Abstract:

To construct a driving risk assessment system for heavy goods vehicle drivers with good generalization and interpretability， based on trajectory data from heavy goods vehicle in Yunnan Province， this paper establishes driving risk assessment indicators covering driving style risk， fatigue risk， and driving environment risk. It then uses Pearson correlation analysis to select 43 key indicators from the initial set of driving risk assessment indicators. Lastly， by applying the CRITIC （criteria importance though intercriteria correlation） empowerment method to determine characteristic weights of various indicators， it proposes a method for assessing the driving risk of heavy goods vehicle drivers. The findings indicate that approximately 82.16% of drivers have driving style risk scores below 30 points， suggesting that the majority of heavy goods vehicle drivers in high-altitude mountainous areas have low risk assessment values. The fatigue risk assessment reveals that 42.3% of samples score below 12 points， indicating that heavy goods vehicle drivers in Yunnan Province engage less frequently in long-distance transportation， with fewer instances of continuous long-duration driving. The driving environment risk assessment is most densely distributed in the 15 to 35 points range， accounting for 75.46%， which suggests that cargo transportation mainly depends on riskier arterial roads.

Key words: traffic safety, heavy goods vehicle, quantifying driving risks, empowerment method, correlation analysis