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Predicting trucking accidents with truck drivers 'safety climate perception across companies: A transfer learning approach
Feb. 21, 2024, 5:41 a.m. | Kailai Sun, Tianxiang Lan, Say Hong Kam, Yang Miang Goh, Yueng-Hsiang Huang
cs.LG updates on arXiv.org arxiv.org
Abstract: There is a rising interest in using artificial intelligence (AI)-powered safety analytics to predict accidents in the trucking industry. Companies may face the practical challenge, however, of not having enough data to develop good safety analytics models. Although pretrained models may offer a solution for such companies, existing safety research using transfer learning has mostly focused on computer vision and natural language processing, rather than accident analytics. To fill the above gap, we propose a …
abstract accidents analytics artificial artificial intelligence arxiv challenge climate companies cs.ai cs.lg data face good industry intelligence perception practical pretrained models safety transfer transfer learning truck trucking type
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