Safety guardian of intelligent transportation: Fisheye image based blind zone detection for Super Large Articulated Bus (SLAB)

Abstract

The Super Large Articulated Buses (SLAB), as a complement to road traffic in big cities, brings great convenience to residents. However, due to its body length of more than 30 m and its unique driving characteristic on the left side of the road, blind zone detection during right turns has garnered significant attention. This paper proposes an intelligent method using fisheye images to address such issues. The proposed strategy is primarily divided into three steps. Firstly, fisheye cameras are mounted on the side of the SLAB’s body to capture fisheye images, and the dual longitude method is employed for distortion correction. Secondly, a vehicle detection method based on Single Shot Multibox Detector (SSD) is proposed, which combines Squeeze-and-Excitation (SE) attention mechanism, Feature Pyramid Network (FPN) and Multi-branch Dilation Block (MDB), called MDB-SSD. Through ablation experiments, the mean average precision (mAP) of this model is observed to increase by 5.31 % on the BDD100k dataset and 7.68 % on the VOC dataset when compared to the baselines. Specifically, the mAP of the MDB-SSD model reaches 40.13 % on the BDD100k dataset and 83.42 % on the VOC dataset, demonstrating significant improvement in detection accuracy. The detection of fisheye images exhibits good robustness, enhancing vehicle detection performance for the blind zone during right turns in SLAB. Finally, based on fisheye images, the proposed cross-longitude distance measurement method demonstrates an average detection error of 3 % for forward distance and 9.8 % for lateral distance, providing convenience for SLAB’s assisted driving. The main focus of this paper provides a solution for the safe operation of SLAB.