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A GNSS Integrity Augmentation System for Ground Vehicle Operations

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posted on 2024-11-23, 10:12 authored by Suraj Bijjahalli, Subramanian Ramasamy, Roberto SabatiniRoberto Sabatini
The employment of GNSS for the navigation of autonomous ground vehicles has so far been applied to mining operations in Australia. Autonomous systems enable the development of navigation strategies such as global path-planning and path optimization for vehicle fleets, thereby lowering overall carbon emissions. Furthermore, autonomous ground vehicle operations can significantly improve safety ratings by eliminating human error arising from stress, fatigue and boredom. Widespread use of GNSS-based autonomous vehicles for ground operations is presently hindered by stringent safety regulations. This places strict integrity requirements on GNSS receivers, which must be able to detect GNSS signal errors and faults, and alert the navigation system in a timely manner. An integrity augmentation system is presented in this paper that can detect GNSS error sources and faults, and alert the navigation system of an autonomous ground vehicle in a timely manner. The system is developed by modelling GNSS error sources like antenna masking, signal attenuation and multipath and assigning threshold values for generating integrity alerts. The performance of the system in terms of GNSS fault detection is validated through a realistic simulation in a 3-D virtual ground environment. Trajectories representing the paths followed by vehicles are generated using a dynamic model of a generic fourwheeled ground vehicle. The integrity augmentation system was demonstrated to successfully detect GNSS errors and respond by issuing predictive (caution flags) and reactive (warning flags) in a timely manner for a range of trajectories and maneuvers.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.egypro.2017.03.120
  2. 2.
    ISSN - Is published in 18766102

Journal

Energy Procedia

Volume

110

Start page

149

End page

155

Total pages

7

Publisher

Elsevier BV

Place published

Netherlands

Language

English

Copyright

© 2017 The Authors. Published by Elsevier Ltd.

Notes

This work is licensed under a Creative Commons Attribution 4.0 International License.

Former Identifier

2006073547

Esploro creation date

2020-06-22

Fedora creation date

2017-05-23

Open access

  • Yes

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