Speed directive for Connected Autonomous Vehicles(CAV) on freeways

Connected Autonomous Vehicles (CAV) is happening due to sensors incorporation in all road conditions and make driving judgements, and these sensors must be reliable for the vehicles to be safe. Accelerated devices hold the main segment among entire hindrance recognition devices. Generally, estimated to be built on vehicles more often. To identify obstacles, these sensors analyze ultrasonic emission and reflection data. Using the intrinsic weaknesses in sensors, we developed adaptive attacks using jamming, random spoofing, and spoofing on ultrasonic sensors. By doing this, we were able to a car into stopping when it shouldn't have and let it keep going. It substantiates our assaults using independent devices and mobile automobiles, like a Tesla Model that has Autopilot. Here, results show that occurrences induce blindness and malfunctions in both autonomous vehicles and sensors, which could lead towards crashes. The proposed deuce resistance strategies nearly improve the safety of accelerated devices and CAV with two methods of verifying signals. The suggested verified signals are sensor leveling physical shift authentication and multiple sensor consistency check, which uses multiple sensors to verify signals at the system level.

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Publication Details

Published
2024-08-08
DOI
https://doi.org/10.1109/iccpct61902.2024.10672727
Citations
1
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
Field-Weighted Citation Impact
0.21
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Speed directive for Connected Autonomous Vehicles(CAV) on freeways

A. Rosi, D. Ferlin Deva Shahila, A. Ashwini, Nalini.N et al.
1 citations
Vehicular Ad Hoc Networks (VANETs)
0.21
article

Speed directive for Connected Autonomous Vehicles(CAV) on freeways

A. Rosi, D. Ferlin Deva Shahila, A. Ashwini, Nalini.N, T Vaishnavi, M. Sangeetha Priya
article en
1 citations

Abstract

Connected Autonomous Vehicles (CAV) is happening due to sensors incorporation in all road conditions and make driving judgements, and these sensors must be reliable for the vehicles to be safe. Accelerated devices hold the main segment among entire hindrance recognition devices. Generally, estimated to be built on vehicles more often. To identify obstacles, these sensors analyze ultrasonic emission and reflection data. Using the intrinsic weaknesses in sensors, we developed adaptive attacks using jamming, random spoofing, and spoofing on ultrasonic sensors. By doing this, we were able to a car into stopping when it shouldn't have and let it keep going. It substantiates our assaults using independent devices and mobile automobiles, like a Tesla Model that has Autopilot. Here, results show that occurrences induce blindness and malfunctions in both autonomous vehicles and sensors, which could lead towards crashes. The proposed deuce resistance strategies nearly improve the safety of accelerated devices and CAV with two methods of verifying signals. The suggested verified signals are sensor leveling physical shift authentication and multiple sensor consistency check, which uses multiple sensors to verify signals at the system level.

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), Saveetha University (IN)
Openalex Percentile: Top 48%
Vehicular Ad Hoc Networks (VANETs)
0.21
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