AI & ML
Mode 0: Architecture, Risk Taxonomy, and Standardization Pathway for RCU-Assisted V2X Safety Communication
arXiv cs.MA0 views
arXiv:2605.25431v5 Announce Type: replace-cross Abstract: The 3GPP V2X resource allocation framework offers two entity classes for coordinating vehicle communication --- base-station scheduling and autonomous vehicle selection --- a design space we show to be structurally incomplete for safety-critical coordination. We propose Mode 0, a third entity class centered on the Roadside Computing Unit (RCU): infrastructure integrating elevated sensing, sidelink communication, and local computation, owned by traffic management authorities rather than network operators. We formalize Mode 0's subfamily taxonomy (Mode 0a through 0c), its traffic risk taxonomy and mandatory-escalation boundary, its cross-domain coexistence with Modes 1--4, and its standardization pathway. Of the three failure modes motivating this proposal --- scheduling saturation, occlusion-driven information gaps, and an institutional authority gap during severe hazards --- only scheduling is evaluated by simulation; information and authority are argued architecturally and evidenced by independent deployment convergence across Chinese local and industry-alliance standards, Chinese operator infrastructure, and European and US C-V2X programs, properties no channel-level simulation can instantiate. In a multi-agent reinforcement learning simulation (88 training runs, 95% confidence intervals), per-vehicle policies (Mode 0c) raise worst-interval delivery reliability at the critical safety load from 0.217 under shared per-class policies (Mode 0a) to 0.792, cutting lost safety messages from 38% to 6%. An idealized model of standardized sensing-based semi-persistent scheduling loses 10% at the same load, and per-vehicle coordination more than halves the longest gaps between safety updates against it (3.9 against 8.4 message periods). With spare spectrum, a safety partition sized by the RCU delivers every safety message. We call for a 3GPP study item to formalize Mode 0.
Source:https://arxiv.org/abs/2605.25431PreviousCoMMa: Contribution-Aware Medical Multi-Agents for Decentralized Oncology Decision SupportNextWho&When Pro: Can LLMs Really Attribute Failures in AI Agents?
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