{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004136153,0.0001312976,0.0002114965,0.0001062685,0.0001408699,0.00003391552,0.0001273175,0.0001185446,0.00002131575],"category_scores_gemma":[0.00001136563,0.0001194944,0.0002823689,0.0002567471,0.0000545042,0.00004150246,0.000002039198,0.0002745412,5.318245e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004265952,"about_ca_system_score_gemma":0.0000809326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004823924,"about_ca_topic_score_gemma":0.001612701,"domain_scores_codex":[0.999109,0.00002789982,0.0002776166,0.0001626007,0.0001910275,0.0002318485],"domain_scores_gemma":[0.9993769,0.000215659,0.00002155769,0.0001923297,0.00007536608,0.00011822],"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":[0.000004247305,0.00001118549,7.616815e-8,0.0004278814,0.0001054864,1.527442e-7,0.00002913422,0.9306038,0.002687532,0.06433585,0.000007483401,0.00178719],"study_design_scores_gemma":[0.0002688132,0.00007453548,0.00001304115,0.0004779324,0.0000631066,0.000001604204,0.00008851227,0.9978069,0.0003750991,0.0006319527,0.00009799992,0.0001004887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001755328,0.0002693465,0.9957716,0.0004710368,0.0002394483,0.0007027611,0.0006966626,0.00006734423,0.00002639979],"genre_scores_gemma":[0.9982662,0.00007909084,0.001420572,0.00003786948,0.00001279353,0.0001166809,0.00001858524,0.00003609364,0.00001215838],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9965108,"threshold_uncertainty_score":0.4872841,"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."}}