Integrated Planner for Autonomous Driving in Urban Environments Including Driving Intention Estimation

Abstract

Thousands are killed every day in traffic accidents, and drivers are mostly to blame. Autonomous driving technology is the ultimate technological solution to this problem. There are still many unresolved problems with autonomous driving technology, such as navigating complex traffic situations. One of the reasons is detecting other drivers’ intentions. Planning, which determines the movement of autonomous vehicles, is the cornerstone of autonomous agent navigation. Planning applications consist of multiple modules with different interfaces. Another challenge is the lack of open-source planning projects that allow cooperation between development teams globally. In this chapter, I will introduce two approaches to the planning problem. The first is developing of an open-source, integrated planner for autonomous navigation called Open Planner. It is composed of a global path planner, intention predictor, local path planner, and behavior planner. The second is a novel technique for estimating the intention and trajectory probabilities of surrounding vehicles, which enables long-term planning and reliable decision-making. Evaluation was achieved using simulation and field experimentation.