A Driver Behavior Recognition Method Based on a Driver Model Framework

نویسندگان

  • Nobuyuki Kuge
  • Tomohiro Yamamura
  • Osamu Shimoyama
  • Andrew Liu
چکیده

A method for detecting drivers’ intentions is essential to facilitate operating mode transitions between driver and driver assistance systems. We propose a driver behavior recognition method using Hidden Markov Models (HMMs) to characterize and detect driving maneuvers and place it in the framework of a cognitive model of human behavior. HMM-based steering behavior models for emergency and normal lane changes as well as for lane keeping were developed using a moving base driving simulator. Analysis of these models after training and recognition tests showed that driver behavior modeling and recognition of different types of lane changes is possible using HMMs.

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تاریخ انتشار 2000