{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T18:41:38Z","timestamp":1773772898423,"version":"3.50.1"},"reference-count":331,"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":[{"name":"\u201cAUTOtech.agil\u201d","award":["FKZ 01IS22088Y"],"award-info":[{"award-number":["FKZ 01IS22088Y"]}]},{"name":"\u201cAUTOtech.agil\u201d","award":["FKZ 01IS22088W"],"award-info":[{"award-number":["FKZ 01IS22088W"]}]},{"DOI":"10.13039\/501100006730","name":"Federal Ministry of Education and Research of Germany","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006730","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.2026.3659192","type":"journal-article","created":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T21:25:27Z","timestamp":1769721927000},"page":"17971-17997","source":"Crossref","is-referenced-by-count":1,"title":["Toward Fully Autonomous Driving: AI, Challenges, Opportunities, and Needs"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-8166-3118","authenticated-orcid":false,"given":"Lars","family":"Ullrich","sequence":"first","affiliation":[{"name":"Chair of Automatic Control, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5973-0794","authenticated-orcid":false,"given":"Michael","family":"Buchholz","sequence":"additional","affiliation":[{"name":"Institute of Measurement, Control and Microtechnology, Ulm University, Ulm, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1651-014X","authenticated-orcid":false,"given":"Klaus","family":"Dietmayer","sequence":"additional","affiliation":[{"name":"Institute of Measurement, Control and Microtechnology, Ulm University, Ulm, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2865-8093","authenticated-orcid":false,"given":"Knut","family":"Graichen","sequence":"additional","affiliation":[{"name":"Chair of Automatic Control, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jth.2017.04.004"},{"key":"ref2","volume-title":"Safety and performance enhancement: The Bosch electronic stability control (ESP)","author":"Liebemann","year":"2004"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-8348-9977-4_33"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.array.2021.100057"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/app122110741"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2017.8123203"},{"key":"ref7","volume-title":"Safe and efficient reinforcement learning for behavioural planning in autonomous driving","author":"Leurent","year":"2020"},{"key":"ref8","first-page":"3145","article-title":"Can autonomous vehicles identify, recover from, and adapt to distribution shifts?","volume-title":"Proc. 37th Int. Conf. Mach. Learn. (ICML)","author":"Filos"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1080\/0014013031000061640"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.3389\/fcomp.2023.1132580"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2016.7795766"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICSA.2017.20"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294279"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2913998"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3229233"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2024.3474469"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3435937"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-50077-5_2"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3293318"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.79"},{"key":"ref21","first-page":"3637","article-title":"Matching networks for one shot learning","volume-title":"Proc. 29th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","volume":"29","author":"Vinyals"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3386252"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-16657-1_10"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-44668-0_13"},{"key":"ref25","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume-title":"Proc. 34th Int. Conf. Mach. Learn. (ICML)","author":"Finn"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-05318-5_2"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01411"},{"key":"ref28","volume-title":"Generalizing in the real world with representation learning","author":"Maharaj","year":"2022"},{"key":"ref29","article-title":"GPT-4 technical report","volume-title":"arXiv:2303.08774","author":"Achiam","year":"2023"},{"key":"ref30","article-title":"LLaMA: Open and efficient foundation language models","author":"Touvron","year":"2023","journal-title":"arXiv:2302.13971"},{"issue":"240","key":"ref31","first-page":"1","article-title":"PaLM: Scaling language modeling with pathways","volume":"24","author":"Chowdhery","year":"2023","journal-title":"J. Mach. Learn. Res."},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01170"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2022.3228594"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2024.124383"},{"issue":"140","key":"ref36","first-page":"1","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2019","journal-title":"J. Mach. Learn. Res."},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s11023-020-09548-1"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.lindif.2023.102274"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8916841"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-658-34754-3_5"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3093077"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2926463"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00252"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00895"},{"key":"ref47","article-title":"INTERACTION dataset: An international, adversarial and cooperative moTION dataset in interactive driving scenarios with semantic maps","author":"Zhan","year":"2019","journal-title":"arXiv:1910.03088"},{"key":"ref48","first-page":"1","article-title":"Shifts: A dataset of real distributional shift across multiple large-scale tasks","volume-title":"Proc. 35th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Malinin"},{"key":"ref49","first-page":"409","article-title":"One thousand and one hours: self-driving motion prediction dataset","volume-title":"Proc. Conf. Rob. Learn.","author":"Houston"},{"key":"ref50","article-title":"NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles","author":"Caesar","year":"2021","journal-title":"arXiv:2106.11810"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8814073"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.2972974"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01032"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561754"},{"key":"ref55","article-title":"1st place solution for waymo open dataset challenge-3D detection and domain adaptation","author":"Ding","year":"2020","journal-title":"arXiv:2006.15505"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9812107"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160855"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_37"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1002\/rob.21918"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2020.1003021"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3156011"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2012.02.016"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2913588"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/3019612.3019643"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-94102-4_3"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1080\/08839514.2019.1600301"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1080\/14494035.2021.1928377"},{"key":"ref68","volume-title":"Automotive Systems and Software Engineering\u2014State of the Art and Future Trends","author":"Dajsuren","year":"2019"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/IV51971.2022.9827271"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01407"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1080\/09617353.2023.2264729"},{"key":"ref72","article-title":"Towards safety concepts for automated vehicles by the example of the project UNICARagil","volume-title":"Proc. 29th Aachen Colloquium Sustainable Mobility","author":"Stolte"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3176879"},{"key":"ref74","article-title":"Concrete problems in AI safety","author":"Amodei","year":"2016","journal-title":"arXiv:1606.06565"},{"key":"ref75","first-page":"1","article-title":"Assessing the adherence of an industrial autonomous driving framework to ISO 26262 software guidelines","volume-title":"Proc. 56th ACM\/IEEE Design Autom. Conf. (DAC)","author":"Tabani"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-021-00445-7"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.101896"},{"key":"ref78","first-page":"1","volume-title":"AI governance: A research agenda","author":"Dafoe","year":"2018"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2024.3496797"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3431437"},{"key":"ref81","article-title":"Safety implications of explainable artificial intelligence in end-to-end autonomous driving","author":"Atakishiyev","year":"2024","journal-title":"arXiv:2403.12176"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/IV55156.2024.10588812"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1080\/10447318.2022.2081282"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1177\/154193128803200221"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1518\/001872095779049543"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1145\/3025453.3025822"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/ICARA51699.2021.9376406"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.3390\/s23084075"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2750080"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-64550-5_10"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00721"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.3390\/ai3010005"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.23919\/ICIF.2018.8455667"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3164236"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1201\/b21974-7"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2022.3167103"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1109\/IV55156.2024.10588731"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2009.2018966"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2771351"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3043716"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-017-9615-3"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-019-09882-z"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01190"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2015.7225908"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793557"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00135"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20077-9_1"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160968"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00865"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00890"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i7.32782"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2985815"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2015.164"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.4271\/2016-01-0128"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2016.2583491"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3118224"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2023.3254657"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3352811"},{"key":"ref119","article-title":"MGTR: Multi-granular transformer for motion prediction with LiDAR","author":"Gan","year":"2023","journal-title":"arXiv:2312.02409"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3151613"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00139"},{"key":"ref122","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00772"},{"key":"ref123","first-page":"1","article-title":"Let occ flow: self-supervised 3D occupancy flow prediction","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"Liu"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1109\/tiv.2024.3459071"},{"key":"ref125","first-page":"15398","article-title":"Multiple futures prediction","volume-title":"Proc. 32th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","volume":"32","author":"Tang"},{"key":"ref126","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460766"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00886"},{"key":"ref128","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_25"},{"key":"ref129","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00643"},{"key":"ref130","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9561683"},{"key":"ref131","doi-asserted-by":"publisher","DOI":"10.1518\/001872095779049480"},{"key":"ref132","doi-asserted-by":"publisher","DOI":"10.1109\/RTSS.2012.74"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1109\/ICAC.2015.18"},{"key":"ref134","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2018.2888904"},{"key":"ref135","doi-asserted-by":"publisher","DOI":"10.1109\/MCOMSTD.001.2000069"},{"key":"ref136","doi-asserted-by":"publisher","DOI":"10.1109\/IV47402.2020.9304816"},{"key":"ref137","doi-asserted-by":"publisher","DOI":"10.3390\/s21030744"},{"key":"ref138","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC48978.2021.9564783"},{"key":"ref139","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2017.2668838"},{"key":"ref140","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2021.3089743"},{"key":"ref141","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2530146"},{"key":"ref142","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01370-7_75"},{"key":"ref143","doi-asserted-by":"publisher","DOI":"10.1007\/s38314-022-1405-9"},{"key":"ref144","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVE45908.2019.8965227"},{"key":"ref145","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294638"},{"key":"ref146","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2983149"},{"key":"ref147","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2018.12.018"},{"key":"ref148","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2020.102150"},{"key":"ref149","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8813875"},{"key":"ref150","doi-asserted-by":"publisher","DOI":"10.1109\/EDCC53658.2021.00009"},{"key":"ref151","first-page":"1","article-title":"Towards collaborative perception in automated driving: Combining vehicle and infrastructure perspectives","volume-title":"Proc. CARS 6th Int. Workshop Crit. Automot. Appl., Robustness & Saf.","author":"Zacchi"},{"key":"ref152","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2019.103201"},{"key":"ref153","first-page":"1","article-title":"AUTOtech.agil: Architecture and Technologies for Orchestrating Automotive Agility","volume-title":"Proc. 32nd Aachen Colloq. Sustain. Mobility","author":"van Kempen"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00264"},{"key":"ref155","volume-title":"Cruise Robotaxi Drives Into Wet Concrete; Waymo Shows Off Same Route","year":"2023"},{"key":"ref156","volume-title":"Part 573 Safety Recall Report 23E-086","year":"2023"},{"key":"ref157","volume-title":"California Regulator Probes Crashes Involving GM\u2019s Cruise Robotaxis","author":"Craft","year":"2023"},{"key":"ref158","first-page":"1","article-title":"Sound.AI\u2014Teaching vehicles how to hear","volume-title":"Proc. 28th Aachen Colloq. Sustain. Mobility","author":"Keutgens"},{"key":"ref159","first-page":"1","article-title":"The hearing sense of vehicles\u2013recognition of sound patterns in the vehicle environment for enhanced situation awareness","volume-title":"Proc. 12th Aachen Acoust. Colloq.","author":"Kwade"},{"key":"ref160","doi-asserted-by":"publisher","DOI":"10.1016\/0001-6918(92)90019-A"},{"key":"ref161","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294411"},{"key":"ref162","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20255"},{"key":"ref163","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2011.5940562"},{"key":"ref164","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2013.6629559"},{"key":"ref165","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2014.2306552"},{"key":"ref166","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2016.2578706"},{"key":"ref167","first-page":"305","article-title":"ALVINN, an autonomous land vehicle in a neural network","volume-title":"Proc. 1st Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","volume":"1","author":"Pomerleau"},{"key":"ref168","article-title":"End to end learning for self-driving cars","author":"Bojarski","year":"2016","journal-title":"arXiv:1604.07316"},{"key":"ref169","doi-asserted-by":"publisher","DOI":"10.2352\/ISSN.2470-1173.2017.19.AVM-023"},{"key":"ref170","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460487"},{"key":"ref171","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00942"},{"key":"ref172","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197408"},{"key":"ref173","first-page":"66","article-title":"Learning by cheating","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"Chen"},{"key":"ref174","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01530"},{"key":"ref175","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19842-7_16"},{"key":"ref176","first-page":"20703","article-title":"Model-based imitation learning for urban driving","volume-title":"Proc. 35th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Hu"},{"key":"ref177","doi-asserted-by":"publisher","DOI":"10.1016\/j.iotcps.2023.04.003"},{"key":"ref178","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/p19-1340"},{"key":"ref179","article-title":"MiniGPT-4: Enhancing vision-language understanding with advanced large language models","author":"Zhu","year":"2023","journal-title":"arXiv:2304.10592"},{"key":"ref180","first-page":"1","article-title":"Visual instruction tuning","volume-title":"Proc. 37th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Liu"},{"key":"ref181","first-page":"2165","article-title":"RT-2: Vision-language-action models transfer web knowledge to robotic control","volume-title":"Proc. Conf. Robot Learn.","author":"Brohan"},{"key":"ref182","article-title":"OpenVLA: An open-source vision-language-action model","author":"Kim","year":"2024","journal-title":"arXiv:2406.09246"},{"key":"ref183","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2024.3402136"},{"key":"ref184","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00788"},{"key":"ref185","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2023.3327715"},{"key":"ref186","article-title":"DriveLM: Driving with graph visual question answering","author":"Sima","year":"2023","journal-title":"arXiv:2312.14150"},{"key":"ref187","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2024.3440097"},{"key":"ref188","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2025.105457"},{"key":"ref189","article-title":"DriveVLM: The convergence of autonomous driving and large vision-language models","author":"Tian","year":"2024","journal-title":"arXiv:2402.12289"},{"key":"ref190","article-title":"OpenDriveVLA: Towards end-to-end autonomous driving with large vision language action model","author":"Zhou","year":"2025","journal-title":"arXiv:2503.23463"},{"key":"ref191","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00376"},{"key":"ref192","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01157"},{"key":"ref193","doi-asserted-by":"publisher","DOI":"10.1109\/IV51971.2022.9827273"},{"key":"ref194","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00646"},{"key":"ref195","first-page":"23230","article-title":"Mismatched no more: Joint model-policy optimization for model-based RL","volume-title":"Proc. 35th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Eysenbach"},{"key":"ref196","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01417"},{"key":"ref197","first-page":"627","article-title":"A reduction of imitation learning and structured prediction to no-regret online learning","volume-title":"Proc. Int. Conf. Artif. Intell. Stat. (AISTATS)","author":"Ross"},{"key":"ref198","volume-title":"A Principled Approach to Safety","year":"2020"},{"key":"ref199","volume-title":"Voluntary Safety Self-Assessment","year":"2021"},{"key":"ref200","volume-title":"Safety Report","year":"2021"},{"key":"ref201","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58589-1_10"},{"key":"ref202","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01580"},{"key":"ref203","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01550"},{"key":"ref204","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01671"},{"key":"ref205","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19839-7_31"},{"key":"ref206","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58568-6_12"},{"key":"ref207","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9341199"},{"key":"ref208","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8967615"},{"key":"ref209","first-page":"947","article-title":"IntentNet: Learning to predict intention from raw sensor data","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"Casas"},{"key":"ref210","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58548-8_28"},{"key":"ref211","doi-asserted-by":"publisher","DOI":"10.1109\/IV51971.2022.9827101"},{"key":"ref212","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01712"},{"key":"ref213","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00532"},{"key":"ref214","first-page":"459","article-title":"PlanT: Explainable planning transformers via object-level representations","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"Renz"},{"key":"ref215","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610648"},{"key":"ref216","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460874"},{"key":"ref217","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-72775-7_6"},{"key":"ref218","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00361"},{"key":"ref219","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610550"},{"key":"ref220","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00731"},{"key":"ref221","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2024.3459071"},{"key":"ref222","first-page":"2170","article-title":"DiffStack: A differentiable and modular control stack for autonomous vehicles","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"Karkus"},{"key":"ref223","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"ref224","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19812-0_38"},{"key":"ref225","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2015.163"},{"key":"ref226","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3163353"},{"key":"ref227","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01408"},{"key":"ref228","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2756099"},{"key":"ref229","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10161419"},{"key":"ref230","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA46639.2022.9811576"},{"key":"ref231","first-page":"1","article-title":"GPT-driver: Learning to drive with GPT","volume-title":"Proc. NeurIPS Found. Models Decis. Making Workshop","author":"Mao"},{"key":"ref232","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2008.12.001"},{"key":"ref233","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2018.04.007"},{"key":"ref234","first-page":"6531","article-title":"Motion transformer with global intention localization and local movement refinement","volume-title":"Proc. 36th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Shi"},{"key":"ref235","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.233"},{"key":"ref236","first-page":"1","article-title":"Scene transformer: A unified architecture for predicting future trajectories of multiple agents","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"Ngiam"},{"key":"ref237","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3298301"},{"key":"ref238","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2014.6856582"},{"key":"ref239","doi-asserted-by":"publisher","DOI":"10.1109\/IV47402.2020.9304723"},{"key":"ref240","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2022.3159994"},{"key":"ref241","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2020.3000323"},{"key":"ref242","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2022.3193923"},{"key":"ref243","article-title":"LanguageMPC: Large language models as decision makers for autonomous driving","author":"Sha","year":"2023","journal-title":"arXiv:2310.03026"},{"key":"ref244","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00718"},{"key":"ref245","first-page":"1","article-title":"Deep imitative models for flexible inference, planning, and control","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Rhinehart"},{"key":"ref246","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01131"},{"key":"ref247","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01494"},{"key":"ref248","first-page":"6119","article-title":"Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline","volume-title":"Proc. 35th Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Wu"},{"key":"ref249","first-page":"718","article-title":"Urban driver: Learning to drive from real-world demonstrations using policy gradients","volume-title":"Proc. Conf. Robo. Learn. (CoRL","author":"Scheel"},{"key":"ref250","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02105"},{"key":"ref251","first-page":"1","article-title":"Hydra-MDP++: Advancing end-to-end driving via hydra-distillation with expert-guided decision analysis","volume-title":"Proc. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit. Workshops","author":"Li"},{"key":"ref252","first-page":"2170","article-title":"Driving policy transfer via modularity and abstraction","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"M\u00fcller"},{"key":"ref253","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00700"},{"key":"ref254","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3200245"},{"key":"ref255","doi-asserted-by":"publisher","DOI":"10.1007\/s44267-025-00095-w"},{"key":"ref256","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01499"},{"key":"ref257","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19839-7_21"},{"key":"ref258","article-title":"Alpamayo-r1: Bridging reasoning and action prediction for generalizable autonomous driving in the long tail","author":"Wang","year":"2025","journal-title":"arXiv:2511.00088"},{"key":"ref259","first-page":"726","article-title":"Safety-enhanced autonomous driving using interpretable sensor fusion transformer","volume-title":"Proc. Conf. Robo. Learn. (CoRL)","author":"Shao"},{"key":"ref260","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611018"},{"key":"ref261","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58589-1_36"},{"key":"ref262","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01254"},{"key":"ref263","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160992"},{"key":"ref264","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2023.3332474"},{"key":"ref265","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3283542"},{"key":"ref266","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00766"},{"key":"ref267","article-title":"FusionAD: Multi-modality fusion for prediction and planning tasks of autonomous driving","author":"Ye","year":"2023","journal-title":"arXiv:2308.01006"},{"key":"ref268","article-title":"VADv2: End-to-end vectorized autonomous driving via probabilistic planning","author":"Chen","year":"2024","journal-title":"arXiv:2402.13243"},{"key":"ref269","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-73650-6_6"},{"key":"ref270","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2024.3434515"},{"key":"ref271","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref272","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2020.3041278"},{"key":"ref273","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.110080"},{"key":"ref274","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59410-7_49"},{"key":"ref275","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6819"},{"key":"ref276","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3093523"},{"key":"ref277","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-30108-7_27"},{"key":"ref278","article-title":"Cosmos-reason1: From physical common sense to embodied reasoning","author":"Azzolini","year":"2025","journal-title":"arXiv:2503.15558"},{"key":"ref279","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58523-5_40"},{"key":"ref280","volume-title":"Automated Driving and AI: Interview in English","author":"Buchner","year":"2019"},{"key":"ref281","volume-title":"Navigating global SDV trends: Insights from market demands and end-to-end roadmaps","author":"Yao"},{"key":"ref282","volume-title":"Thinking, Fast and Slow","author":"Kahneman","year":"2011"},{"key":"ref283","volume-title":"Intelligent Transport Systems (ITS); ITS-G5 Access Layer Specification for Intelligent Transport Systems Operating in the 5 GHz Frequency Band","year":"2019"},{"key":"ref284","volume-title":"Intelligent Transport Systems (ITS); Vehicular Communications; Basic Set of Applications; Part 2: Specification of Cooperative Awareness Basic Service","year":"2019"},{"key":"ref285","volume-title":"Intelligent Transport Systems (ITS); Vehicular Communications; Basic Set of Applications; Analysis of the Collective Perception Service (CPS); Release 2","year":"2019"},{"key":"ref286","volume-title":"Intelligent Transport Systems (ITS); Vehicular Communications; Manoeuvre Coordination Service (MCS); Pre-standardization study; Release 2","year":"2024"},{"key":"ref287","volume-title":"Infrastructure Categorization: ISAD Levels","year":"2021"},{"key":"ref288","volume-title":"Cruise Safety Report 2022","year":"2022"},{"key":"ref289","volume-title":"Developing a Self-Driving System You Can Trust","year":"2021"},{"key":"ref290","volume-title":"Voluntary Safety Self-Assessment (VSSA)","year":"2021"},{"key":"ref291","volume-title":"Introducing Zoox Safety Innovations","year":"2021"},{"key":"ref292","volume-title":"Cruise Safety Report 2022","year":"2022"},{"key":"ref293","volume-title":"Self-Driving Safety Report","year":"2024"},{"key":"ref294","volume-title":"Mobileye Drive-Enabling Autonomous Mobility","year":"2024"},{"key":"ref295","volume-title":"A Principled Approach to Safety","year":"2021"},{"key":"ref296","volume-title":"Toyota Automated Driving-Whitepaper","year":"2022"},{"key":"ref297","volume-title":"Introducing DRIVE PILOT: An Automated Driving System for the Highway","year":"2023"},{"key":"ref298","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3343434"},{"key":"ref299","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2024.3424673"},{"key":"ref300","article-title":"Hydra-MDP: End-to-end multimodal planning with multi-target hydra-distillation","author":"Li","year":"2024","journal-title":"arXiv:2406.06978"},{"key":"ref301","article-title":"Reimagining an autonomous vehicle","author":"Hawke","year":"2021","journal-title":"arXiv:2108.05805"},{"key":"ref302","volume-title":"Wayve\u2019s AV2.0 Approach","year":"2025"},{"key":"ref303","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2020.3014152"},{"key":"ref304","doi-asserted-by":"publisher","DOI":"10.1109\/OJITS.2023.3295502"},{"key":"ref305","first-page":"1704","article-title":"Conditional neural processes","volume-title":"Proc. 35th Int. Conf. Mach. Learn. (ICML)","author":"Garnelo"},{"key":"ref306","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-658-45018-2_5"},{"key":"ref307","first-page":"1","article-title":"A path towards autonomous machine intelligence version 0.9.2, 2022-06-27","volume":"62","author":"LeCun","year":"2022","journal-title":"Open Review"},{"key":"ref308","volume-title":"Die R\u00fcckseite des Spiegels. Versuch Einer Naturgeschichte Menschlichen Erkennens","author":"Lorenz","year":"1973"},{"key":"ref309","doi-asserted-by":"publisher","DOI":"10.1080\/15389588.2024.2380786"},{"key":"ref310","year":"2021","journal-title":"Call for Public Comments on \u2018AI Governance Guidelines for Implementation of AI Principles Ver. 1.0\u2019 Opens"},{"key":"ref311","first-page":"1","article-title":"Positionspapier: Ein Rechtsrahmen f\u00fcr K\u00fcnstliche Intelligenz","year":"2021","journal-title":"Workshop of the DSI Strategy Lab. Balsthal"},{"key":"ref312","volume-title":"Corrigendum to the European Parliament\u2019s position on the Artificial Intelligence Act (P9_TA(2024)0138)","year":"2024"},{"key":"ref313","volume-title":"Bill C-27, Consumer Privacy Protection Act, PART 3 Artificial Intelligence and Data Act.","year":"2022"},{"key":"ref314","volume-title":"Developing Responsible Artificial Intelligence: Release of the New Generation of Artificial Intelligence Governance Principles","year":"2019"},{"key":"ref315","doi-asserted-by":"publisher","DOI":"10.6028\/nist.ai.100-1"},{"key":"ref316","volume-title":"Road Vehicles\u2014Functional Safety","year":"2018"},{"key":"ref317","volume-title":"Road Vehicles\u2014Safety of the Intended Functionality","year":"2022"},{"key":"ref318","volume-title":"Road Vehicles\u2014Safety and Artificial Intelligence","year":"2024"},{"key":"ref319","volume-title":"Standard for Evaluation of Autonomous Products","year":"2020"},{"key":"ref320","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-40953-0_34"},{"key":"ref321","doi-asserted-by":"publisher","DOI":"10.1109\/OJITS.2025.3585274"},{"key":"ref322","article-title":"Building a credible case for safety: Waymo\u2019s approach for the determination of absence of unreasonable risk","author":"Favaro","year":"2023","journal-title":"arXiv:2306.01917"},{"key":"ref323","article-title":"Keynote","volume-title":"Proc. WAD CVPR\u201921","author":"Karpathy"},{"key":"ref324","doi-asserted-by":"publisher","DOI":"10.1109\/IV55156.2024.10588422"},{"key":"ref325","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160969"},{"key":"ref326","doi-asserted-by":"publisher","DOI":"10.1109\/QRS-C51114.2020.00045"},{"key":"ref327","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3079209"},{"key":"ref328","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3195549"},{"key":"ref329","first-page":"1","article-title":"LLM4Drive: A survey of large language models for autonomous driving","volume-title":"Proc. NeurIPS Workshop Open-World Agents","author":"Yang"},{"key":"ref330","doi-asserted-by":"publisher","DOI":"10.3390\/s19194289"},{"key":"ref331","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2023.3259322"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11367669.pdf?arnumber=11367669","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T21:08:05Z","timestamp":1770671285000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11367669\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":331,"URL":"https:\/\/doi.org\/10.1109\/access.2026.3659192","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}