通过路侧基础设施引导，提升车载路面裂缝检测效率与精度。
Infrastructure-Guided Connectivity-Enhanced Road Crack Detection and Estimation
- 利用路侧设备向车辆发送感兴趣区域，减少数据传输量。
- 在实验车平台上实现端到端检测，显著提升裂缝识别效果。
- 适合智能网联汽车、智慧交通系统研发人员参考。
本文提出全球首个基于基础设施引导的通信增强型路面裂缝检测流程，适用于乘用车部署。首先设计专用通信协议，将道路关键区域信息从基础设施传至车辆；结合动态裁剪与帧选择等图像处理技术，向裂缝检测模型提供聚焦图像。基于包含前方视角裂缝样本的精心构建数据集，采用先进检测模型主干网络进行训练，有效提升检测性能。在实验车辆平台上验证了全流程可行性，展示了检测有效性，并展望了未来研究方向。
原文摘要 · Abstract (English)
In this paper, we report the world's first infrastructure-guided communication-enhanced road crack detection pipeline that is effective and implementable on passenger vehicles. We first design a customized communication protocol to transmit the region of interest from the infrastructure to the vehicle. With proper camera image processing (e.g., dynamic cropping and frame selection), the focused images are provided to the crack detection model. Leveraging state-of-the-art crack detection model backbones and a carefully prepared dataset comprising a forward-facing view with a crack, we train the model to improve crack-detection performance. We demonstrate the full detection pipeline on an experimental vehicle platform, showcase the detection effectiveness, and project future research directions.
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