Dynamic Load Balancing for Energy-Delay Tradeoff in a Cloud-RSU-Vehicle Architecture

Abstract

Advanced autonomous driving services at Level 4 and above eliminate the need for constant driver supervision, enabling vehicles to respond autonomously to various driving scenarios. The integration of components under edge environment such as the On Board Unit (OBU), Road Side Units (RSUs), and cloud infrastructure, facilitated by V2X communication, enhances perception, decision-making, and control capabilities. However, existing standards lack guidance on efficient computing resource management in autonomous driving systems. To address this, we propose a dynamic computing load balancing algorithm for the cloud-RSU-vehicle architecture. This algorithm optimizes resource allocation and utilization, considering network conditions, computational capabilities, and processing queues using Lyapunov optimization techniques. The stability of the algorithm and trade-off between processing delay and energy consumption is inspected through simulation. © 2023 IEEE.