Self-driving cars combine mechanical engineering, electrical engineering, computer science, and physics to move safely without constant human control. They must sense the road, understand the environment, predict what other road users might do, and choose safe actions in real time. This matters because autonomous vehicles could reduce crashes, improve mobility, and make transportation more efficient.
Every decision depends on accurate measurements, fast computation, and careful control of the vehicle.
Key Facts
- Stopping distance = reaction distance + braking distance
- For constant deceleration, v^2 = v0^2 + 2aΔx
- Sensor fusion combines lidar, radar, cameras, GPS, and inertial sensors to estimate the car's surroundings.
- Lidar measures distance using time of flight: distance = cΔt/2, where c is the speed of light.
- Radar estimates relative speed using the Doppler effect, which helps track moving vehicles.
- A control system reduces error by comparing the desired path with the actual path and adjusting steering, braking, or acceleration.
Vocabulary
- Lidar
- Lidar is a sensing method that uses laser pulses to measure distances and build a 3D map of nearby objects.
- Sensor fusion
- Sensor fusion is the process of combining data from multiple sensors to create a more reliable estimate of the environment.
- Perception
- Perception is the software task of identifying lanes, signs, vehicles, pedestrians, and obstacles from sensor data.
- Path planning
- Path planning is the process of choosing a safe and efficient route and motion path for the vehicle to follow.
- Feedback control
- Feedback control uses measurements of the car's actual motion to correct errors in speed, position, and steering.
Common Mistakes to Avoid
- Assuming one sensor is enough. A single camera, radar, or lidar can fail or miss information, so autonomous cars use sensor fusion for redundancy and accuracy.
- Confusing perception with decision making. Detecting a pedestrian is not the same as deciding whether to slow down, stop, or change lanes.
- Ignoring stopping distance at high speed. Braking distance increases strongly with speed, so a car traveling twice as fast needs much more than twice the distance to stop.
- Treating GPS as perfectly accurate. GPS can be blocked or reflected by buildings, so self-driving cars also use maps, wheel sensors, cameras, lidar, radar, and inertial measurement units.
Practice Questions
- 1 A lidar pulse returns to the car after 200 ns. Using c = 3.0 x 10^8 m/s, how far away is the object?
- 2 A self-driving car moves at 20 m/s and brakes with a constant acceleration of -5 m/s^2. How much distance does it need to stop?
- 3 A camera sees a lane marking clearly, but radar detects a large object ahead in heavy rain. Explain why sensor fusion is safer than trusting only the camera.