{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MZVH5GJHEUP2CL2CXQXDPCT36R","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":"40e0b779b7d75e5b3ea51f7ce3a5094bc857a99febcc47c8a42a0f0adb182ce5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T10:33:31Z","title_canon_sha256":"329607c2679cbbc6999e0ff7c834faa29ed501adfcf5d14412afbef8d6cada25"},"schema_version":"1.0","source":{"id":"2503.07158","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.07158","created_at":"2026-07-05T11:07:21Z"},{"alias_kind":"arxiv_version","alias_value":"2503.07158v6","created_at":"2026-07-05T11:07:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.07158","created_at":"2026-07-05T11:07:21Z"},{"alias_kind":"pith_short_12","alias_value":"MZVH5GJHEUP2","created_at":"2026-07-05T11:07:21Z"},{"alias_kind":"pith_short_16","alias_value":"MZVH5GJHEUP2CL2C","created_at":"2026-07-05T11:07:21Z"},{"alias_kind":"pith_short_8","alias_value":"MZVH5GJH","created_at":"2026-07-05T11:07:21Z"}],"graph_snapshots":[{"event_id":"sha256:16e7c58c806e71e9299f5900f99b22faa97c78bcb97af0ca6105707d61d2c17a","target":"graph","created_at":"2026-07-05T11:07:21Z","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/2503.07158/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The integration of generative artificial intelligence (GenAI) into transportation planning has the potential to revolutionize tasks such as demand forecasting, infrastructure design, policy evaluation, and traffic simulation. However, there is a critical need for a systematic framework to guide the adoption of GenAI in this interdisciplinary domain. In this survey, we, a multidisciplinary team of researchers spanning computer science and transportation engineering, present the first comprehensive framework for leveraging GenAI in transportation planning. Specifically, we introduce a new taxono","authors_text":"Benjamin Stabler, Ben Zhou, Dongjie Wang, Huaiyuan Yao, Hua Wei, Li Li, Longchao Da, Ram Pendyala, Shreyas Bachiraju, Tiejin Chen, Xiyang Hu, Xuesong Zhou, Yezhou Yang, Yue Zhao, Yushun Dong, Zhengzhong Tu, Zhuoheng Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T10:33:31Z","title":"Generative AI in Transportation Planning: A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.07158","kind":"arxiv","version":6},"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":"sha256:1b2791bead7fd8febd42902076d0bb733918d7a5d4ea4bd281baaba08d69ab88","target":"record","created_at":"2026-07-05T11:07:21Z","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":"40e0b779b7d75e5b3ea51f7ce3a5094bc857a99febcc47c8a42a0f0adb182ce5","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2025-03-10T10:33:31Z","title_canon_sha256":"329607c2679cbbc6999e0ff7c834faa29ed501adfcf5d14412afbef8d6cada25"},"schema_version":"1.0","source":{"id":"2503.07158","kind":"arxiv","version":6}},"canonical_sha256":"666a7e9927251fa12f42bc2e378a7bf459736fe93f85fc08b243d117815f9571","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"666a7e9927251fa12f42bc2e378a7bf459736fe93f85fc08b243d117815f9571","first_computed_at":"2026-07-05T11:07:21.588557Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:07:21.588557Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4jv/2R1kj7SmK0PNPMbDD6jGtvVVd+wJ7SdqR+3h3KYwQU8kRq/+xP/rwJmTOMtW0na20LtFW+RlCrP8f/9sAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:07:21.589151Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.07158","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b2791bead7fd8febd42902076d0bb733918d7a5d4ea4bd281baaba08d69ab88","sha256:16e7c58c806e71e9299f5900f99b22faa97c78bcb97af0ca6105707d61d2c17a"],"state_sha256":"89cf6cae3ffa0647cb16d6f0f9c4b677c633513d6048ecee5577e1466b192c00"}