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

Giulio Mecacci*, Simeon C. Calvert, Filippo Santoni de Sio

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

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.

Original languageEnglish
Pages (from-to)1151-1166
Number of pages16
JournalAI and Society
Volume38
Issue number3
DOIs
Publication statusPublished - 2023

Keywords

  • Autonomous vehicles
  • Meaningful human control
  • Mixed traffic
  • Urban traffic

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