A Driver Behavior Recognition Method Based on a Driver Model Framework

Abstract

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.

Original document

The different versions of the original document can be found in:

• http://pdfs.semanticscholar.org/1c99/600451dedd42dcdc02ed6cfcaa81e70e9899.pdf

• http://web.mit.edu/people/amliu/Papers/SAE2000_Kuge.pdf,

https://www.sae.org/publications/technical-papers/content/2000-01-0349,

https://stuff.mit.edu/people/amliu/Papers/SAE2000_Kuge.pdf,

https://www.mit.edu/~amliu/Papers/SAE2000_Kuge.pdf,

http://papers.sae.org/2000-01-0349,

https://trid.trb.org/view/669619,

https://www.researchgate.net/profile/Tomohiro_Yamamura/publication/244955518_A_Driver_Behavior_Recognition_Method_Based_on_a_Driver_Model_Framework/links/0c96053105f215fd08000000.pdf?disableCoverPage=true,

https://academic.microsoft.com/#/detail/2104425135

• https://www.sae.org/gsdownload/?prodCd=2000-01-0349,

http://dx.doi.org/10.4271/2000-01-0349