Intelligent Adaptive Cruise Control System Design and Implementation İslam Kılıç Electrical and Electronics Engineering Eskisehir Osmangazi University Eskisehir, TURKEY islam.kilic@outlook.com Ahmet Yazıcı Computer Engineering Department Eskisehir Osmangazi University Eskisehir, TURKEY ayazici@ogu.edu.tr Ömür Yıldız Savronik Electronics Inc. Eskisehir, TURKEY omur.yildiz@savronik.com Mustafa Özçelikors Electrical and Electronics Engineering Eskisehir Osmangazi University Eskisehir, TURKEY mozcelikors@gmail.com Atakan Ondoğan Electrical and Electronics Engineering Eskisehir Osmangazi University Eskisehir, TURKEY atakanondogan@outlook.com Abstract- Advanced driver assistance systems (ADAS) have a critical role in the development of the active safety systems for vehicles. There are various sub technologies like Adaptive cruise control (ACC), Collision avoidance system, Blind spot detection etc. under ADAS. All these technologies are also accepted as the preliminary technology of autonomous driving. Therefore, during development of these technologies using a system of system (SOS) control approach would help both decreasing the development costs and unifying all these technologies under autonomous driving. In this paper, a SOS based intelligent ACC system design is proposed. The ACC system has high level control, low level control and sensor units. Keywords: ADAS, Intelligent Adaptive Cruise Control, Model Predictive Control, ACC subsystems, Radar. 1 Introduction Advanced driver assistance systems (ADAS) are increasingly used in automobile in last decade. The advanced sensor technology and the increasing computational power help widespread of the ADAS [1]. It requires many subsystems to work in coordination. ADAS is also accepted as the preliminary technology of autonomous driving which requires large scale system to work in coordination [2]. ADAS may realize a shared understanding of driving decisions and actions. Thus, it could be able to alert driver about possible dangerous situations i.e. lane departure warning. Moreover, it could recognize unconscious by-pass automation [3]. Adaptive cruise control (ACC) is one of the sub technologies in the area of the ADAS. In the literature, there are various studies in this area [1]-[14]. It helps increasing the driving comfort and the driving safety. The ACC system adapts the speed of the host car according to target(leading) car speed and track the safety distance [4]. ACC systems mainly consist of control and sensor subsystems [5]. The sensor subsystem gives information about environment in vision range. Meaningful data for ACC is extracted from raw sensor data in this subsystem. Long range radar sensors are widely used in the ACC systems [1], [4]. There are various control algorithms [6], [7] for the ACC system. In [6], a model predictive control algorithm is used. This algorithm predicts the vehicle acceleration or deceleration for N step future and, then generates the required control inputs. The jerk is also considered for the comfort in this system. Fuzzy logic controller is also used for the ACC [7]. Inputs of the system are relative speed error and distance error. These crisp inputs are converted to fuzzy membership functions and rules are defined for fuzzy inference system. Output of the system is the required deceleration. Defuzzyfication process is applied to output and required crisp deceleration is extracted. In this study, an intelligent ACC system which is based on the autonomous driving control architecture, is proposed. It consists of high level control, low level control, and sensor unit subsystems. It has a system of system(SOS) approach such that other technologies in the area of the ADAS can use the same architecture. In section 2, the current ACC technology and algorithms are presented. The proposed system is given in section 3. In section 4, the simulation and experimental results are given. Section 5 is the conclusion. 2 Preliminaries: The subsystems in ACC The ACC system mainly consists of a Human machine interaction(HMI), Control and Sensor unit to work in coordination as in figure 1.