
Ep#19 Learning to Drive from a World Model
RoboPapers
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Evaluating World Models for Driving Policy
This chapter explores the evaluation process of world models in driving policy development, focusing on the use of LPIPs perception loss to assess simulation accuracy. It discusses the complexities of model accuracy, trajectory mimicry techniques, and real-world user feedback in enhancing driving simulations. The conversation emphasizes the significance of engagement metrics and ongoing research aimed at improving model effectiveness in various driving scenarios.
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