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

Autonomous vehicles Meaningful human control Mixed traffic Urban traffic

Journal

AI & society
ISSN: 0951-5666
Titre abrégé: AI Soc
Pays: Germany
ID NLM: 9883157

Informations de publication

Date de publication:
2023
Historique:
received: 25 06 2021
accepted: 19 05 2022
medline: 14 2 2023
pubmed: 14 2 2023
entrez: 13 2 2023
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 36776534
doi: 10.1007/s00146-022-01605-w
pii: 1605
pmc: PMC9904868
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1151-1166

Informations de copyright

© The Author(s) 2023.

Auteurs

Giulio Mecacci (G)

Nijmegen, The Netherlands Donders Institute for Brain, Cognition and Behaviour, Radboud University.

Simeon C Calvert (SC)

Delft, The Netherlands Department of Transport and Planning, Delft University of Technology.

Filippo Santoni de Sio (F)

Delft, The Netherlands Department of Ethics and Philosophy of Technology, Delft University of Technology.

Classifications MeSH