{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11938957","patent":{"patent_number":"US-11938957","title":"Driving scenario sampling for training/tuning machine learning models for vehicles","assignee":null,"inventors":[],"filing_date":"2020-08-24T00:00:00.000Z","publication_date":"2024-03-26T00:00:00.000Z","cpc_codes":["B60W","G06N","B60W","G06N","B60W","B60W","G06N","G06N","G06N","G06N","G06N"],"num_claims":19,"abstract":"Enclosed are embodiments for sampling driving scenarios for training machine learning models. In an embodiment, a method comprises: assigning, using at least one processor, a set of initial physical states to a set of objects in a map for a set of simulated driving scenarios, wherein the set of initial physical states are assigned according to one or more outputs of a random number generator; generating, using the at least one processor, the set of simulated driving scenarios in the map using the initial physical states of the objects in the set of objects; selecting, using the at least one processor, samples of the simulated driving scenarios; training, using the at least one processor, a machine learning model using the selected samples; and operating, using a control circuit, a vehicle in an environment using the trained machine learning model."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Driving scenario sampling for training/tuning machine learning models for vehicles","description":"Enclosed are embodiments for sampling driving scenarios for training machine learning models. In an embodiment, a method comprises: assigning, using at least one processor, a set of initial physical s","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11938957","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11938957","citation_suggestion":"Patentable. \"Driving scenario sampling for training/tuning machine learning models for vehicles\" (US-11938957). https://patentable.app/patents/US-11938957","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11938957","json":"https://patentable.app/api/llm-context/US-11938957","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T05:12:41.549Z"}