{"id":"W4388918405","doi":"10.1016/j.ifacol.2023.10.459","title":"Switching formation control of multi-lane autonomous vehicle platoons robust to relative position measurement noises","year":2023,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Platoon; Robustness (evolution); Control theory (sociology); Position (finance); Relative velocity; Computer science; Vehicle dynamics; Dead zone; Control (management); Engineering; Control engineering; Automotive engineering; Artificial intelligence","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":[0.0005080611,0.000469627,0.0004085943,0.0001940395,0.0002644486,0.0005208637,0.0005542295,0.0002599117,0.0003402775],"category_scores_gemma":[0.001056732,0.0001838228,0.0002853147,0.0001617941,0.0006325066,0.0004804671,0.0008571077,0.0004693336,0.00005697139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003334774,"about_ca_system_score_gemma":0.000474068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002817482,"about_ca_topic_score_gemma":0.001695595,"domain_scores_codex":[0.9996939,0.00006251223,0.00001270255,0.00008488871,0.00008841285,0.00005752968],"domain_scores_gemma":[0.9995695,0.0001285642,0.0001370655,0.00004081121,0.00008404688,0.00004008549],"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":[0.0002246207,0.00005382322,0.0009569937,0.00006160043,0.00004220252,0.0001274784,0.0001943042,0.9319922,0.02905426,0.006527845,0.0002250892,0.0305396],"study_design_scores_gemma":[0.00001194536,0.0001174989,0.0003082383,0.000001539572,0.000005157326,0.00001018342,0.00001576397,0.9961663,0.002126652,0.001066679,0.0001668619,0.000003045705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2412713,0.0001753678,0.7559335,0.00009972992,0.00006023694,0.00003551492,0.00002024483,0.0003082504,0.002095796],"genre_scores_gemma":[0.9959741,0.00002748185,0.003591218,0.000009777309,0.00000657591,0.0000110627,0.000009850424,0.000005116204,0.000364854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002817482,"threshold_uncertainty_score":0.005602241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02639573765086354,"score_gpt":0.2185704298060483,"score_spread":0.1921746921551848,"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."}}