Autonomy Levels, Software & Artificial Intelligence Easy

Autonomy Levels & Software & AI (Easy)

1 / 15

Why is detecting and eliminating blind spots important for safety?

It prevents accidents with hidden pedestrians or cyclists

It allows the vehicle to be seen more easily

It helps with the path planning of the vehicle

It is required to capture accurate diagnostics during driving

Fact:
AI-powered systems can reconstruct hidden areas and predict traffic movements to help the driver perceive their surroundings more accurately.

2 / 15

Using Vehicle-to-Vehicle communication, autonomous cars can drive very close together automatically to save fuel. What is this software feature called?

Tailgating

Platooning

Draft-Punking

Convoy Mode

Fact:
Future C-V2X communication systems will use weak AI systems in many places to continuously optimize communication and provide excellent latency, reliability and throughput.

3 / 15

Why is 'low latency' important when transmitting LiDAR/Radar data from the roadside unit to a vehicle?

To reduce the cost of the data plan

To ensure the vehicle receives information in near real time for safety

To improve the resolution of the images

To prevent the car's battery from draining

Fact:
Roadside unit sensors can detect objects behind large obstacles that a vehicle's onboard sensors would not be able to.

4 / 15

How many SAE levels of driving automation exist?

3

5

6

7

Fact:
Autonomous vehicles use smart computer systems that learn from millions of driving experiences. This helps them notice things like pedestrians or other cars and make quick, safe decisions — often faster than a human driver.

5 / 15

Which SAE level requires driver supervision at all times?

Level 1

Level 2

Level 3

Level 4

Fact:
AI systems detect when conditions shift outside the ODD and adjust decisions accordingly.

6 / 15

How many SAE levels exist?

Three

Four

Five

Six

Fact:
AI is capable of correctly analyzing and categorizing high quantities of data, such as the ones coming from the vehicle sensors, with great effectivenes when compared to other techniques

7 / 15

What type of AI algorithm is exemplified in Dem3.2 for real-time object detection in camera images?

YOLOv3

U-Net

LSTM

POMDP

Fact:
Software in an autonomous car must manage "mixed-criticality". This means ensuring that vital safety functions (like braking) always have priority and can never be disrupted by comfort functions (like the infotainment system).

8 / 15

What is route planning in automated mobility?

Choosing a path from origin to destination

Painting lane markings

Measuring tire pressure only

Selling vehicle insurance

Fact:
Vehicle management systems rely on timely information about vehicle position, status, and availability to support safe coordination.

9 / 15

What does vehicle access software decide in a digital key system?

Whether a user or device is authorized to unlock or start the vehicle

Which road to build next

How much fuel a country imports

Which traffic law applies abroad

Fact:
Connected vehicle services combine software authorization, positioning, cybersecurity, and user experience design.

10 / 15

What do object-detection algorithms try to find in sensor data?

Relevant objects such as vehicles, pedestrians, cyclists, or obstacles

Radio stations

Fuel prices

Passenger names

Fact:
Object detection and scene understanding turn raw sensor data into information that automated-driving software can use for decisions.

11 / 15

What role does AI play in virtual sensing?

It replaces the need for vehicle hardware

It enables models to infer unmeasured variables from available sensor data

It only controls infotainment systems

It stores historical driving routes

Fact:
AI enables vehicles to interpret complex sensor data and infer missing or unmeasurable variables.

12 / 15

What is the primary role of AI-based perception systems (such as object detection) in lower SAE automation levels (Level 1–2)?

To fully replace the human driver in all driving scenarios

To support driver assistance functions by detecting vehicles, pedestrians, and lanes

To make long-term route planning decisions without human input

To eliminate the need for vehicle sensors

Fact:
At SAE Levels 1–2, AI-based perception helps the driver by recognizing lanes, vehicles, and pedestrians, but the human remains fully responsible for driving decisions.

13 / 15

What is the main goal of a Driver Monitoring System (DMS)?

To replace the human driver entirely

To detect drowsiness, fatigue, and distraction

To improve the vehicle's fuel economy

To provide entertainment for passengers

Fact:
Specialized software algorithms analyze biometric data throughout the day to evaluate a rider's energy level and detect signs of drowsiness or tiredness. These AI-enabled systems facilitate communication between the monitoring device and the vehicle's motor controller to execute preventive actions when needed. While cars are increasingly equipped with systems to detect distraction, the two-wheeled vehicles cannot be automated but can warn the driver in time to prevent accidents.

14 / 15

Which AI technique is commonly used for event-based object detection in autonomous vehicles?

Spiking Neural Network

Convolutional Neural Network (CNN)

Reinforcement Learning Agent

Decision Tree Classifier

Fact:
Spiking Neural Networks (SNNs) are emerging AI technique for event-based vision because they process data as discrete temporal spikes.

15 / 15

What is sensor fusion in automated driving?

Combining data from multiple sensors to form a better understanding of the surroundings

Replacing all sensors with one camera

Using a sensor only while parking

Turning off sensors to save power

Fact:
Sensor fusion helps automated-driving software combine complementary information so that one sensor’s weakness can be balanced by another sensor’s strength.

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Autonomous Vehicles Quiz Game

Autonomy levels & software & AI – Easy

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