{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T21:27:49Z","timestamp":1769722069407,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":43,"publisher":"ACM","funder":[{"name":"Frontier Technologies R&D Program of Jiangsu","award":["#BF2024059"],"award-info":[{"award-number":["#BF2024059"]}]},{"name":"National Natural Science Foundation of China","award":["#62025202"],"award-info":[{"award-number":["#62025202"]}]},{"name":"National Natural Science Foundation of China","award":["#62172199"],"award-info":[{"award-number":["#62172199"]}]},{"name":"the Collaborative Innovation Center of Novel Software Technology and Industrialization","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,20]]},"DOI":"10.1145\/3755881.3755905","type":"proceedings-article","created":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T11:46:17Z","timestamp":1761565577000},"page":"84-95","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-3692-9908","authenticated-orcid":false,"given":"Hao","family":"Gao","sequence":"first","affiliation":[{"name":"Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3214-7882","authenticated-orcid":false,"given":"Jingyue","family":"Wang","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-2489-2298","authenticated-orcid":false,"given":"Wenyang","family":"Fang","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0407-0797","authenticated-orcid":false,"given":"Jingwei","family":"Xu","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3971-5438","authenticated-orcid":false,"given":"Yunpeng","family":"Huang","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5993-1665","authenticated-orcid":false,"given":"Taolue","family":"Chen","sequence":"additional","affiliation":[{"name":"University of London, London, United Kingdom"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7970-1384","authenticated-orcid":false,"given":"Xiaoxing","family":"Ma","sequence":"additional","affiliation":[{"name":"Nanjing University, Nanjing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_3_2_2_2","doi-asserted-by":"crossref","unstructured":"Suneel Belkhale Tianli Ding Ted Xiao Pierre Sermanet Quon Vuong Jonathan Tompson Yevgen Chebotar Debidatta Dwibedi and Dorsa Sadigh. 2024. Rt-h: Action hierarchies using language. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2403.01823 (2024).","DOI":"10.15607\/RSS.2024.XX.049"},{"key":"e_1_3_3_2_3_2","unstructured":"Anthony Brohan Noah Brown Justice Carbajal Yevgen Chebotar Xi Chen Krzysztof Choromanski Tianli Ding Danny Driess Avinava Dubey Chelsea Finn et\u00a0al. 2023. Rt-2: Vision-language-action models transfer web knowledge to robotic control. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2307.15818 (2023)."},{"key":"e_1_3_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"e_1_3_3_2_5_2","unstructured":"Holger Caesar Juraj Kabzan Kok\u00a0Seang Tan Whye\u00a0Kit Fong Eric Wolff Alex Lang Luke Fletcher Oscar Beijbom and Sammy Omari. 2021. nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2106.11810 (2021)."},{"key":"e_1_3_3_2_6_2","first-page":"14554","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Cao Anh-Quan","year":"2024","unstructured":"Anh-Quan Cao, Angela Dai, and Raoul de Charette. 2024. Pasco: Urban 3d panoptic scene completion with uncertainty awareness. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 14554\u201314564."},{"key":"e_1_3_3_2_7_2","doi-asserted-by":"crossref","unstructured":"Jordi Casas Jaime\u00a0L Ferrer David Garcia Josep Perarnau and Alex Torday. 2010. Traffic simulation with aimsun. Fundamentals of traffic simulation (2010) 173\u2013232.","DOI":"10.1007\/978-1-4419-6142-6_5"},{"key":"e_1_3_3_2_8_2","doi-asserted-by":"crossref","unstructured":"Di Chen Meixin Zhu Hao Yang Xuesong Wang and Yinhai Wang. 2024. Data-driven Traffic Simulation: A Comprehensive Review. IEEE Transactions on Intelligent Vehicles (2024).","DOI":"10.1109\/TIV.2024.3367919"},{"key":"e_1_3_3_2_9_2","first-page":"1","volume-title":"Conference on robot learning","author":"Dosovitskiy Alexey","year":"2017","unstructured":"Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun. 2017. CARLA: An open urban driving simulator. In Conference on robot learning. PMLR, 1\u201316."},{"key":"e_1_3_3_2_10_2","unstructured":"Danny Driess Fei Xia Mehdi\u00a0SM Sajjadi Corey Lynch Aakanksha Chowdhery Brian Ichter Ayzaan Wahid Jonathan Tompson Quan Vuong Tianhe Yu et\u00a0al. 2023. Palm-e: An embodied multimodal language model. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2303.03378 (2023)."},{"key":"e_1_3_3_2_11_2","unstructured":"Abhimanyu Dubey Abhinav Jauhri Abhinav Pandey Abhishek Kadian Ahmad Al-Dahle Aiesha Letman Akhil Mathur Alan Schelten Amy Yang Angela Fan et\u00a0al. 2024. The llama 3 herd of models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2407.21783 (2024)."},{"key":"e_1_3_3_2_12_2","doi-asserted-by":"crossref","unstructured":"Martin Fellendorf and Peter Vortisch. 2010. Microscopic traffic flow simulator VISSIM. Fundamentals of traffic simulation (2010) 63\u201393.","DOI":"10.1007\/978-1-4419-6142-6_2"},{"key":"e_1_3_3_2_13_2","doi-asserted-by":"crossref","unstructured":"Shuo Feng Xintao Yan Haowei Sun Yiheng Feng and Henry\u00a0X Liu. 2021. Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment. Nature communications 12 1 (2021) 748.","DOI":"10.1038\/s41467-021-21007-8"},{"key":"e_1_3_3_2_14_2","first-page":"14521","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Gu Xunjiang","year":"2024","unstructured":"Xunjiang Gu, Guanyu Song, Igor Gilitschenski, Marco Pavone, and Boris Ivanovic. 2024. Producing and leveraging online map uncertainty in trajectory prediction. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 14521\u201314530."},{"key":"e_1_3_3_2_15_2","unstructured":"S Huang L Dong W Wang Y Hao S Singhal S Ma T Lv L Cui OK Mohammed B Patra et\u00a0al. 2023. Language is not all you need: aligning perception with language models (2023). arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2302.14045 (2023)."},{"key":"e_1_3_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00890"},{"key":"e_1_3_3_2_17_2","first-page":"20258","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Jiang Haoyi","year":"2024","unstructured":"Haoyi Jiang, Tianheng Cheng, Naiyu Gao, Haoyang Zhang, Tianwei Lin, Wenyu Liu, and Xinggang Wang. 2024. Symphonize 3d semantic scene completion with contextual instance queries. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 20258\u201320267."},{"key":"e_1_3_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00877"},{"key":"e_1_3_3_2_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569938"},{"key":"e_1_3_3_2_20_2","unstructured":"OpenAI. 2024. Introducing OpenAI o1-preview. https:\/\/openai.com\/index\/introducing-openai-o1-preview\/."},{"key":"e_1_3_3_2_21_2","first-page":"15065","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Park Daehee","year":"2024","unstructured":"Daehee Park, Jaeseok Jeong, Sung-Hoon Yoon, Jaewoo Jeong, and Kuk-Jin Yoon. 2024. T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 15065\u201315076."},{"key":"e_1_3_3_2_22_2","unstructured":"Katrin Renz Long Chen Ana-Maria Marcu Jan H\u00fcnermann Benoit Hanotte Alice Karnsund Jamie Shotton Elahe Arani and Oleg Sinavski. 2024. CarLLaVA: Vision language models for camera-only closed-loop driving. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2406.10165 (2024)."},{"key":"e_1_3_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58523-5_40"},{"key":"e_1_3_3_2_24_2","first-page":"15120","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Shao Hao","year":"2024","unstructured":"Hao Shao, Yuxuan Hu, Letian Wang, Guanglu Song, Steven\u00a0L Waslander, Yu Liu, and Hongsheng Li. 2024. Lmdrive: Closed-loop end-to-end driving with large language models. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 15120\u201315130."},{"key":"e_1_3_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01319"},{"key":"e_1_3_3_2_26_2","unstructured":"SP Sharan Francesco Pittaluga Manmohan Chandraker et\u00a0al. 2023. Llm-assist: Enhancing closed-loop planning with language-based reasoning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2401.00125 (2023)."},{"key":"e_1_3_3_2_27_2","first-page":"10400","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Suo Simon","year":"2021","unstructured":"Simon Suo, Sebastian Regalado, Sergio Casas, and Raquel Urtasun. 2021. Trafficsim: Learning to simulate realistic multi-agent behaviors. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 10400\u201310409."},{"key":"e_1_3_3_2_28_2","unstructured":"Tesla. 2023. 2023 Investor Day | Tesla. https:\/\/www.youtube.com\/watch?v=Hl1zEzVUV7w. Accessed: 2024-09-13."},{"key":"e_1_3_3_2_29_2","unstructured":"Tesla. 2024. Full Self-Driving (Supervised) | Tesla. https:\/\/www.youtube.com\/watch?v=TUDiG7PcLBs. Accessed: 2024-09-13."},{"key":"e_1_3_3_2_30_2","doi-asserted-by":"crossref","unstructured":"Chalavadi Vishnu Vineel Abhinav Debaditya Roy C\u00a0Krishna Mohan and Ch\u00a0Sobhan Babu. 2023. Improving multi-agent trajectory prediction using traffic states on interactive driving scenarios. IEEE Robotics and Automation Letters 8 5 (2023) 2708\u20132715.","DOI":"10.1109\/LRA.2023.3258685"},{"key":"e_1_3_3_2_31_2","unstructured":"Wenhai Wang Jiangwei Xie ChuanYang Hu Haoming Zou Jianan Fan Wenwen Tong Yang Wen Silei Wu Hanming Deng Zhiqi Li et\u00a0al. 2023. Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2312.09245 (2023)."},{"key":"e_1_3_3_2_32_2","unstructured":"Xiaofeng Wang Zheng Zhu Guan Huang Xinze Chen Jiagang Zhu and Jiwen Lu. 2023. Drivedreamer: Towards real-world-driven world models for autonomous driving. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2309.09777 (2023)."},{"key":"e_1_3_3_2_33_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01397"},{"key":"e_1_3_3_2_34_2","unstructured":"Jason Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter Fei Xia Ed Chi Quoc Le and Denny Zhou. 2023. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. arxiv:https:\/\/arXiv.org\/abs\/2201.11903\u00a0[cs.CL] https:\/\/arxiv.org\/abs\/2201.11903"},{"key":"e_1_3_3_2_35_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01428"},{"key":"e_1_3_3_2_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01986"},{"key":"e_1_3_3_2_37_2","unstructured":"Licheng Wen Daocheng Fu Xin Li Xinyu Cai Tao Ma Pinlong Cai Min Dou Botian Shi Liang He and Yu Qiao. 2023. Dilu: A knowledge-driven approach to autonomous driving with large language models. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2309.16292 (2023)."},{"key":"e_1_3_3_2_38_2","first-page":"6902","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Wen Yuqing","year":"2024","unstructured":"Yuqing Wen, Yucheng Zhao, Yingfei Liu, Fan Jia, Yanhui Wang, Chong Luo, Chi Zhang, Tiancai Wang, Xiaoyan Sun, and Xiangyu Zhang. 2024. Panacea: Panoramic and controllable video generation for autonomous driving. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 6902\u20136912."},{"key":"e_1_3_3_2_39_2","unstructured":"Wikipedia. 2018. ISO 26262 \u2013 Road vehicles \u2013 Functional safety. https:\/\/en.wikipedia.org\/wiki\/ISO_26262."},{"key":"e_1_3_3_2_40_2","unstructured":"Wikipedia. 2023. Proportional\u2013integral\u2013derivative controller \u2014 Wikipedia The Free Encyclopedia. https:\/\/en.wikipedia.org\/wiki\/Proportional%E2%80%93integral%E2%80%93derivative_controller"},{"key":"e_1_3_3_2_41_2","first-page":"2929","volume-title":"2023 IEEE International Conference on Robotics and Automation (ICRA)","author":"Xu Danfei","year":"2023","unstructured":"Danfei Xu, Yuxiao Chen, Boris Ivanovic, and Marco Pavone. 2023. Bits: Bi-level imitation for traffic simulation. In 2023 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2929\u20132936."},{"key":"e_1_3_3_2_42_2","first-page":"15459","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zhang Jiawei","year":"2024","unstructured":"Jiawei Zhang, Chejian Xu, and Bo Li. 2024. ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 15459\u201315469."},{"key":"e_1_3_3_2_43_2","first-page":"2357","volume-title":"Conference on Robot Learning","author":"Zhang Linrui","year":"2023","unstructured":"Linrui Zhang, Zhenghao Peng, Quanyi Li, and Bolei Zhou. 2023. Cat: Closed-loop adversarial training for safe end-to-end driving. In Conference on Robot Learning. PMLR, 2357\u20132372."},{"key":"e_1_3_3_2_44_2","unstructured":"Guosheng Zhao Xiaofeng Wang Zheng Zhu Xinze Chen Guan Huang Xiaoyi Bao and Xingang Wang. 2024. Drivedreamer-2: Llm-enhanced world models for diverse driving video generation. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2403.06845 (2024)."}],"event":{"name":"Internetware 2025: the 16th International Conference on Internetware","location":"Trondheim Norway","acronym":"Internetware 2025","sponsor":["SIGSOFT ACM Special Interest Group on Artificial Intelligence"]},"container-title":["Proceedings of the 16th International Conference on Internetware"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3755881.3755905","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T11:52:00Z","timestamp":1761565920000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3755881.3755905"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,20]]},"references-count":43,"alternative-id":["10.1145\/3755881.3755905","10.1145\/3755881"],"URL":"https:\/\/doi.org\/10.1145\/3755881.3755905","relation":{},"subject":[],"published":{"date-parts":[[2025,6,20]]},"assertion":[{"value":"2025-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}