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.　　©　2024　The　Authors,　published　by　EDP　Sciences.