A Service Strategy Based on Age of Information Optimization in Collaborative Perception Systems
Edge Computing(EC)technology addresses issues such as single-vehicle perception,sensor processing,and transmission latency by processing data in real-time at the network edge,thus providing support for efficient and secure autonomous driving services.Time-sensitive information is a core issue in autonomous driving,and Age of Information(AoI)is emerging as a crucial metric for addressing real-time and performance concerns.This study introduces the concept of AoI in the EC scenario of autonomous driving.Within the architecture of collaborative perception systems,this study proposes a service strategy that prioritizes maximum AoI as the primary optimization goal.Subsequently,by calculating the theoretical values of the time indicators for the service strategy,the key parameters affecting system performance are identified.Finally,using Monte Carlo methods,comparative experiments are conducted between conventional service strategies and the method proposed in this study.Simulation results indicate that under randomly initialized batch structures,the proposed service policy exhibits the lowest age of information,reducing it by 54.57％compared with the parallel service policy,demonstrating its significant advantage in AoI optimization.
Age of Information(AoI)collaborative perceptionEdge Computing(EC)service strategyFirst Come First Served(FCFS)
万方数据
维普
