The question of whether driver behavior differs based on vehicle occupancy—and more specifically, the characteristics (such as age and relationship) of the occupants—is an important safety question related to the Safe-D application areas of risk assessment, vulnerable users, and driver factors and interfaces; as well as the theme of big data analytics. Although the Strategic Highway Research Program 2 (SHRP2) dataset, and data collected by insurance companies that use Global Positioning System (GPS) vehicle tracking to assess discounts, capture details about the driver and their habits, they lack concrete information (i.e., age, relationships) on passengers in the vehicle for a given trip. The objective of this research is to better understand the impact of vehicle occupants in speeding driving behavior. This will be accomplish through the use of Texas Department of Transportation Travel Survey Program (TxDOT TSP) household travel survey data, which includes a 10% sample of households with a GPS component for trip capture. TxDOT TSP GPS data will be linked to roadway characteristics using the TxDOT Road Highway Inventory Network (RHiNo) data and supplemental speed data from other sources. A crash risk assessment will be developed by linking to TxDOT Crash Records Information System (CRIS) crash data. Statistical analyses of speeding behavior will be performed, with special emphasis placed on vulnerable users (i.e., older drivers, teen drivers, and potential drivers with young children). The results will be used to recommend appropriate safety countermeasures and may be of interest to TxDOT, transportation engineering and public health statistics students, and safe driving technology firms interested in merging traditional planning data for use in a safety application.
AVID Slides (pptx): These slides will be included in his transportation planning session slides to show how planning and safety are related and how data traditionally used for a transportation planning purpose were used for innovative research.
Learning Module Materials (pptx): This presentation may be used in an educational setting to introduce students to the project and dataset, and includes instructions for creating a model using R (code available for download below).
R code (zip): This code is available for download and use with the learning module produced by this project, available above.
Green, L.L. (2017, May). TxDOT Travel Survey Program Data: Exploring Avenues of Added Value. Presentation at the Transportation Planning Applications Conference, Raleigh, NC. (Published)
Start Date: 2017-06-01
End Date: 2018-10-31
Grant Number: 69A3551747115
Total Funding: $149,980
Source Organization: Safe-D National UTC
Project Number: 02-009
Driver Factors and Interfaces
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Texas A&M University
Texas A&M Transportation Institute
College Station, Texas 77843-3135