{"id":"W4413254929","doi":"10.1155/atr/6812281","title":"Trajectory Planning for Autonomous Vehicles at Intersections Based on the Spatial Structure","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Motion planning; Intersection (aeronautics); Computer science; Mathematical optimization; Obstacle; Smoothness; Quadratic programming; Path (computing); Flexibility (engineering); Trajectory; Spline (mechanical); Any-angle path planning; Algorithm; Mathematics; Artificial intelligence; Engineering; Transport engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003825427,0.0005044121,0.0004451401,0.0007424898,0.0006408711,0.0005272964,0.0007128413,0.0004141623,0.001044176],"category_scores_gemma":[0.0009586639,0.0003653806,0.0005573024,0.0008842861,0.0005377231,0.0009473283,0.0009305014,0.00063788,0.0001406809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008239944,"about_ca_system_score_gemma":0.002112479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01569084,"about_ca_topic_score_gemma":0.01462446,"domain_scores_codex":[0.9997315,0.00006174469,0.00001117699,0.00006110827,0.00009190285,0.00004251476],"domain_scores_gemma":[0.9996343,0.0001487998,0.00006027136,0.00003103253,0.00009613185,0.00002946482],"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":[0.00001893621,0.00001519169,0.0007249328,0.00002432296,0.000008679024,0.00002561937,0.00005211946,0.9674829,0.00128886,0.006590509,0.0002095844,0.02355833],"study_design_scores_gemma":[0.000001671546,0.00001226832,0.0001241885,0.000001789607,0.000002641852,0.000006852457,0.00001564177,0.9972233,0.0003031917,0.002055645,0.0002502002,0.00000265603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04318443,0.00007884342,0.9547402,0.00006986506,0.00001017248,0.00003527344,0.00005123354,0.0001419762,0.001688027],"genre_scores_gemma":[0.7793038,0.0001742119,0.2184551,0.00001850624,0.00001108125,0.0001118583,0.0002451102,0.00005203991,0.001628263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01569084,"threshold_uncertainty_score":0.03119898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006101254621034232,"score_gpt":0.2260101926954826,"score_spread":0.2199089380744484,"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."}}