Road damage detection method based on lightweight vehicle equipment

doi:10.13474/j.cnki.11-2246.2024.0526

Abstract

Abstract: In response to the high cost and long detection cycle of traditional road detection methods, which can not meet the needs of large-scale and short-term detection of urban roads, this paper designs a lightweight vehicle mounted road damage data acquisition device and proposes a road damage detection method based on lightweight vehicle mounted devices. This device has the characteristics of small mass and low cost, and can be easily and quickly installed on common urban vehicles such as cars and buses, and synchronously collect inertial data, images, GPS positioning information, and other data. The road damage detection method proposed in this article is based on lightweight vehicle mounted devices, which collect road image data on urban roads to construct a dataset, establish a deep learning model for training and evaluation, and detect and recognize road damage. The accuracy rate is 82.54%, which can meet the requirements of daily inspection of urban roads.

Key words: road engineering, road damage detection, lightweight on-board equipment, deep learning, target detection

CLC Number:

P258

YAO Chuxian, CAI Haonan, ZHANG Yuanbo, TANG Keyi, ZHAN Lu, ZHOU Baoding. Road damage detection method based on lightweight vehicle equipment[J]. Bulletin of Surveying and Mapping, 2024, 0(5): 147-150.

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