Abstract
Conventional statistical methods have utilized a coarse aggregation of information crosswise over subjects that may not be illustrative of any single person. Despite the fact that Generalized Estimating Equations system stretches out summed up direct model to take into account examination of repeated estimations or other similar observations, the non-linear connection between dependent and independent variables that could hinder model performance. In this study, we propose Generalized Estimating Equation based tree model that combines the benefits of both models by separating the data set recursively into subsets with different parameter estimates. For the best use of the proposed model, distracted driving on the intersection is examined. Past examinations have concentrated on evaluating the singular effect of individual geometry and human characteristic variables on driving behaviors. Interactions between factors related with red-light running (e.g., cell phone use, cell phone interface, and driver age) introduce diverse levels of distraction on red-light running. We recognize interactions that are sensitive to red-light running and different as a function of the level of the speed and yellow interval duration. Drivers are more vulnerable to cell phone distractions when their location is close the stop line of the intersection at the beginning of yellow interval.
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Acknowledgments
The data used for this study was from a study conducted at the University of Iowa NADS, as part of a wireless urban arterial project funded by the US Department of Transportation - National Highway Traffic Safety Administration (NHTSA). We would like to express our gratitude for providing descriptions and clarifications. Any opinions, findings, and conclusions or recommendations expressed in this study are those of the authors and do not necessarily reflect the views of NADS or the US Department of Transportation-National Highway Traffic Safety Administration
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Park, H., Pugh, N. (2019). Generalized Estimating Equations Model Based Recursive Partitioning: Applied to Distracted Driving. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2018. Advances in Intelligent Systems and Computing, vol 786. Springer, Cham. https://doi.org/10.1007/978-3-319-93885-1_77
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DOI: https://doi.org/10.1007/978-3-319-93885-1_77
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