A Heterogeneous Communication Network Cooperation Framework for Hybrid V2V–V2I Traffic Signal Optimization in Intelligent Transportation Environments

Abstract

Urban intelligent transportation systems increasingly rely on vehicle-to-infrastructure (V2I) communication for green-light optimal speed advisory (GLOSA) services. However, conventional GLOSA systems are vulnerable to roadside unit (RSU) coverage gaps and communication instability in mixed-traffic environments. In this paper, we propose a heterogeneous communication network cooperation framework that integrates decentralized multi-hop vehicle-to-vehicle (V2V) relaying with conventional V2I communication to extend signal phase and timing (SPaT) dissemination beyond direct RSU coverage. A lightweight gradient-based speed synchronization mechanism supports real-time trajectory adaptation with low computational overhead. The framework is evaluated through microscopic SUMO simulations with explicit communication impairment modeling across varied traffic densities and connected autonomous vehicle (CAV) penetration levels (10–70%). The results demonstrate reductions in travel time reductions of up to 22%, stop frequency of up to 95%, and CO2 emission exceeding 18% relative to V2I-only GLOSA under 70% CAV penetration. At the lower bound of 10% CAV penetration, the framework still achieves measurable improvements of approximately 4–6% in travel time and 15–20% in stop frequency, confirming practical benefit even under minimal connected-vehicle adoption. The proposed framework maintains advisory continuity through distributed relay dissemination, offering a scalable and communication-resilient enhancement to intelligent transportation coordination in heterogeneous environments.