{"id":"W4381248971","doi":"10.3390/app13127234","title":"A Microscopic Traffic Model Considering Time Headway and Distance Headway","year":2023,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Traffic control and management","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Headway; Microscopic traffic flow model; Traffic flow (computer networking); Acceleration; Traffic wave; Simulation; Traffic model; Computer science; Constant (computer programming); Three-phase traffic theory; Traffic generation model; Traffic congestion reconstruction with Kerner's three-phase theory; Statistical physics; Transport engineering; Real-time computing; Engineering; Physics; Traffic congestion; Classical mechanics; Computer network","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":[0.0002201621,0.0007583726,0.000639682,0.0007401966,0.0004201839,0.000891689,0.001683584,0.0007892678,0.002868993],"category_scores_gemma":[0.0007438056,0.0003250185,0.0006946602,0.0007779848,0.0004531749,0.001404111,0.0005691631,0.0008376182,0.0007054661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009332915,"about_ca_system_score_gemma":0.001542328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01745134,"about_ca_topic_score_gemma":0.01088375,"domain_scores_codex":[0.9997424,0.00003135423,0.00001191806,0.00008058968,0.00009573812,0.00003793718],"domain_scores_gemma":[0.9996892,0.00006415667,0.00005154425,0.00003771231,0.000125309,0.00003202254],"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":[0.00002116934,0.0000365713,0.001231578,0.00002984624,0.00001325988,0.00003821504,0.00002175916,0.9761478,0.003457391,0.01112657,0.0007630235,0.007112809],"study_design_scores_gemma":[0.0000037652,0.00002118684,0.0003600329,0.000002614672,0.00001007845,0.00002575541,0.000006167616,0.9967442,0.0002849939,0.001491626,0.001039579,0.000009997241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07463377,0.00016987,0.9107586,0.000241626,0.0001996174,0.0001144437,0.0009349172,0.0007228709,0.01222428],"genre_scores_gemma":[0.9074618,0.0006204729,0.06978734,0.00009882375,0.0001147118,0.0003361891,0.00115699,0.0001641328,0.02025952],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01745134,"threshold_uncertainty_score":0.03469956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01294454454984664,"score_gpt":0.2109996648168695,"score_spread":0.1980551202670228,"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."}}