Connected and Autonomous Vehicles (CAVs)
- Building Trust in Connected and Autonomous Vehicles (TrustCAV), funded by Natural Sciences and Engineering Research Council of Canada (NSERC) CREATE program
- 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
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.
News reports about our research on CAVs:
Machine Learning and Artificial Intelligence
- F. Richard Yu, ``From Information Networking to Intelligence Networking: Motivations, Scenarios, and Challenges," IEEE Network, Apr. 2021, accepted.
Although recent successes based on deep learning have boosted a new wave of interest in machine learning and AI, it is well believed that AI remains far from human intelligence, which requires a lot less datasets and is much more flexible when adapting to new environments. According to the Big History Project, the unique collective learning capability of humans enables us to share intelligence efficiently. In our research, we envision that the next paradigm could be intelligence networking, which will enable intelligence to be easily obtained, like matter, energy, and information.
Blockchain and Distributed Ledger Technology
- 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.
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.
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.