Evaluation of Work Zone Mobility by Utilizing Naturalistic Driving Study Data

The objective of this research is to evaluate work zone mobility by utilizing naturalistic driving study (NDS) data. More specifically, this one-year proof-of-concept project is to ascertain if the existing NDS work zone database can be reused to develop new (or update existing) capacity and traffic flow models for work zones. In this study, a comprehensive literature review was conducted to summarize the past study results on work zone capacity, work zone simulation models, and NDS application in work zone safety studies. It concluded that no past studies were found on application NDS data in relation to work zone mobility. The complimentary NDS data set was collected, including time-series data and forward-view videos, for a total of 420 baseline events and 256 safety-critical events. Forward-view video was reviewed to ensure that it is related to a work zone, which includes a lane or shoulder closure, the presence of barriers, the presence of construction equipment or workers, etc. Time-series data includes variables such as vehicle speed, acceleration, and pedal position at 0.1 s intervals. In addition, radar data and driver risk perceptions were collected for these events. Finally, researchers identified a total of 38 safety-critical events and 64 baseline trips for data analysis based on a set of criteria. Based on the sample size, the analysis focused on three types of freeway work zones (two-toone lane closure, two-to-two, and three-to-three shoulder closure). The fundamental traffic flow theory, Greenshield’s model, and work zone capacity method in the Highway Capacity Manual (HCM) were applied to identify the speed-flow-density relationship for different work zone configurations. The time headway and space headway distributions were further analyzed with driver characteristics such as driver’s gender, age group, risk perceptions. The results concluded that NDS data can be used to develop car-following models at work zones with consideration of driver population factor, which can be applied to improve work zone capacity methods and other work zone planning and simulation tools. Further study is recommended to collect more complete NDS trip data at different work zone configurations.

• Record URL:
  https://stride.ce.ufl.edu/wp-content/uploads/2018/08/B2-Abstract.pdf
• Record URL:
  https://stride.ce.ufl.edu/wp-content/uploads/2021/03/STRIDE-Project-B2-Final-Report.pdf
• 
• Supplemental Notes:
  • This is Phase 1 (Project B2) of a two part project. Phase II is Project I3.

Language

• English

Project

• Status: Completed
• Funding: $49883
• Contract Numbers:

  69A3551747104

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Southeastern Transportation Research, Innovation, Development and Education Center (STRIDE)

  University of Florida
  365 Weil Hall
  Gainesville, FL  United States  32611
• Project Managers:

  Tucker-Thomas, Dawn

• Performing Organizations:

  Auburn University

  Auburn, AL  United States  36830
• Principal Investigators:

  Zhou, Huaguo (Hugo)

• Start Date: 20180816
• Expected Completion Date: 20190815
• Actual Completion Date: 20191031
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Automatic data collection systems; Calibration; Freeways; Highway capacity; Intelligent transportation systems; Mobility; Time series analysis; Traffic flow; Traffic volume; Video; Work zone traffic control; Work zones
• Identifier Terms: Highway Capacity Manual
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;

Filing Info

• Accession Number: 01679761
• Record Type: Research project
• Source Agency: Southeastern Transportation Research, Innovation, Development and Education Center (STRIDE)
• Contract Numbers: 69A3551747104
• Files: UTC, RIP
• Created Date: Aug 27 2018 12:06PM