Assessment of truck driver safety efficiency based on data envelopment analysis

This paper introduces a safety efficiency evaluation framework that integrates Data Envelopment Analysis (DEA) and Super-Efficiency Data Envelopment Analysis (SE-DEA) for quantitatively assessing the safety of truck drivers. The framework utilizes data from onboard equipment to capture drivers’ dang...

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Bibliographic Details
Main Authors: Hu Dunli, Zhang Xiangdong, Zhang Jianhua
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/42/e3sconf_uct2024_04011.pdf
Description
Summary:This paper introduces a safety efficiency evaluation framework that integrates Data Envelopment Analysis (DEA) and Super-Efficiency Data Envelopment Analysis (SE-DEA) for quantitatively assessing the safety of truck drivers. The framework utilizes data from onboard equipment to capture drivers’ dangerous behaviors and poor driving states. Subsequently, it evaluates safety efficiency using the DEA combination model, providing safety rankings. Improvement suggestions are offered to underperforming drivers based on slack variable values. The proposed method is compared with EWM-Topsis and Critic-Topsis models using fixed weights, demonstrating better stability. The study’s outcomes enable freight companies to identify high-risk drivers and offer personalized, targeted safety training.
ISSN:2267-1242