| MODEL PREDICTIVE CONTROL BASED MULTIFUNCTIONAL
ADVANCED DRIVER-ASSISTANCE SYSTEM SPECIALIZED FOR
REAR-END COLLISION AVOIDANCE |
| Hwangjae Lee , Seibum Ben Choi |
| Department of Mechanical Engineering, KAIST |
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| ABSTRACT |
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This paper presents the model predictive control (MPC) based multifunctional advanced driver-assistance
system (MADAS) that is optimized for rear-end collision avoidance. First, the system’s operation is judged by considering the
driver’s intention of avoidance and the possibility of avoiding obstacle vehicles. Once the system is activated, the lateral tire
force corresponding to the driver’s steering input, which is essential for collision avoidance, is realized with the highest priority.
The use of each tire friction circle is then maximized by utilizing available tire forces for braking through quadratic
programming. While the MADAS ensures the lateral maneuver and deceleration of the vehicle, the system still can generate
additional yaw moment calculated from the MPC, the upper level controller, to track the driver’s desired yaw rate or prevent
the vehicle from becoming unstable. The nonlinearity inevitably encountered in maximizing tire forces is reflected through the
extended bicycle model and the combined brushed tire model. The proposed system is verified by the vehicle dynamics software
CarSim, and the simulation results show that the MADAS performs better in rear-end collision avoidance situations than
conventional advanced driver-assistance systems (ADAS). |
| Key Words:
Collision avoidance, Model predictive control (MPC), Friction circle, Advanced driver-assistance system
(ADAS), Nonlinearity, Quadratic programming |
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Corresponding Author.
Seibum Ben Choi , Email. 
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