{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:W73NJL6ESEDBCA2Y6DYE7F5PXK","short_pith_number":"pith:W73NJL6E","canonical_record":{"source":{"id":"2407.17303","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-24T14:17:16Z","cross_cats_sorted":[],"title_canon_sha256":"a3c21f3f65d9f107480a1ab1f4a0660d3bfce059caec2580abc5f10dedffa447","abstract_canon_sha256":"ade576db5002b0a75056db7af614923bdacbb230fb9fe74253aadcce3954feec"},"schema_version":"1.0"},"canonical_sha256":"b7f6d4afc49106110358f0f04f97afbab4ebdbbc6defd981f64ddc496a6cc246","source":{"kind":"arxiv","id":"2407.17303","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.17303","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"arxiv_version","alias_value":"2407.17303v1","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.17303","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"pith_short_12","alias_value":"W73NJL6ESEDB","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"pith_short_16","alias_value":"W73NJL6ESEDBCA2Y","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"pith_short_8","alias_value":"W73NJL6E","created_at":"2026-07-05T08:48:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:W73NJL6ESEDBCA2Y6DYE7F5PXK","target":"record","payload":{"canonical_record":{"source":{"id":"2407.17303","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-24T14:17:16Z","cross_cats_sorted":[],"title_canon_sha256":"a3c21f3f65d9f107480a1ab1f4a0660d3bfce059caec2580abc5f10dedffa447","abstract_canon_sha256":"ade576db5002b0a75056db7af614923bdacbb230fb9fe74253aadcce3954feec"},"schema_version":"1.0"},"canonical_sha256":"b7f6d4afc49106110358f0f04f97afbab4ebdbbc6defd981f64ddc496a6cc246","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:48:06.654454Z","signature_b64":"yuRPe5GCZ0VNp190cPlw8qOudbZf5qTc6qONeuyIIWQ5rvNq6XQkoxEGU8HbtHN4Biso28wdYMKT/2tgfcrrDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7f6d4afc49106110358f0f04f97afbab4ebdbbc6defd981f64ddc496a6cc246","last_reissued_at":"2026-07-05T08:48:06.653976Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:48:06.653976Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.17303","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:48:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j32L0x6Yjn6nV6mCB/k2RoVahJKjAPsgMB12PrgQLVp7iLf9TkjXbm1H87ozvkePM9nXW1Zx4MZSFXsYChbsAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:36:08.129817Z"},"content_sha256":"114c1d806925914e7950c302e7c51b26f0faf9636453589007f88cf107203ef4","schema_version":"1.0","event_id":"sha256:114c1d806925914e7950c302e7c51b26f0faf9636453589007f88cf107203ef4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:W73NJL6ESEDBCA2Y6DYE7F5PXK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MoveLight: Enhancing Traffic Signal Control through Movement-Centric Deep Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chenhao Zheng, Junqi Shao, Rui Zhang, Yucheng Huang, Yuxuan Chen","submitted_at":"2024-07-24T14:17:16Z","abstract_excerpt":"This paper introduces MoveLight, a novel traffic signal control system that enhances urban traffic management through movement-centric deep reinforcement learning. By leveraging detailed real-time data and advanced machine learning techniques, MoveLight overcomes the limitations of traditional traffic signal control methods. It employs a lane-level control approach using the FRAP algorithm to achieve dynamic and adaptive traffic signal control, optimizing traffic flow, reducing congestion, and improving overall efficiency. Our research demonstrates the scalability and effectiveness of MoveLigh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.17303","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/2407.17303/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:48:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ARQKH9rxe8yWK0UxVaLb5VOxF5IU03+x4pU9ET7trDzKAzXbbTI4oYn28ojIe1EL4XGmMS+CA8kXPhd1kSzTAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:36:08.130448Z"},"content_sha256":"4f3430b70740d20e539a5be08ec02edb6f06cf725b0a292a1a781a63b0786036","schema_version":"1.0","event_id":"sha256:4f3430b70740d20e539a5be08ec02edb6f06cf725b0a292a1a781a63b0786036"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W73NJL6ESEDBCA2Y6DYE7F5PXK/bundle.json","state_url":"https://pith.science/pith/W73NJL6ESEDBCA2Y6DYE7F5PXK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W73NJL6ESEDBCA2Y6DYE7F5PXK/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T18:36:08Z","links":{"resolver":"https://pith.science/pith/W73NJL6ESEDBCA2Y6DYE7F5PXK","bundle":"https://pith.science/pith/W73NJL6ESEDBCA2Y6DYE7F5PXK/bundle.json","state":"https://pith.science/pith/W73NJL6ESEDBCA2Y6DYE7F5PXK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W73NJL6ESEDBCA2Y6DYE7F5PXK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:W73NJL6ESEDBCA2Y6DYE7F5PXK","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":"ade576db5002b0a75056db7af614923bdacbb230fb9fe74253aadcce3954feec","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-24T14:17:16Z","title_canon_sha256":"a3c21f3f65d9f107480a1ab1f4a0660d3bfce059caec2580abc5f10dedffa447"},"schema_version":"1.0","source":{"id":"2407.17303","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.17303","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"arxiv_version","alias_value":"2407.17303v1","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.17303","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"pith_short_12","alias_value":"W73NJL6ESEDB","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"pith_short_16","alias_value":"W73NJL6ESEDBCA2Y","created_at":"2026-07-05T08:48:06Z"},{"alias_kind":"pith_short_8","alias_value":"W73NJL6E","created_at":"2026-07-05T08:48:06Z"}],"graph_snapshots":[{"event_id":"sha256:4f3430b70740d20e539a5be08ec02edb6f06cf725b0a292a1a781a63b0786036","target":"graph","created_at":"2026-07-05T08:48:06Z","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/2407.17303/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces MoveLight, a novel traffic signal control system that enhances urban traffic management through movement-centric deep reinforcement learning. By leveraging detailed real-time data and advanced machine learning techniques, MoveLight overcomes the limitations of traditional traffic signal control methods. It employs a lane-level control approach using the FRAP algorithm to achieve dynamic and adaptive traffic signal control, optimizing traffic flow, reducing congestion, and improving overall efficiency. Our research demonstrates the scalability and effectiveness of MoveLigh","authors_text":"Chenhao Zheng, Junqi Shao, Rui Zhang, Yucheng Huang, Yuxuan Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-24T14:17:16Z","title":"MoveLight: Enhancing Traffic Signal Control through Movement-Centric Deep Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.17303","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":"sha256:114c1d806925914e7950c302e7c51b26f0faf9636453589007f88cf107203ef4","target":"record","created_at":"2026-07-05T08:48:06Z","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":"ade576db5002b0a75056db7af614923bdacbb230fb9fe74253aadcce3954feec","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-24T14:17:16Z","title_canon_sha256":"a3c21f3f65d9f107480a1ab1f4a0660d3bfce059caec2580abc5f10dedffa447"},"schema_version":"1.0","source":{"id":"2407.17303","kind":"arxiv","version":1}},"canonical_sha256":"b7f6d4afc49106110358f0f04f97afbab4ebdbbc6defd981f64ddc496a6cc246","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7f6d4afc49106110358f0f04f97afbab4ebdbbc6defd981f64ddc496a6cc246","first_computed_at":"2026-07-05T08:48:06.653976Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:48:06.653976Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yuRPe5GCZ0VNp190cPlw8qOudbZf5qTc6qONeuyIIWQ5rvNq6XQkoxEGU8HbtHN4Biso28wdYMKT/2tgfcrrDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:48:06.654454Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.17303","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:114c1d806925914e7950c302e7c51b26f0faf9636453589007f88cf107203ef4","sha256:4f3430b70740d20e539a5be08ec02edb6f06cf725b0a292a1a781a63b0786036"],"state_sha256":"af70eac3a67ec63cb1bc84ac86530ea3aca560f270b89dc0e3967079451682bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KE5jSEKQanp7NsazrHI2y8+akJ/oj95D+bp6p74RiC6kxz9y0ZcTViRFu/493DwU0//BFcBod8FDhc8e3OdAAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T18:36:08.138570Z","bundle_sha256":"d1141b05c336a640d491a5472a4f3aaa600bd2a044c89cdf0020a42c5c154451"}}