A Multi-sensor Autonomous Integrity Monitoring Approach for Railway and Driver-less Cars

Alessandro Neri, Pietro Salvatori, Cosimo Stallo, and Andrea Coluccia

Abstract: Autonomous driving technology requires high accuracy and high integrity position and navigation. No individual technology can currently meet these requirements anywhere, anytime and under any condition. Sensor fusion is considered as the go-to-solution for the development of fully autonomous driving technology. GNSS is an element of a sensor fusion based navigation system that includes lidars/radars, inertial sensors and cameras. This work shows as the comparison between the speed’s vehicle calculated by odometer and one estimated by GNSS receiver installed on board of train through Doppler is an effective means to face multipath in railway environment, even when just one receiver is available. Moreover, the georeferenced knowledge of the railway is not essential when Doppler are compared, while the pseudorange comparison requires a guess of the baseline between the receivers. Moreover, the proposed multipath detection and exclusion method is fully compatible with other techniques for multipath mitigation. The outcomes of this work, undertaken for railway scenarios, can be partly exploited in driver-less car applications thanks to the analogies between these two transportation sectors.
Published in: Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018)
September 24 - 28, 2018
Hyatt Regency Miami
Miami, Florida
Pages: 1605 - 1621
Cite this article: Neri, Alessandro, Salvatori, Pietro, Stallo, Cosimo, Coluccia, Andrea, "A Multi-sensor Autonomous Integrity Monitoring Approach for Railway and Driver-less Cars," Proceedings of the 31st International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2018), Miami, Florida, September 2018, pp. 1605-1621. https://doi.org/10.33012/2018.15845
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