Knowledge-guided self-learning control strategy for mixed vehicle platoons with delays.

ABSTRACT: As autonomous vehicles and traditional vehicles will coexist for several decades, how to efficiently manage the mixed traffic, while enhancing road throughput, fuel consumption and traffic stability becomes a challenge. This is due to the randomness and heterogeneity of traditional vehicles interspersed among autonomous vehicles. Moreover, communication delays arising from the shared wireless communication network substantially degrade the performance of platooning control for connected autonomous vehicles. To address these challenging problems, this paper proposes a knowledge-guided self-learning mixed platoon control strategy. Firstly, the proposed strategy extracts key features of the continuous and aggregated behavior of traditional vehicles, such as desired time-varying time gap and s

SUBMITTER: Wang J 

PROVIDER: S-EPMC12365019 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature