Autonomous Driving Model

The optimal model size to data size ratio was found to be approximately 1.5:1, and loss consistently improved with scaling. Increasing the number of samples during inference contributes to performance improvement, but beyond a certain point, expanding model capacity becomes more efficient. Additionally, the research showed that pre-training using only logs from other vehicles can enable zero-shot transfer to ego behavior prediction, suggesting possibilities for diversifying data collection strategies.