{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WBAWDGE253Q3IBYNH6MZB6GQXB","short_pith_number":"pith:WBAWDGE2","schema_version":"1.0","canonical_sha256":"b04161989aeee1b4070d3f9990f8d0b86e3c036e86c3e0252fda37d1b0370422","source":{"kind":"arxiv","id":"2305.10080","version":2},"attestation_state":"computed","paper":{"title":"Automatic Traffic Scenario Conversion from OpenSCENARIO to CommonRoad","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.FL","cs.SE"],"primary_cat":"cs.RO","authors_text":"Matthias Althoff, Michael Ratzel, Yuanfei Lin","submitted_at":"2023-05-17T09:26:31Z","abstract_excerpt":"Scenarios are a crucial element for developing, testing, and verifying autonomous driving systems. However, open-source scenarios are often formulated using different terminologies. This limits their usage across different applications as many scenario representation formats are not directly compatible with each other. To address this problem, we present the first open-source converter from the OpenSCENARIO format to the CommonRoad format, which are two of the most popular scenario formats used in autonomous driving. Our converter employs a simulation tool to execute the dynamic elements defin"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2305.10080","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2023-05-17T09:26:31Z","cross_cats_sorted":["cs.FL","cs.SE"],"title_canon_sha256":"fd77ceab02e6cc24608c9a3137310b3ef51f8ef95e87112bd971bec77ae026f5","abstract_canon_sha256":"bc444e119138d15098a83224f5902c02be44fdf52107b24ac020ff22e5efe1b9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:47:56.790693Z","signature_b64":"GFMAwazGRuwmst6VQUsNAZTAHtK4ihBLiYXcR73ohUg3n0NdNwnjlgpjPAB/GThqRWAdDK4+9SZ4Bl39F1dBCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b04161989aeee1b4070d3f9990f8d0b86e3c036e86c3e0252fda37d1b0370422","last_reissued_at":"2026-07-05T07:47:56.790060Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:47:56.790060Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automatic Traffic Scenario Conversion from OpenSCENARIO to CommonRoad","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.FL","cs.SE"],"primary_cat":"cs.RO","authors_text":"Matthias Althoff, Michael Ratzel, Yuanfei Lin","submitted_at":"2023-05-17T09:26:31Z","abstract_excerpt":"Scenarios are a crucial element for developing, testing, and verifying autonomous driving systems. However, open-source scenarios are often formulated using different terminologies. This limits their usage across different applications as many scenario representation formats are not directly compatible with each other. To address this problem, we present the first open-source converter from the OpenSCENARIO format to the CommonRoad format, which are two of the most popular scenario formats used in autonomous driving. Our converter employs a simulation tool to execute the dynamic elements defin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.10080","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2305.10080/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2305.10080","created_at":"2026-07-05T07:47:56.790121+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.10080v2","created_at":"2026-07-05T07:47:56.790121+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.10080","created_at":"2026-07-05T07:47:56.790121+00:00"},{"alias_kind":"pith_short_12","alias_value":"WBAWDGE253Q3","created_at":"2026-07-05T07:47:56.790121+00:00"},{"alias_kind":"pith_short_16","alias_value":"WBAWDGE253Q3IBYN","created_at":"2026-07-05T07:47:56.790121+00:00"},{"alias_kind":"pith_short_8","alias_value":"WBAWDGE2","created_at":"2026-07-05T07:47:56.790121+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2506.23023","citing_title":"Scenario-Based Hierarchical Reinforcement Learning for Automated Driving Decision Making","ref_index":20,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB","json":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB.json","graph_json":"https://pith.science/api/pith-number/WBAWDGE253Q3IBYNH6MZB6GQXB/graph.json","events_json":"https://pith.science/api/pith-number/WBAWDGE253Q3IBYNH6MZB6GQXB/events.json","paper":"https://pith.science/paper/WBAWDGE2"},"agent_actions":{"view_html":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB","download_json":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB.json","view_paper":"https://pith.science/paper/WBAWDGE2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.10080&json=true","fetch_graph":"https://pith.science/api/pith-number/WBAWDGE253Q3IBYNH6MZB6GQXB/graph.json","fetch_events":"https://pith.science/api/pith-number/WBAWDGE253Q3IBYNH6MZB6GQXB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB/action/storage_attestation","attest_author":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB/action/author_attestation","sign_citation":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB/action/citation_signature","submit_replication":"https://pith.science/pith/WBAWDGE253Q3IBYNH6MZB6GQXB/action/replication_record"}},"created_at":"2026-07-05T07:47:56.790121+00:00","updated_at":"2026-07-05T07:47:56.790121+00:00"}