{"id":"W4403635664","doi":"10.1109/tro.2024.3484634","title":"SICNav: Safe and Interactive Crowd Navigation Using Model Predictive Control and Bilevel Optimization","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Evacuation and Crowd Dynamics","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; Artificial Intelligence in Medicine (Canada); University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bilevel optimization; Computer science; Model predictive control; Control (management); Artificial intelligence; Control engineering; Optimization problem; Engineering; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005900658,0.0001476185,0.000119726,0.0001392693,0.0001016323,0.0001077276,0.00002931673,0.00009869224,0.000008189572],"category_scores_gemma":[0.000002565844,0.0001568378,0.00003261672,0.0001462885,0.0000435776,0.0003583248,6.617736e-7,0.0002379313,0.000003204297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205392,"about_ca_system_score_gemma":0.00002693679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003827814,"about_ca_topic_score_gemma":0.000004685035,"domain_scores_codex":[0.9993992,0.00001802715,0.0001776925,0.0001757619,0.0001085627,0.0001207935],"domain_scores_gemma":[0.9996846,0.0000936058,0.00001688387,0.00008353314,0.00005616456,0.00006515867],"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":[0.00001896692,0.00002228992,0.000003178173,0.00005901533,0.00007721785,0.000001843365,0.0004903873,0.9948541,0.0009694222,0.0001644405,0.000007455745,0.003331718],"study_design_scores_gemma":[0.0003134722,0.000043489,0.00001526185,0.0001265417,0.0001242383,0.00001750632,0.00009642234,0.9983884,0.0005127048,0.0002112501,0.000003079136,0.0001476391],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008941897,0.0001103598,0.9897205,0.00008039978,0.0004627214,0.0002026485,0.0001085106,0.0002544906,0.0001184757],"genre_scores_gemma":[0.960824,0.0001446247,0.03882259,0.00003834048,0.00002787764,0.00001286668,0.000009432795,0.00003936176,0.00008090109],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9518821,"threshold_uncertainty_score":0.6395661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01260763696471445,"score_gpt":0.2427243174068686,"score_spread":0.2301166804421541,"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."}}