{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:3V5LZPQDZSFAFGXXFVRBAJWRYA","short_pith_number":"pith:3V5LZPQD","schema_version":"1.0","canonical_sha256":"dd7abcbe03cc8a029af72d621026d1c00df16b0131f59335e77c698f8a15409c","source":{"kind":"arxiv","id":"2111.07162","version":1},"attestation_state":"computed","paper":{"title":"Gaussian Process based Stochastic Model Predictive Control for Cooperative Adaptive Cruise Control","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Javad Mohammadpour Velni, Mahdi Razzaghpour, Sahand Mosharafian, Yaser P. Fallah","submitted_at":"2021-11-13T18:14:52Z","abstract_excerpt":"Cooperative driving relies on communication among vehicles to create situational awareness. One application of cooperative driving is Cooperative Adaptive Cruise Control (CACC) that aims at enhancing highway transportation safety and capacity. Model-based communication (MBC) is a new paradigm with a flexible content structure for broadcasting joint vehicle-driver predictive behavioral models. The vehicle's complex dynamics and diverse driving behaviors add complexity to the modeling process. Gaussian process (GP) is a fully data-driven and non-parametric Bayesian modeling approach which can be"},"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":"2111.07162","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2021-11-13T18:14:52Z","cross_cats_sorted":[],"title_canon_sha256":"7c59236557a09729e621264377d0ea3bcb7ad209898d680c31e8b3a367a4149f","abstract_canon_sha256":"840c499c91c360b1b39bc3c9666d48ac3eac84bb6057c468a87cc87a41eb836c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:40:51.484374Z","signature_b64":"tmTaMSYkgCxwFfNfJS1+dieGtcW3jZl+HuvdQhIRWDowfwxdGi/VI7ot3UwdpmTomhyCfzsYJTNbTzEdWQxkAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dd7abcbe03cc8a029af72d621026d1c00df16b0131f59335e77c698f8a15409c","last_reissued_at":"2026-07-05T03:40:51.483947Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:40:51.483947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Gaussian Process based Stochastic Model Predictive Control for Cooperative Adaptive Cruise Control","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Javad Mohammadpour Velni, Mahdi Razzaghpour, Sahand Mosharafian, Yaser P. Fallah","submitted_at":"2021-11-13T18:14:52Z","abstract_excerpt":"Cooperative driving relies on communication among vehicles to create situational awareness. One application of cooperative driving is Cooperative Adaptive Cruise Control (CACC) that aims at enhancing highway transportation safety and capacity. Model-based communication (MBC) is a new paradigm with a flexible content structure for broadcasting joint vehicle-driver predictive behavioral models. The vehicle's complex dynamics and diverse driving behaviors add complexity to the modeling process. Gaussian process (GP) is a fully data-driven and non-parametric Bayesian modeling approach which can be"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.07162","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/2111.07162/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":"2111.07162","created_at":"2026-07-05T03:40:51.484002+00:00"},{"alias_kind":"arxiv_version","alias_value":"2111.07162v1","created_at":"2026-07-05T03:40:51.484002+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.07162","created_at":"2026-07-05T03:40:51.484002+00:00"},{"alias_kind":"pith_short_12","alias_value":"3V5LZPQDZSFA","created_at":"2026-07-05T03:40:51.484002+00:00"},{"alias_kind":"pith_short_16","alias_value":"3V5LZPQDZSFAFGXX","created_at":"2026-07-05T03:40:51.484002+00:00"},{"alias_kind":"pith_short_8","alias_value":"3V5LZPQD","created_at":"2026-07-05T03:40:51.484002+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/3V5LZPQDZSFAFGXXFVRBAJWRYA","json":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA.json","graph_json":"https://pith.science/api/pith-number/3V5LZPQDZSFAFGXXFVRBAJWRYA/graph.json","events_json":"https://pith.science/api/pith-number/3V5LZPQDZSFAFGXXFVRBAJWRYA/events.json","paper":"https://pith.science/paper/3V5LZPQD"},"agent_actions":{"view_html":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA","download_json":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA.json","view_paper":"https://pith.science/paper/3V5LZPQD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2111.07162&json=true","fetch_graph":"https://pith.science/api/pith-number/3V5LZPQDZSFAFGXXFVRBAJWRYA/graph.json","fetch_events":"https://pith.science/api/pith-number/3V5LZPQDZSFAFGXXFVRBAJWRYA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA/action/storage_attestation","attest_author":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA/action/author_attestation","sign_citation":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA/action/citation_signature","submit_replication":"https://pith.science/pith/3V5LZPQDZSFAFGXXFVRBAJWRYA/action/replication_record"}},"created_at":"2026-07-05T03:40:51.484002+00:00","updated_at":"2026-07-05T03:40:51.484002+00:00"}