Nonlinear Model Predictive Control approach in design of Adaptive Cruise Control with automated switching to cruise control Payman Shakouri n , Andrzej Ordys School of Mechanical and Automotive Engineering, Kingston University London, Friars Avenue, Roehampton Vale, London SW15 3DW, UK article info Article history: Received 15 July 2011 Accepted 17 January 2014 Available online 17 February 2014 Keywords: Vehicle dynamic Adaptive Cruise Control Model Predictive Control Nonlinear Model Predictive Control State-dependent linear model abstract In this paper the Nonlinear Model Predictive Control (NMPC) is used in designing of Adaptive Cruise Control (ACC) and Cruise Control (CC) systems. An algorithm is proposed to carry out automatic switching between ACC and CC, depending on the situation in front of the vehicle. Also, an algorithm based on MPC equation is devised to obtain the prediction of future reference trajectories corresponding to desired speed and distance. NMPC equation used in this paper is developed based on state-dependent representation of linear models corresponding to the modes of the operation: accelerating-throttle is active and braking-brake is active. The developed automated ACC system is tested in simulation against different scenarios proving good performance of the system. Furthermore, the results of proposed control algorithm based on NMPC methods are compared with a different ACC structure. & 2014 Elsevier Ltd. All rights reserved. 1. Introduction Adaptive Cruise Control (ACC) is an extension of the Cruise Control (CC) system which is capable of adjusting the velocity of the vehicle depending on the behaviour of other vehicles moving in front, by applying the brake and modulating the throttle to produce the necessary power (Xiao & Gao, 2010). This system uses the radar or other sensory devices to measure the distance between vehicles (Moon, Moon, & Yi, 2009; Winner, Winter, & Lucas, 2003). The extended version of the ACC is so-called ACC stop & go. Unlike the conventional ACC, which is unable to operate at speed below 30 km/h, the stop & go function, in combination with automatic transmission can operate at low speed and main- tain the safe gap to the vehicle in front all the way down to standstill. Along with the CC and ACC systems another version of the velocity controlling system has been introduced, so-called Look Ahead Cruise Controller (Hellström, Ivarsson, Åslund, & Nielsen, 2009; Kozica, 2005; Keulen et al., 2009). It uses the information about the road ahead of the vehicle to reduce the fuel consump- tion. For that purpose some “derivative velocity controlling sys- tem” is introduced, for instance; Predictive Cruise Control (PCC) (Lattemann, Neiss, Terwen, & Connolly, 2004), Expert Cruise Control (ECC) (Wingren, 2005) or Model Predictive control (MPC), (Axehill & Sjöberg, 2003). It is known that ACC is capable of managing the traffic flow. By making platoons of vehicles it improves highway capacity. In ACC mode many vehicles can move at highway speed with small inter- distance which can increase density of the vehicles on the high- way. It also has the positive effect on the optimisation of fuel consumption especially for heavy vehicles. This is due to signifi- cant effect of the aerodynamic drag dependent on the cross section front area for such vehicles (Vahidi & Eskandarian, 2003). On this matter, Cooperative Adaptive Cruise Control (CACC) has been proposed as an advance in the area of Intelligent Transporta- tion Systems (ITS) – to increase traffic efficiency and to improve passenger comfort and safety (Desjardins & Chaib-draa, 2011; Shladover et al., 2009; ven Arem, ven Driel, & Visser, 2006; Ploeg, Serrarens, & Heijenk, 2011). CACC requires that the distances between vehicles are controlled to a high precision and this in turn implies the use of direct communication – exchange of informa- tion between the vehicles in the platoon. This may be accom- plished in two ways; Inter-Vehicle Communication (IVC) and Roadside-to-Vehicle Communication. IVC is conducted by exchan- ging information about congestion, incidents or emergency between the follower and leader vehicles through wireless com- munication. Other automotive safety system such as collision avoidance has also been incorporated in the vehicle to further assist the driver in enhancing safety and preventing accident with a sequence of warnings and active intervention (Isermann, Mannale, & Schmitt, 2012; Moon et al., 2009). Furthermore, since many automotive safety systems such as ACC, collision avoidance or emergency lane assist require accurate information about both road shape and object position, researches have been carried out on advancing the technologies applied for capturing those Contents lists available at ScienceDirect journal homepage: www.elsevier.com/locate/conengprac Control Engineering Practice 0967-0661/$ - see front matter & 2014 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.conengprac.2014.01.016 n Corresponding author. E-mail address: p.shakouri@kingston.ac.uk (P. Shakouri). Control Engineering Practice 26 (2014) 160–177