A Review of Motion Planning Techniques for Automated Vehicles

Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. However, research challenges such as navigation in urban dynamic environments with obstacle avoidance capabilities, i.e., vulnerable road users (VRU) and vehicles, and cooperative maneuvers among automated and semi-automated vehicles still need further efforts for a real environment implementation. This paper presents a review of motion planning techniques implemented in the intelligent vehicles literature. A description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is also presented. Relevant works in the overtaking and obstacle avoidance maneuvers are presented, allowing the understanding of the gaps and challenges to be addressed in the next years. Finally, an overview of future research direction and applications is given.

I. Introduction

The application of intelligent transportation systems is significantly aiding drivers, reducing some driving-associated tedious tasks. Specifically, highway driving has become safer thanks to the development of the Cruise Control (CC), Adaptive CC (ACC) and, lately, the Cooperative ACC (CACC) where both longitudinal actuators, throttle and brake pedals, are controlled using a pre-defined gap with the preceding vehicle [1]. For urban environments, systems like emergency braking with assistance of active suspension [2], automatic parking [3] or blind angle vehicle detection [4] are also contributing toward a safer driving in populated areas.