During the last century, there has been considerable economic growth and development of cities around the world. The growth has led to an expansion of car-ownership and ultimately increased congestion of the road network. Traffic engineers and transport planners have attempted to mitigate the consequences of congestion of motorways and freeways using a number of techniques. One of which has been Ramp Metering, that regulates the flow of traffic entering the motorway in order to improve mainline flow and minimise congestion. Many ramp metering algorithms have been developed based on a variety of strategies. The more advanced algorithms allow coordination between a series of subsequent on-ramps to improve the performance of the network holistically. One of the leading ramp metering solutions is the SCATS Ramp Metering System (SRMS). This study evaluates the effectiveness of the SRMS using state-of-the-art microsimulation modelling. SRMS is implemented in AIMSUN using the SCATSIM interface applied to a freeway stretch of over 25km with seventeen on-ramps,. Arterial roads parallel to the freeway are included in the study to account for the route diversion effects due to on-ramp delays. The calibration of the coordinated ramp meters was conducted in conjunction with RMS and a number of different demand conditions were modelled to understand the sensitivity of ramp metering. The study considers a series of key performance metrics discussed within the literature and highlights the strengths and limitations of the microsimulation modelling paradigm.