{"id":"W7132993979","doi":"","title":"Adaptive Transit Signal Priority Algorithms for Optimizing Bus Reliability and Travel Time using Deep Reinforcement Learning","year":2022,"lang":"","type":"dissertation","venue":"TSpace","topic":"Traffic control and management","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hudbay Minerals (Canada)","funders":"","keywords":"Headway; Reliability (semiconductor); Intersection (aeronautics); Schedule; Signal timing; Expediting; Reinforcement learning; Public transport; Microsimulation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006430483,0.0008921335,0.0007949538,0.0003816517,0.00023218,0.000590389,0.001058565,0.0007773997,0.001793463],"category_scores_gemma":[0.001930458,0.0003909842,0.0005011446,0.0003304235,0.0005140097,0.000509307,0.0007821915,0.001316861,0.0002681367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001042828,"about_ca_system_score_gemma":0.001479448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01368821,"about_ca_topic_score_gemma":0.01285004,"domain_scores_codex":[0.9998128,0.00004895138,0.000009824732,0.0000481761,0.00003512612,0.00004517408],"domain_scores_gemma":[0.9993616,0.0003835378,0.00006863193,0.00002528435,0.0001151012,0.00004589665],"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":[0.00003481757,0.00005017223,0.000536342,0.00002819592,0.00002342093,0.00002023732,0.0000206707,0.9675583,0.0005478135,0.001882937,0.0006088486,0.0286884],"study_design_scores_gemma":[0.000003824176,0.00001022091,0.00003012501,0.00000168064,0.000001849738,0.000001450569,0.000001615686,0.9994255,0.00008563232,0.0003774423,0.00005984831,8.202683e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1092593,0.0007748184,0.8817533,0.0005288584,0.00009069112,0.00008238972,0.0001104766,0.001095202,0.006305017],"genre_scores_gemma":[0.885224,0.0002135112,0.1097276,0.0002446294,0.00003875855,0.0001347015,0.0002590147,0.00008832227,0.004069507],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01368821,"threshold_uncertainty_score":0.02721709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01592152701531121,"score_gpt":0.2673188787192636,"score_spread":0.2513973517039524,"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."}}