How Self-Driving Cars Work? | Tech for Product Managers

Understanding of Self-Driving Car

To understand how self-driving cars work, think of them as having three key abilities:

1. Ability to See
2. Ability to Think
3. Ability to Act

These three pillars — perception, decision-making, and execution — are powered by a combination of sensors, software, and hardware. Let’s break it down.

1. Ability to See??

Before a car can drive itself, it needs to understand its surroundings.

This is where sensors come in.

Self-driving cars use a variety of sensors to gather data from the environment. Each type of sensor has a specific role:

1. LIDAR (Light Detection and Ranging): Think of LIDAR as the car’s laser eyes. It emits beams of light that bounce off objects and return to the sensor, helping the car create a detailed 3D map of its surroundings. LIDAR is especially good at detecting obstacles, pedestrians, and other vehicles — even in the dark.
2. Cameras: Cameras provide visual data, much like human eyes. They help the car recognize traffic lights, road signs, lane markings, and even facial expressions of pedestrians (yes, it’s that advanced). Some self-driving cars have up to 12 cameras for a 360-degree view.
3. Radar: Radar works by sending out radio waves that bounce back when they hit an object. It’s particularly useful for detecting the speed and distance of nearby vehicles, even in poor weather conditions like rain or fog.
4. Ultrasonic Sensors: These sensors, like parking, are often used for close-range detection. They can sense curbs, parked cars, and other objects nearby.
5. GPS and Maps: To know where it’s going, a self-driving car relies on GPS and highly detailed digital maps. These maps include information about road geometry, traffic patterns, and landmarks.

2. Ability to Think?

Once the sensors collect data, the car needs to process it.

This is where Artificial Intelligence (AI) takes the wheel.

The AI system of a self-driving car is like a hyper-intelligent brain that can analyze and interpret massive amounts of information in real time.

Machine Learning: At the heart of self-driving car technology is machine learning, a type of AI that allows the car to learn and improve from experience. For example, the car’s algorithms can recognize patterns, like how pedestrians typically behave at crosswalks or how other drivers merge onto highways.

Neural Networks:Neural networks are inspired by the human brain. They enable the car to make decisions, such as whether to stop, speed up, or change lanes. These networks are trained using millions of miles of driving data, both real and simulated.

Perception Models: AI uses perception models to classify and predict. For instance, it can differentiate between a cyclist and a pedestrian, predict where they’re likely to move, and adjust the car’s behavior accordingly.

3. Acting to Act??

Finally, the car needs to act on the decisions made by its AI. This is where the control system comes into play.

It ensures the car accelerates, brakes, and steers with precision.

Actuators: Actuators are like the car’s muscles. They control the throttle, brakes, and steering to execute the AI’s commands.

Real-Time Processing: Self-driving cars operate in real time, making split-second decisions. For example, if a ball rolls into the street, the car’s system processes this information instantly and stops before a child runs after it.

How Can Self-Driving Car Help Uber?

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