Following societal and policy pressures for responsible innovation, innovators are more and more expected to consider the broader socio-ethical context of their work, and more importantly, to integrate such considerations into their daily practices. This may require the involvement of ‘outsiders’ in innovation trajectories, including e.g. societal and governmental actors. However, methods on how to functionally organize such integration in light of responsible innovation have only recently started to emerge. We present an approach to do just that, in which we first develop value profiles of the involved actors, and second, design a workshop setting that allows innovators to develop design requirements in collaboration with representatives of parties that are not usually involved in such innovation design practices. Using a case study in automated vehicle development, we positively demonstrate the possibility and utility of our approach. We stress that in this study we wish to demonstrate the functionality of our developed method, and did not search for scientifically valid outcomes regarding this technical field.@en

Modern cars are increasingly being equipped with automated driving functions. For governments it is important to gain insight in the mobility impacts of automated vehicles. This is important as the introduction of automated vehicles affects current investment decisions about infrastructure projects and other policy measures like road pricing. Quantitative literature with respect to the impact of automated vehicles focuses mostly on capacity implications. Literature about large scale mobility impacts is mainly qualitative. This paper introduces a System Dynamics model (SD-model) to quantitatively explore the impacts of early forms of automated vehicles (level 1, 2 and 3) on mobility. The model is explorative and can be used to evaluate different scenarios in a short time. This model is applied in a case study for the Netherlands to assess the impact of automated vehicles on mode choice, time of day choice and travel times on characteristic relations in the Netherlands. In contrast to other studies the SD-model is able to simulate the effects of AVs over time, can simulate mixed automated vehicle types and has a constant feedback between the assignment and the demand side of the model. A scenario for autonomous driving and a scenario for cooperative driving is considered. The simulations show that car traffic will increase and the level of congestion does not necessarily decrease and might even increase on some relations, especially in the autonomous scenario. Furthermore, in the cooperative scenario the increase in number of trips by car is larger, the average speeds are higher and there is less congestion compared to the autonomous scenario.@en