This article presents the use of a model-based approach for the development of real-time, embedded, hybrid control software. The concepts are illustrated with a scenario involving speed-profile tracking and vehicle following applications for passenger vehicles. The model-based approach was developed in partnership between the University of California at Berkeley, Ford Research Labs, and GM. An ACC and CACC system has been tested in prototype phase, both at highway speeds and in stop-and-go situations. Robotic technologies, such as range, velocity, and acceleration measurements, and their processing and fusion were used as part of the system. In addition, vehicles can present very nonlinear behavior, especially at low speeds, and their control presents a formidable challenge. The problem domain of intelligent cruise-control applications has been described in detail, along with control and software development methodologies. We are currently working on applying the same model-based approach to the development of intelligent cruise-control systems for automated transit buses.