Resilient distributed model-free adaptive traffic signal control via controller dynamic linearization under DoS attacks
Year: 2026
Type: article
Abstract: The increasing complexity and persistent network security challenges in traffic signal control are key issues requiring urgent attention to meet growing traffic demands. To address these issues, this paper proposes a resilient distributed model-free adaptive traffic signal control strategy (CDL-DMFAC) that integrates controller dynamic linearization (CDL) with multi-agent modeling. In the proposed framework, each signal phase at an intersection is modeled as an independent agent, and a compact form dynamic linearization (CFDL) is employed to construct an unknown ideal controller, enabling balanced control of multi-phase queue lengths. Furthermore, a denial-of-service (DoS) attack compensation mechanism is designed to mitigate the negative impact of communication interruptions or delays on signal timing decisions. Experimental results show that CDL-DMFAC effectively suppresses queue growth and delay accumulation under various attack intensities, with its performance advantage becoming more pronounced as attack severity increases. Notably, under the most challenging scenario-high traffic demand with multiple intersections simultaneously subjected to DoS attacks-the proposed method achieves reductions of 28.3% in average queue length and 36.32% in average waiting time compared to conventional signal control methods. These results highlight the method's strong resilience against attacks, operational stability, and potential for deployment in larger-scale urban traffic networks.
Source: PLoS ONE
Authors: Ye Ren, Haoyang Sun, Ting Lei, Honghai Ji, Shida Liu, Li Wang
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,382
OpenAlex ID: W7128674398