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Autonomous Vehicles and AI

Definition

Autonomous-vehicle systems combine sensors, perception, prediction, planning and control. Their safety is a property of the complete system, not a single neural network.

What is an autonomous vehicle system?

An autonomous-driving system combines sensors such as cameras, radar or lidar with software for perception, localization, prediction, planning and vehicle control.

What AI does inside the stack

Machine-learning models identify lanes, objects, road signs and other vehicles and may help predict how the scene will change. Planning software then decides a safe path, while control software turns that plan into steering, braking and acceleration commands.

Why one model is not the whole car

Vehicle safety depends on sensor coverage, mapping, redundancy, control, validation and fallback behavior as well as AI perception. A high benchmark score on object detection does not by itself demonstrate safe autonomous driving.

Related terms, defined

Reference guide and primary sources

Wikipedia is used here as a terminology and history reference guide. Current model versions, institutional statistics and product-specific claims are also linked to first-party or institutional sources because those details can change faster than encyclopedia articles.