As a result of the continuous improvement in passengers’ requirements for the quality of train operation, the comfort of high-speed train operation has been paid increasing attention. The evaluation of comfort has gradually changed from the narrow sense of a comfort evaluation model containing only vibration to the generalized evaluation of passengers’ overall satisfaction with the ride environment of specific lines. The factors affecting comfort evaluation include physical, physiological, and psychological aspects. To address the problems that the existing comfort evaluation model has a single index and that the weight determination of some indicators is greatly affected by subjectivity, we built a high-speed train comfort evaluation model based on variable weight theory. Combined with the actual working conditions of the Baolan passenger dedicated line, dynamic detection data and noise monitoring data captured by a track inspection car were combined with a passenger ride comfort questionnaire survey. In addition, the initial weight value of each factor was optimized by constructing an equilibrium function to realize the balance between the various factors, so as to realize the comprehensive fuzzy evaluation of high-speed train comfort. The results show that the comprehensive evaluation result of the comfort degree of the high-speed train on the Tongwei to Lanzhou section of the Baolan passenger dedicated line has a grade of II. The fuzzy scores of the evaluations using variable weights and constant weights were analyzed from the perspective of membership degree. The variable weight optimization avoids the one-sidedness and extremeness of the constant weight calculation. The comprehensive evaluation results are closer to the real situation. The research results can provide a reference for the comfort evaluation of high-speed trains with extreme differences in state values and constant weights and help in the acquisition of more realistic evaluation results.

The accumulation of sand on desert roads poses a significant threat to the smooth transportation and driving safety of these roads. To address this issue, a combined approach using the variable weight theory and cloud model theory is proposed for conducting a safety risk assessment of sand accumulation on desert roads. An evaluation index system for sand accumulation hazards is obtained through the analysis of regional geomorphological conditions, wind dynamic conditions, and engineering design factors. The evaluation index system’s constant weights are determined using the Five-Point Scale Method and Analytic Hierarchy Process. Moreover, the Variable Weight Theory is used to optimize these weights based on the actual state of the project, thereby enhancing the accuracy of risk assessment. Finally, based on the cloud model theory, a safety risk assessment model is constructed for sand accumulation hazards on desert highways. The sand accumulation hazard level of the highway is determined through this model, and the comprehensive evaluation results are visualized and presented intuitively using the MATLAB software. The experimental section of the new Wuhai-Maqin expressway sand prevention test is taken as an example for practical verification. The results show that the sand accumulation disaster level of the experimental section is grade Ⅲ, which is basically consistent with the actual engineering situation, verifying the reliability and applicability of the model. Therefore, this model could serve as an essential reference for risk assessments of sand accumulation hazards, location optimization selection, and the establishment of effective sand prevention engineering measures for desert highways.