There is a broad range of robotics technologies that are currently being applied to the generic topic of intelligent transportation systems (ITS). One of the most important research topics in this field is adaptive cruise control (ACC), aiming at adapting the vehicle speed to a predefined value while keeping a safe gap with regard to potential obstacles. For this purpose, a monocular vision system provides the distance between the ego vehicle and the preceding vehicle on the road. The complete system can be understood as a vision-based ACC controller, based on fuzzy logic, which assists the velocity vehicle control offering driving strategies and actuation over the throttle of a car. This controller is embedded in an automatic driving system installed in two testbed mass-produced cars operating in a real environment. The results obtained in these experiments show a very good performance of the vision-based gap controller, which is adaptable to all speeds and safe gap selections.