Semi-autonomous connected vehicle safety systems and collision avoidance: findings from two simulated cooperative adaptive cruise control studies

Automated vehicle safety systems present a challenge for transportation safety: the more a vehicle does to manage a driver’s safety, the lower the demand placed on the driver. This can lead drivers to become less attentive, leaving them with insufficient information when faced with a situation that requires them to quickly resume control of the automated task. Keeping drivers aware of their situation and knowledgeable about the capabilities and limitations of a semi-autonomous system, so that they can intervene when appropriate, is critical to the success of automated transportation.This article describes experiments that had the goal of assessing driver workload while using cooperative adaptive cruise control (CACC) and adaptive cruise control (ACC) systems and evaluating whether CACC improves or diminishes crash avoidance when driver intervention is required. Two driving simulator studies allowed participants to drive in a controlled environment with simulated CACC vehicles directly transmitting vehicle-to-vehicle data to improve automated response time

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/614107147
• Authors:
  • Roldan, Stephanie M
  • Inman, Vaughan W
  • Balk, Stacy A
  • Philips, Brian H
• Publication Date: 2018-6

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 30-35
• Serial:
  • ITE Journal
  • Volume: 88
  • Issue Number: 6
  • Publisher: Institute of Transportation Engineers (ITE)
  • ISSN: 0162-8178
  • Serial URL: https://www.ite.org/publications/ite-journal/

Subject/Index Terms

• TRT Terms: Autonomous intelligent cruise control; Connected vehicles; Crash avoidance systems; Drivers; Human factors; Intelligent vehicles; Simulation; Vehicle safety; Workload
• Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01673220
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 25 2018 9:40AM