Simulation provides a safe and controlled environment ideal for human testing [49, 142, 120]. Simulation of real environments has reached new heights in terms of photo-realism. Often, a team of professional graphical artists would have to be hired to compete with modern commercial simulators. Meanwhile, machine vision methods are currently being developed that attempt to automatically provide geometrically consistent and photo-realistic 3D models of real scenes [189, 139, 115, 19, 140, 111, 132]. Often the only requirement is a set of images of that scene. A road engineer wishing to simulate the environment of a real road for driving experiments could potentially use these tools. This thesis develops a driving simulator that uses machine vision methods to reconstruct a real road automatically. A computer graphics method called projective texture mapping is applied to enhance the photo-realism of the 3D models[144, 43]. This essentially creates a virtual projector in the 3D environment to automatically assign image coordinates to a 3D model. These principles are demonstrated using custom shaders developed for an OpenGL rendering pipeline. Projective texture mapping presents a list of challenges to overcome, these include reverse projection and projection onto surfaces not immediately in front of the projector [53]. A significant challenge was the removal of dynamic foreground objects. 3D reconstruction systems create 3D models based on static objects captured in images. Dynamic objects are rarely reconstructed. Projective texture mapping of images, including these dynamic objects, can result in visual artefacts. A workflow is developed to resolve this, resulting in videos and 3D reconstructions of streets with no moving vehicles on the scene. The final simulator using 3D reconstruction and projective texture mapping is then developed. The rendering camera had a motion model introduced to enable human interaction. The final system is presented, experimentally tested, and future potential works are discussed.