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Deriving robust control policies for realistic urban navigation scenarios is not a trivial task.
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2018
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F. Codevilla, E. Santana, A. Lopez, and A. Gaidon, “Exploring the limitations of behavior cloning for autonomous driving,” in 2019 IEEE/CVF International Conference on Computer Vision (ICCV) , 2019, pp. 9328–9337
2019
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2019
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2020
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2021
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2021
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Z. Zhang, A. Liniger, D. Dai, F. Yu, and L. Van Gool, “End-to-end urban driving by imitating a reinforcement learning coach,” in 2021 IEEE/CVF International Conference on Computer Vision (ICCV) , 2021, pp. 15 202–15 212
2021
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2021
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2021
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2021
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2021
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E. Bronstein, M. Palatucci, D. Notz, B. White, A. Kuefler, Y. Lu, S. Paul, P. Nikdel, P. Mougin, H. Chen et al. , “Hierarchical model-based imitation learning for planning in autonomous driving,” in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2022, pp. 8652–8659
2022
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S. Teng, L. Chen, Y. Ai, Y. Zhou, Z. Xuanyuan, and X. Hu, “Hierarchical interpretable imitation learning for end-to-end autonomous driving,” IEEE Transactions on Intelligent Vehicles , vol. 8, no. 1, pp. 673–683, 2023
2023
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