{"id":"W4386917757","doi":"10.36227/techrxiv.24152175.v1","title":"Adaptive Velocity and Acceleration Control of Autonomous Vehicle Systems","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Platoon; Acceleration; Control theory (sociology); Collision avoidance; Adaptive control; Limit (mathematics); Nonlinear system; Computer science; Stability (learning theory); Control (management); Collision; Engineering; Control engineering; Mathematics; Physics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000278406,0.0004358528,0.000273575,0.0002664004,0.0002173477,0.0004755186,0.0004476187,0.0003816743,0.0008500038],"category_scores_gemma":[0.0007396649,0.0001336897,0.0001922268,0.0002340604,0.0004095454,0.0003653684,0.0005547873,0.0004360859,0.0001608998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002134463,"about_ca_system_score_gemma":0.0003696784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003557354,"about_ca_topic_score_gemma":0.001747036,"domain_scores_codex":[0.999719,0.0000561531,0.00001244492,0.00005988936,0.0001185061,0.00003406488],"domain_scores_gemma":[0.9997833,0.00006440272,0.00004088641,0.00001608532,0.00007979172,0.00001559737],"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":[0.0001019157,0.00004808884,0.0005842635,0.000110491,0.00004535374,0.0001482474,0.0001125261,0.8199301,0.02302376,0.03498979,0.001229674,0.1196757],"study_design_scores_gemma":[0.00001220562,0.00008040025,0.0002160221,0.000004257178,0.000003739406,0.00001787365,0.000008022458,0.992257,0.0009613294,0.004168223,0.002264516,0.000006540039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03531466,0.0006579356,0.9559192,0.0001726611,0.0001733139,0.00002810935,0.00002038779,0.0002878244,0.007425907],"genre_scores_gemma":[0.979474,0.0002777767,0.01597624,0.00004292034,0.0001205111,0.00004393112,0.00002763465,0.00001380304,0.004023202],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003557354,"threshold_uncertainty_score":0.007073283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02288090793608885,"score_gpt":0.2082355207468808,"score_spread":0.1853546128107919,"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."}}