Utilizing Telematics to Understand Driving Behavior During Missed Exits and Wrong Turns

Texas is currently experiencing its largest population growth in decades. More and more lands are being urbanized and complex design methods are often adopted. As a result, drivers are likely confused at certain locations such as ramps, roadway exits and intersections. The overarching goal of this project is to identify unsafe and inefficient locations of Texas state highways, where driving behaviors often reveal excessive abnormities (e.g., hard brakes, control stops and/or missing of road entrances/exits). Problematic locations are due to misleading roadway designs or signage configurations in many cases. In the past, Texas Department of Transportation (TxDOT) could not identify such locations until either a driver called to complain or crashes occurred frequently. The emerging telematics data from connected vehicles (CVs) will enable such possibility to identify and fix problematic locations proactively. Applying the state-of-the-art big data analytics and Artificial Intelligence (AI) techniques on the emerging vehicle telematics data (delivered by Wejo and INRIX), the research team will demonstrate how to identify problematic locations within the selected area. The research team will also integrate multiple advanced computing techniques (e.g., high-performance computing, cloud-computing etc.) to cost-effectively streamline the process of traffic big data fusion, cleaning, and reduction for TxDOT's future practices.

• Record URL:
  https://library.ctr.utexas.edu/Presto/project=0-7200

Language

• English

Project

• Status: Active
• Funding: $403,695
• Contract Numbers:

  0-7200

• Sponsor Organizations:

  Texas Department of Transportation

  125 E. 11th Street
  Austin, TX  United States  78701-2483
• Managing Organizations:

  Texas Department of Transportation

  125 E. 11th Street
  Austin, TX  United States  78701-2483
• Project Managers:

  Adediwura, Jade

• Performing Organizations:

  Texas A&M Transportation Institute

  Texas A&M University System
  3135 TAMU
  College Station, TX  United States  77843-3135

  University of Texas at Arlington

  Box 19308
  Arlington, TX  United States  76019-0308
• Principal Investigators:

  Wu, Dayong

• Start Date: 20230901
• Expected Completion Date: 20250831
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Artificial intelligence; Connected vehicles; Crash risk forecasting; Data analysis; Driver errors; High risk locations; Highway factors in crashes; Highway safety; Telematics; Traffic crashes
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01894850
• Record Type: Research project
• Source Agency: Texas Department of Transportation
• Contract Numbers: 0-7200
• Files: RIP, STATEDOT
• Created Date: Sep 27 2023 4:18PM