Delay Margin Analysis of a Large-Scale Optimal Velocity Model using the Parallel Processing Delay Margin Finder (parDMF)

摘要

A connected vehicle model with delays due to human reaction times and sensing and communication lines is considered. In particular, we investigate how time delays affect the equilibrium stability of this model in large scale. We focus mainly on the delay margin (DM) of this equilibrium, i.e., the largest delay that the system can accommodate without losing stability. We present how DM is influenced by the sparsity of sensor and communication lines and the number of vehicles. Different from previous work, no assumption is imposed on the structure of the network topology; the large-scale dynamics is treated in a computationally efficient manner by utilizing our recently developed parallel processing computational tool Delay Margin Finder (parDMF).