Improving Vehicle Localization Confidence under Different Road Geometries The Ohio State University

Format:

Book

Conference/Event

Author/Creator:

Javed, Nur Uddin, author.

Contributor:

Ahmed, Qadeer

Singh, Yuvraj

Tan, Shengzhe

Conference Name:

WCX SAE World Congress Experience (2025-04-08 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2025

Summary:

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

Notes:

Vendor supplied data

Publisher Number:

2025-01-8043

Access Restriction:

Restricted for use by site license