{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T07:12:14Z","timestamp":1775891534186,"version":"3.50.1"},"reference-count":216,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["CNS:CAREER-2047454"],"award-info":[{"award-number":["CNS:CAREER-2047454"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1109\/tits.2023.3259322","type":"journal-article","created":{"date-parts":[[2023,3,30]],"date-time":"2023-03-30T17:38:16Z","timestamp":1680197896000},"page":"6971-6988","source":"Crossref","is-referenced-by-count":206,"title":["A Survey on Safety-Critical Driving Scenario Generation\u2014A Methodological Perspective"],"prefix":"10.1109","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3218-8792","authenticated-orcid":false,"given":"Wenhao","family":"Ding","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7598-639X","authenticated-orcid":false,"given":"Chejian","family":"Xu","sequence":"additional","affiliation":[{"name":"Computer Science Department, University of Illinois at Urbana--Champaign, Urbana, IL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4636-3451","authenticated-orcid":false,"given":"Mansur","family":"Arief","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Haohong","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Bo","family":"Li","sequence":"additional","affiliation":[{"name":"Computer Science Department, University of Illinois at Urbana--Champaign, Urbana, IL, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9400-8446","authenticated-orcid":false,"given":"Ding","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"}]}],"member":"263","reference":[{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00978"},{"key":"ref207","doi-asserted-by":"publisher","DOI":"10.1186\/s40535-016-0018-x"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/IV48863.2021.9576023"},{"key":"ref208","article-title":"Structured adversarial attack: Towards general implementation and better interpretability","author":"xu","year":"2018","journal-title":"arXiv 1808 01664"},{"key":"ref59","first-page":"1","article-title":"Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment","volume":"12","author":"feng","year":"2021","journal-title":"Nature Commun"},{"key":"ref205","first-page":"2484","article-title":"Simple black-box adversarial attacks","author":"guo","year":"2019","journal-title":"Proc 36th Int Conf Mach Learn"},{"key":"ref58","first-page":"233","article-title":"CriSGen: Constraint-based generation of critical scenarios for autonomous vehicles","author":"nonnengart","year":"2019","journal-title":"Proc Int Symp Formal Methods"},{"key":"ref206","article-title":"The neuro-symbolic concept learner: Interpreting scenes, words, and sentences from natural supervision","author":"mao","year":"2019","journal-title":"arXiv 1904 12584"},{"key":"ref53","article-title":"Scalable end-to-end autonomous vehicle testing via rare-event simulation","author":"o\u2019kelly","year":"2018","journal-title":"arXiv 1811 00145"},{"key":"ref203","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00807"},{"key":"ref52","article-title":"Learning to simulate","author":"ruiz","year":"2018","journal-title":"arXiv 1810 02513"},{"key":"ref204","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2021.3058873"},{"key":"ref201","doi-asserted-by":"publisher","DOI":"10.1287\/mnsc.6.4.366"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793740"},{"key":"ref202","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_24"},{"key":"ref209","article-title":"Spatially transformed adversarial examples","author":"xiao","year":"2018","journal-title":"ArXiv 1801 02612"},{"key":"ref210","article-title":"Conditional generative adversarial nets","author":"mirza","year":"2014","journal-title":"arXiv 1411 1784"},{"key":"ref211","first-page":"3483","article-title":"Learning structured output representation using deep conditional generative models","volume":"28","author":"sohn","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/3485730.3485935"},{"key":"ref50","article-title":"Adversarial domain randomization","author":"khirodkar","year":"2018","journal-title":"arXiv 1812 00491"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01373"},{"key":"ref45","article-title":"Analyzing and improving neural networks by generating semantic counterexamples through differentiable rendering","author":"jain","year":"2019","journal-title":"arXiv 1910 00727"},{"key":"ref48","article-title":"Adversarial objects against LiDAR-based autonomous driving systems","author":"cao","year":"2019","journal-title":"arXiv 1907 05418"},{"key":"ref216","article-title":"A survey of zero-shot generalisation in deep reinforcement learning","author":"kirk","year":"2021","journal-title":"arXiv 2111 09794"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP42928.2021.9506016"},{"key":"ref42","article-title":"End to end learning for self-driving cars","author":"bojarski","year":"2016","journal-title":"arXiv 1604 07316 [cs]"},{"key":"ref214","article-title":"Distributionally robust optimization: A review","author":"rahimian","year":"2019","journal-title":"arXiv 1908 05659"},{"key":"ref41","article-title":"Real-time prediction of intermediate-horizon automotive collision risk","author":"wulfe","year":"2018","journal-title":"arXiv 1802 01532"},{"key":"ref215","article-title":"Curriculum learning: A survey","author":"soviany","year":"2021","journal-title":"arXiv 2101 10382"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/IROS40897.2019.8968225"},{"key":"ref212","article-title":"A survey on offline reinforcement learning: Taxonomy, review, and open problems","author":"figueiredo prudencio","year":"2022","journal-title":"arXiv 2203 01387"},{"key":"ref43","first-page":"4565","article-title":"Generative adversarial imitation learning","volume":"29","author":"ho","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref213","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2007.03.003"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8794443"},{"key":"ref8","author":"schnelle","year":"2019","journal-title":"Review of Simulation Frameworks and Standards Related to Driving Scenarios"},{"key":"ref7","author":"najm","year":"2007","journal-title":"Pre-crash scenario typology for crash avoidance research"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2021.106454"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2993730"},{"key":"ref3","article-title":"A survey on scenario-based testing for automated driving systems in high-fidelity simulation","author":"zhong","year":"2021","journal-title":"arXiv 2112 00964"},{"key":"ref6","author":"thorn","year":"2018","journal-title":"A framework for automated driving system testable cases and scenarios"},{"key":"ref5","year":"2022","journal-title":"California Department of Motor Vehicle Disengagement Report"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1016\/j.iatssr.2017.02.001"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8917406"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8813845"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8917516"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569672"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1186\/s13673-020-00231-z"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00095"},{"key":"ref31","article-title":"A new multi-vehicle trajectory generator to simulate vehicle-to-vehicle encounters","author":"ding","year":"2018","journal-title":"arXiv 1809 05680"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636318"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197145"},{"key":"ref32","author":"h\u00e5kansson","year":"2021","journal-title":"Driving scenario generation using generative adversarial networks"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2016.7795683"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2015.55"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00715"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01113"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aaw0863"},{"key":"ref25","article-title":"RELATE: Physically plausible multi-object scene synthesis using structured latent spaces","author":"ehrhardt","year":"2020","journal-title":"arXiv 2007 01272"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569682"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2794604"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8813994"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00465"},{"key":"ref27","article-title":"Transfer learning from synthetic to real LiDAR point cloud for semantic segmentation","author":"xiao","year":"2021","journal-title":"arXiv 2107 05399"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58520-4_42"},{"key":"ref200","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref128","first-page":"1928","article-title":"Asynchronous methods for deep reinforcement learning","author":"mnih","year":"2016","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref129","article-title":"Continuous control with deep reinforcement learning","author":"lillicrap","year":"2015","journal-title":"arXiv 1509 02971"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.3141\/2083-12"},{"key":"ref126","doi-asserted-by":"publisher","DOI":"10.1007\/BF00992696"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1016\/S0001-4575(00)00019-1"},{"key":"ref127","author":"sutton","year":"2018","journal-title":"Reinforcement Learning An Introduction"},{"key":"ref99","first-page":"34","article-title":"Use of speed limiters in cars for increased safety and a better environment","author":"almqvist","year":"1991","journal-title":"Transp Res Rec"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19839-7_20"},{"key":"ref98","first-page":"67","author":"allen","year":"1978","journal-title":"Analysis of Traffic Conflicts and Collisions[R]"},{"key":"ref125","article-title":"A tutorial on Bayesian optimization","author":"frazier","year":"2018","journal-title":"arXiv 1807 02811"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00411"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2701846"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"ref134","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989024"},{"key":"ref95","article-title":"Near miss determination through use of a scale of danger","author":"hayward","year":"1972","journal-title":"Proc 51st Annu Meeting Highway Res Board"},{"key":"ref131","doi-asserted-by":"publisher","DOI":"10.1115\/DSCC2015-9718"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00780"},{"key":"ref132","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2582208"},{"key":"ref130","article-title":"Multi-agent actor-critic for mixed cooperative-competitive environments","author":"lowe","year":"2017","journal-title":"arXiv 1706 02275"},{"key":"ref91","article-title":"Open-ended learning leads to generally capable agents","author":"team","year":"2021","journal-title":"arXiv 2107 12808"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9341493"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC48978.2021.9564898"},{"key":"ref139","article-title":"Proximal policy optimization algorithms","author":"schulman","year":"2017","journal-title":"arXiv 1707 06347"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2018.8500374"},{"key":"ref137","article-title":"Deep probabilistic accelerated evaluation: A robust certifiable rare-event simulation methodology for black-box safety-critical systems","author":"arief","year":"2020","journal-title":"arXiv 2006 15722"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2019.8814230"},{"key":"ref138","article-title":"Accelerated policy evaluation: Learning adversarial environments with adaptive importance sampling","author":"xu","year":"2021","journal-title":"arXiv 2106 10566"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294629"},{"key":"ref135","doi-asserted-by":"publisher","DOI":"10.23919\/ACC.2018.8431590"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317919"},{"key":"ref136","doi-asserted-by":"publisher","DOI":"10.1109\/WSC.2018.8632355"},{"key":"ref82","article-title":"CausalAF: Causal autoregressive flow for safety-critical driving scenario generation","author":"ding","year":"2021","journal-title":"arXiv 2110 13939"},{"key":"ref144","author":"drive contributors","year":"2021","journal-title":"DI-Drive OpenDILab Decision Intelligence Platform for Autonomous Driving Simulation"},{"key":"ref81","article-title":"Semantically adversarial driving scenario generation with explicit knowledge integration","author":"ding","year":"2021","journal-title":"arXiv 2106 04066"},{"key":"ref145","author":"smullyan","year":"1995","journal-title":"First-Order Logic"},{"key":"ref84","article-title":"Robust trajectory prediction against adversarial attacks","author":"cao","year":"2022","journal-title":"arXiv 2208 00094"},{"key":"ref142","first-page":"1","article-title":"CARLA: An open urban driving simulator","author":"dosovitskiy","year":"2017","journal-title":"Proc 1st Annu Conf Robot Learn"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01473"},{"key":"ref143","author":"contributors","year":"2019","journal-title":"Carla scenario runner"},{"key":"ref140","doi-asserted-by":"publisher","DOI":"10.1145\/336512.336546"},{"key":"ref141","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00895"},{"key":"ref80","article-title":"SMARTS: Scalable multi-agent reinforcement learning training school for autonomous driving","author":"zhou","year":"2020","journal-title":"arXiv 2010 09776"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1109\/CCCI52664.2021.9583209"},{"key":"ref108","first-page":"168","article-title":"Learning dynamic Bayesian networks","author":"ghahramani","year":"1997","journal-title":"Proc Int School Neural Netw Initiated IIASS EMFCSC"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2018.8500632"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1016\/S0377-2217(02)00181-9"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390196"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-021-06120-5"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-99229-7_39"},{"key":"ref74","article-title":"MetaDrive: Composing diverse driving scenarios for generalizable reinforcement learning","author":"li","year":"2021","journal-title":"arXiv 2109 12674"},{"key":"ref105","article-title":"Waymo&#x2019;s safety methodologies and safety readiness determinations","author":"webb","year":"2020","journal-title":"arXiv 2011 00054"},{"key":"ref77","article-title":"CausalCity: Complex simulations with agency for causal discovery and reasoning","author":"mcduff","year":"2021","journal-title":"arXiv 2106 13364"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1109\/WSC.2003.1261412"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294368"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1109\/WSC.2010.5679071"},{"key":"ref71","article-title":"Adaptive stress testing of airborne collision avoidance systems","author":"lee","year":"2015","journal-title":"Proc IEEE\/AIAA 34th Digit Avionics Syst Conf (DASC)"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01026"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197351"},{"key":"ref112","article-title":"Generative adversarial nets","volume":"27","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref73","author":"ros","year":"2019","journal-title":"Carla autonomous driving challenge 2019"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197228"},{"key":"ref110","article-title":"An introduction to convolutional neural networks","author":"o\u2019shea","year":"2015","journal-title":"arXiv 1511 08458"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3091477"},{"key":"ref119","article-title":"Denoising diffusion implicit models","author":"song","year":"2020","journal-title":"arXiv 2010 02502"},{"key":"ref67","article-title":"Certifiable deep importance sampling for rare-event simulation of black-box systems","author":"arief","year":"2021","journal-title":"arXiv 2111 02204"},{"key":"ref117","article-title":"Neural ordinary differential equations","author":"chen","year":"2018","journal-title":"arXiv 1806 07366"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/832"},{"key":"ref118","article-title":"Denoising diffusion probabilistic models","author":"ho","year":"2020","journal-title":"arXiv 2006 11239"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/IROS51168.2021.9636072"},{"key":"ref115","article-title":"WaveNet: A generative model for raw audio","author":"oord","year":"2016","journal-title":"arXiv 1609 03499"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294729"},{"key":"ref116","article-title":"Density estimation using real NVP","author":"dinh","year":"2016","journal-title":"arXiv 1605 08803"},{"key":"ref66","first-page":"595","article-title":"Deep probabilistic accelerated evaluation: A robust certifiable rare-event simulation methodology for black-box safety-critical systems","author":"arief","year":"2021","journal-title":"Proc Int Conf Artif Intell Statist"},{"key":"ref113","article-title":"Auto-encoding variational Bayes","author":"kingma","year":"2013","journal-title":"arXiv 1312 6114"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01679"},{"key":"ref114","first-page":"1747","article-title":"Pixel recurrent neural networks","author":"van oord","year":"2016","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1177\/03611981211018697"},{"key":"ref122","author":"fern\u00e1ndez llorca","year":"2021","journal-title":"Trustworthy autonomous vehicles"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202133"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2019.8917403"},{"key":"ref120","article-title":"TrafficGen: Learning to generate diverse and realistic traffic scenarios","author":"feng","year":"2022","journal-title":"arXiv 2210 06609"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2018.8500400"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1145\/3054912"},{"key":"ref168","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"ref169","article-title":"One thousand and one hours: Self-driving motion prediction dataset","author":"houston","year":"2020","journal-title":"arXiv 2006 14480"},{"key":"ref170","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00252"},{"key":"ref177","article-title":"Learning to balance: Bayesian meta-learning for imbalanced and out-of-distribution tasks","author":"lee","year":"2019","journal-title":"arXiv 1905 12917"},{"key":"ref178","first-page":"2","article-title":"Torcs, the open racing car simulator","volume":"4","author":"wymann","year":"2000","journal-title":"Software Available"},{"key":"ref175","article-title":"One million scenes for autonomous driving: Once dataset","author":"mao","year":"2021","journal-title":"arXiv 2106 11037"},{"key":"ref176","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00949"},{"key":"ref173","first-page":"6433","author":"wilson","year":"2020","journal-title":"Argoverse 2 Next generation datasets for self-driving perception and forecasting"},{"key":"ref174","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC48978.2021.9565009"},{"key":"ref171","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9197385"},{"key":"ref172","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA40945.2020.9196884"},{"key":"ref179","doi-asserted-by":"crossref","first-page":"39","DOI":"10.5772\/5618","article-title":"Webots: Professional mobile robot simulation","volume":"1","author":"michel","year":"2004","journal-title":"Int J Adv Robot Syst"},{"key":"ref180","year":"2016","journal-title":"OpenAI Gym Car Racing"},{"key":"ref181","doi-asserted-by":"publisher","DOI":"10.3141\/2622-02"},{"key":"ref188","year":"2018","journal-title":"Apollo Simulation"},{"key":"ref189","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1073-7"},{"key":"ref186","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-67361-5_40"},{"key":"ref187","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569938"},{"key":"ref184","year":"2018","journal-title":"Environment Simulator Minimalistic (esmini)"},{"key":"ref185","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00152"},{"key":"ref182","author":"leurent","year":"2018","journal-title":"An Environment for Autonomous Driving Decision-Making"},{"key":"ref183","year":"2018","journal-title":"Deepdrive Simulation"},{"key":"ref148","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2008.04.005"},{"key":"ref149","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref146","article-title":"Generalizing goal-conditioned reinforcement learning with variational causal reasoning","author":"ding","year":"2022","journal-title":"arXiv 2207 09081"},{"key":"ref147","author":"bennett","year":"2010","journal-title":"OpenStreetMap"},{"key":"ref155","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.534"},{"key":"ref156","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.243"},{"key":"ref153","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_33"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1177\/0278364916679498"},{"key":"ref151","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref152","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.352"},{"key":"ref150","first-page":"1028","article-title":"A new benchmark for vision-based cyclist detection","author":"li","year":"2016","journal-title":"Proc IEEE Intell Vehicles Symp (IV)"},{"key":"ref159","year":"2018","journal-title":"Udacity dataset"},{"key":"ref157","first-page":"2636","article-title":"BDD100K: A diverse driving dataset for heterogeneous multitask learning","author":"yu","year":"2020","journal-title":"Proc IEEE Conf Comput Vis and Pattern Recog"},{"key":"ref158","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569552"},{"key":"ref166","doi-asserted-by":"publisher","DOI":"10.1109\/IV47402.2020.9304839"},{"key":"ref167","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294728"},{"key":"ref164","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2019.8793925"},{"key":"ref165","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 [cs]"},{"key":"ref162","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2926463"},{"key":"ref163","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2019.2907676"},{"key":"ref160","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2018.2791533"},{"key":"ref161","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00868"},{"key":"ref13","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2014","journal-title":"arXiv 1412 6572"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2020.100285"},{"key":"ref15","first-page":"1","article-title":"Automated generation of virtual driving scenarios from test drive data","author":"van der made","year":"2015","journal-title":"Proc 24th Int Tech Conf Enhanced Saf Vehicles (ESV) Nat Highway Traffic Saf Admin"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2018.8500406"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/IROS45743.2020.9340696"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00175"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01118"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.2969927"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.3390\/app10228154"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569371"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17641-8_18"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/SIBGRAPI.2018.00067"},{"key":"ref191","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC45102.2020.9294422"},{"key":"ref192","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00965"},{"key":"ref190","first-page":"1","article-title":"Deep latent competition: Learning to race using visual control policies in latent space","author":"schwarting","year":"2020","journal-title":"Proc Conf Robot Learn"},{"key":"ref199","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569929"},{"key":"ref197","year":"2018","journal-title":"SUMO NETEDIT"},{"key":"ref198","year":"2020","journal-title":"SMARTS Scenario Studio"},{"key":"ref195","doi-asserted-by":"publisher","DOI":"10.1109\/ICALT.2009.24"},{"key":"ref196","first-page":"1","article-title":"SafeBench: A benchmarking platform for safety evaluation of autonomous vehicles","author":"xu","year":"2022","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref193","article-title":"AutoDRIVE simulator: A simulator for scaled autonomous vehicle research and education","author":"vilas samak","year":"2021","journal-title":"arXiv 2103 10030"},{"key":"ref194","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2004.180"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6979\/10175858\/10089194-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/10175858\/10089194.pdf?arnumber=10089194","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T17:46:17Z","timestamp":1690825577000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10089194\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7]]},"references-count":216,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/tits.2023.3259322","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7]]}}}