SCCA-YOLO: A Spatial and Channel Collaborative Attention Enhanced YOLO Network for Highway Autonomous Driving Perception System.

Abstract

In the domain of autonomous driving perception systems, where extensive research has been conducted on urban environments, the investigation of rural scenarios has gained prominence due to the overarching objective of achieving comprehensive autonomous driving capabilities. The inherent complexity and unpredictability associated with rural road conditions present distinct challenges for autonomous driving technologies. Consequently, this study introduces a spatial channel collaborative attention YOLO network specifically designed for rural road contexts. This network incorporates an innovative attention mechanism that integrates spatial attention with shared semantics and channel self-attention in a sequential manner, thereby enhancing the accuracy of YOLOv8. Furthermore, the integration of the Ghost module is employed to facilitate the network's lightweight characteristics. Our evaluations, conducted on both proprietary and publicly available datasets, demonstrate the effectiveness of our detection network's performance.