Traffic simulation is a critical tool used by psychologists and engineers to study road behavior and improve safety standards. However, the creation of large 3D virtual environments requires specific technical expertise that traditionally trained traffic researchers may not have. This research proposes an approach to utilize fundamental image processing techniques to identify key features of an environment from a top-down view such as satellite imagery and map. The segmented data from the processed image is then utilized to create an approximate 3D virtual environment. A mesh of the detected roads is automatically generated while buildings and vegetation are selected from a library based on detected attributes. This research would enable traffic researchers with little to no 3D modeling experience to create large complex environments to study a variety of traffic scenarios.