Edge Computing for Autonomous Driving: Opportunities and Challenges

Speaker:  Shaoshan Liu – Fremont, CA, United States
Topic(s):  Architecture, Embedded Systems and Electronics, Robotics


Safety is the utmost important requirement for autonomous vehicles, hence the ultimate challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver enough computing power, redundancy, and security so as to guarantee the safety of autonomous vehicles. Specifically, autonomous driving systems are extremely complex systems that tightly integrate many technologies, including sensing, localization, perception, decision making, as well as the smooth interactions with cloud platforms for high-definition (HD) map generation and data storage. These complexities impose numerous challenges for the design of autonomous vehicle edge computing systems. First, the edge computing systems for autonomous driving need to process an enormous amount of data in real-time, and often the incoming data from different sensors is highly heterogeneous. Since autonomous vehicle edge computing systems are mobile systems, they often have very strict energy consumption restrictions. Hence, it is imperative to deliver sufficient computing power with reasonable energy consumption, to guarantee the safety of autonomous vehicles, even at high speed. Second, in addition to the edge system design, vehicle-to-everything (V2X) provides redundancy for autonomous driving workloads, and alleviates stringent performance and energy constraints on the edge side. With V2X, more research is required to define how vehicles can cooperate with each other and with the infrastructure. Last but not least, safety cannot be guaranteed with security compromised. Thus, protecting autonomous driving edge computing systems against attacks at different layers of the sensing and computing stack is of paramount concern. In this talk, we review state-of-the-art approaches in these areas as well as to explore the potential solutions to address these challenges.

About this Lecture

Number of Slides:  40
Duration:  45 minutes
Languages Available:  English
Last Updated: 

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