Smart cities and smart mobility are part of our present and future. New technologies are being developed to hinder the increasing traffic, pollution and energy consumption; one of these are fully autonomous driving vehicles, that are expected to be available globally by 2040. Perception and decision making tasks are only some of the numerous challenge that this technology have to improve in order to be efficient and safe for everyone. This thesis aim is to develop a proof of concept able to detect, track and forecast pedestrian trajectories, to improve safety in assisted or automated driving scenario, and is part of a project being conducted by Centro Ricerche Fiat (CRF-FCA) and Politecnico di Torino.