DocumentCode :
181734
Title :
Driver intention recognition method based on comprehensive lane-change environment assessment
Author :
Jieyun Ding ; Ruina Dang ; Jianqiang Wang ; Keqiang Li
Author_Institution :
State Key Lab. of Automotive Safety & Energy, Tsinghua Univ., Beijing, China
fYear :
2014
fDate :
8-11 June 2014
Firstpage :
214
Lastpage :
220
Abstract :
A driver intention recognition method designed for lateral driving assistance systems is proposed based on comprehensive lane-change environment assessment. A new symbol, Comprehensive Decision Index is designed using fuzzy method to assess the influence of surrounding traffic environment on drivers´ lane-change decisions. Meanwhile, Hidden Markov Model is applied to recognize driver intention. In the model structure, multiple observation variables are used and the elements´ density functions in observation matrix are given the form of Gaussian 3-component mixture model. Finally, data of lane changes performed on driving simulator are used to testify the performance of the proposed method. The results show that the Comprehensive Decision Index is able to make an effective assessment on the environment´s influence on drivers´ lane-change decisions and the algorithm using it as one of the observation signals can both guarantee the accuracy of recognition results and improve the real-time performance.
Keywords :
Gaussian processes; driver information systems; fuzzy set theory; hidden Markov models; Gaussian 3-component mixture model; comprehensive decision index; comprehensive lane-change environment assessment; driver intention recognition method; driving simulator; fuzzy method; hidden Markov model; lateral driving assistance systems; Intelligent vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium Proceedings, 2014 IEEE
Conference_Location :
Dearborn, MI
Type :
conf
DOI :
10.1109/IVS.2014.6856483
Filename :
6856483
Link To Document :
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