{"id":"W7118504762","doi":"10.1109/vtc2025-fall65116.2025.11310111","title":"Enhancing Cooperative Adaptive Cruise Control in Vehicle Platooning Through Intent Sharing and Multi-Agent Reinforcement Learning","year":2025,"lang":"","type":"article","venue":"","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Platoon; Cruise control; Cooperative Adaptive Cruise Control; Acceleration; Reinforcement learning; String (physics); Control (management); State (computer science)","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":[0.0009128232,0.0005527131,0.0003826928,0.0002091813,0.00029639,0.0003320501,0.000724584,0.0003461072,0.0004727501],"category_scores_gemma":[0.001986314,0.000218707,0.0002451833,0.0001243203,0.0005771561,0.0006478449,0.0009465047,0.0005217741,0.00009035342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003226751,"about_ca_system_score_gemma":0.0006013254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002953242,"about_ca_topic_score_gemma":0.001951554,"domain_scores_codex":[0.9996413,0.0001120934,0.0000168712,0.00006788103,0.0001078995,0.0000540077],"domain_scores_gemma":[0.9990373,0.0003956581,0.0002029134,0.0000918795,0.0001900105,0.00008238005],"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":[0.0001548009,0.000220495,0.001518949,0.0000441984,0.00005144114,0.0001212183,0.0002079519,0.9291633,0.01498186,0.003802389,0.0001993877,0.0495339],"study_design_scores_gemma":[0.00001102021,0.00009271669,0.0001682903,0.000001616047,0.000004759045,0.0000105034,0.000007818484,0.9977263,0.00104064,0.0008171964,0.0001153903,0.000003785007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1696716,0.0001148637,0.8277315,0.0001003335,0.00002707537,0.00005405963,0.000006730663,0.0002458634,0.002047948],"genre_scores_gemma":[0.9838157,0.00002078562,0.01571919,0.00001913185,0.00000820585,0.00002075277,0.000005073943,0.00000527151,0.0003858555],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002953242,"threshold_uncertainty_score":0.005872071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585519242863103,"score_gpt":0.2361268954445371,"score_spread":0.2202717030159061,"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."}}