{"id":"W3164298177","doi":"10.3390/electronics10101221","title":"Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies","year":2021,"lang":"en","type":"article","venue":"Electronics","topic":"Traffic control and management","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Pakistan Institute of Engineering and Applied Sciences","keywords":"Platoon; Collision avoidance; Vehicle-to-vehicle; Computer science; Traffic flow (computer networking); Wireless; Traffic congestion; Collision; Intelligent transportation system; Traffic conflict; Flow (mathematics); Computer network; Simulation; Transport engineering; Engineering; Computer security; Floating car data; Telecommunications; Artificial intelligence; Control (management)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007718515,0.0001124753,0.0001525452,0.00003691895,0.00005560416,0.00004566388,0.00006172722,0.00003559466,0.000006286135],"category_scores_gemma":[0.000001209754,0.0001244184,0.000032528,0.0001359935,0.00001581036,0.0000960917,0.00003463895,0.0001010729,0.000001195063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007951695,"about_ca_system_score_gemma":0.00004034652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001000804,"about_ca_topic_score_gemma":0.00004534653,"domain_scores_codex":[0.9993201,0.00001115156,0.0001653016,0.0001495066,0.0001026374,0.0002512789],"domain_scores_gemma":[0.9997782,0.00001659129,0.00002330298,0.0001341344,0.00001897655,0.00002880246],"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":[0.000005767787,0.00001620069,0.000003762495,0.0001881393,0.0001026529,0.00002344766,0.0001491042,0.8989539,0.004273176,0.003985117,0.00004137504,0.09225741],"study_design_scores_gemma":[0.000707591,0.00004562347,0.0007869063,0.0001204438,0.00008714235,0.0000131928,0.0007717808,0.9789219,0.004170233,0.0002381557,0.01391551,0.0002214669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9607463,0.03017812,0.00767303,0.00002187607,0.0001030674,0.0001085255,0.0000024115,0.0001570669,0.001009563],"genre_scores_gemma":[0.9915207,0.002835097,0.005506155,0.00000748716,0.00001858269,0.000005497214,0.000003862228,0.00001870326,0.00008390602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09203594,"threshold_uncertainty_score":0.5073635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006785474675822916,"score_gpt":0.2014058306729093,"score_spread":0.1946203559970864,"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."}}