ADORe : Unified Modular Framework for Vehicle and Infrastructure-Based System Level Automation

Abstract

Recent advancements in automated driving have primarily focused on achieving autonomy within individual vehicles. However, a broader paradigm shift is emerging that leverages both vehicle-level autonomy and collaboration with other road users and infrastructure to optimize traffic flow and enhance safety. This paper introduces ADORe(R) (Automated Driving Open Research), an open-source Automated Driving System developed by the German Aerospace Center (DLR). ADORe adopts a modular, system-level approach, enabling seamless integration between Single-Agent Automated Driving for local autonomy and Multi-Agent Autonomous Driving for infrastructure-assisted decision-making. By utilizing vehicle-to-infrastructure (V2X) communication, ADORe facilitates coordinated multi-agent planning, dynamic route optimization, and improved situational awareness through shared data. The framework supports flexible testing via simulation tools like CARLA and SUMO, alongside deployment on research vehicles equipped with advanced sensors and teleoperation capabilities. Successful demonstrations in research projects like the German national Gaia-X4ROMS and MAD Urban validate ADORe's capability to bridge the gap between isolated autonomous driving and cooperative traffic systems. This collaborative approach highlights the potential of automated driving systems as a cornerstone of intelligent transportation systems, advancing safety, efficiency, and interoperability.