{"id":"W3084397995","doi":"10.32393/csme.2020.1173","title":"A Vehicle Path Following Controller for Coupled Longitudinal and Lateral Motion","year":2020,"lang":"en","type":"article","venue":"Progress in Canadian Mechanical Engineering. Volume 3","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Path (computing); Motion control; Control theory (sociology); Computer science; Motion (physics); Controller (irrigation); Computer vision; Control (management); Artificial intelligence; Robot","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":[0.0003026524,0.000601305,0.0004332561,0.000248016,0.0005871209,0.0005377403,0.0009120352,0.0005246921,0.002257125],"category_scores_gemma":[0.0005072373,0.0002204653,0.0003455787,0.0001538067,0.0002952557,0.0004423876,0.0005967581,0.0006667986,0.0005258918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003890659,"about_ca_system_score_gemma":0.0009812929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005056454,"about_ca_topic_score_gemma":0.004831445,"domain_scores_codex":[0.9997807,0.00002115628,0.00001194828,0.00007197901,0.00008540459,0.00002879461],"domain_scores_gemma":[0.9997496,0.00004878922,0.00004566134,0.00001621868,0.0001256413,0.00001411737],"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":[0.0002908225,0.0001963428,0.001516132,0.0003729842,0.0001051074,0.0004389529,0.0003977062,0.5804491,0.1187554,0.01445971,0.004884122,0.2781337],"study_design_scores_gemma":[0.00004354602,0.0002071565,0.0004031424,0.00001274332,0.00002548626,0.00008361119,0.00001812784,0.9866702,0.008050118,0.0006637396,0.003806708,0.0000153234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02075508,0.000108005,0.9723333,0.00009915125,0.0000825106,0.0001028384,0.00003635998,0.001351068,0.005131755],"genre_scores_gemma":[0.8921496,0.0001352955,0.09917732,0.0001077769,0.00004237263,0.0002879668,0.000112339,0.00005540084,0.007932036],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005056454,"threshold_uncertainty_score":0.01005399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00706821046508693,"score_gpt":0.1929041019093333,"score_spread":0.1858358914442464,"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."}}