{"id":"W4396909936","doi":"10.1109/tiv.2024.3401051","title":"Bayesian Fault Injection Safety Testing for Highly Automated Vehicles With Uncertainty","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Vehicles","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Natural Science Foundation of China","keywords":"Monte Carlo method; Computer science; Fault (geology); Bayesian probability; Reliability engineering; Collision; Bayesian network; Dynamic Bayesian network; Reliability (semiconductor); Software deployment; Simulation; Data mining; Engineering; Artificial intelligence; Statistics","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":[0.001400042,0.00064185,0.0006381241,0.0007892299,0.0003663008,0.0005540462,0.001037991,0.000583224,0.0008000463],"category_scores_gemma":[0.006029665,0.0003748426,0.0005915457,0.0003141488,0.0005959377,0.001048997,0.0007779641,0.0008036547,0.0001140352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136469,"about_ca_system_score_gemma":0.001492058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01170249,"about_ca_topic_score_gemma":0.006850847,"domain_scores_codex":[0.9988216,0.000314141,0.00005634962,0.000181624,0.000495512,0.000130757],"domain_scores_gemma":[0.9966885,0.002113205,0.0003830307,0.0001582946,0.0005251041,0.0001317703],"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":[0.0001981849,0.00008394775,0.005635863,0.00006738037,0.00003557637,0.00009822362,0.00006860757,0.9347633,0.003539343,0.004735094,0.0004507366,0.05032375],"study_design_scores_gemma":[0.000005474868,0.00002133293,0.0003715387,0.000002382313,0.000003784703,0.00001046068,0.000004418635,0.9974082,0.0008799913,0.001200174,0.00008850571,0.000003764404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1134634,0.0003221002,0.88292,0.0002561923,0.00004315986,0.00006590012,0.00007394976,0.0009682705,0.001886954],"genre_scores_gemma":[0.9651643,0.00009182219,0.03404262,0.00005908179,0.00001348929,0.00004248474,0.0001218782,0.00002696799,0.0004373637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01170249,"threshold_uncertainty_score":0.0232687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06249454754738269,"score_gpt":0.3446773087093376,"score_spread":0.2821827611619549,"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."}}