> For the complete documentation index, see [llms.txt](https://rocape.gitbook.io/selfdrivingen/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://rocape.gitbook.io/selfdrivingen/chap7.md).

# CHAPTER 7 Getting started with Autonomous Driving Planning

This chapter will focus on the planning layer of autonomous vehicle systems which consists of three layers: Task planning, Behavior planning and Motion planning. Task planning is also called as path planning, in task planning, A\* algorithm as a discrete space search algorithm is primarily used to solve the problem of optimal path search in discrete space. Behavior planning is a core part of behavior planning for autonomous vehicle systems. The Finite-State Machine (FSM) and Hierarchical Finite-State Machine are often used to design a behavioral decision model. In order to make the motion planning easier to understand, a series methods of spline interpolation will be illustrated.

**Representation of a directed graph**

![image-20221003004557614](/files/kHrsAxQHHnbqLSAsJlri)

**A grid is a directed graph**

![image-20221003004623276](/files/6ykYvmgFlqW7WAeYZIa3)

**Breadth-First Algorithm (BFS)**

![image-20221003004645332](/files/R3dBFhD6ChlFheWzLTnV)

**\[TO DO: The detail of the methods]**