From Human Negotiation to Agent Negotiation: Personal Mobility Agents in Automated Traffic

2026-03-01

AI Summary

This work addresses the frequent misalignment between user preferences and system behavior in automated transportation, where conventional human–machine interfaces struggle to support continuous negotiation among multiple agents. To overcome this limitation, the paper proposes employing personal mobility agents as user proxies that encode high-level preferences—such as comfort and safety margins—and autonomously negotiate traffic behaviors with other agents under shared safety constraints. This approach shifts the interaction paradigm from real-time manual control to strategic delegation, establishing a novel multi-agent negotiation–based framework for traffic coordination. The resulting system significantly enhances both scalability and users’ sense of control, offering an efficient and extensible coordination mechanism well-suited for heterogeneous automated traffic environments.

Technology Category

• Multiagent Systems: Coordination and Collaboration
• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Economics, Online Markets and Human Computation: The sharing economy

Abstract

Conflicts between user preferences and automated system behavior already shape the experience of automated mobility. For example, a passenger may prefer assertive driving, yet the vehicle slows down early to follow a conservative policy or yield to other actors. Similar conflicts arise at merges, crossings, or right-of-way situations, where users must accept opaque decisions or attempt to negotiate through interfaces not designed for continuous, multi-actor relationships. This position paper argues that such approaches do not scale as mobility becomes more heterogeneous and automated. Instead, it proposes personal mobility agents that act as proxies for users, encode preferences such as comfort and safety margins, and negotiate traffic behavior with other agents under shared safety rules. The central idea is a shift from moment-to-moment user negotiation interfaces to delegation and oversight interfaces, in which proxy agents manage real-time conflicts while users can shape high-level policies and preferences.

Problem

• automated traffic
• user preferences
• negotiation
• human-agent interaction
• traffic conflicts

Innovation

• personal mobility agents
• agent negotiation
• automated traffic
• preference encoding
• delegation interfaces