A Study of Individual Characteristics of Driving Behavior based on Hidden Markov Model
Drivers’ individual difference is one of the key factors to influence the accuracy of driving behavior models. The accuracy of the model should include the effect characteristics of individual difference on driving behavior. The overtaking process was the object of research in this paper. The operation data of accelerator and steering wheel of each driver was analyzed with the character of time series. Based on both of the operation data, hidden markov model (HMM) was employed to model the individual characteristics of driving behavior. Two individual models were built for each driver, one trained from accelerator data and one learned from steering wheel angle data. The models can be used to identify different drivers and the accuracy can reach to 85%. It proved that individual difference is one factor which can’t be ignored in driving behavior model, and HMM has effectiveness in modeling it.
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Supplemental Notes:
- Abstract reprinted with permission from Intelligent Transportation Society of America.
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Corporate Authors:
1100 17th Street, NW, 12th Floor
Washington, DC United States 20036 -
Authors:
- Zhang, Xingjian
- Zhao, Xiaohua
- Rong, Jian
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Conference:
- 19th ITS World Congress
- Location: Vienna , Austria
- Date: 2012-10-22 to 2012-10-26
- Publication Date: 2012
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Maps; References; Tables;
- Pagination: 11p
- Monograph Title: 19th ITS World Congress, Vienna, Austria, 22 to 26 October 2012
Subject/Index Terms
- TRT Terms: Accelerators (Devices); Drivers; Markov processes; Passing; Steering wheels; Time series; Travel behavior
- Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors; I73: Traffic Control; I83: Accidents and the Human Factor;
Filing Info
- Accession Number: 01501702
- Record Type: Publication
- Files: TRIS
- Created Date: Dec 23 2013 7:52AM