Title :
Roll prediction-based optimal control for safe path following
Author :
Sanghyun Hong ; Hedrick, J. Karl
Author_Institution :
Dept. of Mech. Eng., Univ. of California, Berkeley, Berkeley, CA, USA
Abstract :
Autonomous vehicles can risk dangerous rollover if they corner without taking roll motion into consideration. This paper proposes a control algorithm to follow a curved road while simultaneously preventing rollover. Model predictive control is applied to minimize roll motion throughout cornering. The prediction of vehicle state is based on a four-wheel nonlinear vehicle model with roll dynamics and a tire brush model. Full braking is utilized as a control actuator to achieve an optimal balance in the trade-off between vehicle speed and roll motion. CarSim simulations show the performance of the proposed control approach and the influence of vehicle parameters on control performance.
Keywords :
braking; mobile robots; motion control; optimal control; path planning; predictive control; road vehicles; tyres; vehicle dynamics; CarSim simulation; autonomous vehicle; control actuator; control algorithm; control performance; curved road; four-wheel nonlinear vehicle model; full braking; model predictive control; optimal balance; roll dynamics; roll motion; roll prediction-based optimal control; safe path following; tire brush model; vehicle parameter; vehicle speed; vehicle state; Acceleration; Force; Simulation; Tires; Vehicle dynamics; Vehicles; Wheels;
Conference_Titel :
American Control Conference (ACC), 2015
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4799-8685-9
DOI :
10.1109/ACC.2015.7171835