A software Tool for Securing Deep Learning against Adversarial Attacks for CAVs
The scope of this project is to realize a technology transfer of previously developed adversarial attack resilient perception algorithm for autonomous navigation in connected and automated vehicles. The project will attain its objectives by developing a graphical user interface (GUI) designed for the automatic generation of a robust perception algorithm. This involves utilizing a baseline perception neural network and offering options for training and evaluation using various publicly available image datasets. Furthermore, the initiative includes training students on the utilization of the developed GUI, aiming to cultivate a generation of proficient individuals poised to contribute to the advancement of the United States Department of Transportation (USDOT) and society as a whole. Practical applications and understanding of the proposed technology will be demonstrated through workshops, employing an autonomous F1/10 car testbed that emulates a Connected and Autonomous Vehicle (CAV) perception module. The technology’s viability will be showcased by implementing it on an autonomous vehicle within the AVL DrivingCube SCENIUS at CU-ICAR, highlighting its real-world applicability and potential impact on autonomous vehicle technology.
Language
- English
Project
- Status: Active
- Funding: $186260
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Contract Numbers:
69A3551747117
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 1600 Harden Street
Columbia, South Carolina United States 29204Clemson University
216 Lowry Hall
Clemson, SC, SC United States 29634 -
Managing Organizations:
Center for Connected Multimodal Mobility
Clemson University
Clemson, SC United States 29634 -
Performing Organizations:
Clemson University
216 Lowry Hall
Clemson, SC, SC United States 29634 1600 Harden Street
Columbia, South Carolina United States 29204 -
Principal Investigators:
Pisu, Pierluigi
- Start Date: 20231001
- Expected Completion Date: 20240930
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Computer security; Connected vehicles; Education and training methods; Graphical user interfaces; Machine learning; Software
- Subject Areas: Data and Information Technology; Education and Training; Highways; Security and Emergencies; Vehicles and Equipment;
Filing Info
- Accession Number: 01907175
- Record Type: Research project
- Source Agency: Center for Connected Multimodal Mobility
- Contract Numbers: 69A3551747117
- Files: UTC, RIP
- Created Date: Feb 6 2024 8:12PM