{"id":"W4367360147","doi":"10.5220/0011792500003479","title":"Optimizing CAV Driving Behaviour to Reduce Traffic Congestion and GHG Emissions","year":2023,"lang":"en","type":"article","venue":"","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Greenhouse gas; Computer science; Traffic congestion; Environmental science; Transport engineering; Automotive engineering; Business; Engineering","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":[0.0002787503,0.0003645121,0.0002744463,0.0004252953,0.0003479661,0.0006439157,0.0004220031,0.0003224067,0.003169227],"category_scores_gemma":[0.0008643875,0.0001476593,0.000220725,0.0002916752,0.0001843054,0.0003625591,0.0002673712,0.0002622791,0.0008126132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005117384,"about_ca_system_score_gemma":0.001087928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01071204,"about_ca_topic_score_gemma":0.02132161,"domain_scores_codex":[0.9997544,0.00005741089,0.000007734735,0.00004332143,0.00006501034,0.00007218464],"domain_scores_gemma":[0.9996636,0.00005457545,0.00004301713,0.00002799568,0.0001760968,0.00003471184],"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":[0.001634576,0.002807508,0.1152569,0.0004354491,0.000228517,0.0002236978,0.0005727409,0.3105009,0.2706028,0.004755356,0.005361957,0.2876196],"study_design_scores_gemma":[0.00009848311,0.002283664,0.167477,0.0000730954,0.0001958757,0.0001847349,0.001886765,0.7397369,0.07267301,0.00389538,0.01141652,0.00007860269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9351737,0.0001455269,0.04088248,0.0002203907,0.00004496097,0.00007026565,0.0001526845,0.0006715806,0.02263837],"genre_scores_gemma":[0.9940085,0.00003129675,0.003460625,0.00002138197,0.000003379716,0.000009235089,0.00006859589,0.00003802414,0.002358938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01071204,"threshold_uncertainty_score":0.02129936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01739270741946293,"score_gpt":0.2553266645956087,"score_spread":0.2379339571761457,"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."}}