A new lead discipline as a driver for the development of trustworthy autonomous systems
Automated and autonomous transport systems have the potential to make an important contribution to climate protection and to mastering social challenges in the field of mobility.
The economic and technological developments of recent decades have been driven mainly by various leading economic sectors. Since the end of the Second World War, mechanical engineering developed into a more differentiated discipline, mechatronics, with the help of control and electrical engineering, automation technology, and microelectronics until the 1990s. Since the 1990s, computer science has played a decisive role in the development of new technologies and services, and thus also in new business models. Since then, it has made a significant contribution to economic growth.
Autonomous systems, unlike e. g. smartphones, also have a direct influence on the physical world and will bring about a whole new level of digital penetration of our society through their diverse applications: Industry 4.0, autonomous driving as well as networked energy and health systems are just a few examples.
This makes it all the more important to provide autonomous systems with a high degree of trustworthiness. It requires a sound understanding of trust and responsibility, which can be transferred to technical systems and used in development and operation. By combining social sciences, humanities and human sciences with natural and engineering sciences, we want to create the new lead discipline called "Autonomics". With this, we want to meet the challenges in the development and use of autonomous systems. The potential offered by the integration of more and more decision-making competence in machines with the help of new approaches to artificial intelligence is to be fully exploited. The goals of autonomy are manifold: In addition to the global goal of sustainability, trustworthiness, quality of life, and economic efficiency play a major role. Environmental pollution is to be reduced, for example, by using existing transport systems more efficiently. Accidents are to be avoided (trustworthiness), more comfort is to be created when traveling (quality of life), resources are to be conserved and costs and time expenditure reduced (economic efficiency).
For the development and deployment of autonomous systems, technical and social trustworthiness is of crucial importance. Autonomics should address precisely these issues. How can one be sure that automated and autonomous systems have been sufficiently tested? How can it be guaranteed that the systems know the solutions for all conceivable (and also not yet conceivable) situations and can implement them successfully and safely? How can trust be created in the new systems? These questions pose new challenges and opportunities for autonomics: Human-machine systems are to be understood as teams in which all team members exchange their intentions. Methods and tools have to be developed that ensure a sufficiently high level of trustworthiness and give people a feeling of security before and during the use of automated and autonomous systems. Science can make a decisive contribution here by bringing together with business and politics various disciplines such as social sciences, psychology, philosophy, human, natural and engineering sciences such as physics, mathematics and computer science. In principle, transdisciplinary approaches are required to master the complexity of human-machine systems, but also political, economic, and social issues and their solutions. In the new lead discipline Autonomics, these questions and challenges of highly automated and autonomous systems will be addressed jointly.
In this context, the DLR Institute of Systems Engineering for Future Mobility, together with institutions and companies from science, industry, and politics, will build up appropriate competencies in the sub-area of transport autonomics, whereby the new institute will make a decisive contribution to the research and development of reliable, highly automated and autonomous transport systems of the future.