Traffic congestion is a problem experienced daily by most of us. Among various traffic management schemes, efficient utilisation of the existing roadside infrastructure combined with in-vehicle technologies offers a promising solution to address traffic congestion and related problems. This approach has resulted in the development of Intelligent Vehicle Highway Systems (IVHSs). An IVHS basically consists of roadside infrastructures interacting with automated intelligent vehicles (IVs) that are organised in a closely spaced groups called platoons. With platooning, more vehicles can be accommodated on the highway, thus increasing the traffic flow. In the present situation, most of the existing traffic management and control centers use conventional roadside-based control measures to improve the traffic performance. The objective of the thesis is to provide a framework and a systematic approach for integrating traffic control and management methods into the IVHS. The focus of the thesis is on combining the control capabilities offered by automated platoons with those of the roadside infrastructure. We aim at developing traffic management and control methods to be implemented at various control levels, by incorporating intelligence from and within vehicles. Thus the roadside controllers use both IV-based and conventional traffic control measures for controlling and managing platoons, such that the performance of the traffic is improved.