awareness of its regional impacts. Tailored environmental policies and innovative financial instruments can foster green growth and sustainable development.

In the context of increasing environmental challenges and limitations of traditional energy resources, the development of energy innovations becomes a key factor in transitioning to a circular economy. This research is dedicated to examining the implementation of energy innovations by countries worldwide in the pursuit of Sustainable Development Goals. The transition to a circular economy requires a comprehensive understanding of the organizational and economic support for energy innovations, including ecological, technical, and socio-financial determinants of societal development. In this context, the advancement of energy innovations plays a crucial role in forming a sustainable economic system within its circulation. The research methodology includes bibliometric analysis to identify knowledge clusters regarding energy innovations. The economic indicators of energy innovations across different countries were analyzed. The impact of innovation and research and development (R&D) on the development of renewable energy was conducted. The insights were elaborated for the transition to a circular economy using a scenario-based approach. These insights outline the development trajectory of energy innovations in the context of a circular economy while considering ecological, technical, social, and economic challenges. Finally, the study provides a roadmap for implementing energy innovations in the context of economic decarbonization and the transition to a circular model while ensuring the achievement of the Sustainable Development Goals.

Cities are increasingly integrating micromobility, which heightens the need for robust analytical methods to identify high-risk intersections. This study presents a three-stage methodological approach that combines six years of accident data, spatial hotspot analysis, and calibrated floating-car traffic data to estimate exposure and calculate intersection crash rates in Central Vilnius. Testing the proposed approach identified eight high-risk intersections, with intersection crash rates (ICR) ranging from 0.044 to 0.151, indicating substantial differences in exposure-adjusted risk across the network. The validation of floating-car data (FCD) produced a determination coefficient (R2) of 0.87, confirming reliable exposure estimates where traditional traffic counts are not available. One selected intersection was analyzed in greater depth using drone-based observations and conflict assessment, leading to two redesign alternatives. Both reduced conflicts, though the signalized option eliminated uncontrolled conflict points and offered the strongest expected safety improvement. The suggested methodological approach demonstrates how integrating accident data, exposure estimation, and behavioral analysis can support evidence-based scalable interventions to improve micromobility safety. Despite certain limitations, it enables the rapid identification of problematic intersections, provides site-specific safety diagnosis, and facilitates the development of data-driven design improvements to enhance the safety of micromobility users. As the world strives to shift towards greater sustainability, the concept of micromobility, defined as the use of lightweight, short-distance modes of transport, has gained growing attention among users and policymakers.

This study introduces an original sustainability-oriented methodology for calculating pollutant emissions (g/km) based on the ECE-15 driving cycle, aimed at evaluating passenger car compliance with various Euro emission standards. Four vehicles—two diesel and two gasoline-powered—representing Euro 4 to Euro 6 categories, respectively, were tested under controlled laboratory conditions. CO, HC, NOx, and CO2 emissions were measured and analyzed using the developed method. The Euro 4 Nissan Qashqai+2 exceeded the CO limit by 2.07 times, while NOx and HC emissions were below the threshold by 1.46 and 50%, respectively. CO2 exceeded the limit by only 6.2%. The Euro 5 Nissan Qashqai showed extremely low CO and HC levels—33 and 333 times below the limit—but exceeded NOx by 1.32 times, with CO2 emissions 62.8% above the target. Both Euro 6 vehicles (VW Passat) exhibited undetectable CO emissions, HC levels under 2% of the limit, and NOx reduced by 3.81 to 15 times. However, their CO2 emissions remained elevated, at 2.9% and 51.4% above the standard, respectively. The results confirm the effectiveness of modern emission control technologies, while also highlighting that CO2 remains a major challenge, particularly for powerful gasoline vehicles.