During the last decades the road traffic has increased tremendously leading to congestion, safety issues and increased environmental impacts. As a result, many countries are continuously trying to find improvements and new solutions to solve these issues. One way of improving the traffic conditions is by the use of so called intelligent transport systems, where information and communication technologies are being used for traffic management and control. One such system commonly used for traffic management purposes are variable speed limit systems. These systems are making use of signs to show speed limits adjusted to the prevailing road or traffic conditions. The rapid development in telecommunication technologies has enabled communication between vehicles, and between vehicles and the infrastructure, so called cooperative systems. This opens up for  the possibility to further improve the performance of a standard variable speed limit system by adding cooperative system features.

The overall aim of this thesis is to investigate the potential benefits of incorporating infrastructure to vehicle communication and autonomous control to an existing variable speed limit system. We show how such a cooperative variable speed limit system can be modeled and evaluated by the use of microscopic traffic simulation. Results from the evaluation indicate increased flow harmonization in terms of narrowing of the acceleration rate distribution and reduced exhaust emissions.

Further, we compare four control algorithms for deciding on speed limits in variable speed limit systems. Differences in the resulting traffic performance between the control algorithms are quantified by the use of microscopic traffic simulation. It is concluded that the dened objective for the algorithms have a decisive influence on the effects of the variable speed limit system.

The results from this thesis are useful for further development of variable speed limit systems, both with respect to incorporating cooperative features and by improving the speed setting control algorithms.