Model predictive assisting control of vehicle following task based on driver model
2010 IEEE International Conference on Control Applications, 2010•ieeexplore.ieee.org
A personalized driver assisting system that makes use of the driver's behavior model is
developed. As a model of driving behavior, the Probability-weighted ARX (PrARX) model, a
type of hybrid dynamical system models, is introduced. A PrARX model that describes the
driver's vehicle-following skill on expressways is identified using a simple gradient descent
algorithm from actual driving data collected on a driving simulator. The obtained PrARX
model describes the driver's logical decision making as well as continuous maneuver in a …
developed. As a model of driving behavior, the Probability-weighted ARX (PrARX) model, a
type of hybrid dynamical system models, is introduced. A PrARX model that describes the
driver's vehicle-following skill on expressways is identified using a simple gradient descent
algorithm from actual driving data collected on a driving simulator. The obtained PrARX
model describes the driver's logical decision making as well as continuous maneuver in a …
A personalized driver assisting system that makes use of the driver's behavior model is developed. As a model of driving behavior, the Probability-weighted ARX (PrARX) model, a type of hybrid dynamical system models, is introduced. A PrARX model that describes the driver's vehicle-following skill on expressways is identified using a simple gradient descent algorithm from actual driving data collected on a driving simulator. The obtained PrARX model describes the driver's logical decision making as well as continuous maneuver in a uniform manner. Finally, the optimization of the braking assist is formulated as a mixed-integer linear programming (MILP) problem using the identified driver model, and computed online in the model predictive control framework.
ieeexplore.ieee.org
以上显示的是最相近的搜索结果。 查看全部搜索结果