{"id":"W4226061075","doi":"10.3390/vehicles4020021","title":"Motion Planning for Autonomous Vehicles Based on Sequential Optimization","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Kinematics; Acceleration; Trajectory; Trajectory optimization; Control theory (sociology); Nonlinear system; Computer science; Finite element method; Node (physics); Mathematics; Engineering; Physics; Artificial intelligence; Classical mechanics; Structural 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004805874,0.0001379547,0.0001352468,0.0002023116,0.0005812561,0.0001327866,0.000575384,0.00004363486,0.0000139707],"category_scores_gemma":[0.00004871617,0.0001521976,0.00007054373,0.0002980215,0.00002180643,0.0002117103,0.0001463492,0.0001590463,0.000007653973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001556757,"about_ca_system_score_gemma":0.00009857578,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001221352,"about_ca_topic_score_gemma":7.267805e-8,"domain_scores_codex":[0.9985751,0.0001311296,0.0002104588,0.0004238694,0.0003667612,0.0002927129],"domain_scores_gemma":[0.9992119,0.0001937134,0.0001255119,0.0003576216,0.00004736289,0.00006390278],"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":[0.00001823419,0.00006511599,0.0002839223,0.000007954329,0.000006333987,0.00001514331,0.0002607879,0.9848963,0.0004098413,0.001054481,0.0006191082,0.01236275],"study_design_scores_gemma":[0.0005634436,0.0002677265,0.0007169278,0.00001466405,0.00000667395,0.00000882685,0.00003487591,0.9957429,0.001233328,0.000369236,0.0008655298,0.0001758811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007970813,0.00003739064,0.9894575,0.0009602077,0.0006249338,0.0002851273,0.00002346336,0.0004062049,0.0002343158],"genre_scores_gemma":[0.5611535,3.079398e-7,0.4378074,0.0006007293,0.0001125027,0.0001437526,0.00006338856,0.00002049082,0.00009804707],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5531826,"threshold_uncertainty_score":0.6206437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0349628547379694,"score_gpt":0.2689507922467902,"score_spread":0.2339879375088208,"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."}}