{"id":"W4402196825","doi":"10.1139/tcsme-2023-0051","title":"Research on dynamic constraint mechanism and motion control of intelligent vehicles based on preview distance optimization under complex road conditions","year":2024,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Mechanism (biology); Constraint (computer-aided design); Motion (physics); Computer science; Control theory (sociology); Control engineering; Control (management); Motion control; Engineering; Simulation; Artificial intelligence; Mechanical engineering; Robot; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004412254,0.0005467039,0.0004773187,0.0003459537,0.0003432581,0.0007188942,0.0008262171,0.0004007008,0.0006688776],"category_scores_gemma":[0.001011441,0.0002707178,0.0003633171,0.0002730828,0.00059311,0.001044743,0.0005360633,0.0004447857,0.0000862106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005206545,"about_ca_system_score_gemma":0.0007844241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006120121,"about_ca_topic_score_gemma":0.002567035,"domain_scores_codex":[0.9996867,0.00004138591,0.0000151589,0.0001027284,0.0001051445,0.00004896883],"domain_scores_gemma":[0.9995758,0.0001439858,0.0001065854,0.00003558947,0.000113801,0.00002429552],"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":[0.00007752612,0.00003525291,0.001187471,0.000128655,0.00004212663,0.00009301981,0.0001651679,0.9221096,0.02055408,0.01454419,0.000225314,0.04083757],"study_design_scores_gemma":[0.00000590621,0.00006155294,0.000359359,0.000003454488,0.000006564249,0.00001310319,0.00001854972,0.9951556,0.002589252,0.00136777,0.0004106888,0.000008211182],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07450997,0.0004084466,0.9217556,0.00008556625,0.0000257713,0.00002743697,0.00001560371,0.0001334919,0.003038153],"genre_scores_gemma":[0.9785039,0.0002435146,0.02002689,0.00002202203,0.00001340852,0.00003653341,0.00002400233,0.00001774326,0.001112012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006120121,"threshold_uncertainty_score":0.012169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069332685489609,"score_gpt":0.2583561839434593,"score_spread":0.2376628570885632,"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."}}