How to coordinate CAVs and HDVs in traffic?
Multi-agent Path Finding for Mixed Autonomy Traffic Coordination
September 9, 2024
https://arxiv.org/pdf/2409.03881This paper introduces BK-PBS, a new algorithm for coordinating autonomous vehicles (CAVs) in mixed traffic with human drivers (HDVs). It tackles the challenge of unpredictable HDV behavior by:
- Predicting HDV actions: Using a conditional prediction model trained on HDV driving data, it forecasts how HDVs might react to CAV maneuvers.
- Proactive planning: Instead of treating HDVs as static obstacles, BK-PBS anticipates their actions and plans CAV trajectories to influence HDV behavior for smoother traffic flow.
This is relevant to LLM-based multi-agent systems because it demonstrates:
- Combining LLMs with traditional AI: The LLM (conditional prediction model) enhances a classical search-based AI algorithm (PBS).
- Value of behavior prediction: Proactively accounting for agent behavior, especially in mixed-autonomy settings, leads to more efficient coordination.