{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:JLF23KEEMJNDFI6KNLCAZAUIOG","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"186725e8f55dcf5aef06d91e52d00166a25022a47eb5fd6cd4deba97a44cd55d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-04T14:20:50Z","title_canon_sha256":"8312369c2672fc42a8b5e7c646a7ccd87adeb4a2eafd59fdff179fcf0cec78eb"},"schema_version":"1.0","source":{"id":"2310.02843","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.02843","created_at":"2026-07-05T06:57:14Z"},{"alias_kind":"arxiv_version","alias_value":"2310.02843v1","created_at":"2026-07-05T06:57:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.02843","created_at":"2026-07-05T06:57:14Z"},{"alias_kind":"pith_short_12","alias_value":"JLF23KEEMJND","created_at":"2026-07-05T06:57:14Z"},{"alias_kind":"pith_short_16","alias_value":"JLF23KEEMJNDFI6K","created_at":"2026-07-05T06:57:14Z"},{"alias_kind":"pith_short_8","alias_value":"JLF23KEE","created_at":"2026-07-05T06:57:14Z"}],"graph_snapshots":[{"event_id":"sha256:c5e4e37705d1c9eb8d858fcf18c6e0452e46b02b8b14302fcdce159780e51207","target":"graph","created_at":"2026-07-05T06:57:14Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2310.02843/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model Predictive Control (MPC) has been widely applied to the motion planning of autonomous vehicles. An MPC-controlled vehicle is required to predict its own trajectories in a finite prediction horizon according to its model. Beyond this, the vehicle should also incorporate the prediction of the trajectory of its nearby vehicles, or target vehicles (TVs) into its decision-making. The conventional trajectory prediction methods, such as the constant-speed-based ones, are too trivial to accurately capture the potential collision risks. In this report, we propose a novel MPC-based motion planning","authors_text":"Jizheng Liu, Marion Leibold, Martin Buss, Ni Dang, Zengjie Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-04T14:20:50Z","title":"Incorporating Target Vehicle Trajectories Predicted by Deep Learning Into Model Predictive Controlled Vehicles"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.02843","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:0036a56615050562ff3a234cf2ad4d45a164d4831ba2f15923cbd42ef1ae0221","target":"record","created_at":"2026-07-05T06:57:14Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"186725e8f55dcf5aef06d91e52d00166a25022a47eb5fd6cd4deba97a44cd55d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-10-04T14:20:50Z","title_canon_sha256":"8312369c2672fc42a8b5e7c646a7ccd87adeb4a2eafd59fdff179fcf0cec78eb"},"schema_version":"1.0","source":{"id":"2310.02843","kind":"arxiv","version":1}},"canonical_sha256":"4acbada884625a32a3ca6ac40c828871af52f4ce482df0499e1b412fe1d2d301","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4acbada884625a32a3ca6ac40c828871af52f4ce482df0499e1b412fe1d2d301","first_computed_at":"2026-07-05T06:57:14.557338Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:57:14.557338Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"c1t/MB0XnDXqDt2kLDzpLKBhSEtZ4Wnuw0VqZDjQmcUh8TEkTFjoT7kZSB33wenj/eHHlhQ27knl2I17PWg9Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:57:14.557897Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.02843","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0036a56615050562ff3a234cf2ad4d45a164d4831ba2f15923cbd42ef1ae0221","sha256:c5e4e37705d1c9eb8d858fcf18c6e0452e46b02b8b14302fcdce159780e51207"],"state_sha256":"c353ea5d32b55243b107867ef482b6196b5d0fd947ff30538b0ba5489e8279a1"}