Improving Vehicle Localization Confidence under Different Road Geometries

2025-01-8043

04/01/2025

Features
Event
WCX SAE World Congress Experience
Authors Abstract
Content
A significant challenge to the scalability of automated driving systems is the potential unavailability of GPS information for localization. To address this issue, a methodology using a static 2D map of road and lane geometry and vehicle on board sensors data is proposed to ensure reliable localization and navigation for automated vehicles in GPS-denied situations. In this study, a dead reckoning system based on vehicle kinematics is implemented by using onboard sensor data from the vehicle's Controller Area Network (CAN). However, the kinematic dead reckoning estimate has error accumulation, the drift in the dead reckoning position estimate is eliminated by using an arc-length based map matching approach. This innovative approach was tested and validated at various safety-critical intersection scenarios, including four-way intersection, roundabout, slip-lane intersection, and curved road. This approach ensures the continuous and reliable localization of automated vehicles, thereby significantly enhancing their safety and operational reliability in environments with compromised or unavailable GPS signals. The reliability of the map matching approach is quantified by calculating the 95% confidence intervals of error for various scenarios.
Meta TagsDetails
DOI
https://doi.org/10.4271/2025-01-8043
Pages
12
Citation
Javed, N., Singh, Y., Tan, S., and Ahmed, Q., "Improving Vehicle Localization Confidence under Different Road Geometries," SAE Technical Paper 2025-01-8043, 2025, https://doi.org/10.4271/2025-01-8043.
Additional Details
Publisher
Published
Apr 01
Product Code
2025-01-8043
Content Type
Technical Paper
Language
English