M2 explores the acceptance, cooperation and governance of selfexplaining ACPS in the domain of mobility. User acceptance and trust are essential when humans interact with automated systems in complex, realistic situations. Acceptance is necessary to mitigate automation misuse and disuse and to meet legal and ethical constraints. One way to ensure a high level of user acceptance is to involve humans actively in the decision processes of Automated Cyber-Physical Systems (ACPS). Successful cooperation between these two cooperation partners can be significantly enhanced if the automation provides information about its purpose, process, and performance. For this purpose, it is necessary that future ACPS involve humans in an efficient communication about reasons and justifications of planned actions and to resolve potential conflicts of interest. For humans and ACPS to become team players they must be able to observe, understand, and predict each other's states and actions. Existing approaches are focusing on the question of human performance in future automated systems and understanding the factors of human trust in automation in general. In this project we are moving beyond managing human performance in ACPS to the challenge of a mutual partnership between the human and the machine and establish successful communication, understanding and acceptance. Our research in communicating and debating justifications builds on neurophysiological human state assessment. We will investigate increasing levels of complexity of communication between the human and the ACPS, from unidirectional explanations provided by the ACPS to humans to interactive bi-directional debates for understanding and conflict resolution. Another way to ensure a high level of user acceptance concerns the design of the legal framework that governs the decision process of ACPS in an environment of traffic control. The assumption is that a system of automated traffic control has to comply with citizens’ fundamental rights and warrant fair procedures and outcomes of decision-making in order to increase acceptance.