DocumentCode :
3501073
Title :
An experimental study on longitudinal driving assistance based on model predictive control
Author :
Okuda, Haruhisa ; Tazaki, Yuichi ; Suzuki, Takumi
Author_Institution :
Nagoya Univ. Green Mobility Collaborative Res. Center, Nagoya, Japan
fYear :
2013
fDate :
23-26 June 2013
Firstpage :
183
Lastpage :
188
Abstract :
This paper presents a novel personalized driver assistance system(PDAS) based on the model predictive control(MPC) together with a continuous/discrete hybrid dynamical system model of the driving behavior. First of all, the driving behavior is identified as the piecewise ARX model. Then, it is explicitly embedded in the optimization problem for finding the optimal assisting output. Since the driving behavior includes some binary variables, the optimization problem is formulated as the mixed integer programming. Some adaptation mechanism to accommodate to the change of the situation is particularly discussed. Finally, the proposed scheme is tested by using the real vehicle wherein the real-time assisting control based on MPC is implemented.
Keywords :
continuous systems; discrete systems; driver information systems; integer programming; predictive control; time-varying systems; MPC; PDAS; continuous dynamical system model; discrete hybrid dynamical system model; driving behavior; longitudinal driving assistance; mixed integer programming; model predictive control; optimization problem; personalized driver assistance system; piecewise ARX model; piecewise auto regressive exogenous model; real-time assisting control; Acceleration; Hidden Markov models; Linear programming; Mathematical model; Optimization; Predictive models; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2013 IEEE
Conference_Location :
Gold Coast, QLD
ISSN :
1931-0587
Print_ISBN :
978-1-4673-2754-1
Type :
conf
DOI :
10.1109/IVS.2013.6629468
Filename :
6629468
Link To Document :
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