Abstract
The automation of road vehicles has become a necessity to improve the efficiency and safety of this system. In a vehicle formation it is important to maintain a safety distance between the vehicles. The control of a vehicle spacing distance and longitudinal velocity can be achieved through the implementation of a model-based predictive controller. This implementation of a cooperative adaptive cruise control allows the access of another vehicle state information through vehicular communication technology and promote state prediction and ultimately system stability. The optimization algorithm performs the computation of the control input in a control horizon window and ensures that the spacing error takes only positive values. The results of the proposed controller are evaluated through the computational tool Simulink in the two-vehicle platoon. The controller is implemented in the precedent vehicle. To assess the performance of the proposed controller different control parameters and constraints were used.
Highlights
In the last few decades, the amount of road traffic as increased dramatically, which led to a clear road congestion issue that has become more relevant in recent years(Dey et al 2015; van Arem, van Driel, and Visser 2006)
To analyze the performance of the proposed model predictive control, simulations based on Simulink have been carried out by performing tests with different control parameters and constraints
The present paper focuses on model predictive control (MPC) in vehicle platoon control
Summary
In the last few decades, the amount of road traffic as increased dramatically, which led to a clear road congestion issue that has become more relevant in recent years(Dey et al 2015; van Arem, van Driel, and Visser 2006). At the turn of the century, the issue of automated or intelligent transportation has become more relevant and there has an effort to improve highway capacity and safety(Vahidi and Eskandarian 2003). During this time a research and development program of the University of California has founded, the California Partners for Advanced Transportation Technology (PATH), to deal with intelligent transportation systems. Among their research it is possible to identify relevant work from complex Automated Highway systems and string stability, to cruise control systems
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