{"id":"W4386980319","doi":"10.1111/mice.13099","title":"Identifying dynamic interaction patterns in mandatory and discretionary lane changes using graph structure","year":2023,"lang":"en","type":"article","venue":"Computer-Aided Civil and Infrastructure Engineering","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; Science and Technology Commission of Shanghai Municipality; Canadian Institute for Advanced Research","keywords":"Computer science; Hidden Markov model; Graph; Process (computing); Trajectory; Data mining; Artificial intelligence; Theoretical computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0003877773,0.0004595665,0.0003330583,0.002511829,0.0003835935,0.0006518193,0.0006496645,0.0006065467,0.0009855813],"category_scores_gemma":[0.002658106,0.0002431969,0.0007658117,0.001542738,0.0005530229,0.001188648,0.0006129532,0.000552569,0.0002089986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008893492,"about_ca_system_score_gemma":0.0006690341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0201821,"about_ca_topic_score_gemma":0.03251192,"domain_scores_codex":[0.9996285,0.00007526028,0.00002042039,0.000135657,0.0000702934,0.00006983383],"domain_scores_gemma":[0.9982499,0.0009414944,0.0003353684,0.0001553898,0.00022476,0.00009297818],"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":[0.0002635733,0.0002563493,0.1458419,0.000281663,0.0002297627,0.0006916475,0.0007965484,0.7174282,0.008122675,0.02258865,0.003707413,0.09979158],"study_design_scores_gemma":[0.000005888029,0.00003706699,0.03171923,0.00001805543,0.00004180615,0.0001029787,0.0002243739,0.9548257,0.0009065541,0.01068614,0.0014086,0.00002358241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.653912,0.0005115944,0.3375665,0.0003086992,0.00003163496,0.0001378347,0.002702149,0.0007675639,0.004062051],"genre_scores_gemma":[0.9789368,0.0001550841,0.01834305,0.00002391376,0.000009264721,0.00005201612,0.00174192,0.00002855292,0.000709512],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0201821,"threshold_uncertainty_score":0.04012924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005751290321224317,"score_gpt":0.2057796549704942,"score_spread":0.2000283646492699,"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."}}