As part of my project, I will start by reviewing the existing literature on methods for generating 3D blind spot data from diverse sources such as lasers and photographs. My goal is to evaluate the capabilities of current technologies, considering aspects like the required equipment, its cost, necessary processing capabilities, and the potential to develop an easy-to-use application that minimizes user input for data processing.

The initial phase involves summarizing the capabilities of existing approaches. For instance, laser scanners are known for their accuracy in generating 3D models, but they can be costly and often require substantial computational resources. Photogrammetry offers a less expensive alternative, utilizing standard cameras to create 3D data, though it may offer reduced accuracy in certain applications.

Once I have a clear understanding of these technologies, I will select the most promising approach based on a balance of accuracy, cost, ease of use, and equipment availability. Upon securing the necessary tools, I will apply this technology to generate blind spot data from a passenger vehicle as part of a pilot project. This practical application will allow me to assess the feasibility of the chosen method in real-world conditions.

If time allows, or if generating 3D point cloud data proves impractical or unfeasible, I will shift my focus to developing a 2D visibility tool. This tool will be based on the modified FERIC approach currently implemented in an Excel spreadsheet. I plan to enhance this tool by integrating methods to account for mirror visibility, thereby providing a more comprehensive analysis of blind spots.

Throughout this project, I will document my findings and methodologies meticulously, ensuring that the results can be replicated and applied to similar studies or practical applications in automotive safety.