Stability-Aware Communication via Weighted Potential Games for Multi-Agent Trajectory Prediction

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Abstract
Multi-agent trajectory prediction relies heavily on information exchange, where incomplete state sharing, limited interaction frequency, and communication uncertainty readily induce collaborative instability. Current approaches primarily rely on heuristic interaction rules, failing to explicitly quantify the trade-off between communication overhead and prediction gains. This implicit assumption often leads to suboptimal information exchange and lacks evolutionary stability for communication strategies in dynamic traffic environments. Specifically, we propose the Stability-aware Communication via Weighted Potential Games (SC-WPG) framework. First, we leverage the continuous-time dynamics of Liquid Neural Networks (LNNs) to design a dynamic phase-coupling mechanism that aligns the temporal evolution of agent states, alleviating strategy asynchrony. Second, we establish a liquid state-sharing pool to exchange compact latent representations encoded from local observations, while promoting efficient implicit state fusion through spatio-temporal attention mechanisms. Finally, communication scheduling is formulated as a weighted potential game to explicitly quantify the trade-off between gains and costs. A stability-aware weight adaptation mechanism based on latent-state variation is introduced to regularize communication behavior under dynamic constraints. Experimental results on the NGSIM and HighD datasets show that SC-WPG achieves the lowest average root mean square error (RMSE) of 0.89 and 0.55, respectively. These results correspond to improvements of 10.1% and 6.8% over the strongest competing baselines under the same communication-constrained setting.
Funding Information
  • Open Research Fund of the Key Laboratory of the Ministry of Education on Application of Artificial Intelligence in Equipment (2024-AAIE-KF04-04)
  • Scientific and technological research project in Henan Province (252102210185)
  • Key Scientific Research Project of Colleges and Universities in Henan Province (26A520040)

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