{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T03:37:37Z","timestamp":1769744257752,"version":"3.49.0"},"reference-count":70,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T00:00:00Z","timestamp":1747612800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,19]],"date-time":"2025-05-19T00:00:00Z","timestamp":1747612800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,19]]},"DOI":"10.1109\/icra55743.2025.11128453","type":"proceedings-article","created":{"date-parts":[[2025,9,2]],"date-time":"2025-09-02T17:28:56Z","timestamp":1756834136000},"page":"14888-14895","source":"Crossref","is-referenced-by-count":1,"title":["Dual-AEB: Synergizing Rule-Based and Multimodal Large Language Models for Effective Emergency Braking"],"prefix":"10.1109","author":[{"given":"Wei","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University,China"}]},{"given":"Pengfei","family":"Li","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University,China"}]},{"given":"Junli","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University,China"}]},{"given":"Bingchuan","family":"Sun","sequence":"additional","affiliation":[{"name":"Lenovo Research"}]},{"given":"Qihao","family":"Jin","sequence":"additional","affiliation":[{"name":"Fudan University,Academy for Engineering and Technology,China"}]},{"given":"Guangjun","family":"Bao","sequence":"additional","affiliation":[{"name":"Lenovo Research"}]},{"given":"Shibo","family":"Rui","sequence":"additional","affiliation":[{"name":"Lenovo Research"}]},{"given":"Yang","family":"Yu","sequence":"additional","affiliation":[{"name":"Lenovo Research"}]},{"given":"Wenchao","family":"Ding","sequence":"additional","affiliation":[{"name":"Fudan University,Academy for Engineering and Technology,China"}]},{"given":"Peng","family":"Li","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University,China"}]},{"given":"Yilun","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute for AI Industry Research (AIR), Tsinghua University,China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/1188089"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2016.11.009"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.12815\/kits.2013.12.3.65"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2015.03.029"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1080\/15389588.2016.1186802"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2020.105538"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1080\/15389588.2019.1679797"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2015.7225845"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1080\/15389588.2016.1155210"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/S0001-4575(00)00019-1"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/s12144-022-03375-6"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/S0001-4575(02)00022-2"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317839"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2020.2986005"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3454122"},{"key":"ref16","volume-title":"Emergency-braking distance prediction using deep learning","author":"Zhang","year":"2021"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.3390\/s24010212"},{"key":"ref18","volume-title":"LLM-Assist: Enhancing closed-loop planning with language-based reasoning","author":"Sharan","year":"2023"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2016.11.009"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2015.03.029"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1080\/15389588.2016.1186802"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.simpat.2021.102450"},{"key":"ref23","first-page":"1415","article-title":"Improvement of an autonomous emergency-braking decision-making system for commercial vehicles based on unsafe control strategy analysis","author":"Zhou","year":"2023","journal-title":"Journal of Tsinghua University (Science and Technology)"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1080\/00423110412331282850"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1049\/itr2.12284"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/icves56941.2022.9987182"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3390\/s19214671"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1049\/cps2.12034"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/app13020946"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/WSAI51899.2021.9486316"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICECA52323.2021.9675885"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3435937"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3209889.3209897"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1017\/psa.2023.8"},{"key":"ref35","volume-title":"Language models are few-shot learners","author":"Brown","year":"2020"},{"key":"ref36","volume-title":"The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)","author":"Yang","year":"2023"},{"key":"ref37","volume-title":"GPT-Driver: Learning to drive with GPT","author":"Mao","year":"2023"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52733.2024.01432"},{"key":"ref39","volume-title":"LanguageMPC: Large language models as decision makers for autonomous driving","author":"Sha","year":"2023"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/wacvw60836.2024.00102"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611018"},{"key":"ref42","volume-title":"DriveVLM: The convergence of autonomous driving and large vision-language models","author":"Tian","year":"2024"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610855"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611448"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611090"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610744"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610065"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610676"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10610072"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611663"},{"key":"ref51","volume-title":"PlanAgent: A multi-modal large language agent for closed-loop vehicle motion planning","author":"Zheng","year":"2024"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48506.2021.9560867"},{"issue":"15349","key":"ref53","article-title":"NAVSIM: Data-driven non-reactive autonomous vehicle simulation and benchmarking","volume":"2406","author":"Dauner","year":"2024","journal-title":"arXiv"},{"key":"ref54","article-title":"Parting with misconceptions about learning-based vehicle motion planning","volume-title":"Conference on Robot Learning (CoRL)","author":"Dauner","year":"2023"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02080"},{"key":"ref56","article-title":"Bench2Drive: Towards multi-ability benchmarking of closed-loop end-to-end autonomous driving","author":"Jia","year":"2024","journal-title":"arXiv preprint"},{"key":"ref57","volume-title":"Carla: An open urban driving simulator","author":"Dosovitskiy","year":"2017"},{"key":"ref58","volume-title":"Chain-of-thought prompting elicits reasoning in large language models","author":"Wei","year":"2023"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA48891.2023.10160326"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.3115\/1073083.1073135"},{"key":"ref61","first-page":"65","article-title":"METEOR: An automatic metric for mt evaluation with improved correlation with human judgments","volume-title":"Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and\/or summarization","author":"Banerjee","year":"2005"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.3115\/1218955.1219032"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01712"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00766"},{"key":"ref65","volume-title":"LLaVA-OneVision: Easy visual task transfer","author":"Li","year":"2024"},{"key":"ref66","volume-title":"Rethinking the open-loop evaluation of end-to-end autonomous driving in nuscenes","author":"Zhai","year":"2023"},{"key":"ref67","first-page":"6119","article-title":"Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline","volume":"35","author":"Wu","year":"2022","journal-title":"Advances in Neural Information Processing Systems"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02105"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00731"},{"key":"ref70","article-title":"Think2Drive: Efficient reinforcement learning by thinking in latent world model for quasi-realistic autonomous driving (in carla-v2)","volume-title":"ECCV","author":"Li","year":"2024"}],"event":{"name":"2025 IEEE International Conference on Robotics and Automation (ICRA)","location":"Atlanta, GA, USA","start":{"date-parts":[[2025,5,19]]},"end":{"date-parts":[[2025,5,23]]}},"container-title":["2025 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11127273\/11127223\/11128453.pdf?arnumber=11128453","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T06:46:44Z","timestamp":1756882004000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11128453\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,19]]},"references-count":70,"URL":"https:\/\/doi.org\/10.1109\/icra55743.2025.11128453","relation":{},"subject":[],"published":{"date-parts":[[2025,5,19]]}}}