As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethics. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems are typically being presented in the form of an idealized unsolvable decision-making problem, the so-called trolley problem, which is grossly misleading. We argue that an applied engineering ethical approach for the development of new technology is what is needed; the approach should be applied, meaning that it should focus on the analysis of complex real-world engineering problems. Software plays a crucial role for the control of self-driving cars; therefore, software engineering solutions should seriously handle ethical and social considerations. In this paper we take a closer look at the regulative instruments, standards, design, and implementations of components, systems, and services and we present practical social and ethical challenges that have to be met, as well as novel expectations for software engineering.

Operating heavy vehicles, for instance an excavator, requires a high level of attention to the operation done using the vehicle and awareness of the surroundings. Digital transformation in heavy vehicles aims to improve productivity and user experience, but it can also increase the operators mental load because of a higher demand of attention to instrumentation and controls, subsequently leading to reduced situation awareness. One way to mitigate this, is to display information within the operators' field of view, which enhances information detectability through quick glances, using mixed reality interfaces. This work explores two types of mixed reality visualizations and compares them to a traditional display setup in a simulated excavator environment. We have utilized eye-tracking glasses to study users' attention to the task, surrounding awareness, and interfaces, followed by a NASA-RTLX questionnaire to evaluate the users' reported mental workload. The results indicate benefits for the mixed reality approaches, with lower workload ratings together with an improved rate in detection of presented information.

As an envisaged future of transportation, self-driving cars are being discussed from various perspectives, including social, economical, engineering, computer science, design, and ethical aspects. On the one hand, self-driving cars present new engineering problems that are being gradually successfully solved. On the other hand, social and ethical problems have up to now being presented in the form of an idealized unsolvable decision-making problem, the so-called "trolley problem", which is built on the assumptions that are neither technically nor ethically justifiable. The intrinsic unfairness of the trolley problem comes from the assumption that lives of different people have different values. In this paper, techno-social arguments are used to show the infeasibility of the trolley problem when addressing the ethics of selfdriving cars. We argue that different components can contribute to an "unfair" behaviour and features, which requires ethical analysis on multiple levels and stages of the development process. Instead of an idealized and intrinsically unfair thought experiment, we present real-life techno-social challenges relevant for the domain of software fairness in the context of self-driving cars.

No abstract