Vehicular Ad Hoc Networks (VANETs) are a cornerstone of intelligent transportation systems, facilitating real-time communication between vehicles and infrastructure. However, the dynamic nature of VANETs introduces significant challenges in routing, especially in minimizing communication delay while ensuring route stability. This paper proposes a hierarchical evolutionary optimization framework for delay-constrained routing in vehicular networks. Leveraging multi-objective optimization, the framework balances delay and stability objectives and incorporates adaptive mechanisms like incremental route adjustments and LSTM-based predictive modeling. Simulation results confirm that the proposed framework maintains low delay and high stability, adapting effectively to frequent topology changes in dynamic vehicular environments.
@article{arxiv.2503.12050,
title = {Hierarchical Evolutionary Optimization with Predictive Modeling for Stable Delay-Constrained Routing in Vehicular Networks},
author = {Zhang Zhiou and Guo Weian and Zhang Qin and Lin Haibin and Li Dongyang},
journal= {arXiv preprint arXiv:2503.12050},
year = {2025}
}