Single photon avalanche detectors (SPADs) will be employed to give full waveform LiDAR signals or histograms over a range of 5-100m at a spatial resolution of the order of centimeters in all three dimensions (x,y,z). The purpose of this project is to develop and implement algorithms to detect and resolve multiple returns from single and arrayed SPADs in order to provide 3D information about the viewed scene from the perspective of an autonomous or assisted road vehicle. Ultimately information derived from a scanned linear or imaged 2D LiDAR array will be processed to provide information for the vehicle to include classical 3D environmental mapping, actor (vehicle, pedestrian, road signs etc,) detection, classification and location, and road surface (potholes, obstacles, line markings) characterization. Improved performance and robustness of said algorithms, in a variety of driving conditions (time of the day, weather, traffic, urban/country etc.), will also be envisioned, the fusion of LiDAR and HDR image data being one of the possible research tracks. Specifically, this project will investigate algorithms to process the LiDAR data rapidly and accurately to provide data to the complete automotive system for situational awareness. In addition, the student should examine FPGA and potentially ASIC friendly algorithms (‘design for product’) to allow low cost and low power solutions, He/she will work with engineers at ST and a companion student at University of Edinburgh who will develop the detection array to determine overall system performance. As such, he/she will have access to facilities in all three Edinburgh locations.