![]() ![]() This includes controlling, taking over, or guiding the activities of those systems, in part, or in full. In this paper we explore human autonomy and humans’ ability to leverage the automation for their own aims. The questions are how and at what level (from deciding what the situation is about, to specific actions). ![]() What we know is that the introduction of automation in vehicles or whole transport systems means that human autonomy is affected–in various ways. This question of what human roles the system requires, or that are desirable from human points of view, is still a current topic. At the limits of what artificial intelligence can do, various human roles are invented, such as the human in the vehicle or the human in the control center with the role of taking over if an automation fails. Artificial intelligence (AI) will give rise to new complementary roles of autonomous systems and human autonomy, and human responsibilities will shift. An autonomous system can impede human autonomy, which refers to the freedom to reason without constraints from authority and preconceptions ( Stensson and Jansson, 2014). The label autonomous system is today given to a technological system that can manage itself to some degree. There are good reasons to believe that those control systems also will be autonomous systems. At the same time, concepts for controlling and coordinating the traffic systems in which they operate are also developed. Industry is currently in a race to build and deploy autonomous vehicles in all areas of transport. Our conclusion is that human autonomy in relation to autonomous systems is based on fundamental trade-offs between technological opportunities to automate and values of what human actors find meaningful. We also discuss the temporal nature of autonomy in minute-to-minute operative work. We discuss how autonomy at a lower level can prevent autonomy on higher levels, and vice versa. We use the Score notation to analyze patterns of temporal developments that span levels of the abstraction hierarchy and discuss implications for human-automation communication in traffic management. We use a temporal method, called the Joint Control Framework to describe human and automated work in an abstraction hierarchy labeled Levels of Autonomy in Cognitive Control. Our approach to designing for human collaboration with autonomous systems builds on scenario-based design and cognitive work analysis facilitated by computer simulations. This paper describes a design case of a future autonomous management system for drone traffic in cities in a key scenario we call The Computer in Brussels. This involves learning new practices and changing habitual ways of thinking and acting, including reconsidering human autonomy in relation to autonomous systems. Humans will interact with systems at a more overarching level or only in specific situations. The roles of human operators are changing due to increased intelligence and autonomy of computer systems. 2Department of Information and Computer Science, Linköping University, Linköping, Sweden. ![]() ![]()
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