A DRIVER BEHAVIOR RECOGNITION METHOD BASED ON A DRIVER MODEL FRAMEWORK

In this paper, the authors [present a model based approach in the development of a lane change detection and recognition model by using information processing models of human driver behavior generation. Using driver behavior data that is measured with a driving simulation the authors develop a Hidden Markov Method (HMM)-based driver behavior recognition model that takes into consideration the driver model characteristics. The authors conclude that driver behavior modeling and recognition of different types of lane changes is possible using HMMs.

• Supplemental Notes:
  • Publication Date: 2000 Society of Automotive Engineers, Warrendale PA
• Corporate Authors:

  Delphi Automotive Systems

  Troy, MI  United States 

  Siemens Corporation

  ,    

  Bayerische Motoren Werke

  ,    

  Motorola, Inc.

  ,    
• Authors:
  • Kuge, Nobuyuki
  • Yamamura, Tomohiro
  • Shimoyama, Osamu
  • Liu, Andrew
• Publication Date: 2000

Language

• English

Media Info

• Pagination: p. 47-54
• Serial:
  • Intelligent vehicle systems
  • Publisher: Delphi Automotive Systems

Subject/Index Terms

• TRT Terms: Driver support systems; Lane changing

Filing Info

• Accession Number: 00801314
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: PATH
• Created Date: Nov 7 2000 12:00AM