%0 Generic
%A Lattarulo, Ray
%A Hidalgo, Carlos
%A Arizala, Asier
%A Perez, Joshue
%T AUDRIC2: 												A Modular and Highly Interconnected Automated Driving Framework Focus on Decision Making and Vehicle Control
%J IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
%D 2021
%X Last years, automated vehicle technologies made considerable progress in academia and the industry. However, there is still a need for more scalable solutions which ensure fast progress between the prototypes and the final deployments. In this sense, this work introduces the updated version of the AUtomated DRIving Core framework (AUDRIC), which aims for robust and reliable vehicle decision-making and control algorithms. The solution is modular and provides MATLAB and ROS interfaces. Also, it has the integration links between the CARLA simulator and Dynacar (in-house simulator). The Autoware. AI framework was integrated to support vehicle perception. This framework targets non-holonomic ground vehicles, such as passenger cars, buses, shuttles, non-holonomic industrial AGV, etc. A simulation around Tecnalia premises was used to verify the provided functionalities (Basque Country, Spain). This framework will continue its development with the support of the European project SHOW. Vehicle cooperation functions are considered as an upcoming feature.
%~