{"id":"W4403353133","doi":"10.1007/978-3-031-66968-2_64","title":"Multi-objective Predictive Control for Intelligent Vehicles by Considering Stability Constraints in Complex Scenarios","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in mechanical engineering","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Model predictive control; Stability (learning theory); Control (management); Computer science; Control theory (sociology); Engineering; Artificial intelligence; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005162039,0.001125648,0.000948309,0.0003996449,0.0003976483,0.001248278,0.0009113707,0.0008272791,0.002127487],"category_scores_gemma":[0.0009735048,0.0005547905,0.000466647,0.0006183962,0.0005969125,0.001061764,0.001056789,0.0009909562,0.0002667827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005295741,"about_ca_system_score_gemma":0.0005542762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004937266,"about_ca_topic_score_gemma":0.004865669,"domain_scores_codex":[0.9998358,0.00004416169,0.000007142719,0.00003097571,0.00005317415,0.00002869263],"domain_scores_gemma":[0.9997148,0.0001597481,0.00004392174,0.00001558181,0.00005068114,0.00001519146],"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":[0.00001300257,0.00000957971,0.00003978959,0.00004218181,0.00001232737,0.00003309689,0.00001977188,0.9840715,0.0004448136,0.004460744,0.0004609928,0.01039229],"study_design_scores_gemma":[0.000001572383,0.000008178567,0.000028757,0.000003581141,0.000001837127,0.00000320167,0.00000293816,0.9977846,0.00006302087,0.001933286,0.0001676379,0.000001532628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02119977,0.001106817,0.9651577,0.0001992218,0.0001005049,0.00003993371,0.0000642023,0.0001829878,0.01194889],"genre_scores_gemma":[0.9611168,0.0006278873,0.03302573,0.00006720953,0.0000873235,0.0001357681,0.00009403703,0.00005943627,0.004785734],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004937266,"threshold_uncertainty_score":0.009817064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01425690750587758,"score_gpt":0.2165799817991831,"score_spread":0.2023230742933055,"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."}}