Manual vs. Adaptive Cruise Control--Can Driver's Expectation be Matched?

The role of the driver in the longitudinal car following control task will change from operator to supervisor with most of manual control replaced by automation as adaptive cruise control (ACC) technologies become commonplace. The extent to which manual control can be replaced by ACC will be determined by many factors. An important issue is the compatibility between ACC performance and the driver’s expectations. This paper describes the results of a simulation study of the performance of ACC relative to driver expectation. Driver’s expectation is quantitatively defined as the expected deceleration rate for several time-to-collision (TTC) levels, and an absolute minimum TTC that drivers tried to avoid in all cases. A two-level ACC algorithm was used to simulate the performance of an ACC equipped vehicle in various scenarios, and the result was compared to the driver’s expectations. The investigation has focused on scenarios which ACC is able to manage technically, but where driver expectations might be breached. By systematically changing variables such as the parameters of the ACC algorithms, traffic scenarios and time-headway settings, a large number of situations have been tested. The results have revealed that whilst appropriate ACC settings can be found which will meet the driver’s expectations, the ACC settings that are most capable in a range of traffic conditions are not necessarily the most user-friendly. A discussion on the implications of the findings is also presented.

• Record URL:
  • http://www.sciencedirect.com/science/article/B6VGJ-4JYKKNP-1/1/b8346170038503e51e58a2705dc0994c
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier
• Authors:
  • Zheng, Pengjun
  • McDonald, Mike
• Publication Date: 2005-10

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 421-431
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 13
  • Issue Number: 5
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Algorithms; Autonomous intelligent cruise control; Behavior; Car following; Cruise control; Drivers; Driving; Simulation
• Uncontrolled Terms: Driver expectations; Time-to-collision; Traffic conditions
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment; I91: Vehicle Design and Safety;

Filing Info

• Accession Number: 01029191
• Record Type: Publication
• Files: TRIS, ATRI
• Created Date: Jul 21 2006 2:33PM