Embedded and probabilistic health management for the GPS of autonomous vehicles
Abstract
The aim of this paper is to propose a complementary Health Management module to monitor the GPS accuracy for autonomous vehicles. Based on sensor information, the error causes of GPS can be observed in some specific contexts (urban, climate...). The proposed module relies on a Bayesian Network model that allows to reinforce the belief of GPS failure based on evidence. A hardware/software implementation of the Health Management module is also proposed for real-time and on-line purposes on an embedded platform.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Refraction of the GPS signal in the atmospheric layer is a cause of error in GPS signal.
“In addition to the aforementioned errors, the refraction of the GPS signal in the atmospheric layer was mentioned to be a cause of error in GPS signal [114].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [114]
Cites
(1988) · Cited by 16,582 · see citing works
Modeling and Reasoning with Bayesian Networks
Darwiche, A. Y. (2009) · Cambridge University Press eBooks · doi:10.1017/cbo9780511811357 · Cited by 1,120 · see citing works
R2U2: Monitoring and Diagnosis of Security Threats for Unmanned Aerial Systems
Schumann, J. M. P., Moosbrugger, P., & Rozier, K. Y. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-23820-3_15 · Cited by 73 · see citing works
Software health management with Bayesian networks
Schumann, J. M. P., Mbaya, T., Mengshoel, O. J., Pipatsrisawat, K., Srivastava, A. N., Choi, A., & Darwiche, A. Y. (2013) · Innovations in Systems and Software Engineering · doi:10.1007/s11334-013-0214-y · Cited by 36 · see citing works
FPGA implementation of Bayesian network inference for an embedded diagnosis
Zermani, S., Dezan, C., Chenini, H., Diguet, J.-P., & Euler, R. (2015) · IEEE Conference on Prognostics and Health Management · doi:10.1109/icphm.2015.7245057 · Cited by 31 · see citing works
Self-citationNominal GNSS pseudorange measurement model for vehicular urban applications
Salós, D., Macabiau, C., Martineau, A., et al. (2010) · IEEE/ION Position Location and Navigation Symposium · doi:10.1109/plans.2010.5507319 · Cited by 30 · see citing works
Ricks, B., & Mengshoel, O. J. (2018) · doi:10.1184/r1/6711110 · Cited by 23 · see citing works
A Run-Time Method Based on Observable Data for the Quality Assessment of GNSS Positioning Solutions
Dovis, F., Muhammad, B., Cianca, E., et al. (2015) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2015.2430513 · Cited by 22 · see citing works
Reliable Positioning Domain Computation for Urban Navigation
Drevelle, V., & Bonnifait, P. (2013) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2013.2252058 · Cited by 18 · see citing works
Bayesian network-based framework for the design of reconfigurable health management monitors
Zermani, S., Dezan, C., Euler, R., et al. (2015) · NASA/ESA Conference on Adaptive Hardware and Systems (AHS) · doi:10.1109/ahs.2015.7231163 · Cited by 14 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
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
- Zermani, S., Dezan, C., Hireche, C., Euler, R., & Diguet, J.-P.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Venue
- 2016 5th Mediterranean Conference on Embedded Computing (MECO)
- Publisher
- IEEE
- Published
- 2016-06
- Pages
- 401-404
- OpenAlex
- W2480899904
- Cited by
- 6
- References
- 10
- Citations by year
- 2022: 1 · 2020: 1 · 2019: 2 · 2017: 2
- FWCI
- 3.30
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Mediterranean Conference on Embedded Computing (MECO) (publishedVersion)
- HAL (submittedVersion)
- Funders
- Centre National de la Recherche Scientifique
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › IoT and GPS-based Vehicle Safety Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Engineering and Test Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
- Keywords
- autonomous vehicles, Bayesian networks, probabilistic reasoning, embedded systems, real-time implementation, sensor error detection
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
