Mathematical Approach on Multi-Sensor Error Propagation for Ego-Vehicle Localization

Seok-Won Ki and Jong-Hoon Won

Abstract: Autonomous driving technology is playing an important role in making roads safer and more efficient without driver intervention. One of the key elements of the autonomous driving technology is accurate localization, where determining the accurate localization of a vehicle in complex environments such as an urban area is still a major challenge. To overcome this challenge, multiple sensors such as Global Navigation Satellite System (GNSS), Inertial Measurement Unit (IMU), Light Detection and Ranging (LiDAR), and Vehicle-to-Everything (V2X) are widely employed to provide essential information for the localization of autonomous vehicle. However, each of these sensors has its own limitations and is sensitive to the uncertain noises that can occur in real-world environments. Therefore, improving localization accuracy by incorporating multiple sensors and reducing uncertainty is essential. The objective of this paper is to propose multi-sensor localization system utilizing V2X, IMU, and LiDAR and investigate the error propagation in the proposed localization system. To this end, this paper analyzes the impact of errors in each sensor on the overall multi-sensor localization system. The feasibility of the proposed error propagation approach is validated through experimental simulation tests.
Published in: Proceedings of the ION 2024 Pacific PNT Meeting
April 15 - 18, 2024
Hilton Waikiki Beach
Honolulu, Hawaii
Pages: 455 - 462
Cite this article: Ki, Seok-Won, Won, Jong-Hoon, "Mathematical Approach on Multi-Sensor Error Propagation for Ego-Vehicle Localization," Proceedings of the ION 2024 Pacific PNT Meeting, Honolulu, Hawaii, April 2024, pp. 455-462.
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