Lane detection aided online dead reckoning for gnss denied environments

7Citations
Citations of this article
13Readers
Mendeley users who have this article in their library.

Abstract

With the emerging interest of autonomous vehicles (AV), the performance and reliability of the land vehicle navigation are also becoming important. Generally, the navigation system for passenger car has been heavily relied on the existing Global Navigation Satellite System (GNSS) in recent decades. However, there are many cases in real world driving where the satellite signals are challenged; for example, urban streets with buildings, tunnels, or even underpasses. In this paper, we propose a novel method for simultaneous vehicle dead reckoning, based on the lane detection model in GNSS-denied situations. The proposed method fuses the Inertial Navigation System (INS) with learning-based lane detection model to estimate the global position of vehicle, and effectively bounds the error drift compared to standalone INS. The integration of INS and lane model is accomplished by UKF to minimize linearization errors and computing time. The proposed method is evaluated through the real-vehicle experiments on highway driving, and the comparative discussions for other dead-reckoning algorithms with the same system configuration are presented.

Cite

CITATION STYLE

APA

Jeon, J., Hwang, Y., Jeong, Y., Park, S., Kweon, I. S., & Choi, S. B. (2021). Lane detection aided online dead reckoning for gnss denied environments. Sensors, 21(20). https://doi.org/10.3390/s21206805

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free