Intelligent Wireless Network System Silicon Design for Vehicle to Vehicle and AI/ML Cloud Communication with Enhanced Safety and Security Capability
Keywords:
Artificial Intelligence, Connected, Safety, Security, Silicon design, Vehicle, Wireless networkAbstract
The advancement of intelligent, wireless, connected, and autonomous vehicles has necessitated the development of robust communication systems to ensure safety, security, and performance. A crucial enabler is Vehicle-to-Vehicle (V2V) communication, which facilitates real-time data exchange to enhance safety features such as collision avoidance and adaptive driving. This paper explores the design of intelligent wireless network systems supporting V2V communication and AI/ML cloud integration, focusing on System-on-Chip (SoC) solutions tailored for these applications. To support high-speed, low-latency data exchange, the SoC incorporates advanced Radio Frequency (RF) modules, signal processing units, and AI/ML accelerators, alongside communication technologies like 5G NR, Wi-Fi 6, and V2X. These technologies ensure reliable communication even in dense traffic environments, providing necessary bandwidth and low latency while optimizing energy efficiency. AI/ML accelerators enable real-time, edge-based decision-making for tasks such as hazard detection and route optimization, reducing cloud dependency and enhancing system response time. The SoC design also integrates robust security protocols, including end-to-end encryption, secure boot, and Trusted Execution Environments (TEEs), ensuring data protection against cyber threats. A case study with autonomous vehicles demonstrates a 94% reduction in accidents and real-time response times under 10 milliseconds, showing the system's effectiveness in enhancing road safety. In conclusion, the proposed SoC design offers a scalable, efficient solution for connected vehicle systems, contributing to developing safer, more intelligent roadways.
References
D. Maroua, “A state-of-the-art on federated learning for vehicular communications,” Vehicular Communications, vol. 45, p. 100709, Dec. 2023, doi: https://doi.org/10.1016/j.vehcom.2023.100709.
A. Paul, N. Chilamkurti, A. Daniel, and S. Rho, “Introduction: intelligent vehicular communications,” Fundamentals, Architectures and Solutions, pp. 1–20, Jan. 2017, doi: https://doi.org/10.1016/b978-0-12-809266-8.00001-6.
B. Kelechava, “ISO 26262:2018 - road vehicles functional safety standards,” The ANSI Blog, Feb. 15, 2019. https://blog.ansi.org/2019/02/iso-26262-2018-road-vehicle-functional-safety/.
T. David, K. Muhammad, and K. Nassisid, “Enhancing Vehicular Networks with Generative AI: Opportunities and Challenges,” Arxiv.org, 2024. https://arxiv.org/html/2407.11020v1 (accessed Feb. 20, 2025).
S. K. Baduge , S. Thilakarathna , J. S. Perera , M. Arashpour , “Artificial intelligence and smart vision for building and construction 4.0: Machine and deep learning methods and applications,” Automation in Construction, vol. 141, no. 2, p. 104440, Sep. 2022, Available: https://www.sciencedirect.com/science/article/pii/S0926580522003132.
A. Biswas and H.-C. Wang, “Autonomous Vehicles Enabled by the Integration of IoT, Edge Intelligence, 5G, and Block chain,” Sensors, vol. 23, no. 4, p. 1963, Jan. 2023. Available: https://www.mdpi.com/1424-8220/23/4/1963.
J. Koon, “Increased Automotive Data Use Raises Privacy, Security Concerns,” Semiconductor Engineering, Mar. 07, 2024. https://semiengineering.com/increased-automotive-data-use-raises-privacy-security-concerns/.
M. Y. Idna Idris I. Ahmedy, T. K. Soon, M. Yahuza, and U. Ali, “Cognitive radio and machine learning modalities for enhancing the smart transportation system: A systematic literature review,” ICT express, vol. 10, May 2024, doi: https://doi.org/10.1016/j.icte.2024.05.001.
M. Sadaf, Z. Iqbal, A. R. Javed, I. Saba, M. Krichen, “Connected and Automated Vehicles: Infrastructure, Applications, Security, Critical Challenges, and Future Aspects,” Technologies, vol. 11, no. 5, p. 117, Oct. 2023, Available: https://www.mdpi.com/2227-7080/11/5/117.
