Roadside-assisted Cooperative Planning using Future Path Sharing for Autonomous Driving

TL;DR

This paper proposes a cooperative path-planning approach for autonomous vehicles at intersections using future path sharing via roadside units, improving safety and efficiency through coordinated action plans.

Contribution

It introduces a novel cooperative path-planning model utilizing future path sharing and RSUs, enhancing intersection safety and efficiency beyond existing real-time sharing methods.

Findings

Vehicles travel more safely with coordinated path planning.

Introduction of RSU reduces intersection crossing time by over 23%.

Simulation results demonstrate improved efficiency and safety.

Abstract

Cooperative intelligent transportation systems (ITS) are used by autonomous vehicles to communicate with surrounding autonomous vehicles and roadside units (RSU). Current C-ITS applications focus primarily on real-time information sharing, such as cooperative perception. In addition to real-time information sharing, self-driving cars need to coordinate their action plans to achieve higher safety and efficiency. For this reason, this study defines a vehicle's future action plan/path and designs a cooperative path-planning model at intersections using future path sharing based on the future path information of multiple vehicles. The notion is that when the RSU detects a potential conflict of vehicle paths or an acceleration opportunity according to the shared future paths, it will generate a coordinated path update that adjusts the speeds of the vehicles. We implemented the proposed method using the open-source Autoware autonomous driving software and evaluated it with the LGSVL autonomous vehicle simulator. We conducted simulation experiments with two vehicles at a blind intersection scenario, finding that each car can travel safely and more efficiently by planning a path that reflects the action plans of all vehicles involved. The time consumed by introducing the RSU is 23.0 % and 28.1 % shorter than that of the stand-alone autonomous driving case at the intersection.