{"id":"W4413639580","doi":"10.1109/tits.2025.3600180","title":"Event-Triggered Adaptive Optimal Control of Vehicular Platoons via Fuzzy ADP With Prescribed Performance","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Traffic control and management","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"National Natural Science Foundation of China","keywords":"Fuzzy logic; Control theory (sociology); Optimal control; Computer science; Control (management); Fuzzy control system; Mathematical optimization; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001360912,0.0002944735,0.0004257816,0.0003321538,0.0000958647,0.00002413631,0.0001597472,0.0001131815,0.0000301284],"category_scores_gemma":[4.888328e-7,0.0002696453,0.0001724358,0.0004027345,0.00005053889,0.000173189,1.535658e-7,0.0002269978,0.00001796379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009819127,"about_ca_system_score_gemma":0.00004373051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008439305,"about_ca_topic_score_gemma":0.0001709894,"domain_scores_codex":[0.9983613,0.00003885641,0.0007069482,0.0002817113,0.0003349348,0.0002762146],"domain_scores_gemma":[0.9993216,0.00007274246,0.00008963173,0.0002812982,0.0001542811,0.00008047643],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000522721,0.0001485385,0.00004234712,0.0003732589,0.0008100155,0.000005955862,0.0005893493,0.9877659,0.001143928,0.0003985342,0.00005847946,0.008140972],"study_design_scores_gemma":[0.003945617,0.0007056181,0.002357248,0.0009849136,0.001048475,0.00000358784,0.001255009,0.9451168,0.04011771,0.000009731226,0.003815787,0.0006394912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08683621,0.0005117957,0.9097436,0.0000226745,0.0008873747,0.001182676,0.0001524522,0.000298661,0.0003645621],"genre_scores_gemma":[0.9987431,0.0001337506,0.0001813337,0.00002129549,0.00001913164,0.0004647706,0.00001941971,0.00003411404,0.0003831559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9119068,"threshold_uncertainty_score":0.9999756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007868717707687342,"score_gpt":0.1959822066068172,"score_spread":0.1881134888991298,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}