An ABS control algorithm based on extremum seeking is presented in this brief. The optimum slip ratio between the tire patch and the road is searched online without having to estimate road friction conditions. This is achieved by adapting the extremum-seeking algorithm as a self-optimization routine that seeks the peak point of the tire force-slip curve. As an additional novelty, the proposed algorithm incorporates driver steering input into the optimization procedure to determine the operating region of the tires on the "tire force"-"slip ratio" characteristic-curve. The algorithm operates the tires near the peak point of the force-slip curve during straight line braking. When the driver demands lateral motion in addition to braking, the operating regions of the tires are modified automatically, for improving the lateral stability of the vehicle by increasing the tire lateral forces. A validated, full vehicle model is presented and used in a simulation study to demonstrate the effectiveness of the proposed approach. Simulation results show the benefits of the proposed ABS controller.Index Terms-ABS control problem, extremum-seeking algorithm (ESA), lateral stability, optimum slip ratio.

This paper presents the cooperative adaptive cruise control implementation of Team Mekar at the Grand Cooperative Driving Challenge (GCDC). The Team Mekar vehicle used a dSpace microautobox for access to the vehicle controller area network bus and for control of the autonomous throttle intervention and the electric-motor-operated brake pedal. The vehicle was equipped with real-time kinematic Global Positioning System (RTK GPS) and an IEEE 802.11p modem installed in an onboard computer for vehicle-to-vehicle (V2V) communication. The Team Mekar vehicle did not have an original-equipment-manufacturer-supplied adaptive cruise control (ACC). ACC/Cooperative adaptive cruise control (CACC) based on V2V-communicated GPS position/velocity and preceding vehicle acceleration feedforward were implemented in the Team Mekar vehicle. This paper presents experimental and simulation results of the Team Mekar CACC implementation, along with a discussion of the problems encountered during the GCDC cooperative mobility runs

Unsymmetrical loading on a car like μ-split braking, side wind forces, or unilateral loss of tire pressure results in unexpected yaw disturbances that require yaw stabilization either by the driver or by an automatic driver-assist system. The use of two-degrees-of-freedom control architecture known as the model regulator is investigated here as a robust steering controller for such yaw stabilization tasks in a driver-assist system. The yaw stability-enhancing steering controller is designed in the parameter space to satisfy a frequency-domain mixed sensitivity constraint. To evaluate the resulting controller design, a real-time hardware-in-the-loop simulator is developed. Steering tests with and without the controller in this hardware-in-the-loop setup allow the driver to see the effect of the proposed controller to improve vehicle-handling quality. The hardware-in-the-loop simulation setup can also be used for real-time driver-in-the-loop simulation of other vehicle control systems.

No abstract

No abstract