In its rather short history robotic research has come a long way in the half century since it started to exist as a noticeable scientic eld. Due to its roots in engineering, computer science, mathematics, and several other 'classical' scientic branches,a grand diversity of methodologies and approaches existed from the very beginning. Hence, the researchers in this eld are in particular used to adopting ideas that originate in other elds. As a fairly logical consequence of this, scientists tended to biology during the 1970s in order to nd approaches that are ideally adapted to the conditions of our natural environment. Doing so allows for introducing principles to robotics that have already shown their great potential by prevailing in a tough evolutionary selection process for millions of years. The variety of these approaches spans from efficient locomotion, to sensor processing methodologies and all the way to control architectures. Thus, the full spectrum of challenges for autonomous interaction with the surroundings while pursuing a task can be covered by such means. A feature that has proven to be amongst the most challenging to recreate is the human ability of biped locomotion. This is mainly caused by the fact that walking,running and so on are highly complex processes involving the need for energy efficient actuation, sophisticated control architectures and algorithms, and an elaborate mechanical design while at the same time posting restrictions concerning stability and weight. However, it is of special interest since our environment is favoring this specic kind of locomotion and thus promises to open up an enormous potential if mastered. More than the mere scientic interest, it is the fascination of understanding and recreating parts of oneself that drives the ongoing eorts in this area of research. The fact that this is not at all an easy task to tackle is not only caused by the highly dynamical processes but also has its roots in the challenging design process. That is because it cannot be limited to just one aspect like e.g. the control architecture, actuation, sensors, or mechanical design alone. Each aspect has to be incorporated into a sound general concept in order to allow for a successful outcome in the end. Since control is in this context inseparably coupled with the mechanics of the system, both has to be dealt with here.
Nowadays, vehicle control systems such as anti-lock braking systems, electronic stability control, and cruise control systems yield many advantages. The electronic control units that are deployed in this specific application domain are embedded systems that are integrated in larger systems to achieve predefined applications. Embedded systems consist of embedded hardware and a large software part. Model-based development for embedded systems offers significant software-development benefits that are pointed out in this thesis. The vehicle control system Adaptive Cruise Control is developed in this thesis using a model-based software development process for embedded systems. As a modern industrial design tool that is prevalent in this domain, simulink,is used for modeling the environment, the system behavior, for determining controller parameters, and for simulation purposes. Using an appropriate toolchain, the embedded code is automatically generated. The adaptive cruise control system could be successfully implemented and tested within this short timespan using a waterfall model without increments. The vehicle plant and important filters are fully deduced in detail. Therefore, the design of further vehicle control systems needs less effort for development and precise simulation.