ReasonLight uses multimodal foundation models to refine RL-proposed traffic signal phases based on camera images and sensor data, enabling zero-shot adaptation to unseen events such as emergency vehicle priority.
illm-tsc: Integration reinforcement learning and large language model for traffic signal control policy improvement. arxiv 2024
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ReasonLight: A Multimodal Foundation Model-Enhanced Reinforcement Learning Framework for Zero-Shot Traffic Signal Control
ReasonLight uses multimodal foundation models to refine RL-proposed traffic signal phases based on camera images and sensor data, enabling zero-shot adaptation to unseen events such as emergency vehicle priority.
- Earth Science Foundation Models: From Perception to Reasoning and Discovery