A GNSS Integrity Augmentation System for Ground Vehicle Operations
Open accessAbstract
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 four-wheeled 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.
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Bijjahalli et al. presented a hierarchical approach at component level along with hybrid Bayesian networks for detection of a fault in GPS sensors, particularly multipath or antenna masking problems for GPS.
“Bijjahalli et al. [129] presented a hierarchical approach at a component level along with hybrid Bayesian networks for the detection of a fault in GPS sensors, particularly multipath or antenna masking problems for GPS.”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [129]
The Introduction and Section 2 describe a GNSS integrity system for ground vehicles that detects faults associated with multipath and antenna masking. They do not describe a hierarchical component-level approach or hybrid Bayesian networks; the paper instead describes modelling error sources and generating integrity alerts. Page numbers are unavailable in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredThe GPS monitor shown in Figure 13 takes care of the sensor's RTK correction status, the number of active satellites, and the covariance of data provided by the sensor.
“The GPS monitor shown in Figure 13 takes care of the sensor's real-time kinematic (RTK) correction status, the number of active satellites, and the covariance of data provided by the sensor.”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [129]
Section 4 (Integrity Thresholds; page unavailable) says the system uses the number of visible satellites to trigger antenna-masking alerts, supporting the satellite-count part. Our copy does not describe a GPS monitor that checks RTK correction status or sensor-data covariance, and its listed figures do not include Figure 13. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe proposed method deals with GPS issues, such as multipath of signal, complete loss of signal, and antenna masking.
“The proposed method deals with GPS issues, such as multipath of signal, complete loss of signal, and antenna masking.”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [129]
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Cited by
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Raouf, I., Khan, A., Khalid, S., Sohail, M., Azad, M. M., & Kim, H. S. (2022) · Mathematics · doi:10.3390/math10183233 · Cited by 41 · see citing works
- Authors
- Bijjahalli, S., Ramasamy, S., & Sabatini, R.
- Affiliations
- RMIT University (AU)
- Corresponding author
- Bijjahalli, Suraj
- Venue
- Energy Procedia
- Publisher
- Elsevier BV
- Published
- 2017-03
- Volume
- 110
- Pages
- 149-155
- ISSN
- 1876-6102 (ISSN-L)
- OpenAlex
- W2605902880
- Cited by
- 6
- References
- 11
- Citations by year
- 2023: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 1
- FWCI
- 0.96
- Type
- conference paper
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Energy Procedia (publishedVersion, cc-by-nc-nd)
- RMIT Research Repository (RMIT University Library) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › GNSS positioning and interference
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Engineering › Mechanical Engineering › IoT and GPS-based Vehicle Safety Systems
- Keywords
- autonomous ground vehicles, signal attenuation, multipath propagation, mining operations, vehicle trajectory simulation, autonomous vehicle safety
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