{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:TLBDWLL3WUVTP34UT2H5NFNKTX","short_pith_number":"pith:TLBDWLL3","schema_version":"1.0","canonical_sha256":"9ac23b2d7bb52b37ef949e8fd695aa9df8281eff12a5b8487b2b746e6a1982e8","source":{"kind":"arxiv","id":"2504.07507","version":2},"attestation_state":"computed","paper":{"title":"Drive in Corridors: Enhancing the Safety of End-to-end Autonomous Driving via Corridor Learning and Planning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Jingchu Liu, Ke Wu, Lisen Mu, Ruichen Yang, Wenchao Ding, Zhiwei Zhang, Zhongxue Gan, Zijun Xu","submitted_at":"2025-04-10T07:10:40Z","abstract_excerpt":"Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a scalable manner. However, existing approaches often face safety risks due to the lack of explicit behavior constraints. To address this issue, we uncover a new paradigm by introducing the corridor as the intermediate representation. Widely adopted in robotics planning, the corridors represents spatio-temporal obstacle-free zones for the vehicle to traverse. To ensure accurate corridor prediction in diverse traffic s"},"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":"2504.07507","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-04-10T07:10:40Z","cross_cats_sorted":[],"title_canon_sha256":"d57b61284956d7fff83cec84352549a262078f07521c8c5a4d0d1fd183f4715b","abstract_canon_sha256":"820d28c34a22fff9c8f082ffd7198be31214f392be4a2c6f773caeff61bb9a63"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:00:43.730048Z","signature_b64":"roeyeURfQMKalJeHN/ra5e2SSIBJXTbpZAWeVo39uzn4Ar3ADiP1eXRbVVWw9UCZbYP17ZXaNv7ISPYu/KbACw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9ac23b2d7bb52b37ef949e8fd695aa9df8281eff12a5b8487b2b746e6a1982e8","last_reissued_at":"2026-07-05T11:00:43.729549Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:00:43.729549Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Drive in Corridors: Enhancing the Safety of End-to-end Autonomous Driving via Corridor Learning and Planning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Jingchu Liu, Ke Wu, Lisen Mu, Ruichen Yang, Wenchao Ding, Zhiwei Zhang, Zhongxue Gan, Zijun Xu","submitted_at":"2025-04-10T07:10:40Z","abstract_excerpt":"Safety remains one of the most critical challenges in autonomous driving systems. In recent years, the end-to-end driving has shown great promise in advancing vehicle autonomy in a scalable manner. However, existing approaches often face safety risks due to the lack of explicit behavior constraints. To address this issue, we uncover a new paradigm by introducing the corridor as the intermediate representation. Widely adopted in robotics planning, the corridors represents spatio-temporal obstacle-free zones for the vehicle to traverse. To ensure accurate corridor prediction in diverse traffic s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.07507","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/2504.07507/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":"2504.07507","created_at":"2026-07-05T11:00:43.729612+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.07507v2","created_at":"2026-07-05T11:00:43.729612+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.07507","created_at":"2026-07-05T11:00:43.729612+00:00"},{"alias_kind":"pith_short_12","alias_value":"TLBDWLL3WUVT","created_at":"2026-07-05T11:00:43.729612+00:00"},{"alias_kind":"pith_short_16","alias_value":"TLBDWLL3WUVTP34U","created_at":"2026-07-05T11:00:43.729612+00:00"},{"alias_kind":"pith_short_8","alias_value":"TLBDWLL3","created_at":"2026-07-05T11:00:43.729612+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX","json":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX.json","graph_json":"https://pith.science/api/pith-number/TLBDWLL3WUVTP34UT2H5NFNKTX/graph.json","events_json":"https://pith.science/api/pith-number/TLBDWLL3WUVTP34UT2H5NFNKTX/events.json","paper":"https://pith.science/paper/TLBDWLL3"},"agent_actions":{"view_html":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX","download_json":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX.json","view_paper":"https://pith.science/paper/TLBDWLL3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.07507&json=true","fetch_graph":"https://pith.science/api/pith-number/TLBDWLL3WUVTP34UT2H5NFNKTX/graph.json","fetch_events":"https://pith.science/api/pith-number/TLBDWLL3WUVTP34UT2H5NFNKTX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX/action/storage_attestation","attest_author":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX/action/author_attestation","sign_citation":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX/action/citation_signature","submit_replication":"https://pith.science/pith/TLBDWLL3WUVTP34UT2H5NFNKTX/action/replication_record"}},"created_at":"2026-07-05T11:00:43.729612+00:00","updated_at":"2026-07-05T11:00:43.729612+00:00"}