Low-Complexity Heuristic Optimization of RIS Orientation for V2V Visible Light Communication at Urban Intersections

The rapid growth of Intelligent Transportation Systems (ITS) and autonomous vehicles highlights the need to enhance V2V connectivity. Recently, millimeter waves (mmWave) are used extensively to offer high data rates; however, they suffer from blockage sensitivity and high path loss, especially in dense urban areas. Visible Light Communication (VLC) emerges as a promising alternative due to its wide bandwidth, immunity to electromagnetic interference, and inherent security. Nevertheless, its dependency on Line-of-Sight (LOS) restricts performance at road intersections. To address this challenge, this paper proposes a Reconfigurable Intelligent Surface (RIS)-assisted V2V VLC system that enhances link reliability in LOS-blocked intersections. We formulate the optimization problem to jointly tune the RIS elements' orientation to maximize total system capacity (Max-Sum) while ensuring fairness among communicating vehicles (Max-Min). To reduce computational complexity, we introduce a low-complexity heuristic approach based on analytical derivation of optimal RIS angles for a simplified one-to-one V2V model, which is then generalized for multiple vehicles. Simulation results demonstrate that the proposed heuristic achieves near-optimal performance with significantly reduced computation time, proving its potential for practical ITS deployments.