For smart vehicles driving through signalised intersections, it is crucial to determine whether the vehicle has right of way given the state of the traffic lights. To address this issue, camera based sensors can be used to determine whether the vehicle has permission to proceed straight, turn left or turn right. This paper proposes a novel end to end intersection right of way recognition model called LightFormer to generate right of way status for available driving directions in complex urban intersections. The model includes a spatial temporal inner structure with an attention mechanism, which incorporates features from past image to contribute to the classification of the current frame right of way status. In addition, a modified, multi weight arcface loss is introduced to enhance the model classification performance. Finally, the proposed LightFormer is trained and tested on two public traffic light datasets with manually augmented labels to demonstrate its effectiveness.

翻译：对于驶入信号交叉口的智能车辆而言，根据交通灯状态判断自身是否具有通行权至关重要。针对该问题，可采用基于摄像头的传感器判定车辆是否被允许直行、左转或右转。本文提出一种新型端到端交叉路口通行权识别模型LightFormer，用于生成复杂城市交叉口中各可行驶方向的通行权状态。该模型包含具有注意力机制的时空内部结构，通过融合历史图像特征提升当前帧通行权状态的分类精度。此外，引入改进的多权重弧面损失函数（multi-weight arcface loss）以增强模型分类性能。最后，通过两个经人工标注增强的公共交通灯数据集对LightFormer进行训练与测试，验证了其有效性。