Multisensory Approach for Stopped Vehicle Detection on Highways to Enhance Collision Prevention

Road accidents caused by stopped vehicles pose a significant threat to road safety. Traditional detection systems, often relying on single-sensor technologies, suffer from limitations such as poor performance in adverse weather conditions and high false positive rates. This research presents a novel multisensory detection system designed to improve the accuracy and reliability of detecting stopped vehicles on highways. By combining multiple sensor modalities, the system effectively overcomes the limitations of individual sensors. Experimental results demonstrate that the multisensory approach surpasses traditional radar and camera-based systems, achieving a remarkable detection accuracy of $\mathbf{9 5 \%}$. This significant improvement can contribute to a significant reduction in accidents caused by stopped vehicles. The proposed multisensory detection system offers a promising solution for enhancing road safety and improving traffic management systems.