Development of a Structural Equations Model to Understand Factors Influencing the Driver State

  • Miguel A. Perez (Creator)
  • Sara Khoeini (Creator)
  • Shivam Sharda (Creator)
  • Denise Capasso da Silva (Creator)



Project Description Safety research has largely focused on developing crash prediction models to directly relate traffic, roadway, and environmental factors to crash frequency and severity, but could not account for unobserved variables (i.e., engagement in risky driver behaviors) that contribute to a crash. The factors that contribute to engagement in risky driving behaviors are not well understood. This study uses the unique information in the NDS data to model driver state and behaviors as a function of different explanatory factors. Therefore, it is envisioned that the study would support the design of preventive measures that could proactively minimize risky driving state/behaviors to begin with. Data Request Scope This request includes elements of the vehicle, drivers, trips, and events categories found in the "Data" section of the InSight website. The tables included were not filtered in any way. Data Specification Vehicle: Vehicle Details Vehicle Condition Driver: Demographics Driver History Driver Knowledge Risk Perception Risk Taking Sensation Seeking Driver Behavior Sleeping Habits Trips: Trip Summary Events: Event Details Post-crash Interview A full list of requested variables can be found below in the file DataDictionary.pdf.
Date made available2018

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