ORAMA

In virtually every aspect of modern engineering applications is apparent the need for treatment of unknown large-scale systems with complex interconnections and delay effects in uncertain environments, ubiquitous in contemporary societies, such as, individual vehicles and vehicles’ platoons in traffic and interacting
transportation networks. Real-time control of these systems is critical for ensuring their secure and efficient operation, with tremendous socioeconomic and environmental benefits. Their dramatically complex nature however, compels the state-of-the-art (SoA) methods to resort to precarious simplifications and modeling for enabling control design, imperiling systems security and efficiency, which calls for radical and drastic solutions that go far beyond the SoA.

It is the purpose of ORAMA to introduce a paradigm-shifting framework for efficient and secure design, addressing two scientific challenges

1. avoiding improper simplifications of systems’ behavior and
2. learning the system’s dynamic behavior (for control purposes), leveraging the abundance of available data and measurement sources.

To accomplish its goals, ORAMA will pioneer feedback control and analysis of unknown, interconnected delay systems, via a fundamental rethinking of techniques within and across control theory, mathematics, and machine learning, systems and transportation engineering. ORAMA’s new science will be immediately put in practice via demonstration in traffic with platoons of connected and automated vehicles.

ORAMA’s risk stems from the immense mathematical and engineering sophistication of each separate category of large-scale, delay, and highly uncertain systems, requiring introduction of ground-breaking concepts and delicate unification of methods from different disciplines. However, on the way towards achieving its goals, ORAMA will not only push existing knowledge frontiers, having immediate societal impact, but will also open unprecedented research arenas for systems & control and transportation engineers, computer scientists and mathematicians.