{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T05:44:35Z","timestamp":1782798275807,"version":"3.54.5"},"reference-count":135,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100002560","name":"Soonchunhyang University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002560","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2026.3704955","type":"journal-article","created":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T20:11:53Z","timestamp":1781813513000},"page":"95498-95518","source":"Crossref","is-referenced-by-count":0,"title":["Diffusion Models for End-to-End Autonomous Driving: A Survey of Perception, Prediction, Planning, and Control"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-3257-8745","authenticated-orcid":false,"given":"Junsu","family":"Choi","sequence":"first","affiliation":[{"name":"Department of Smart Automotive, Soonchunhyang University, Asan-si, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1946-1707","authenticated-orcid":false,"given":"Juhyung","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Smart Automotive, Soonchunhyang University, Asan-si, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3159-8394","authenticated-orcid":false,"given":"Sungjin","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Smart Automotive, Soonchunhyang University, Asan-si, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"End to end learning for self-driving cars","author":"Bojarski","year":"2016","journal-title":"arXiv:1604.07316"},{"key":"ref2","article-title":"End-to-end driving via conditional imitation learning","author":"Codevilla","year":"2017","journal-title":"arXiv:1710.02410"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2019.XV.031"},{"key":"ref4","article-title":"Learning by cheating","volume-title":"Proc. CoRL","author":"Chen"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00886"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01417"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01712"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3200245"},{"key":"ref9","article-title":"Safety-enhanced autonomous driving using interpretable sensor fusion transformer (InterFuser)","volume-title":"Proc. CoRL","author":"Shao"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-00257-z"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00757"},{"key":"ref12","article-title":"Fighting copycat agents in behavioral cloning from observation histories","volume-title":"Proc. NeurIPS","author":"Zhao"},{"key":"ref13","article-title":"Causal confusion in imitation learning","volume-title":"Proc. NeurIPS","author":"de Haan"},{"key":"ref14","article-title":"Rethinking the open-loop evaluation of end-to-end autonomous driving in nuScenes","author":"Zhai","year":"2023","journal-title":"arXiv:2305.10430"},{"key":"ref15","article-title":"NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles","author":"Caesar","year":"2021","journal-title":"arXiv:2106.11810"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.52202\/079017-0902"},{"key":"ref17","article-title":"Denoising diffusion probabilistic models","volume-title":"Proc. NeurIPS","author":"Ho"},{"key":"ref18","article-title":"Diffusion-based planning for autonomous driving with flexible guidance","volume-title":"Proc. ICLR","author":"Zheng"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01694"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73397-0_19"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v40i16.38403"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.52202\/075280-3014"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i8.32951"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.01124"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01453"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2023.XIX.026"},{"key":"ref27","article-title":"DiffE2E: Rethinking end-to-end driving with a hybrid action diffusion and supervised policy","author":"Zhao","year":"2025","journal-title":"arXiv:2505.19516"},{"key":"ref28","article-title":"DifFUSER: Diffusion model for robust multi-sensor fusion in 3D object detection and BEV segmentation","author":"Le","year":"2024","journal-title":"arXiv:2404.04629"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00801"},{"key":"ref30","article-title":"Using ensemble diffusion to estimate uncertainty for end-to-end autonomous driving","author":"Wintel","year":"2025","journal-title":"arXiv:2506.00560"},{"key":"ref31","article-title":"TrajDiffuse: A conditional diffusion model for environment-aware trajectory prediction","author":"Qingze","year":"2024","journal-title":"arXiv:2410.10804"},{"key":"ref32","article-title":"Diffusion-based environment-aware trajectory prediction","author":"Westny","year":"2024","journal-title":"arXiv:2403.11643"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00930"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51701.2025.02527"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.00154"},{"key":"ref36","article-title":"Planning with diffusion for flexible behavior synthesis","volume-title":"Proc. ICML","author":"Janner"},{"key":"ref37","article-title":"Safe and stylized trajectory planning for autonomous driving via diffusion model","author":"Pei","year":"2026","journal-title":"arXiv:2602.04329"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2026.104541"},{"key":"ref39","article-title":"Diffusion policies as an expressive policy class for offline reinforcement learning (Diffusion-QL)","volume-title":"Proc. ICLR","author":"Wang"},{"key":"ref40","article-title":"IDQL: Implicit Q-learning as an actor-critic method with diffusion policies","author":"Hansen-Estruch","year":"2023","journal-title":"arXiv:2304.10573"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.52202\/079017-1585"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610324"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72664-4_14"},{"key":"ref44","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-73235-5_4","article-title":"SLEDGE: Synthesizing driving environments with generative models and rule-based traffic","volume-title":"Proc. ECCV","author":"Chitta"},{"key":"ref45","article-title":"TCP: Trajectory-guided control prediction for end-to-end autonomous driving","volume-title":"Proc. NeurIPS","author":"Zhang"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00766"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01580"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01267-0_15"},{"key":"ref49","article-title":"CARLA: An open urban driving simulator","volume-title":"Proc. CoRL","author":"Dosovitskiy"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00942"},{"key":"ref51","article-title":"Deep unsupervised learning using nonequilibrium thermodynamics","volume-title":"Proc. ICML","author":"Sohl-Dickstein"},{"key":"ref52","article-title":"Generative modeling by estimating gradients of the data distribution","volume-title":"Proc. NeurIPS","author":"Song"},{"key":"ref53","article-title":"Denoising diffusion implicit models","volume-title":"Proc. ICLR","author":"Song"},{"key":"ref54","article-title":"Score-based generative modeling through stochastic differential equations","volume-title":"Proc. ICLR","author":"Song"},{"key":"ref55","article-title":"Image super-resolution via iterative refinement","author":"Saharia","year":"2021","journal-title":"arXiv:2104.07636"},{"key":"ref56","article-title":"Diffusion models beat GANs on image synthesis","volume-title":"Proc. NeurIPS","author":"Dhariwal"},{"key":"ref57","article-title":"Classifier-free diffusion guidance","author":"Ho","year":"2022","journal-title":"arXiv:2207.12598"},{"key":"ref58","article-title":"GLIDE: Towards photorealistic image generation and editing with text-guided diffusion models","author":"Nichol","year":"2021","journal-title":"arXiv:2112.10741"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00355"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"ref61","article-title":"Hierarchical text-conditional image generation with CLIP latents","author":"Ramesh","year":"2022","journal-title":"arXiv:2204.06125"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.52202\/068431-2643"},{"key":"ref63","article-title":"Scalable diffusion models with transformers","author":"Peebles","year":"2022","journal-title":"arXiv:2212.09748"},{"key":"ref64","volume-title":"Video Generation Models As World Simulators","year":"2024"},{"key":"ref65","article-title":"Consistency models","volume-title":"Proc. ICML","author":"Song"},{"key":"ref66","article-title":"Flow straight and fast: Learning to generate and transfer data with rectified flow","volume-title":"Proc. ICLR","author":"Liu"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20077-9_1"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160968"},{"key":"ref69","article-title":"Diffusion posterior sampling for general noisy inverse problems","author":"Chung","year":"2022"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1926"},{"key":"ref71","article-title":"BEVerse: Unified perception and prediction in birds-eye-view for vision-centric autonomous driving","author":"Zhang","year":"2022","journal-title":"arXiv:2205.09743"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9812383"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01339"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/ACC.1998.703255"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2016.2638961"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.52202\/068431-0418"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-025-1562-4"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.00743"},{"key":"ref79","article-title":"Progressive distillation for fast sampling of diffusion models","volume-title":"Proc. ICLR","author":"Salimans"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.52202\/079017-2422"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00978"},{"key":"ref82","article-title":"CAT: Closed-loop adversarial training for safe end-to-end driving","volume-title":"Proc. CoRL","author":"Zhang"},{"key":"ref83","article-title":"CDSTraj: Characterized diffusion and spatial\u2013temporal interaction network for trajectory prediction in autonomous driving","volume-title":"Proc. IJCAI","author":"Liao"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2025.3553125"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51701.2025.02584"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73229-4_27"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51701.2025.02384"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.52202\/079017-1771"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01530"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72983-6_1"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.65109\/papw1165"},{"key":"ref92","article-title":"Prior-guided diffusion planning for offline reinforcement learning","volume-title":"Proc. NeurIPS","author":"Ki"},{"key":"ref93","article-title":"KING: Generating safety-critical driving scenarios for robust imitation via kinematics gradients","volume-title":"Proc. ECCV","author":"Li"},{"key":"ref94","article-title":"PlannerRFT: Reinforcing diffusion planners through closed-loop and sample-efficient fine-tuning","author":"Li","year":"2026","journal-title":"arXiv:2601.12901"},{"key":"ref95","article-title":"A reduction of imitation learning and structured prediction to no-regret online learning (DAgger)","volume-title":"Proc. AISTATS","author":"Ross"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01178"},{"key":"ref97","article-title":"Object-aware regularization for addressing causal confusion in imitation learning (OREO)","volume-title":"Proc. NeurIPS","author":"Agarwal"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.52202\/079017-3812"},{"key":"ref99","article-title":"A knowledge-driven diffusion policy for end-to-end autonomous driving based on expert routing","author":"Xu","year":"2025","journal-title":"arXiv:2509.04853"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3259322"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00095"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10161463"},{"key":"ref103","article-title":"Language-guided traffic simulation via scene-level diffusion","author":"Zhong","year":"2023","journal-title":"arXiv:2306.06344"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.52202\/075280-2582"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01026"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00252"},{"key":"ref108","article-title":"Argoverse 2: Next generation datasets for self-driving perception and forecasting","author":"Wilson","year":"2023","journal-title":"arXiv:2301.00493"},{"key":"ref109","article-title":"A2D2: Audi autonomous driving dataset","author":"Geyer","year":"2020","journal-title":"arXiv:2004.06320"},{"key":"ref110","volume-title":"ONCE: One Million Scenes for Autonomous Driving","year":"2021"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2926463"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00271"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00939"},{"key":"ref116","volume-title":"OpenLane","year":"2026"},{"key":"ref117","volume-title":"OpenLane-V2","year":"2026"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00957"},{"key":"ref119","article-title":"WOD-E2E: Waymo open dataset for end-to-end driving in challenging long-tail scenarios","author":"Xu","year":"2025","journal-title":"arXiv:2510.26125"},{"key":"ref120","volume-title":"CODA: A Real-World Road Corner Case Dataset for Object Detection in Autonomous Driving","year":"2026"},{"key":"ref121","volume-title":"DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detection","year":"2026"},{"key":"ref122","article-title":"Can the waymo open motion dataset support realistic behavioral modeling? A validation study with naturalistic trajectories","author":"Zhang","year":"2025","journal-title":"arXiv:2509.03515"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2025.105476"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2024.3394735"},{"key":"ref125","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00781"},{"key":"ref126","article-title":"GradNorm: Gradient normalization for adaptive loss balancing in deep multitask networks","volume-title":"Proc. ICML","volume":"80","author":"Chen"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01408"},{"key":"ref128","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01374"},{"key":"ref129","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-63387-9_5"},{"key":"ref130","doi-asserted-by":"publisher","DOI":"10.1109\/IV55152.2023.10186386"},{"key":"ref131","article-title":"RAPiD: Real-time deterministic trajectory planning via diffusion behavior priors for safe and efficient autonomous driving","author":"Reddy","year":"2026","journal-title":"arXiv:2602.07339"},{"key":"ref132","doi-asserted-by":"publisher","DOI":"10.52202\/075280-2442"},{"key":"ref133","article-title":"DiffVLA: Vision-language guided diffusion planning for autonomous driving","author":"Jiang","year":"2025","journal-title":"arXiv:2505.19381"},{"key":"ref134","article-title":"DriveVLM: The convergence of autonomous driving and large vision-language models","author":"Tian","year":"2024","journal-title":"arXiv:2402.12289"},{"key":"ref135","article-title":"WOMD-reasoning: A large-scale dataset for interaction reasoning in driving","author":"Li","year":"2024","journal-title":"arXiv:2407.04281"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11570108.pdf?arnumber=11570108","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T05:11:02Z","timestamp":1782796262000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11570108\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":135,"URL":"https:\/\/doi.org\/10.1109\/access.2026.3704955","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}