The steady increase in vehicular connections to other vehicles, communication networks and other systems has introduced the concept of the Internet of Vehicles (IoV). In order to keep pace with this evolution, the effect of non-uniform road traffic patterns on the design of IoV networks must be taken into consideration. This traffic-aware approach is necessary because it requires the use of observable traffic patterns from existing data to depict the behaviour and individual characteristics of vehicles which is fundamental to the design and implementation of the IoV and its related applications. This work fuses data science, road traffic theory and microscopic traffic simulation principles to model vehicular traffic patterns using a section of the road network from the Luxembourg data set. As an extension of what has been done in other works, this approach uses a wider range of traffic data, varying traffic types and an augmentation of the existing data set to illustrate the non-uniform, varying nature of road traffic. The findings of this work show that by applying a data-driven approach to simulating road traffic for the purposes of IoV design, the effect of different vehicular traffic volumes on a road network play a significant role in assessing departure and depart delay times, vehicular speed and overall travel time hence providing an alternate approach to planning and designing data-centric, edge-driven IoV networks.