Precise evaluation of vehicle CO₂ emissions under real-world driving conditions is essential for meeting stringent regulations. While laboratory procedures such as WLTC ensure repeatability, they fail to reflect transient conditions typical of everyday driving, and PEMS-based RDE measurements remain costly. This study proposes a data-driven approach for reconstructing instantaneous CO₂ concentration using onboard engine parameters - engine speed, exhaust gas temperature and exhaust mass flow rate - without direct CO₂ sensing. Linear, nonlinear and ensemble machine learning models were evaluated using an RDE dataset of 5200 synchronized observations collected on a mixed urban-rural route. Ensemble methods, particularly Random Forest (R² = 0.715, RMSE = 15,307 ppm) and XGBoost (R² = 0.669), achieved the highest accuracy and reproduced steady-state conditions and rapid CO₂ drops during fuel-cut events. The results confirm that reliable CO₂ estimation can be achieved using a minimal OBD-based input set, enabling cost-effective emission monitoring and real-time onboard applications.

As automotive technology advances in the realm of digitization, vehicles are becoming smarter and, at the same time, more vulnerable to various threats. This paper focuses on techniques for detecting faults to mitigate the risk of freight transportation. Our observations show that vehicle uptime varies significantly even under similar operating conditions. This variation stems from differences in the wear and tear of moving and stationary parts, the characteristics of transported loads, driving styles, the quality of maintenance, etc. These factors are particularly crucial for abnormal vehicles designed to carry AILs (Abnormal Indivisible Loads). Such vehicles are especially prone to surprising threats, requiring efficient techniques for monitoring separate vehicle components and providing drivers with vital information about their operational status. The presented article proposes an original concept of an integrated three-level monitoring system based on the AOP (All-in-One Platform) principle, using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, which is a tool oriented to distinguish points from three categories: basic, boundary, and external. This is a solution not yet found in the literature. It is based on assessments of LOFs (Local Outlier Factors) and to detect anomalies in the measured values of operational parameters. The purpose of our study was to determine whether providing truck drivers with current information from an active threat warning system could help reduce unplanned downtimes.

Aviation is the youngest of the transport industries, yet despite its short history, it is considered one of the most important spheres of transport, both in terms of passenger and cargo transportation. Civil aviation is used by an increasing number of people, and the number of aircraft used by airlines around the world continues to grow. An inherent element that is a particularly important aspect of this mode of transportation is security. In civil aviation, there are numerous dangers associated with events occurring before the flight, during the flight, as well as those associated with the landing process. The events need to be controlled and their causes actively sought and ultimately prevented. The Polish Civil Aviation Authority, as part of the creation of the National Civil Aviation Safety Program, developed the National Safety Plan 2020-2023. The document covers threats identified in the Systemic, European, and National Areas. They are characterized and classified based on the materiality (significance) of the event. The aim of this article is to characterize and analyze selected factors (e.g. collisions with birds, helicopter events) that affect the number of safety incidents in civil aviation. The background of the study was the analysis and synthesis of the literature on the subject, while the main research method was the statistical analysis of historical data on aviation incidents. The data provided in Poland's National Security Plan 2020-2023 were used to distinguish the factors associated with the threats present and synthetically evaluate their impact. The analyses made it possible to identify areas of particular safety risks and form the basis for further detailed research.

Celem artykułu jest wskazanie różnic między ogólnodostępnym narzędziem prognozującym wykorzystywanym w planowaniu dostaw a dedykowanym, stworzonym specjalnie dla danej