Driver Models for Both Human and Autonomous Vehicles with Different Sensing Technologies and Near-crash Activity

This project will develop a multi-agent model with both human drivers and autonomous and semi-autonomous vehicles. The model will build upon successful models used in the Defense Advanced Research Projects Agency (DARPA) Grand Challenge vehicles, and will also incorporate results from the project experience in automotive industry project. This model takes dynamic inputs about the changing situation and behavior of others, and uses mathematical or symbolic processing to carry out the functions required to simulate the perception, attention, cognition, and control behavior of interest. The project will integrate different component models, including control theory models, decision and judgment models, learning classifier systems, joint human-automation system models, and attention models, to build a comprehensive model needed to make predictions in pre-crash situations, and needed to make quantitative estimates of hypothesized safety improvements.These models will be cross-validated and verified using both the driver simulation experiments in Project 1, Pre-crash Multi-vehicle Experimental Analysis Using a Networked Multiple Driving Simulator Facility and data obtained from driving simulator and field driving experiments.

Language

  • English

Project

  • Status: Active
  • Funding: $332030.00
  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    1200 New Jersey Avenue
    Washington, DC  United States  20590
  • Performing Organizations:

    Ohio State University, Columbus

    410 West Tenth Avenue
    Columbus, OH  United States  43210
  • Principal Investigators:

    Woods, David

    Lee, John

    Homaifar, Abdollah

    Fisher, Donald

    Ozguner, Umit

  • Start Date: 20130930
  • Expected Completion Date: 0
  • Actual Completion Date: 0
  • Source Data: RiP Project 35919

Subject/Index Terms

Filing Info

  • Accession Number: 01503185
  • Record Type: Research project
  • Source Agency: Crash Imminent Safety University Transportation Center
  • Files: UTC, RiP
  • Created Date: Jan 4 2014 1:00AM