An overview of development GPS navigation for autonomous car
Abstract
An autonomous car navigation system based on Global Positioning System (GPS) is a new and promising technology, which uses real time geographical data received from several GPS satellites to calculate longitude, latitude, speed and course to help navigate a car. The goal of the project is to make an auto-navigational car model that can route through known or pre-programmed co-ordinates autonomously without any control by human. It is designed to demonstrate the feasibility of using a low-cost strap-down inertial measurement unit (IMU) to navigate between intermittent GPS fixes. The present hardware consists of a GPS receiver, IMU, compass and a data processing computer. This research paper demonstrates a prototype development of autonomous car to enable the aerial vehicle accomplish the required autonomy and maintain satisfactory automated driving operation. Design objectives include simplicity, robustness, versatility and improved operational utility. The driverless car features an advanced, highly autonomous drive control system with an anti-drift from its course algorithms. The discovery of interacting hardware and software had led to breakthrough improvements in the efficiency of maintaining planned route on the track.
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GPS algorithms are preferably applied on prototypes due to the involved damage in testing developed GPS algorithms.
“Due to the involved damage in testing the developed GPS algorithms, researchers prefer applying their proposed methodologies on prototypes; for example, Wan Rahiman et al. tested their proposed algorithm on a prototype vehicle that reaches its destination in three steps, using input from GPS [116].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [116]
The major drawback of GPS for AVs is degradation in accuracy when there is no direct line of sight between satellite and vehicle, e.g., inside a tunnel or near tall buildings.
“The major drawback of GPS for AVs is degradation in its accuracy when there is no direct line of sight between satellite (transmitter) and vehicle (receiver), e.g., inside a tunnel or near tall buildings”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [116]
Cites
Introduction to GPS: The Global Positioning System
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Hofmann-Wellenhof, B., Lichtenegger, H., & Collins, J. J. (2001) · Springer eBooks · doi:10.1007/978-3-7091-6199-9 · Cited by 577 · see citing works
GPS/dead reckoning for vehicle tracking in the "urban canyon" environment
Vicek, C., McLain, P., & Murphy, M. (1993) · Vehicle Navigation and Information Systems Conference (VNIS) · doi:10.1109/vnis.1993.585671 · Cited by 36 · see citing works
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Driving a car using reflexive fuzzy behaviors
Pin, F. G., & Watanabe, Y. (2002) · Proceedings of ... IEEE International Conference on Fuzzy Systems · doi:10.1109/fuzzy.1993.327602 · Cited by 19 · see citing works
Terrestrial navigation based on integrated GPS and INS
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Sensor Technology in Autonomous Vehicles : A review
Campbell, S., O'Mahony, N., Krpalcova, L., Riordan, D., Walsh, J., Murphy, A., & Ryan, C. (2018) · 2018 29th Irish Signals and Systems Conference (ISSC) · doi:10.1109/issc.2018.8585340 · Cited by 241 · see citing works
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
Kochańska, J., Burduk, A., Markowski, M., Kłusek, A., & Wojciechowska, M. (2023) · Sustainability · doi:10.3390/su15021113 · Cited by 15 · see citing works
- Authors
- Rahiman, W., & Zainal, Z.
- Affiliations
- Universiti Sains Malaysia (MY)
- ORCID
- Rahiman, Wan
- Venue
- 2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA)
- Publisher
- IEEE
- Published
- 2013-06
- Pages
- 1112-1118
- OpenAlex
- W2050936627
- Cited by
- 67
- References
- 6
- Citations by year
- 2025: 8 · 2024: 10 · 2023: 6 · 2022: 13 · 2021: 4 · 2020: 9 · 2019: 4 · 2018: 4 · 2017: 3 · 2016: 4 · 2015: 1 · 2014: 1
- FWCI
- 3.53
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Conference on Industrial Electronics and Applications (ICIEA) (publishedVersion)
- Funders
- Universiti Sains Malaysia
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
- Keywords
- autonomous vehicles, GPS navigation, dead reckoning, path following
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