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

Area of Science:

• Sociotechnical systems
• Human-computer interaction
• Urban planning

Background:

• Urban traffic involves diverse users, complicating safe vehicle automation.
• Existing coordination strategies negatively impact human values like safety and accountability.
• Implementing full automation in complex urban environments presents significant challenges.

Purpose of the Study:

• To propose Meaningful Human Control (MHC) as a framework for addressing coordination issues in urban automation.
• To demonstrate how designing for MHC can mitigate negative value impacts of automation strategies.
• To safeguard human values such as safety, democracy, autonomy, and accountability during the transition to automation.

Main Methods:

• Conceptual analysis applying Meaningful Human Control theory to sociotechnical systems.
• Framework development for designing automation strategies that preserve human control.
• Illustrative application within a dynamic urban traffic scenario.

Main Results:

• Negative value impacts of current strategies are linked to a lack of Meaningful Human Control.
• "Designing for meaningful human control" is presented as a viable solution for coordination issues.
• The MHC framework can be applied to dynamic urban environments.

Conclusions:

• Meaningful Human Control theory provides essential tools to reduce unwanted consequences of automation.
• Designing for MHC offers a strategy to address coordination challenges in urban automation.
• This approach facilitates a safe and responsible transition to full vehicle automation while maintaining human oversight.