{"id":"W4302774312","doi":"10.1155/2022/4357954","title":"Lane-Changing Model of Intelligent Connected Vehicle Considering the Factor of Turn Signal","year":2022,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Traffic control and management","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Shanxi Agricultural University","keywords":"Cellular automaton; Computer science; Scheduling (production processes); SIGNAL (programming language); Traffic flow (computer networking); Simulation; Intelligent transportation system; Transport engineering; Real-time computing; Engineering; Computer security; Artificial intelligence","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":[0.0003503085,0.00079395,0.0006194633,0.0007409729,0.0007439432,0.001105848,0.002122251,0.001109297,0.00361414],"category_scores_gemma":[0.0008060824,0.0004197901,0.001070671,0.0006169639,0.0008084059,0.001468099,0.0007108546,0.0009891876,0.0006402371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001145458,"about_ca_system_score_gemma":0.0008175186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02261427,"about_ca_topic_score_gemma":0.009779132,"domain_scores_codex":[0.9996343,0.00006006193,0.00001580535,0.0001283139,0.00008810709,0.00007346978],"domain_scores_gemma":[0.9996186,0.00009206563,0.00007002208,0.00002179618,0.0001618683,0.00003551661],"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":[0.00003833336,0.00002420313,0.001205329,0.00005129243,0.0000279757,0.0002201788,0.0001986666,0.9632406,0.002548014,0.02648813,0.000592155,0.005365202],"study_design_scores_gemma":[0.000002838136,0.00001254449,0.0001156989,0.000002447802,0.000009744009,0.00001922652,0.00001447689,0.9967804,0.00011734,0.002643286,0.0002768652,0.000005130972],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1143308,0.0007147063,0.8585541,0.000583323,0.0002113381,0.00007553711,0.0003248425,0.0004055868,0.02479978],"genre_scores_gemma":[0.9764625,0.0005030543,0.008766436,0.00006447857,0.00006047851,0.0001083016,0.0001812061,0.00004658261,0.01380683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02261427,"threshold_uncertainty_score":0.04496527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01261564474794756,"score_gpt":0.2061023917378649,"score_spread":0.1934867469899173,"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."}}