Introduction to Path Planning Algorithms
Path planning is a critical component in self-driving cars, enabling the vehicle to generate safe and feasible trajectories from a starting point to a goal while avoiding obstacles. This knowledge point focuses on three key algorithms: A* search, Rapidly-exploring Random Tree (RRT), and lattice planning. These methods build on map representations (prerequisite: map-representation-types) like occupancy grids or vector maps to navigate complex environments.
Why these algorithms? They balance computational efficiency, optimality, and adaptability to dynamic scenarios in autonomous driving.
- A* search provides optimal paths in structured environments.
- RRT excels in high-dimensional spaces with obstacles.
- Lattice planning generates smooth, drivable trajectories.
In self-driving cars, path planning integrates with decision making to handle traffic rules and pedestrian avoidance, ensuring collision-free motion.