Trust-Aware V2V Charging Coordination via Hierarchical Decision under Mode Uncertainty

Résumé fourni par la source

As Electric Vehicle (EV) adoption accelerates, the limitations of fixed charging infrastructure, such as spatial inflexibility and peak-time congestion, become more evident. Vehicle-to-Vehicle (V2V) charging allows EV with surplus energy to directly supply others, offering a decentralized complement to conventional infrastructure. Depending on real-time context, energy exchange can occur in either a static mode (while parked) or a dynamic mode (in motion along overlapping routes). Selecting the appropriate mode and coordinating trustworthy peers under uncertain traffic, energy, and spatial conditions poses a significant challenge. This paper presents a hierarchical framework for trust-aware V2V charging coordination under mode uncertainty. At the strategic layer, a fuzzy logic-based trust estimator selects the most reliable charging mode based on factors such as energy gap, location density, and traffic state. At the operational layer, a unified Large Neighborhood Search (LNS) algorithm performs robust EV pairing, using greedy heuristics for static mode and DTW-based trajectory alignment for dynamic mode. Trust-weighted objectives and soft constraint penalties are incorporated to enhance decision robustness and mitigate unreliable matches. Experiments on real-world Helsinki mobility data demonstrate that the framework improves match success rates, reduces waiting times and trajectory deviations, and enhances the overall resilience of V2V energy coordination.

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