DocumentCode
2378760
Title
Real-time driver characterization during car following using stochastic evolving models
Author
Filev, Dimitar ; Jianbo Lu ; Tseng, Fan-Shuo ; Prakah-Asante, K.
Author_Institution
Powertrain Control Res. & Adv. Eng., Ford Motor Co., Dearborn, MI, USA
fYear
2011
fDate
9-12 Oct. 2011
Firstpage
1031
Lastpage
1036
Abstract
This paper studies characterizing the driving behavior during steady-state and transient car-following. An approach utilizing the online learning of an evolving Takagi-Sugeno fuzzy model that is combined with a probabilistic model is applied to capture the multi-model and evolving nature of the driving behavior. The approach is validated by testing on a vehicle during different driving conditions.
Keywords
driver information systems; fuzzy set theory; learning (artificial intelligence); stochastic processes; evolving Takagi-Sugeno fuzzy model; online learning; probabilistic model; real time driver characterization; steady state car following; stochastic evolving models; transient car following; Data models; Real time systems; Roads; Steady-state; Stochastic processes; Vectors; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location
Anchorage, AK
ISSN
1062-922X
Print_ISBN
978-1-4577-0652-3
Type
conf
DOI
10.1109/ICSMC.2011.6083810
Filename
6083810
Link To Document