{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:7ZBT63IV6LDUOTTHV4MJS3K6IQ","short_pith_number":"pith:7ZBT63IV","schema_version":"1.0","canonical_sha256":"fe433f6d15f2c7474e67af18996d5e443eea2af0824bf5d32194ce247d622537","source":{"kind":"arxiv","id":"2110.04052","version":1},"attestation_state":"computed","paper":{"title":"Safe Imitation Learning on Real-Life Highway Data for Human-like Autonomous Driving","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Flavia Sofia Acerbo, Herman van der Auweraer, Mohsen Alirezaei, Tong Duy Son","submitted_at":"2021-10-08T12:01:29Z","abstract_excerpt":"This paper presents a safe imitation learning approach for autonomous vehicle driving, with attention on real-life human driving data and experimental validation. In order to increase occupant's acceptance and gain drivers' trust, the autonomous driving function needs to provide a both safe and comfortable behavior such as risk-free and naturalistic driving. Our goal is to obtain such behavior via imitation learning of a planning policy from human driving data. In particular, we propose to incorporate barrier functions and smooth spline-based motion parametrization in the training loss functio"},"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":"2110.04052","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2021-10-08T12:01:29Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"6bd2086c14c6c70b48261f5f0024d695ffe3de74dffb49690be70b8fb2a3eee9","abstract_canon_sha256":"4cb97fb870d5b48f2b7ece2cec84c34a53c459bcb48ffbb2e89f1329d8a3e57f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:21:00.368827Z","signature_b64":"UhNu6ceKHk9ixLk7YA9QIU/+mge/GdCqwMRLzuCkPfSLnCsRjZ4UWXB+6fD44I10V+kHQVYPWKoVmlvOnF8bAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe433f6d15f2c7474e67af18996d5e443eea2af0824bf5d32194ce247d622537","last_reissued_at":"2026-07-05T03:21:00.368482Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:21:00.368482Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Safe Imitation Learning on Real-Life Highway Data for Human-like Autonomous Driving","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Flavia Sofia Acerbo, Herman van der Auweraer, Mohsen Alirezaei, Tong Duy Son","submitted_at":"2021-10-08T12:01:29Z","abstract_excerpt":"This paper presents a safe imitation learning approach for autonomous vehicle driving, with attention on real-life human driving data and experimental validation. In order to increase occupant's acceptance and gain drivers' trust, the autonomous driving function needs to provide a both safe and comfortable behavior such as risk-free and naturalistic driving. Our goal is to obtain such behavior via imitation learning of a planning policy from human driving data. In particular, we propose to incorporate barrier functions and smooth spline-based motion parametrization in the training loss functio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.04052","kind":"arxiv","version":1},"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/2110.04052/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":"2110.04052","created_at":"2026-07-05T03:21:00.368544+00:00"},{"alias_kind":"arxiv_version","alias_value":"2110.04052v1","created_at":"2026-07-05T03:21:00.368544+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.04052","created_at":"2026-07-05T03:21:00.368544+00:00"},{"alias_kind":"pith_short_12","alias_value":"7ZBT63IV6LDU","created_at":"2026-07-05T03:21:00.368544+00:00"},{"alias_kind":"pith_short_16","alias_value":"7ZBT63IV6LDUOTTH","created_at":"2026-07-05T03:21:00.368544+00:00"},{"alias_kind":"pith_short_8","alias_value":"7ZBT63IV","created_at":"2026-07-05T03:21:00.368544+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/7ZBT63IV6LDUOTTHV4MJS3K6IQ","json":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ.json","graph_json":"https://pith.science/api/pith-number/7ZBT63IV6LDUOTTHV4MJS3K6IQ/graph.json","events_json":"https://pith.science/api/pith-number/7ZBT63IV6LDUOTTHV4MJS3K6IQ/events.json","paper":"https://pith.science/paper/7ZBT63IV"},"agent_actions":{"view_html":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ","download_json":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ.json","view_paper":"https://pith.science/paper/7ZBT63IV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2110.04052&json=true","fetch_graph":"https://pith.science/api/pith-number/7ZBT63IV6LDUOTTHV4MJS3K6IQ/graph.json","fetch_events":"https://pith.science/api/pith-number/7ZBT63IV6LDUOTTHV4MJS3K6IQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ/action/storage_attestation","attest_author":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ/action/author_attestation","sign_citation":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ/action/citation_signature","submit_replication":"https://pith.science/pith/7ZBT63IV6LDUOTTHV4MJS3K6IQ/action/replication_record"}},"created_at":"2026-07-05T03:21:00.368544+00:00","updated_at":"2026-07-05T03:21:00.368544+00:00"}