Adaptive bandwidth data-aware technology in vehicular network communication environments

Vehicular networks support high-frequency data exchange for autonomous driving, but they demand dynamic bandwidth allocation. This drives the development of adaptive bandwidth data-aware technology. However, traditional adaptive bandwidth data-aware techniques face issues like imprecise bandwidth allocation and insufficient data accuracy. This study proposes an adaptive bandwidth data-aware technology based on spectrum allocation to improve data sensing accuracy. The technology integrates an adaptive merge strategy into the fireworks algorithm by dynamically adjusting explosion range and merge probability to optimize spectrum allocation. Experimental results show that the technology achieves a sensing accuracy of 99.0%, with a maximum adaptive adjustment time of only 243 ms. In real-world operation, system stability and data security reach 90.0% and 98.3% respectively, significantly outperforming comparative techniques. These results demonstrate that the proposed technology delivers excellent accuracy and efficiency in bandwidth data sensing. It effectively addresses the current challenges of low accuracy and inefficiency, offering new ideas for bandwidth data sensing and supporting the intelligent and efficient development of autonomous driving.