Feasibility of Using In-Vehicle Video Data to Explore How to Modify Driver Behavior that Causes Non-Recurring Congestion

TRB / SHRP2 Program

Overview

The SHRP2 L10 project is intended “to examine existing studies using video cameras and other onboard devices to collect data and determine the potential for using these data to explore how to modify driver behavior in an attempt to reduce non-recurring congestion.” It was found that the majority of crashes or near crashes have the potential to be prevented if appropriate instrumentation is installed to issue warnings to drivers in a timely fashion. After analyzing several datasets from naturalistic driving studies, a step-by-step guidance is provided to analyze video data for studying driver behavior in relation to non-recurring congestion.

Source Organization Location

Washington, DC


Operations Area of Practice

  • Connected Vehicles
  • Data Acquisition, Support and Hosting
  • System Performance Definition, Monitoring and Reporting
  • Hazard Identification

Organizational Capability Element

  • Performance Measurement
  • Reliability Predictive Models
  • Vehicle Systems/Connected Vehicles

Content Type

  • Research

Role in Organization

  • Associate Engineer
  • Engineer
  • Principal Engineer
  • Researcher/Academic
  • Senior Engineer

Publishing Organization

  • SHRP2 Program

Maturity Level of Program

  • Assessment (L1)
  • Deployment (L3)
  • Development (L2)
  • Monitoring (L4)

Objective

  • Learning

Document Downloads

Prime Contractor
Virginia Tech Transportation Institute (SAIC)
Author
H. Rakha, J. Du, S. Park et al.
Issue Date
June 30th, 2011
Publication Number
S2-L10-RR-1
ISBN Number
978-0-309-12898-8
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