A Look at Motion Planning for Autonomous Vehicles at an Intersection

TL;DR

This paper reviews current approaches to motion planning for autonomous vehicles at intersections, analyzing their challenges, discrepancies, and open issues to guide future research and benchmarking efforts.

Contribution

It provides a comprehensive analysis of existing intersection management methods, highlighting discrepancies, critical factors, and open issues in autonomous vehicle trajectory planning.

Findings

Identifies key challenges in autonomous intersection management.

Highlights discrepancies and gaps in current solutions.

Proposes factors for benchmarking intersection algorithms.

Abstract

Autonomous Vehicles are currently being tested in a variety of scenarios. As we move towards Autonomous Vehicles, how should intersections look? To answer that question, we break down an intersection management into the different conundrums and scenarios involved in the trajectory planning and current approaches to solve them. Then, a brief analysis of current works in autonomous intersection is conducted. With a critical eye, we try to delve into the discrepancies of existing solutions while presenting some critical and important factors that have been addressed. Furthermore, open issues that have to be addressed are also emphasized. We also try to answer the question of how to benchmark intersection management algorithms by providing some factors that impact autonomous navigation at intersection.