Abstract-The automation of the overtaking maneuver is considered to be one of the toughest challenges in the development of autonomous vehicles. This operation involves two vehicles (the overtaking and the overtaken) cooperatively driving, as well as the surveillance of any other vehicles that are involved in the maneuver. This operation consists of two lane changes-one from the right to the left lane of the road, and the other is to return to the right lane after passing. Lane-change maneuvers have been used to move into or out of a circulation lane or platoon; however, overtaking operations have not received much coverage in the literature. In this paper, we present an overtaking system for autonomous vehicles equipped with path-tracking and lane-change capabilities. The system uses fuzzy controllers that mimic human behavior and reactions during overtaking maneuvers. The system is based on the information that is supplied by a high-precision Global Positioning System and a wireless network environment. It is able to drive an automated vehicle and overtake a second vehicle that is driving in the same lane of the road.Index Terms-Fuzzy control, hybrid control, intelligent control, proportional-integral differential (PID) control, road vehicle control.

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There is a broad range of diverse technologies under the generic topic of intelligent transportation systems (ITS) that holds the answer to many of the transportation problems. In this paper, one approach to ITS is presented. One of the most important research topics in this field is adaptive cruise control (ACC). The main features of this kind of controller are the adaptation of the speed of the car to a predefined one and the keeping of a safe gap between the controlled car and the preceding vehicle on the road. We present an ACC controller based on fuzzy logic, which assists the speed and distance vehicle control, offering driving strategies and actuation over the throttle of a car. The driving information is supplied by the car tachometer and a RTK differential GPS, and the actuation over the car is made through an electronic interface that simulates the electrical signal of the accelerator pedal directly to the onboard computer. This control is embedded in an automatic driving system installed in two testbed mass-produced cars instrumented for testing the work of these controllers in a real environment. The results obtained in these experiments show a very good performance of the gap controller, which is adaptable to all the speeds and safe gap selections. Index Terms-Autonomous vehicles, longitudinal control, intelligent vehicles, field experiments, fuzzy logic, adaptive cruise control (ACC), safe gap, Stop&Go, platoon driving, wireless communications, intelligent transportation systems (ITS). I. INTRODUCTION I NTELLIGENT transportation systems (ITS) apply robotic techniques to achieve safe and efficient driving. In the automotive industry, sensors are mainly used to give information to the driver and, in some cases, they are connected to a computer that performs some guiding actions, attempting to minimize injuries and to prevent collisions [1]. One of the applications of ITS is the providing of assistance to the control of some of the vehicle elements, like the throttle pedal and consequently, the speed-control assistance. A cruise control (CC) system is a common application of these techniques. It consists of maintaining the vehicle speed at a user (driver) pre-set speed. These kind of systems are already mass installed in top of the line end Manuscript