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The ride comfort of bus passengers is a critical factor that is recognized to attract greater ridership towards a sustainable public transport system. However, it is challenging to predict bus passenger comfort due to the complex non-linear interaction among various factors. In an application-based study, 18 real driving tests were conducted to analyze the correlation between factors induced by motion sickness and the driving status of the vehicle. We used the user&#x2019;s feedback module (UFM) to record the feelings of passengers, and the six degrees of freedom (6-df) motion parameters were obtained by the accelerometer in the micro electro mechanical system (MEMS) of the smartphone. Then, the data were discriminated and analyzed, and thresholds of the variables affecting the discomfort of passengers in different conditions were obtained. Finally, we established a prediction model of motion sickness duration based on the driving status of vehicles. The result shows that passenger&#x2019;s comfort is most sensitive to vertical acceleration changes when the vehicle is decelerated, and the duration of motion sickness (DMS) can be effectively predicted (79.8&#x0025;) by the vehicle&#x2019;s lateral acceleration, roll, and pitch angular velocity indicators. The findings of this study provide insights into the potential theoretical basis for policymakers to improve the adjustment of the driving strategies and path trajectory of city buses.

Can Variations of Vehicle Driving Status Provide Accurate Predictors of Discomfort? A Study on the Actual Driving Test