Roadside LiDAR Assisted Cooperative Localization for Connected Autonomous Vehicles

TL;DR

This paper proposes a roadside LiDAR and V2I communication system to enhance connected autonomous vehicle localization, especially when high-definition maps are unavailable or insufficient, demonstrating improved accuracy over traditional methods.

Contribution

It introduces a novel roadside LiDAR assisted localization method leveraging V2I communication to improve accuracy without relying on costly high-definition maps.

Findings

Outperforms traditional NDT scan matching in accuracy

Effective in scenarios lacking detailed 3D maps

Enhances safety by improving localization reliability

Abstract

Advancements in LiDAR technology have led to more cost-effective production while simultaneously improving precision and resolution. As a result, LiDAR has become integral to vehicle localization, achieving centimeter-level accuracy through techniques like Normal Distributions Transform (NDT) and other advanced 3D registration algorithms. Nonetheless, these approaches are reliant on high-definition 3D point cloud maps, the creation of which involves significant expenditure. When such maps are unavailable or lack sufficient features for 3D registration algorithms, localization accuracy diminishes, posing a risk to road safety. To address this, we proposed to use LiDAR-equipped roadside unit and Vehicle-to-Infrastructure (V2I) communication to accurately estimate the connected autonomous vehicle's position and help the vehicle when its self-localization is not accurate enough. Our simulation results indicate that this method outperforms traditional NDT scan matching-based approaches in terms of localization accuracy.