{"id":"W2991422210","doi":"10.1115/dscc2019-9069","title":"Hierarchical Nonlinear Moving Horizon Estimation of Vehicle Lateral Speed and Road Friction Coefficient","year":2019,"lang":"en","type":"article","venue":"","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nonlinear system; Horizon; Friction coefficient; Estimation; Control theory (sociology); Computer science; Moving horizon estimation; Dynamical friction; Control (management); Engineering; Mathematics; Physics; Artificial intelligence; Materials science; Kalman filter; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.00009131475,0.00007247873,0.0001308089,0.00005072523,0.00001776977,0.00002284543,0.00003802755,0.00005142922,0.0000195183],"category_scores_gemma":[0.000003982147,0.0000662798,0.00002533236,0.0000711847,0.000008456957,0.00007039614,0.00001498931,0.00007169177,0.00001800671],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002365104,"about_ca_system_score_gemma":0.000004218236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008333692,"about_ca_topic_score_gemma":0.000005895212,"domain_scores_codex":[0.9994941,0.00001097922,0.0001778079,0.0000970219,0.0001069171,0.0001132128],"domain_scores_gemma":[0.9998094,0.00001573225,0.00002181653,0.00009712112,0.00001944543,0.00003652625],"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":[0.00002143591,0.00003217058,0.005173149,0.0001240327,0.00003308487,0.000001141602,0.0002172368,0.806039,0.1286145,0.001638793,0.00001434216,0.05809121],"study_design_scores_gemma":[0.0003866392,0.0000809132,0.01357432,0.00001979289,0.000005014428,0.000002496704,0.00002161274,0.9851087,0.0006619589,0.00002211386,0.00004251712,0.00007388413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9886872,0.00003917379,0.008612385,0.00002515984,0.0001994924,0.0001507388,0.000004226019,0.00009130232,0.002190371],"genre_scores_gemma":[0.9992959,0.000005258955,0.0005014789,0.000005102397,0.00003402168,0.000001437248,0.000007740208,0.0000125227,0.0001365286],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1790698,"threshold_uncertainty_score":0.2702812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003622324871004336,"score_gpt":0.1913632825065528,"score_spread":0.1877409576355485,"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."}}