{"id":"W2998852889","doi":"10.1155/2020/1456207","title":"Trajectory Planning Method for Mixed Vehicles Considering Traffic Stability and Fuel Consumption at the Signalized Intersection","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Intersection (aeronautics); Fuel efficiency; Trajectory; Automotive engineering; Controller (irrigation); MATLAB; Computer science; PID controller; Control theory (sociology); Simulation; Engineering; Transport engineering; Control (management); Control 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002313241,0.00009564293,0.00017806,0.0000374966,0.00005207667,0.00001415807,0.00003737954,0.00002980997,0.00001214239],"category_scores_gemma":[0.00001904373,0.00007748843,0.00008412974,0.00004657071,0.00002132423,0.0001853532,0.000001224196,0.0001117502,2.481165e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000481985,"about_ca_system_score_gemma":0.000008008443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.599259e-7,"about_ca_topic_score_gemma":0.00008021292,"domain_scores_codex":[0.9993224,0.00003033503,0.000355321,0.00009349897,0.0001028894,0.00009559108],"domain_scores_gemma":[0.9995362,0.0002004372,0.0001228122,0.00003797578,0.00004871032,0.00005390332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0006436068,0.000008177335,0.0001491149,0.0002882407,0.00008140509,0.000003570693,0.00552723,0.8813863,0.08635519,0.00001695513,0.0000449109,0.02549526],"study_design_scores_gemma":[0.0227047,0.001475534,0.6397873,0.00050891,0.001400746,0.0000533572,0.02063319,0.2497028,0.04331165,0.000600063,0.0188489,0.0009728776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.826243,0.001153473,0.1718572,0.0002203574,0.0002322232,0.0002292049,0.000008772994,0.0000519944,0.000003780223],"genre_scores_gemma":[0.9919717,0.0001053639,0.007781156,0.00004885359,0.00005747893,0.00001330877,0.000007708034,0.00001328883,0.000001156413],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6396382,"threshold_uncertainty_score":0.3159887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0249293617118127,"score_gpt":0.258431260142387,"score_spread":0.2335018984305743,"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."}}