How does behavioral planning work in autonomous driving systems?

Behavioral planning makes tactical driving decisions: When to change lanes, whether to yield, how to navigate intersections. Approaches include: Finite State Machines (FSM) with states like lane following, lane change, yield, and transitions based on conditions; rule-based systems encoding traffic laws and driving heuristics; decision trees or behavior trees for structured decision making; and learning-based approaches (reinforcement learning, imitation learning). Planning considers: Other vehicles' predicted behavior, traffic rules, efficiency, safety margins, and passenger comfort. Output is a high-level maneuver directive that motion planning converts to a trajectory. Validation requires extensive scenario testing including edge cases.