Design and Implementation of Intelligent Overtaking System Using Model Predictive Control

In this paper, an intelligent overtaking system is developed, which includes overtaking possibility strategy (OPS), autonomous overtaking control scheme, and then successfully implemented on an autonomous vehicle. The OPS is based on the image recognition technology for detecting surrounding vehicles and lane lines, and further calculate the time to lane crossing (TLC) as the basis of overtaking or keep within your lane. Thus, this research can implement two functions, such as lane following and overtake. An autonomous overtaking control scheme using the successive linearization based model predictive control is developed to derive the appropriate throttle, brake and steering angle actuators for a car. This control approach can provide stable and safety overtaking maneuvers effectively. Finally, the proposed system has been incorporated into an electrical golf car and tested in a real-road environment, where the communication of the whole sensors, actuators as well as vehicle control unit (VCU) are used the controller area network (CAN) bus to realize control and data collection. Some of the experimental results demonstrate the feasibility of using the overtaking strategies by considering various traffic situations.