KOALA2 - cooperative interacting vehicles with low latency communication

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Wireless communication systems have considerably evolved over the last years and advanced technologies for improving vehicle safety and traffic efficiency are available. In particular WLAN-V2X and Cellular V2X considerably shorten, in comparison to conventional communication systems, the communication latency. While the project KOALA in the first phase of SPP1835 mainly focused on the reduction of the latency generated by the communication system as well as on modelling the latency, the follow-up project KOALA2 addresses how these low latency communication systems can be exploited for communication-based vehicle automation in a holistic approach. KOALA2 has three main objectives: (i) The exchange of sensor data among vehicles for cooperative perception can easily exceed the available data rate of the communication link. In contrast to previous approaches for data congestion control, KOALA2 studies adaptive schemes that dynamically adjust the generated object lists to match the instantaneous data rate, in consideration of the present driving situation. (ii) For scenario-based maneuver coordination among vehicles in cooperative use cases (such as lane change, platooning and emergency steering) the project develops design patterns for communication, in order to complement sensor-based maneuver planning by explicit communication. The state-of-the-art broadcast-based information dissemination is extended by communication in groups of vehicles, which exclusively encompasses the actors of the corresponding maneuver. The design patterns are used in a messaging framework that realizes a reliable communication for planning, execution and completion (or termination) of cooperative driving maneuvers. (iii) The developed techniques are prototypically implemented and experimentally validated. The project sustainably improves the cooperative perception as well as the cooperative maneuver and trajectory planning as key technologies for safety-relevant time critical use cases in cooperative automated driving.