Learn Before
Modular vs. End-to-End Driving Systems with Limited Paired Training Data
A modular self-driving pipeline learns separate perception and decision stages, such as detecting lanes, vehicles, and traffic signals before choosing an action. When labels for these intermediate tasks are more available than paired sensor-input and driving-action examples, the modular pipeline is usually more practical than a fully end-to-end model. As direct input-to-action training data increases, the end-to-end option becomes more feasible.
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Modular vs. End-to-End Driving Systems with Limited Paired Training Data
Learn After
Why is a modular driving system often considered a better near-term option than a fully end-to-end one?
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