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We present DSDrive, a streamlined end-to-end paradigm tailored for integrating the reasoning and planning of autonomous vehicles into a unified framework.
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun, “CARLA: An Open Urban Driving Simulator,” in Conference on Robot Learning , 2017, pp. 1–16
2017
Earlier work this paper cites.
2018
Earlier work this paper cites.
J. Guo, U. Kurup, and M. Shah, “Is it safe to drive? an overview of factors, metrics, and datasets for driveability assessment in autonomous driving,” IEEE Transactions on Intelligent Transportation Systems , vol. 21, no. 8, pp. 3135–3151, 2019
2019
Earlier work this paper cites.
S. Mozaffari, O. Y. Al-Jarrah, M. Dianati, P. Jennings, and A. Mouzakitis, “Deep Learning-Based Vehicle Behavior Prediction for Autonomous Driving Applications: A Review,” IEEE Transactions on Intelligent Transportation Systems , vol. 23, no. 1, pp. 33–47, 2020
2020
Earlier work this paper cites.
K. Muhammad, A. Ullah, J. Lloret, J. Del Ser, and V. H. C. De Albuquerque, “Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions,” IEEE Transactions on Intelligent Transportation Systems , vol. 22, no. 7, pp. 4316–4336, 2020
2020
Earlier work this paper cites.
Y. Xiao, F. Codevilla, A. Gurram, O. Urfalioglu, and A. M. López, “Multimodal End-to-End Autonomous Driving,” IEEE Transactions on Intelligent Transportation Systems , vol. 23, no. 1, pp. 537–547, 2020
2020
Earlier work this paper cites.
L. Chen, Y. Li, C. Huang, B. Li, Y. Xing, D. Tian, L. Li, Z. Hu, X. Na, Z. Li et al. , “Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys,” IEEE Transactions on Intelligent Vehicles , vol. 8, no. 2, pp. 1046–1056, 2022
2022
Earlier work this paper cites.
C. Zhang, R. Guo, W. Zeng, Y. Xiong, B. Dai, R. Hu, M. Ren, and R. Urtasun, “Rethinking Closed-Loop Training for Autonomous Driving,” in European Conference on Computer Vision , 2022, pp. 264–282
2022
Earlier work this paper cites.
S. Hu, L. Chen, P. Wu, H. Li, J. Yan, and D. Tao, “ST-P3: End-to-End Vision-Based Autonomous Driving via Spatial-Temporal Feature Learning,” in European Conference on Computer Vision , 2022, pp. 533–549
2022
Earlier work this paper cites.
Y. Hu, J. Yang, L. Chen, K. Li, C. Sima, X. Zhu, S. Chai, S. Du, T. Lin, W. Wang, L. Lu, X. Jia, Q. Liu, J. Dai, Y. Qiao, and H. Li, “Goal-oriented Autonomous Driving,” 2022
2022
Earlier work this paper cites.
J. Cui, H. Qiu, D. Chen, P. Stone, and Y. Zhu, “COOPERNAUT: End-to-End Driving With Cooperative Perception for Networked Vehicles,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 17 252–17 262
2022
Earlier work this paper cites.
2023
Earlier work this paper cites.
T. Gong, L. Zhu, F. R. Yu, and T. Tang, “Edge intelligence in intelligent transportation systems: A survey,” IEEE Transactions on Intelligent Transportation Systems , vol. 24, no. 9, pp. 8919–8944, 2023
2023
Earlier work this paper cites.
2023
Earlier work this paper cites.
Y. Hu, J. Yang, L. Chen, K. Li, C. Sima, X. Zhu, S. Chai, S. Du, T. Lin, W. Wang et al. , “Planning-Oriented Autonomous Driving,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 17 853–17 862
2023
Earlier work this paper cites.
X. Jia, P. Wu, L. Chen, J. Xie, C. He, J. Yan, and H. Li, “Think Twice Before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 21 983–21 994
2023
Earlier work this paper cites.
H. Shao, L. Wang, R. Chen, S. L. Waslander, H. Li, and Y. Liu, “ReasonNet: End-to-End Driving With Temporal and Global Reasoning,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023, pp. 13 723–13 733
2023
Cited alongside, same era.
B. Jiang, S. Chen, Q. Xu, B. Liao, J. Chen, H. Zhou, Q. Zhang, W. Liu, C. Huang, and X. Wang, “VAD: Vectorized Scene Representation for Efficient Autonomous Driving,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2023, pp. 8340–8350
2023
Cited alongside, same era.
Y. Lu, J. Fu, G. Tucker, X. Pan, E. Bronstein, R. Roelofs, B. Sapp, B. White, A. Faust, S. Whiteson et al. , “Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios,” in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems , 2023, pp. 7553–7560
2023
Cited alongside, same era.
2024
Later among the works it cites.
C. Sima, K. Renz, K. Chitta, L. Chen, H. Zhang, C. Xie, J. Beißwenger, P. Luo, A. Geiger, and H. Li, “DriveLM: Driving with Graph Visual Question Answering,” in European Conference on Computer Vision , 2024, pp. 256–274
2024
Later among the works it cites.
C. Pan, B. Yaman, T. Nesti, A. Mallik, A. G. Allievi, S. Velipasalar, and L. Ren, “VLP: Vision Language Planning for Autonomous Driving,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 14 760–14 769
2024
Later among the works it cites.
2024
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2023
Cited alongside, same era.
J. Li, D. Li, S. Savarese, and S. Hoi, “BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models,” in International Conference on Machine Learning , 2023, pp. 19 730–19 742
2023
Cited alongside, same era.
Anthropic, “Claude 3.5 Sonnet,” https://www.anthropic.com/news/claude-3.5-sonnet , Jul. 2024, [Computer software]
2024
Cited alongside, same era.
M. Nie, R. Peng, C. Wang, X. Cai, J. Han, H. Xu, and L. Zhang, “Reason2Drive: Towards Interpretable and Chain-Based Reasoning for Autonomous Driving,” in European Conference on Computer Vision , 2024, pp. 292–308
2024
Cited alongside, same era.
X. Zhou, M. Liu, E. Yurtsever, B. L. Zagar, W. Zimmer, H. Cao, and A. C. Knoll, “Vision Language Models in Autonomous Driving: A Survey and Outlook,” IEEE Transactions on Intelligent Vehicles , 2024
2024
Cited alongside, same era.
L. Chen, O. Sinavski, J. Hünermann, A. Karnsund, A. J. Willmott, D. Birch, D. Maund, and J. Shotton, “Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving,” in 2024 IEEE International Conference on Robotics and Automation , 2024, pp. 14 093–14 100
2024
Cited alongside, same era.
2024
Cited alongside, same era.
2024
Cited alongside, same era.
2024
Cited alongside, same era.
Later among the works it cites.
H. Shao, Y. Hu, L. Wang, G. Song, S. L. Waslander, Y. Liu, and H. Li, “LMDrive: Closed-Loop End-to-End Driving with Large Language Models,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2024, pp. 15 120–15 130
2024
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2024
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