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PMSS Project Details


Project ID:FHWA-PROJ-11-0171
Project Name: Exploration of Integrated Vehicle-Based Safety Systems Naturalistic Driving Data
Status: Completed
Last Name:Lochrane
First Name:Taylor
Office: Office of Operations Research and Development
Team:Trans Ops Concepts and Analysis Team
Project Description:The car-following and lane-changing driving behavior is different in work zones than during normal conditions. The overall objective of this project is to mine the naturalistic driving behavior dataset and extract instances when drivers were passing through work zones. This research will examine the data to determine whether driving behavior changes in work zones compared to driving behavior not in work zones.
Laboratories: Saxton Transportation Operations Laboratory
Start Date: February 25, 2011
End Date: February 8, 2013
(1) Establish database in the Saxton Transportation Operations Laboratory.
Background Information: This study will involve many units within the United States Department of Transportation from Federal Highway Administration. The data was provided from the John A. Volpe National Transportation Systems Center.
Test Methodology: Statistical analysis will be used.
  • Federal Highway Administration: Office of Research, Development, and Technology - Office of Safety Research and Development; Role(s): Advisory
  • U.S. Department of Transportation: Research and Innovative Technology Administration (RITA); Role(s): Other stakeholder
  • ; Role(s):
  • University of Central Florida; Role(s): Technical, Advisory
Expected Benefits:Modeling and simulation of work zones.
Deliverables:Name: Paper for Transportation Research Board.
Product Type(s): Conference displays, Article
Description: This paper will include the various thresholds to the Wiedemann Psycho-Physical model to accurately model driver behavior in work zones.
Keywords: Work Zones
Transportation Operations
Human Factors
Instrumented Vehicles
Car Following
Lane Changing
Subject Areas: Vehicles and Equipment
Safety and Human Factors
Operations and Traffic Management
Data and Information Technology
Planning and Forecasting