{"id":"W2911991143","doi":"10.1155/2019/6039741","title":"Optimal Signal Control Algorithm for Signalized Intersections under a V2I Communication Environment","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Korea Agency for Infrastructure Technology Advancement; Ministry of Land, Infrastructure and Transport","keywords":"VisSim; Intersection (aeronautics); Signal timing; SIGNAL (programming language); Computation; Algorithm; Computer science; Optimal control; Simulation; Real-time computing; Engineering; Mathematical optimization; Traffic signal; Mathematics; Transport engineering","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":[0.0004765029,0.0004255382,0.0004754515,0.0003822546,0.0003608681,0.0006827651,0.0007775468,0.000449411,0.001060063],"category_scores_gemma":[0.001181796,0.0001878796,0.0002945451,0.0003609396,0.0004811246,0.0006554046,0.0004717233,0.0005746596,0.0001352879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000783079,"about_ca_system_score_gemma":0.001671897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008404397,"about_ca_topic_score_gemma":0.00440386,"domain_scores_codex":[0.9995726,0.00006376115,0.00002074706,0.0001105778,0.0001601724,0.00007216423],"domain_scores_gemma":[0.9995982,0.0001279828,0.00008500785,0.00002075665,0.0001498151,0.0000183129],"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":[0.00006996215,0.00002722045,0.0004665974,0.00003586806,0.00001181882,0.00002668675,0.0000660942,0.9441357,0.003423193,0.009168588,0.0003863772,0.04218202],"study_design_scores_gemma":[0.000006294963,0.0000255364,0.00005189577,0.000001607062,0.00000231685,0.000004719267,0.000006979641,0.9985322,0.0006126704,0.0005978888,0.000155864,0.000002132488],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02592337,0.00006177642,0.9718351,0.00006417325,0.00001424598,0.00003196716,0.00001197021,0.0001230593,0.001934375],"genre_scores_gemma":[0.901871,0.0001036533,0.09622461,0.00003733343,0.00001737403,0.00008593607,0.00005282989,0.00002313026,0.00158407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008404397,"threshold_uncertainty_score":0.016711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004697368854633846,"score_gpt":0.2022191365492055,"score_spread":0.1975217676945716,"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."}}