随着道路运输行业的快速发展，营运车辆事故数量不断增加，尤其是营运车辆由于其特殊的运行特性，面临更为复杂的交通环境和风险。该文就不可观测异质性对营运车辆事故严重程度的影响进行了分析。基于我国营运客车与营运货车的交通事故数据，从驾驶员行为、车辆类型、道路特征和环境条件4个方面选取相关变量，构建了随机参数Logit模型。该模型通过引入随机参数有效捕捉个体间的异质性和不确定性，提升了模型的解释力和预测性能。在此基础上，进一步应用SHAP方法分析各影响因素的方向性、重要性以及变量间的非线性交互关系。研究结果表明：对于营运客车，复杂道路线形和车辆类型会显著增加事故的严重程度，尤其是复杂道路条件与操作不当的交互效应会显著增加事故的严重程度；而对于营运货车，危化品运输车辆与复杂道路条件的交互效应较强，超速行为会显著提升重大事故的发生概率。通过对10个多维度指标的SHAP可解释性分析，量化了各指标对事故严重程度的贡献，发现客车事故主要受道路环境因素影响，货车事故则更显著地关联车辆属性，从而进一步量化了人因风险与环境因素对事故严重程度的不同影响。

With the rapid development of the road transport industry, the number of accidents involving operational vehicles is continuously increasing. Especially, operational vehicles, due to their unique operational characteristics, face more complex traffic environments and risks. This study analyzes the impact of unobserved heterogeneity on the severity of operational vehicle accidents. Based on traffic accident data of operational buses and trucks in China, relevant variables are selected from such four aspects as driver behavior, vehicle type, road characteristics and environmental conditions, and a random parameter Logit model is constructed. By introducing random parameters, the model can effectively capture the heterogeneity and uncertainty between individuals, thus improving its explanatory power and predictive performance. The SHAP method is further applied to analyze the direction, importance, and non-linear interactions between variables. The results show that, for operational buses, complex road shapes and vehicle types significantly increase the severity of accidents, especially the interaction effect between complex road conditions and improper operations, which notably raises the accident severity. For operational trucks, the interaction effect between hazardous material transport vehicles and complex road conditions is stronger, and speeding behavior significantly increases the probability of major accidents. The SHAP analysis quantifies the contribution of 10 multidimensional factors to accident severity, revealing that bus accidents are mainly influenced by road environment factors, while truck accidents are more significantly related to vehicle attributes. This further quantifies the differing impacts of human factors and environmental factors on the severity of accidents.