{"id":"W2125129403","doi":"10.1002/atr.5670400102","title":"The simple platoon advancement model of its technologies applied to vehicle control at signalised intersections","year":2006,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Platoon; Cruise control; Queue; Throughput; Collision avoidance; Traffic flow (computer networking); Engineering; Simple (philosophy); Intelligent transportation system; Collision; Simulation; Computer science; Automotive engineering; Control (management); Transport engineering; Artificial intelligence; Computer network; Computer security; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003748748,0.0004328154,0.0004088493,0.0003749037,0.0004774416,0.001131209,0.0009978699,0.0006679772,0.004515656],"category_scores_gemma":[0.0009185689,0.0001938029,0.0004582712,0.0004648739,0.001233246,0.001329639,0.0008041445,0.00072346,0.0005128825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181201,"about_ca_system_score_gemma":0.001075033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01147949,"about_ca_topic_score_gemma":0.00412243,"domain_scores_codex":[0.99963,0.0001044903,0.00001357051,0.00006235921,0.0001283773,0.00006125429],"domain_scores_gemma":[0.9996551,0.0001039415,0.00005719988,0.00003338826,0.00009554133,0.00005472456],"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":[0.00003963929,0.00002177037,0.0004037662,0.00003573603,0.00001102175,0.00009095425,0.0000961508,0.801798,0.001131735,0.1904492,0.0006829677,0.005239008],"study_design_scores_gemma":[0.00001167333,0.00003618292,0.00008206293,0.000003914151,0.000004898376,0.00001406117,0.00001455723,0.9772372,0.0001302978,0.02087067,0.00158926,0.000005324078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.143778,0.0006212147,0.7744046,0.001204997,0.0002613222,0.00017648,0.0003582996,0.0002551372,0.07893994],"genre_scores_gemma":[0.9702481,0.0004053882,0.01311283,0.00007720058,0.00008023725,0.0001559649,0.0001004553,0.00002263504,0.01579709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01147949,"threshold_uncertainty_score":0.02282536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004973359292503814,"score_gpt":0.1939498808385564,"score_spread":0.1889765215460526,"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."}}