Incorporating Driver Behaviors into Connected and Automated Vehicle Simulation

The adoption of connected vehicle (CV) technology is anticipated at various levels of development and deployment over the next decade. One primary challenge with these new technologies is the lack of platform to enable a robust and reliable evaluation of their benefits given the complexity of interactions among wireless communications, algorithms, and human behaviors. Underlying driver behavior models in microscopic simulation are not always well-suited for modern applications using CV and automated vehicle (AV) technology. This study proposed a framework for incorporating realistic driver behaviors into a microscopic traffic simulation for AV/CV applications using VISSIM microscopic simulation software. The framework consists of three levels of driver behavior adjustment: event-based, continuous, and semiautomated/automated driver behavior adjustment. The framework provides several examples and details on how various applications can be properly modeled in a traffic simulation environment. To demonstrate the framework, researchers conducted a case study of a simulation evaluation of cooperative adaptive cruise control (CACC). CACC enables the vehicles to follow each other in a very tight spacing (also known as platooning) using wireless connectivity and automated longitudinal control. The case study shows that a modified driver model can be successfully used in the simulation to evaluate the benefits of AV/CV applications such as CACC with respect to their mobility, safety, and environmental performance.

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• Record URL:
  https://rosap.ntl.bts.gov/view/dot/30917
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Texas A&M Transportation Institute

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

  Center for Advancing Transportation Leadership and Safety (ATLAS Center)

  University of Michigan
  2901 Baxter Road
  Ann Arbor, MI  United States  48109

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Songchitruksa, Praprut
  • Bibeka, Apoorba
  • Lin, Lu (Irene)
  • Zhang, Yunlong
• Publication Date: 2016-5-24

Language

• English

Media Info

• Media Type: Digital/other
• Features: Appendices; Figures; References; Tables;
• Pagination: 104p

Subject/Index Terms

• TRT Terms: Autonomous intelligent cruise control; Behavior; Case studies; Drivers; Intelligent vehicles; Mobile communication systems; Technological innovations; Traffic simulation
• Identifier Terms: VISSIM (Computer model)
• Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01603500
• Record Type: Publication
• Report/Paper Numbers: ATLAS-2016-13
• Contract Numbers: DTRT13-G-UTC54
• Files: UTC, TRIS, RITA, ATRI, USDOT
• Created Date: Jun 28 2016 4:41PM