Browse Topic: Public transportation systems
Computer vision, automated landing and embedded AI for tomorrow's cockpits. Airbus, Toulouse, France At the VivaTech forum in June, Airbus showcased a demonstration highlighting the use of computer vision to enhance automated landing procedures and operational efficiency. The “Vision Landing Application” utilizes artificial intelligence to analyze runway features in real-time using onboard cameras. The goal of this research is to create an additional and independent positioning source to guide pilots and/or their aircraft reliably, opening up the perspective of bringing autoland (fully automated landing procedure) capabilities to airports that lack advanced ground infrastructure. While the technology is still in the research phase and far from commercial certification, this technical exploration aligns directly with Airbus' global roadmap for Smart Automation. Airbus already has a head start, since it has already conducted numerous research projects during the last decade, which have led to the demonstrator at Airbus' stand at this year's show.
Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance prediction In comparison to LR's 4,409 kg MAE (mean absolute error), 7,061 kg RMSE (root mean square error), and 0.9825 R2 value, XGBoost significantly excelled with validation results showing an R2 value of 0.9992 and an RMSE of 1,514 kg In the absence of labelled test targets, cross-validation nevertheless showed a constant degree of generalizability The residual diagnostics showed that the model was reliable for practical execution with low-variance deviations that were unbiased An accurate ATOW estimate improves the demand-capacity balance and On-Time Performance (OTP) in ATM, which in turn affects the runway schedule, wake turbulence diversion, slot allocation, and fuel planning The results highlight the need to include ATOW predictions in both tactical and strategic planning to reduce delays, increase airspace usage, and promote sustainable aviation operation and possesses significant improvements will consist of weather and runway conditions, stochastic ambiguity computation, and drift monitoring to keep up with ever-changing operating variables while maintaining accurate forecasts.
Innovators at NASA Johnson Space Center (JSC) have developed an Earthbound robotic training system called “ARGOS” for short. It can actively simulate an astronaut’s weightlessness in space by using an overhead runway and bridge drive system to partially or fully offload their weight using attached cables, effectively suspending them off the ground. Although the test subject’s torso and legs are offloaded, their arms and any weighty hand tools are not.
Rubber components are an important part of the suspension system of high-speed trains, and the complex nonlinear characteristics of rubber parts have a significant impact on the vehicle dynamic performance. This paper establishes a nonlinear dynamics model of the liquid composite swivel arm positioning node, which can reflect the dynamic stiffness and dynamic damping characteristics of the rubber components that change nonlinearly with the frequency and amplitude, and also has a fast calculation speed. The vehicle dynamics simulation model considering the longitudinal stiffness nonlinear characteristics of the arm node is established, and the influence of the stiffness nonlinearity of the liquid composite arm positioning node on the dynamic performance of the vehicle, such as straight-line stability and curve passing ability, is studied in depth through numerical simulation.
Items per page:
50
1 – 50 of 1251