Connected Cruise Control (CCC) is a system, that is currently under development within a HTAS project. CCC aims to improve throughput in dense motorway traffic by advising drivers how to drive. The advice will integrate a lane advice, a headway advice and speed advice. The CCC advice will be provided via a nomadic device, using input from traffic flow predictions, loop data, floating car data and data of the direct surroundings from a camera inside the vehicle. The advantage of CCC lies in the potentially rapid implementation, in contrast to Cooperative Adaptive Cruise Control (CACC) systems. An additional advantage is the support in terms of lateral driver behaviour advice, However, since it is an advisory system, the actual effectiveness of the system totally depends on the driver response: Is a driver capable and willing to adhere to the advice? If not, the CCC system will not have any beneficial effect on throughput. A way to include the driver capabilities and willingness to accept the advice is to focus on use cases. Also, it is important to include the driver in the actual design by early driving simulator experiments and including Human Factors knowledge in the design of the HMI (Human Machine lnterface). A large user survey with over 230 respondents has been done, looking into driver frustratÌons in driving in dense motorway traffic. lf the system can reduce some of the frustrations, acceptance of the rsystem will increase. This paper will discuss the possibilities and need of ADAS to solve specific driver problems in congestion, and discusses the outcomes of a first driving simulator experiment related to headway advice. The possibilities for driver feedback are discussed and the next set of experiments for the CCC system from a human factors point of view are discussed.