{"id":"W4304775246","doi":"10.3390/vehicles4040060","title":"Improved Technique for Autonomous Vehicle Motion Planning Based on Integral Constraints and Sequential Optimization","year":2022,"lang":"en","type":"article","venue":"Vehicles","topic":"Vehicle Dynamics and Control Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kinematics; Integral sliding mode; Nonlinear system; Curvature; Trajectory; Motion planning; Node (physics); Piecewise; Trajectory optimization; Mathematical optimization; Computer science; Motion (physics); Degrees of freedom (physics and chemistry); Nonlinear programming; Control theory (sociology); Mathematics; Geometry; Engineering; Artificial intelligence; Mathematical analysis; Optimal control; Robot; Structural engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003609486,0.0006352548,0.0005889205,0.0005450963,0.0003657584,0.0003897226,0.0006804091,0.0003982782,0.001816971],"category_scores_gemma":[0.0005396043,0.0003844157,0.0007708583,0.0005973479,0.000377189,0.0006132106,0.0007858303,0.0007770449,0.0002972862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004397142,"about_ca_system_score_gemma":0.001106521,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006761702,"about_ca_topic_score_gemma":0.004449818,"domain_scores_codex":[0.9996982,0.00004594575,0.00001563053,0.0000688463,0.0001380429,0.00003351572],"domain_scores_gemma":[0.9998448,0.00005978903,0.00002029232,0.00001995289,0.00004478171,0.00001040312],"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":[0.00005856789,0.00003184931,0.0005249528,0.0001058137,0.00002919447,0.00009421665,0.0001484208,0.8353888,0.01515219,0.02900446,0.0007334256,0.1187282],"study_design_scores_gemma":[0.000003546596,0.00003236777,0.00006816943,0.000003773003,0.000004480287,0.00001763918,0.000005162161,0.995527,0.001076533,0.00220303,0.001053896,0.000004415658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00420567,0.00004324751,0.9946223,0.00001559184,0.000008883445,0.00001365771,0.000009834015,0.00009038476,0.0009904006],"genre_scores_gemma":[0.3557223,0.0002281625,0.6395258,0.0000293009,0.00003246576,0.0001841265,0.000110595,0.0001021164,0.004065102],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006761702,"threshold_uncertainty_score":0.01344466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008584506742554305,"score_gpt":0.2092172765419211,"score_spread":0.2006327697993668,"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."}}