Human–machine coordination in mixed traffic as a problem of Meaningful Human Control

Human–machine coordination in mixed traffic as a problem of Meaningful Human Control

Mecacci, Giulio (Donders Institute for Brain, Cognition and Behaviour)
Calvert, S.C. (TU Delft Transport and Planning)
Santoni De Sio, F. (TU Delft Ethics & Philosophy of Technology)

2023

The urban traffic environment is characterized by the presence of a highly differentiated pool of users, including vulnerable ones. This makes vehicle automation particularly difficult to implement, as a safe coordination among those users is hard to achieve in such an open scenario. Different strategies have been proposed to address these coordination issues, but all of them have been found to be costly for they negatively affect a range of human values (e.g. safety, democracy, accountability…). In this paper, we claim that the negative value impacts entailed by each of these strategies can be interpreted as lack of what we call Meaningful Human Control over different parts of a sociotechnical system. We argue that Meaningful Human Control theory provides the conceptual tools to reduce those unwanted consequences, and show how “designing for meaningful human control” constitutes a valid strategy to address coordination issues. Furthermore, we showcase a possible application of this framework in a highly dynamic urban scenario, aiming to safeguard important values such as safety, democracy, individual autonomy, and accountability. Our meaningful human control framework offers a perspective on coordination issues that allows to keep human actors in control while minimizing the active, operational role of the drivers. This approach makes ultimately possible to promote a safe and responsible transition to full automation.

Autonomous vehicles
Meaningful human control
Mixed traffic
Urban traffic

http://resolver.tudelft.nl/uuid:1781fee6-3349-4af0-bfec-7ed594151bfb

https://doi.org/10.1007/s00146-022-01605-w

0951-5666

AI&Society: the journal of human-centered systems and machine intelligence, 38 (3), 1151-1166

Institutional Repository

journal article

© 2023 Giulio Mecacci, S.C. Calvert, F. Santoni De Sio