Assessing the Static and Dynamic Safety Performance of Heavy Vehicle Drivers Using Slacks-Based Measure Super-Efficiency Data Envelopment Analysis and the Malmquist Index

Road freight transportation is essential for social production, commodity circulation, and online consumption, offering flexibility and efficiency. However, traffic accidents and fatalities involving heavy vehicles have been high, mainly as a result of driver error. This research establishes a framework for evaluating the static and dynamic safety efficiency of heavy vehicle drivers, utilizing data envelopment analysis and the Malmquist index. First, the drivers’ aggressive behavior, abnormal status, and risky maneuver data were collected to construct a risk indicator database. Second, the static efficiency of drivers is evaluated using data envelopment analysis to obtain individual efficiency scores and rankings, and the improvement direction for each individual is determined based on the reference set. Furthermore, the model’s accuracy and stability were verified through one-way ANOVA and ranked difference tests. After that, the Malmquist index was used to analyze the dynamic efficiency of individuals and to examine the changing trend in individual efficiency over time. Finally, the static and dynamic efficiencies were combined to further analyze overall driving performance, and targeted improvement measures were implemented for different drivers. The study provides a comprehensive evaluation of drivers’ static and dynamic efficiency, offering targeted improvement measures and supporting freight management platforms.

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Publication Details

Journal
Transportation Research Record Journal of the Transportation Research Board
Published
2026-09-29
DOI
https://doi.org/10.1177/03611981261475664
Primary Topic
Vehicle emissions and performance
Type
article
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Assessing the Static and Dynamic Safety Performance of Heavy Vehicle Drivers Using Slacks-Based Measure Super-Efficiency Data Envelopment Analysis and the Malmquist Index

Ying Yao, Jianhua Zhang, Xiaohua Zhao, Jushang Ou
Transportation Research Record Journal of the Transportation Research Board
Vehicle emissions and performance
article

Assessing the Static and Dynamic Safety Performance of Heavy Vehicle Drivers Using Slacks-Based Measure Super-Efficiency Data Envelopment Analysis and the Malmquist Index

Ying Yao, Jianhua Zhang, Xiaohua Zhao, Jushang Ou
article en

Abstract

Road freight transportation is essential for social production, commodity circulation, and online consumption, offering flexibility and efficiency. However, traffic accidents and fatalities involving heavy vehicles have been high, mainly as a result of driver error. This research establishes a framework for evaluating the static and dynamic safety efficiency of heavy vehicle drivers, utilizing data envelopment analysis and the Malmquist index. First, the drivers’ aggressive behavior, abnormal status, and risky maneuver data were collected to construct a risk indicator database. Second, the static efficiency of drivers is evaluated using data envelopment analysis to obtain individual efficiency scores and rankings, and the improvement direction for each individual is determined based on the reference set. Furthermore, the model’s accuracy and stability were verified through one-way ANOVA and ranked difference tests. After that, the Malmquist index was used to analyze the dynamic efficiency of individuals and to examine the changing trend in individual efficiency over time. Finally, the static and dynamic efficiencies were combined to further analyze overall driving performance, and targeted improvement measures were implemented for different drivers. The study provides a comprehensive evaluation of drivers’ static and dynamic efficiency, offering targeted improvement measures and supporting freight management platforms.

Transportation Research Record Journal of the Transportation Research Board
Beijing University of Technology (CN), Shanxi Transportation Research Institute (CN)
Decent work and economic growth
Openalex Percentile: Top 20%
Vehicle emissions and performance
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