Evaluating overtaking and filtering maneuver of motorcyclists and car drivers using advanced trajectory data analysis

The present paper compares motorized two-wheeler (MTW) and passenger car's interactions with the rest of the traffic in urban roads while performing overtaking and filtering maneuvers. To better understand filtering maneuvers of motorcyclists and car drivers, an attempt was made to propose a new measure, i.e. pore size ratio. Additionally, the factors affecting lateral width acceptance for motorcyclists and car drivers while overtaking and filtering were studied using advanced trajectory data. A regression model was developed to predict the significant factors affecting motorcyclist's and car driver's decisions to accept lateral width with the adjacent vehicle while performing overtaking and filtering maneuvers. Finally, a comparative analysis between machine learning and the probit model revealed that, in the present case, machine learning models perform better than the probit model in terms of the model's discernment power. The findings of this study will help ameliorate the power of existing microsimulation tools.