AI for Autonomous Vehicles: Understanding Self-Driving Cars MCQ Test
Explore key concepts like computer vision, sensor fusion and machine learning algorithms driving automation. Perfect for students and tech professionals.
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- 📋 Total Number of Questions: 40
- ⏳ Time Allotted: 40 Minutes
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1. What is the primary role of AI in autonomous vehicles?
- Controlling engine efficiency
- Enabling decision-making and navigation
- Designing car interiors
- Monitoring tire pressure
2. Which type of sensor is most commonly used in self-driving cars to detect nearby objects?
- Lidar
- Thermometers
- Pressure sensors
- Speedometers
3. What does "perception" refer to in the context of autonomous vehicles?
- Monitoring driver fatigue
- Calculating the fastest route to a destination
- Understanding the surrounding environment using sensors
- Predicting fuel consumption
4. Which algorithm is typically used for path planning in self-driving cars?
- A* (A-star) algorithm
- Random forest
- K-means clustering
- Naive Bayes
5. What is the purpose of computer vision in self-driving cars?
- To monitor driver health
- To optimize fuel efficiency
- To predict weather conditions
- To interpret visual data from cameras
6. What is the significance of "sensor fusion" in self-driving cars?
- Balancing tire pressure
- Synchronizing the engine with brakes
- Integrating sound systems in vehicles
- Combining data from multiple sensors for accurate decision-making
7. Which AI framework is often used in developing self-driving technology?
- TensorFlow
- React
- Bootstrap
- AngularJS
8. What is the primary function of radar sensors in autonomous vehicles?
- Enhancing fuel efficiency
- Mapping the Earth's magnetic field
- Detecting objects and measuring distances in various weather conditions
- Monitoring in-car temperature
9. Which level of vehicle autonomy requires no human intervention during driving?
- Level 5
- Level 1
- Level 3
- Level 2
10. What role does reinforcement learning play in autonomous driving?
- Improving fuel economy
- Maintaining tire pressure
- Designing interior components
- Training vehicles to make decisions based on trial and error
11. What is the primary use of GPS in autonomous vehicles?
- Providing location and navigation data
- Detecting nearby obstacles
- Enhancing fuel efficiency
- Monitoring speed limits
12. Which company pioneered autonomous vehicle technology with its "Autopilot" feature?
- Amazon
- Microsoft
- Tesla
- General Motors
13. What is "end-to-end learning" in the context of self-driving cars?
- Designing engines that respond to voice commands
- Running multiple simulations in a single trial
- Learning fuel-efficient driving techniques
- Training neural networks to directly map sensor data to driving actions
14. What is the main advantage of using Lidar over cameras in autonomous vehicles?
- Accurate depth perception in low-light conditions
- Detecting sound frequencies
- Monitoring internal vehicle systems
- Capturing color images
15. What is "dynamic object tracking" in self-driving cars?
- Monitoring the movement of objects in real-time
- Identifying static objects only
- Recording tire wear
- Measuring fuel efficiency
16. Which ethical concern is associated with AI in autonomous vehicles?
- Decision-making in life-and-death situations
- Increasing car prices
- Decreasing human driving jobs
- Slower adoption of green technologies
17. How does AI use predictive analytics in autonomous vehicles?
- By analyzing user preferences for car color
- By predicting fuel efficiency
- By forecasting the movement of pedestrians and other vehicles
- By calculating future tire wear
18. What is the purpose of a high-definition map in autonomous vehicles?
- Measuring fuel consumption
- Recording music preferences of drivers
- Monitoring in-car temperature
- Providing detailed road and traffic information for navigation
19. Which machine learning model is commonly used for image classification in autonomous vehicles?
- Convolutional Neural Networks (CNNs)
- Support Vector Machines (SVMs)
- K-means clustering
- Linear regression
20. What is "vehicle-to-vehicle (V2V) communication"?
- Synchronizing music between cars
- Transmitting radio signals to passengers
- Exchange of information between nearby vehicles to improve safety and efficiency
- Enabling vehicles to recharge each other
21. What type of data does radar in self-driving cars primarily collect?
- Distance and velocity of objects
- Sound frequencies
- Weather patterns
- GPS coordinates
22. How do self-driving cars identify traffic signals?
- Using computer vision algorithms
- By detecting sound waves
- By interpreting radio frequencies
- By connecting to the driver's smartphone
23. What is a key challenge in deploying autonomous vehicles?
- Reducing the cost of vehicle interiors
- Handling unpredictable human behavior on roads
- Monitoring engine wear
- Detecting tire pressure in real-time
24. How does AI help in parking an autonomous vehicle?
- By using sensors and algorithms to guide precise movements
- By predicting traffic patterns
- By enhancing fuel efficiency
- By monitoring battery levels
25. What is a key benefit of AI in autonomous vehicle safety?
- Increasing vehicle speed limits
- Reducing accidents caused by human error
- Enhancing engine performance
- Improving road infrastructure
26. What is the role of edge computing in autonomous vehicles?
- Processing data locally for real-time decision-making
- Connecting vehicles to social media platforms
- Managing cloud storage for drivers
- Designing lightweight car frames
27. What is the main role of a "control system" in autonomous vehicles?
- Calculating fuel economy
- Designing car interiors
- Executing driving decisions such as steering and braking
- Monitoring battery life
28. What type of AI technique is used to simulate driving in virtual environments?
- Reinforcement learning
- Genetic algorithms
- Linear regression
- Bayesian networks
29. How does AI help in reducing traffic congestion with autonomous vehicles?
- By optimizing routes based on real-time traffic data
- By enforcing speed limits
- By reducing engine power during peak hours
- By synchronizing with traffic cameras
30. Which of the following is a key feature of Tesla’s AI-based autopilot?
- Predicting weather changes
- Lane keeping and adaptive cruise control
- Enhancing vehicle design aesthetics
- Measuring passenger comfort levels
31. What does "Level 4" autonomy indicate in self-driving cars?
- The car can drive itself under specific conditions without human intervention
- Full self-driving capability under all conditions
- Limited driver assistance features
- Partial automation requiring constant human monitoring
32. Which AI concept helps self-driving cars predict the behavior of other vehicles?
- Genetic algorithms
- Natural language processing
- Probabilistic reasoning
- Semantic analysis
33. What is the main focus of AI research in autonomous vehicles today?
- Improving decision-making and safety in real-world scenarios
- Enhancing luxury features like in-car entertainment
- Developing faster fuel engines
- Reducing vehicle weight
34. How do self-driving cars recognize road signs?
- By analyzing sound frequencies
- Using pre-trained image recognition models
- By detecting magnetic fields
- Through manual driver input
35. Which system helps autonomous vehicles to detect pedestrians?
- Lidar and computer vision algorithms
- Tire pressure monitoring system
- Engine cooling system
- GPS navigation
36. What is the primary challenge in urban environments for self-driving cars?
- Handling complex and dynamic scenarios involving pedestrians and vehicles
- Maintaining fuel efficiency
- Navigating on highways only
- Identifying vehicle color
37. Which of the following is an example of unsupervised learning in autonomous vehicles?
- Predicting the time of arrival based on historical data
- Identifying road signs with labeled data
- Training neural networks to detect pedestrians
- Clustering traffic patterns to optimize routes
38. What is the role of a "fail-safe system" in autonomous vehicles?
- Ensuring the vehicle can safely stop in case of a system failure
- Improving engine performance
- Enhancing GPS signal strength
- Monitoring tire pressure
39. How does an autonomous vehicle interpret traffic laws?
- By relying solely on driver input
- By using rule-based algorithms combined with machine learning
- By scanning traffic laws into the onboard system
- By interpreting magnetic road markers
40. Which of these technologies enhances night driving for autonomous vehicles?
- Infrared cameras
- Radar detectors
- Solar panels
- Magnetic sensors