Solar-powered VANET framework coordinates roadside units for smart traffic in arid regions

Researchers have unveiled an integrated solar-powered vehicular ad hoc network (VANET) framework that coordinates roadside unit placement, activation scheduling and traffic prediction within a single architecture, designed for sustainable intelligent transportation systems in arid regions where abundant sunshine meets highly dynamic traffic demand.

Existing solar-powered VANET approaches typically treat these decisions as separate problems, which limits their ability to match long-term infrastructure siting with short-term communication demand and energy availability. The new framework, described in Scientific Reports, addresses this by coupling spatial and temporal decisions in a unified design.

At the core of the system, a Discrete Grey Wolf Optimization method performs spacing-aware roadside unit siting, maximizing traffic coverage, network centrality and solar harvesting potential while penalizing redundancy. A Traffic-Aware Duty Cycling controller then regulates roadside unit operation through traffic hysteresis, battery state-of-charge guards and minimum dwell times, ensuring units stay responsive without draining their batteries.

A Joint Activation Score links long-term site utility to runtime activation decisions, while a Random Forest-based traffic anticipation module enables proactive scheduling. The team also introduced an Activation Timeliness Gain metric to quantify how much the framework improves activation timing.

Performance was evaluated through trace-driven simulations on the Ha’il City road network in Saudi Arabia, using measured solar irradiance and real traffic data. Under the evaluated conditions, the framework achieved packet delivery ratios of 94.5 to 97.9 percent, cut end-to-end delay by 7 to 35 milliseconds, and lowered per-roadside-unit energy consumption by 20 to 33 percent relative to representative baselines, all while maintaining fully off-grid operation.

Predictive assistance proved particularly valuable during traffic surges, advancing roadside unit activation by up to 2.1 minutes without additional energy cost. This proactive behavior allows the network to prepare for demand spikes before they materialize, rather than reacting after congestion has already formed.

The authors emphasize that the results demonstrate coordinated spatio-temporal design can simultaneously enhance communication reliability, responsiveness and energy efficiency. However, the findings are scoped to the specific conditions tested: the Ha’il topology, the evaluated traffic densities, the particular irradiance trace and a log-distance radio model.

Because the study relies on simulation rather than field deployment, real-world performance may differ, and the paper is being shared early as a peer-reviewed, accepted version subject to further edits before the final Version of Record. Even so, the work offers a concrete template for energy-autonomous roadside communication, showing how optimization, duty cycling and machine-learning-based prediction can be combined to keep vehicular networks running entirely on harvested solar energy in sun-rich, resource-constrained environments.

Subject of Research: An integrated solar-powered VANET architecture coordinating roadside unit siting, duty cycling and traffic prediction for smart traffic management in arid regions.

Article Title: Solar-powered VANET architecture for sustainable and smart traffic management in arid regions

Article References: Hajlaoui, R., Filali, A., Mahfoudhi, S., Alghazi, S., & Moulahi, T. (2026). Solar-powered VANET architecture for sustainable and smart traffic management in arid regions. Scientific Reports. https://doi.org/10.1038/s41598-026-75638-2

Image Credits: AI Generated

DOI: 10.1038/s41598-026-75638-2

Keywords: VANET, solar power, intelligent transportation systems, roadside units, traffic prediction, energy efficiency, arid regions, Grey Wolf Optimization, Random Forest, packet delivery ratio, duty cycling, Ha'il City