Autonomous vehicle ultrasonic sensor vulnerability and impact assessment
Open accessAbstract
Vehicles today are relying more on technologies to bring about fully autonomous features. The conventional wirings within are being simplified into a network of electronic components, and this network is controlled via advanced sensing of the environment to make decisions in real-time. However, with the heavy reliance on the sensor readings, any inaccurate reading from the sensors could result in decisions that may cause life-threatening incidents. As such, this research focuses on the in-depth assessment of potential vulnerabilities of an important and commonly used obstacle sensing device, which is the ultrasonic sensor, in modern as well as autonomous vehicles. This research will help bring awareness to the car manufacturers and AV researchers so as to mitigate such issues.
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Ultrasonic sensors have interference due to noise and blind zones in close proximity, which can lead to inaccurate readings.
“On the other hand, ultrasonic sensors have interference due to noise and blind zones in close proximity, which can lead to inaccurate readings [27].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [27]
Cites
Hoppe, T., Kiltz, S., & Dittmann, J. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-87698-4_21 · Cited by 277 · see citing works
Adventures in Automotive Networks and Control Units
Miller, C., & Valasek, C. (2013) · TIB KMO / FLOWWORKS GmbH · doi:10.5446/38906 · Cited by 254 · see citing works
Autonomous Vehicle Security: A Taxonomy of Attacks and Defences
Thing, V. L. L., & Wu, J. (2016) · IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) · doi:10.1109/ithings-greencom-cpscom-smartdata.2016.52 · Cited by 177 · see citing works
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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
- Lim, B. S., Keoh, S. L., & Thing, V. L. L.
- Affiliations
- University of Glasgow (GB)
- Agency for Science, Technology and Research (SG)
- Venue
- 2018 IEEE 4th World Forum on Internet of Things (WF-IoT)
- Publisher
- IEEE
- Published
- 2018-02
- Pages
- 231-236
- OpenAlex
- W2786080675
- Cited by
- 76
- References
- 3
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 10 · 2023: 13 · 2022: 15 · 2021: 12 · 2020: 6 · 2019: 4 · 2018: 1
- FWCI
- 6.15
- Type
- conference paper
- Language
- en
- Open access
- green
- eprints.gla.ac.uk
- Licence
- cc-by-sa
- Locations
- IEEE World Forum on Internet of Things (WF-IoT) (publishedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Safety Systems Engineering in Autonomy
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Keywords
- autonomous vehicles, ultrasonic sensors, obstacle detection, sensor faults, impact assessment, sensor reliability, vehicle safety
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