The transport sector is experiencing a fast and revolutionary development, moving towards the deployment of autonomous vehicles. Thus, the accuracy of the position information and the integrity of the navigation system have become key factors. In this paper, we address the problem of the enhancement of the integrity of the position provided by a Global Navigation Satellite System receiver by exploiting sensor fusion. To this aim, we estimate the lateral offset and heading of the vehicle with respect to a georeferenced roadway centerline from the images supplied by an on-board camera. Moreover, we perform integrity monitoring based on the implementation of the Solution Separation in the parity space. The numerical results indicate that the use of sensor fusion and digital map allows to attain a longitudinal Protection Level reduction with respect to the case in which sensor fusion is not exploited. More specifically, a decrease of about 70% is achieved when a single constellation is used, while reduction is less relevant, about 15%, when two constellations are employed.

Baldoni, S., Battisti, F., Brizzi, M., Neri, A. (2022). GNSS-Imaging Data Fusion for Integrity Enhancement in Autonomous Vehicles. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1-1 [10.1109/TAES.2022.3165771].

GNSS-Imaging Data Fusion for Integrity Enhancement in Autonomous Vehicles

Baldoni S.;Brizzi M.;Neri A.
2022

Abstract

The transport sector is experiencing a fast and revolutionary development, moving towards the deployment of autonomous vehicles. Thus, the accuracy of the position information and the integrity of the navigation system have become key factors. In this paper, we address the problem of the enhancement of the integrity of the position provided by a Global Navigation Satellite System receiver by exploiting sensor fusion. To this aim, we estimate the lateral offset and heading of the vehicle with respect to a georeferenced roadway centerline from the images supplied by an on-board camera. Moreover, we perform integrity monitoring based on the implementation of the Solution Separation in the parity space. The numerical results indicate that the use of sensor fusion and digital map allows to attain a longitudinal Protection Level reduction with respect to the case in which sensor fusion is not exploited. More specifically, a decrease of about 70% is achieved when a single constellation is used, while reduction is less relevant, about 15%, when two constellations are employed.
Baldoni, S., Battisti, F., Brizzi, M., Neri, A. (2022). GNSS-Imaging Data Fusion for Integrity Enhancement in Autonomous Vehicles. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1-1 [10.1109/TAES.2022.3165771].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/404408
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