Model Predictive Control for Feasible Region of Active Collision Avoidance

2017 ◽  
Author(s):  
Guirong Zhuo ◽  
Cheng Wu ◽  
Fengbo Zhang
Keyword(s):  
Model Predictive Control ◽  
Collision Avoidance ◽  
Predictive Control ◽  
Feasible Region

scholarly journals Collision Avoidance Effects on the Mobility of a UAV Swarm Using Chaotic Ant Colony with Model Predictive Control

2018 ◽  
Vol 93 (1-2) ◽  
pp. 227-243 ◽  
Author(s):  
Jan Dentler ◽  
Martin Rosalie ◽  
Grégoire Danoy ◽  
Pascal Bouvry ◽  
Somasundar Kannan ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Collision Avoidance ◽  
Predictive Control ◽  
Ant Colony ◽  
Uav Swarm

Active steering control for autonomous vehicles based on a driver-in-the-loop platform: A case study of collision avoidance

2019 ◽  
Vol 233 (10) ◽  
pp. 1422-1437
Author(s):  
Keji Chen ◽  
Xiaofei Pei ◽  
Daoyuan Sun ◽  
Zhenfu Chen ◽  
Xuexun Guo ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Model Predictive Control ◽  
Collision Avoidance ◽  
Predictive Control ◽  
Autonomous Vehicle ◽  
Steering Control ◽  
Safe Driving ◽  
Active Steering ◽  
Active Steering Control

Leveraging the advancements in sensor and mapping technologies, the collision-free autonomous vehicle becomes possible in the future. In this article, a case study of collision avoidance by active steering control is presented and verified by a driver-in-the-loop platform. The proposed control system integrates a risk assessment algorithm and a hierarchical model predictive control approach to ensure a safe driving. First, a fuzzy logic is used to estimate the potential conflict. Besides, a nonlinear model predictive control is introduced in the upper layer of the model predictive controller to generate a collision-free trajectory. Furthermore, the lower layer determines the optimal steering angle based on the linear time-variant model predictive control to follow the replanning path. The performance of the controller has been evaluated in the real-time driver-in-the-loop test. The results show that the autonomous vehicle is able to avoid the collision with the surrounding vehicle that is operated by a real driver, and the performance of collision avoidance is improved by means of the risk assessment.

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