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This paper introduces an infrastructure-guided road crack detection pipeline that leverages vehicle-to-infrastructure (V2I) communication to transmit regions of interest to the vehicle. By dynamically cropping and selecting frames based on infrastructure input, the system focuses image processing on relevant areas, improving detection efficiency. Experiments on a vehicle platform demonstrate the pipeline's effectiveness in enhancing crack detection performance using a crack detection model trained on a forward-facing view dataset.
Road crack detection gets a boost by having the infrastructure tell the car where to look.
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.
