Connected Vehicle (CV) technologies have been progressing rapidly in the US. The capability afforded by Vehicle-to-Vehicle (V2V) communication improves situational awareness and provides advantages for many of the traffic problems caused by reduced visibility or No-Line-of-Sight situations, being useful for both autonomous and non-autonomous driving. Additionally, with the traffic light Signal Phase and Timing (SPaT) and Map Data (MAP) information and other advisory information provided with Vehicle-to-Infrastructure (V2I) communication, outcomes which benefit the driver in the long run, such as reducing fuel consumption with speed regulation or decreasing traffic congestion through optimal speed advisories, providing red light violation warning messages and intersection motion assist messages for collision-free intersection maneuvering are all made possible. However, developing applications to obtain these benefits requires an intensive development process within a lengthy testing period. Understanding the intersection better is a large part of this development process. Being able to see what information is broadcasted and how this information translates into the real world would both benefit the development of these highly useful applications and also ensure faster evaluation, when presented visually, using an easy to use and interactive tool. Moreover, recordings of this broadcasted information can be modified and used for repeated testing. Modification of the data makes it flexible and allows us to use it for a variety of testing scenarios at a virtually populated intersection. Based on this premise, this paper presents and demonstrates visualization tools to project SPaT, MAP and Basic Safety Message (BSM) information into easy to read real-world based graphs. Also, it provides information about the modification of the real-world data to allow creation of a virtually populated intersection, along with the capability to also inject virtual vehicles at this intersection.