Connected and Autonomous Vehicles (CAVs)

Connected vehicle systems provide connectivity among vehicles to enable crash prevention, between vehicles and the infrastructure to enable safety, mobility and environmental benefits; among vehicles, infrastructure, and wireless devices to provide continuous real-time connectivity to all system users. An autonomous vehicle (a.k.a. driverless vehicle, self-driving vehicle, and robotic vehicle) is a vehicle that is capable of sensing its environment and navigating without human input. The potential of CV and AV has been acknowledged with the establishment of ambitious research programs around the globe. Despite the potential vision of CV and AV systems, there are numerous design challenges, including cybersecurity and artificial intelligence, remaining to be addressed before widespread deployment of CV and AV systems.

• Building Trust in Connected and Autonomous Vehicles (TrustCAV), funded by Natural Sciences and Engineering Research Council of Canada (NSERC) CREATE program

News reports about our research on CAVs:

• May 2020, Carleton Story: Driving the Next Generation: Richard Yu Receives Funding to Train Students In Connected and Autonomous Vehicle Technology
• Dec. 2019, Carleton News: Carleton’s Richard Yu Recognized as a Highly Cited Researcher Globally
• Apr. 2019, CTV News: Autonomous Cars Tested against Cyber-Attacks
• Feb. 2019, CBC News: Research Collaboration with BlackBerry/QNX to Develop and Secure Autonomous Vehicles
• Apr. 2018, CTV News: Research on Cybersecurity of Connected/Autonomous Vehicles at Carleton
• Apr. 2018, Ottawa Business Journal: Carleton University, BlackBerry QNX Join Forces to Put Brakes on Cyber Threats to Self-Driving Cars
• Apr. 2018, Carleton Stories: Connected Autonomous Vehicle Research at Carleton
• Jan. 2018, Ingenious Magazine: Connecting and Protecting Canada’s Roadways

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Machine Learning and Embodied Artificial Intelligence

Recent advances in machine learning and AI, exemplified by ChatGPT and Sora, have swept across the globe. redefining the boundaries of what machines can accomplish. These breakthroughs have paved the way for the emergence of embodied AI, where AI systems are given physical forms, such as robots and autonomous vehicles. While existing AI research predominantly focuses on the ``engineering" aspects, there is a notable gap in the ``science" aspects of AI systems. We propose the concept of ``Intropy" to quantify intelligence. By leveraging Intropy-based approaches within machine learning algorithms, we can delve deeper into understanding the cognitive processes of embodied AI systems.

Recent Results:

• F. Richard Yu and A.W. Yu, A Brief History of Intelligence, Springer, ISBN 978-3-031-15950-3, 2023.

Blockchain and Distributed Ledger Technology

Recently, with the tremendous development of crypto-currencies, distributed ledger technology (DLT) (e.g., blockchain) has attracted significant attention. Although DLT has great potential to create new foundations for our economic and social systems, the existing DLT has a number of drawbacks (e.g., scalability) that prevent it from being used as a generic platform for distributed ledger across the globe. We propose a service-oriented blockchain system with virtualization and decoupled management/control and execution. This is a paradigm shift from the existing “blockchain-oriented” DLT systems to next generation“service-oriented” DLT systems. In addition, we present mathematical modeling and optimization for blockchain systems from the aspects of scalability, decentralization, latency and security.

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• F. Richard Yu, Blockchain Technology and Applications - From Theory to Practice, ISBN 978-1729142592, Kindle Direct Publishing, 2019.
• F. Richard Yu, “A Service-Oriented Blockchain System with Virtualization,” Trans. Blockchain Technology and Applications, vol. 1, no. 1, pp. 1-10, 2019.
• F. Richard Yu, J. Liu, Y. He, P. Si, and Y. Zhang, “Virtualization for Distributed Ledger Technology (vDLT),” IEEE Access, vol. 6, pp. 25019-25028, 2018.

Wireless Cyber-Physical Systems

Wireless cyber-physical systems (CPS) are integrations of wireless communication, computation, networking, and physical processes. Examples of wireless CPS include connected and autonomous vehicles, intelligent transportation, communication-based train control (CBTC), industrial Internet, smart grid, etc. CPS integrates the dynamics of the physical processes with those of networking, providing abstractions and modeling, design, and analysis techniques for the integrated whole. Although the layered structure is one of the key reasons behind the success of the Internet, cross-layer/cross-system design is appropriate and may even be necessary in wireless CPS.

Security and Privacy in Networks

Security and privacy are becoming more and more important issues in networks. Two classes of approaches, prevention-based (such as authentication) and detection-based (such as intrusion detection), can be used to protect high security wireless networks. As the front line of defense, user authentication is crucial for integrity, confidentiality and non-repudiation. Moreover, intrusion detection systems (IDSs), serving as the second wall of protection, can effectively help identify malicious activities. In addition, privacy concerns have drawn more and more attentions, involving the right of mandating personal privacy concerning storing, re-purposing, provision to third parties, and displaying of information pertaining to oneself via the network. Many technical challenges remain to be addressed to develop security and privacy schemes in future networks.