Sensor Technology in Autonomous Vehicles : A review
Abstract
This paper will review the main sensor technologies used to create an autonomous vehicle. Sensors are key components for all types of autonomous vehicles because they can provide the data required to perceive the surrounding environment and therefore aid the decision-making process. This paper explains how each of these sensors work, their advantages and disadvantages and how sensor fusion techniques can be utilised to create a more optimum and efficient system for autonomous vehicles.
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The main obstacle for the automotive RADAR system is to yield high-resolution information in an environment that incorporates several dynamic objects in an immensely clustered automotive scene with a high update rate.
“However, the main obstacle for the automotive RADAR system is to yield high-resolution information in an environment that incorporates several dynamic objects in an immensely clustered automotive scene with a high update rate [82,83].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [83]
Cites
Stanley: The robot that won the DARPA Grand Challenge
Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Hoffmann, G., et al. (2006) · Journal of Field Robotics · doi:10.1002/rob.20147 · Cited by 2,237 · see citing works
Autonomous driving in urban environments: Boss and the Urban Challenge
Urmson, C., Anhalt, J., Bagnell, D., Baker, C., Bittner, R., Clark, M. N., Dolan, J., Duggins, D., Galatali, T., Geyer, C., et al. (2008) · Journal of Field Robotics · doi:10.1002/rob.20255 · Cited by 1,555 · see citing works
(2001) · doi:10.1201/9781420038545 · Cited by 397 · see citing works
A Fully-Integrated 77-GHz FMCW Radar Transceiver in 65-nm CMOS Technology
Lee, J., Li, Y.-A., Hung, M.-H., et al. (2010) · IEEE Journal of Solid-State Circuits · doi:10.1109/jssc.2010.2075250 · Cited by 345 · see citing works
Autonomous Ground Vehicles—Concepts and a Path to the Future
Luettel, T., Himmelsbach, M., & Wuensche, H. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2189803 · Cited by 339 · see citing works
Bimbraw, K. (2015) · International Conference on Informatics in Control, Automation and Robotics (ICINCO) · doi:10.5220/0005540501910198 · Cited by 324 · see citing works
Stanley: The Robot That Won the DARPA Grand Challenge
Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J. R., Fong, P., Gale, J., Halpenny, M., Hoffmann, G. M., et al. (2007) · Springer tracts in advanced robotics · doi:10.1007/978-3-540-73429-1_1 · Cited by 237 · see citing works
Parking space detection using ultrasonic sensor in parking assistance system
Park, W.-J., Kim, B.-S., Seo, D.-E., Kim, D.-S., & Lee, K.-H. (2008) · 2008 IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2008.4621296 · Cited by 122 · see citing works
Radar waveform for automotive radar systems and applications
Rohling, H., & Moller, C. (2008) · Proceedings of the IEEE National Radar Conference · doi:10.1109/radar.2008.4721121 · Cited by 114 · see citing works
An overview of development GPS navigation for autonomous car
Rahiman, W., & Zainal, Z. (2013) · 2013 IEEE 8th Conference on Industrial Electronics and Applications (ICIEA) · doi:10.1109/iciea.2013.6566533 · Cited by 67 · see citing works
Indoor robot localization by RSSI/IMU sensor fusion
Malyavej, V., Kumkeaw, W., & Aorpimai, M. (2013) · International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) · doi:10.1109/ecticon.2013.6559517 · Cited by 63 · see citing works
Wang, S., Deng, Z., & Yin, G. (2016) · Sensors · doi:10.3390/s16030280 · Cited by 50 · see citing works
Real-time distance measurement using a modified camera
Liu, X., Qin, T. L., Wanchun, C., et al. (2010) · IEEE Sensors Applications Symposium (SAS) · doi:10.1109/sas.2010.5439423 · Cited by 24 · see citing works
Fusing vision and odometry for accurate indoor robot localization
Bischoff, B., Nguyen-Tuong, D., Streichert, F., et al. (2012) · International Conference on Control, Automation, Robotics and Vision (ICARCV) · doi:10.1109/icarcv.2012.6485183 · Cited by 23 · see citing works
Comparison of two sensor data fusion methods in a tightly coupled UWB/IMU 3-D localization system
Miraglia, G., Maleki, K. N., & Hook, L. R. (2017) · International Conference on Engineering, Technology and Innovation (ICE/ITMC) · doi:10.1109/ice.2017.8279941 · Cited by 21 · see citing works
Jeon, D., Choi, H., & Kim, J. (2016) · International Conference on Ubiquitous Robots and Ambient Intelligence · doi:10.1109/urai.2016.7734018 · Cited by 17 · see citing works
Suganuma, N., & Uozumi, T. (2012) · Society of Instrument and Control Engineers of Japan · Cited by 16 · see citing works
Intelligent vehicle localization using GPS, compass, and machine vision
Limsoonthrakul, S., Dailey, M. N., & Parnichkun, M. (2009) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2009.5354042 · Cited by 14 · see citing works
Perception in autonomous ground vehicles
Ilas, C. (2013) · International Conference on Electronics, Computers and Artificial Intelligence (ECAI) · doi:10.1109/ecai.2013.6636180 · Cited by 9 · see citing works
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Li, H., Bin Kaleem, M., Liu, Z., Wu, Y., Liu, W., & Huang, Z. (2023) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2023.100128 · Cited by 95 · 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
- Campbell, S., O'Mahony, N., Krpalcova, L., Riordan, D., Walsh, J., Murphy, A., & Ryan, C.
- Affiliations
- Munster Technological University (IE)
- University of Limerick (IE)
- Venue
- 2018 29th Irish Signals and Systems Conference (ISSC)
- Publisher
- IEEE
- Published
- 2018-06
- Pages
- 1-4
- OpenAlex
- W2908305534
- Cited by
- 241
- References
- 19
- Citations by year
- 2026: 4 · 2025: 26 · 2024: 39 · 2023: 57 · 2022: 55 · 2021: 38 · 2020: 18 · 2019: 4
- FWCI
- 15.38
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Irish Signals and Systems Conference (publishedVersion)
- Funders
- Science Foundation Ireland
- European Regional Development Fund
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Keywords
- autonomous vehicles, automotive sensors, sensor fusion, environmental perception, sensor technology, decision-making
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