Grants and Contributions:

Title:

A High-Fidelity Virtual Platform to Assess Certified Robustness of Deep Learning and Deep Reinforcement Learning Algorithms for Autonomous Driving

Agreement Number:

1016395

Agreement Value:

$121,220.00

Agreement Date:

Mar 22, 2024 - Mar 31, 2026

Description:

In the realm of Autonomous Driving (AD), the application of Deep Learning (DL) and Deep Reinforcement Learning (DRL) has been pivotal. However, ensuring the robustness of these technologies against cyber threats remains a critical challenge. This project proposes the development of a high-fidelity virtual platform to assess the certified robustness of DL and DRL algorithms in AD, focusing on cybersecurity vulnerabilities. The proposed framework leverages the capabilities of the Carla open-source simulator to create a realistic virtual environment that mimics real-world cyberattack scenarios on AD systems. This project will have three phases: the first phase will involve identifying and training baseline DL/DRL algorithms for AD and selecting the state-of-the-art methods suitable for various AD scenarios. In the second phase, the focus will be on developing a virtual platform prototype capable of accurately simulating diverse cyberattack scenarios, thereby providing a testbed for evaluating the resilience of DL/DRL-based AVs. The final phase involves training certified defense algorithms designed explicitly for DL/DRLbased AV systems, emphasizing their optimization for AD requirements and testing against a spectrum of cyber threats.

Organization:

National Research Council Canada

Expected Results:

In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.

Location:

Waterloo, Ontario, CA N2L 3G1

Reference Number:

172-2023-2024-Q4-1016395

Agreement Type:

Grant

Report Type:

Grants and Contributions

Recipient Business Number:

119260685

Recipient Type:

Academia

Recipient's Legal Name:

University of Waterloo

Federal Riding Name:

Waterloo

Federal Riding Number:

35112

Program:

Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives

Program Purpose:

Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.

NAICS Code:

541710 - R&D in the physical, engineering and life sciences