Senna decouples language-based high-level planning from an LVLM with low-level trajectory prediction from an E2E model, reporting 27% lower planning error and 33% lower collisions after pre-training on DriveX and fine-tuning on nuScenes.
Textual explanations for self-driving vehicles,
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PSI is a benchmark dataset for pedestrian intention prediction, driver decision modeling, and reasoning generation in traffic interactions, enriched with human textual explanations.
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Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
Senna decouples language-based high-level planning from an LVLM with low-level trajectory prediction from an E2E model, reporting 27% lower planning error and 33% lower collisions after pre-training on DriveX and fine-tuning on nuScenes.
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PSI: A Benchmark for Human Interpretation and Response in Traffic Interactions
PSI is a benchmark dataset for pedestrian intention prediction, driver decision modeling, and reasoning generation in traffic interactions, enriched with human textual explanations.