SocialDriveGen: generating diverse traffic scenarios with controllable social interactions

Jiaguo TIAN; Zhengbang ZHU; Shenyu ZHANG; Li XU; Bo ZHENG; Xu LIU; Weijie PENG; Shizeng YAO; Weinan ZHANG

doi:10.1007/s11704-026-51974-4

Front. Comput. Sci. ›› 2026, Vol. 20 ›› Issue (9) :2009380 DOI: 10.1007/s11704-026-51974-4

Artificial Intelligence

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SocialDriveGen: generating diverse traffic scenarios with controllable social interactions

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Jiaguo TIAN, Zhengbang ZHU, Shenyu ZHANG, Li XU, Bo ZHENG, Xu LIU, Weijie PENG, Shizeng YAO, Weinan ZHANG. SocialDriveGen: generating diverse traffic scenarios with controllable social interactions. Front. Comput. Sci., 2026, 20 (9) : 2009380 DOI:10.1007/s11704-026-51974-4

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References

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[1]	Schwarting W, Pierson A, Alonso-Mora J, Karaman S, Rus D . Social behavior for autonomous vehicles. Proceedings of the National Academy of Sciences of the United States of America, 2019, 116( 50): 24972–24978

[2]	Dai Z P, Zhou T Z, Shao K, Mguni D H, Wang B, Hao J Y. Socially-attentive policy optimization in multi-agent self-driving system. In: Proceedings of the 6th Conference on Robot Learning. 2023, 946−955

[3]	Zhang S Y, Tian J G, Zhu Z B, Huang S, Yang J C, Zhang W N. DriveGen: towards infinite diverse traffic scenarios with large models. In: Proceedings of 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2025, 10100−10107

[4]	Yang B, Su H Y, Gkanatsios N, Ke T W, Jain A, Schneider J, Fragkiadaki K. Diffusion-ES: gradient-free planning with diffusion for autonomous and instruction-guided driving. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024, 15342−15353

[5]

Wilson B, Qi W, Agarwal T, Lambert J, Singh J, Khandelwal S, Pan B, Kumar R, Hartnett A, Pontes J K, Ramanan D, Carr P, Hays J. Argoverse 2: next generation datasets for self-driving perception and forecasting. In: Proceedings of the 35th International Conference on Neural Information Processing Systems, 2021

[6]	Caesar H, Bankiti V, Lang A H, Vora S, Liong V E, Xu Q, Krishnan A, Pan Y, Baldan G, Beijbom O. nuScenes: a multimodal dataset for autonomous driving. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020, 11618−11628