Quiz dotyczący sztucznej inteligencji w kolejnictwie

Odpowiedzi i wyjaśnienia pojawiają się w miarę rozwiązywania quizu.

1. Jaka jest główna korzyść z konserwacji predykcyjnej na kolei?
   • Sprawia, że pociągi jeżdżą szybciej niż prędkość znamionowa
   • Oznacza komponenty, które mogą ulec awarii, zanim spowodują awarię lub wypadek
   • Eliminuje potrzebę stosowania jakichkolwiek fizycznych ścieżek
   • Zastępuje bilety kolejowe systemem rozpoznawania twarzy
2. Which approach can examine railway camera images for visible track or lineside defects?
   • Text-to-speech synthesis without image input
   • An audio-only voiceprint matcher
   • A language translation system with no visual processing
   • Computer vision trained or configured to recognize relevant visual features
3. What functions can Automatic Train Operation perform in the railway operational framework?
   • Only printing passenger tickets
   • Only predicting the weather without controlling motion
   • Automated traction, braking, speed regulation, and stopping functions
   • Only renaming maintenance image files
4. How should an energy-efficient railway speed profile relate to operational requirements?
   • Optimize energy use while satisfying applicable journey, capacity, and speed constraints
   • Ignore stopping and speed requirements whenever energy use falls
   • Guarantee a fixed percentage saving on every route
   • Stop all trains indefinitely to claim perfect efficiency
5. What does a railway digital twin represent?
   • A second human driver with the same appearance
   • A replacement for the physical track made only of software
   • A virtual representation of physical rail assets or infrastructure
   • A guarantee that every simulated result occurs in the real network
6. Does the presence of ATO establish that a railway uses machine learning to drive its trains?
   • Yes; every automated control system is necessarily a neural network
   • No; ATO specifies automated functions, while the implementation must be examined to identify any learned model
   • Yes; all ATO controllers are trained on social-media video
   • No; ATO has no connection with train motion
7. Why should a railway maintenance team assess an AI fault alert before deciding on an intervention?
   • An alert can be mistaken and must be considered with engineering evidence and operational consequences
   • Every alert proves that a component will fail at a known time
   • A model score eliminates the need for asset information
   • Ignoring all alerts is always more accurate than reviewing them
8. In the ERA ATO principles, what limits an energy-efficient speed profile besides journey timing requirements?
   • Only the color of the train's exterior
   • Only the length of its passenger announcements
   • No other speed constraint once the energy objective is set
   • The ETCS most restrictive speed profile