{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003422257,0.0006444575,0.0004747755,0.0007047413,0.0006421641,0.0006074324,0.0005532976,0.0003105193,0.0005701258],"category_scores_gemma":[0.0005914216,0.0002139736,0.0003402141,0.000425025,0.0004388794,0.0005553132,0.0006031684,0.0003138321,0.00008159461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000504993,"about_ca_system_score_gemma":0.0006743897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006060905,"about_ca_topic_score_gemma":0.004604846,"domain_scores_codex":[0.9997906,0.00004964079,0.000009924789,0.00004461882,0.0000556911,0.00004956274],"domain_scores_gemma":[0.9996777,0.00008271068,0.00007391354,0.00002479993,0.00008174176,0.00005921481],"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":[0.0001164373,0.0001123093,0.002891583,0.00004249504,0.00007298697,0.00008564577,0.0001623556,0.913918,0.01597268,0.004084252,0.0006307912,0.06191052],"study_design_scores_gemma":[0.000009464135,0.0000633362,0.0004140077,0.0000021515,0.00001158953,0.00001214207,0.00003274452,0.9965078,0.001201169,0.001220712,0.0005193598,0.0000056163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2762945,0.0003155268,0.7161599,0.0001823027,0.00008520089,0.0001368329,0.00006005899,0.0006454868,0.006120098],"genre_scores_gemma":[0.9807202,0.00007288641,0.01854268,0.00002074798,0.00001183267,0.0000389479,0.00004036529,0.00001135426,0.0005410328],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006060905,"threshold_uncertainty_score":0.01205122,"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."}}