Joint Dynamic Lane Reversal and Variable Speed Limit Control: A Graphormer-Based Approach

The paper proposes a graph-based method for jointly controlling dynamic lane reversal and variable speed limits in traffic networks, ensuring the network remains strongly connected during lane changes. It introduces a transformer model with Global Endpoint Relation-Aware Spatio-Temporal Self-Attention (GERASTSA) that is pretrained on traffic forecasting and fine-tuned with proximal policy optimization. Experiments on a 6×6 grid show the learned policy can make two-thirds of roads one-way during peak hours, reducing daily delay by up to 90% compared to a fixed configuration.

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• llms
• rag
• fine-tuning
• safety