RUBICONe: Wireless RAFT-Unified Behaviors for Intervehicular Cooperative Operations and Negotiations

2026-03-19

AI Summary

This work addresses the limitations of单车智能 in lane-changing decisions, which stem from restricted local perception and environmental interference, leading to insufficient global situational awareness and high-risk misjudgments. To overcome these challenges, the paper proposes a wireless communication–based distributed consensus framework that extends the RAFT consensus algorithm—originally designed for distributed systems—to the vehicular networking context for the first time. By enabling multi-vehicle perception fusion, the framework facilitates collaborative decision-making for lane changes, an inherently irreversible maneuver. Integrating software-defined radio with distributed cooperative communication, the approach significantly mitigates the impact of environmental disturbances in experimental evaluations, effectively reducing individual vehicle misjudgments and enhancing the robustness, safety, and contextual completeness of lane-change decisions.

Technology Category

• Multiagent Systems: Agent Communication
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Reasoning under Uncertainty: Sequential Decision Making

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

Just as Caesar declared "alea iacta est" (the die is cast) upon crossing the Rubicone river, lane change decisions in autonomous vehicles also represent critical points of no return. RUBICONe addresses this challenge by recognizing that lane change decision-making relying solely on a single vehicle's perception would be as precarious as crossing an unknown river alone. By implementing a distributed consensus framework that extends the RAFT algorithm with wireless connectivity, RUBICONe enables multiple vehicles to collectively process and aggregate their perceptions. Using multiple software-defined radio (SDR) devices as the experimental platform, this study demonstrates how consensus-based decision-making significantly reduces the impact of environmental interference and mitigates the risk of misjudgments by individual vehicles. Just as crossing the Rubicone marked a point of irrevocable action backed by collective intelligence, RUBICONe ensures that lane change decisions are made with comprehensive situational awareness and distributed consensus, showcasing the reliability gain of consensus in wireless communications.

Problem

• lane change
• autonomous vehicles
• perception
• decision-making
• environmental interference

Innovation

• distributed consensus
• wireless vehicular cooperation
• RAFT algorithm
• software-defined radio (SDR)
• lane change decision-making