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Prediction, decision-making, and motion planning are essential for autonomous driving.
Differential flatness of mechanical control systems: A catalog of prototype systems
Murray, R. M.; Rathinam, M.; and Sluis, W. 1995 · 1995
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Differential flatness and absolute equivalence of nonlinear control systems
van Nieuwstadt, M.; Rathinam, M.; and Murray, R. M. 1998 · 1998
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A behavioral planning framework for autonomous driving
Wei, J.; Snider, J. M.; Gu, T.; Dolan, J. M.; and Litkouhi, B. 2014 · 2014
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Deepdriving: Learning affordance for direct perception in autonomous driving
Chen, C.; Seff, A.; Kornhauser, A.; and Xiao, J. 2015 · 2015
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Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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LIDAR-based driving path generation using fully convolutional neural networks
Caltagirone, L.; Bellone, M.; Svensson, L.; and Wahde, M. 2017 · 2017
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Adding navigation to the equation: Turning decisions for end-to-end vehicle control
Hubschneider, C.; Bauer, A.; Weber, M.; and Zöllner, J. M. 2017 · 2017
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An overview of multi-task learning in deep neural networks
Ruder, S. 2017 · 2017
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A machine learning approach for personalized autonomous lane change initiation and control
Vallon, C.; Ercan, Z.; Carvalho, A.; and Borrelli, F. 2017 · 2017
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Large-scale cost function learning for path planning using deep inverse reinforcement learning
Wulfmeier, M.; Rao, D.; Wang, D. Z.; Ondruska, P.; and Posner, I. 2017 · 2017
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Spatially-partitioned environmental representation and planning architecture for on-road autonomous driving
Zhan, W.; Chen, J.; Chan, C.-Y.; Liu, C.; and Tomizuka, M. 2017 · 2017
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Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst
Bansal, M.; Krizhevsky, A.; and Ogale, A. 2018 · 2018
Cited alongside, same era.
End-to-end driving via conditional imitation learning
Codevilla, F.; Müller, M.; López, A.; Koltun, V.; and Dosovitskiy, A. 2018 · 2018
Cited alongside, same era.
Improving language understanding by generative pre-training
Radford, A.; Narasimhan, K.; Salimans, T.; Sutskever, I.; et al. 2018 · 2018
Cited alongside, same era.
Voxelnet: End-to-end learning for point cloud based 3d object detection
Zhou, Y.; and Tuzel, O. 2018 · 2018
Cited alongside, same era.
Machine learning method to ensure robust decision-making of AVs
Tami, R.; Soualmi, B.; Doufene, A.; Ibanez, J.; and Dauwels, J. 2019 · 2019
Cited alongside, same era.
Game Theoretic Planning for Self-Driving Cars in Competitive Scenarios
One thousand and one hours: Self-driving motion prediction dataset
Houston, J.; Zuidhof, G.; Bergamini, L.; Ye, Y.; Chen, L.; Jain, A.; Omari, S.; Iglovikov, V.; and Ondruska, P. 2021 · 2021
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Fiery: Future instance prediction in bird’s-eye view from surround monocular cameras
Hu, A.; Murez, Z.; Mohan, N.; Dudas, S.; Hawke, J.; Badrinarayanan, V.; Cipolla, R.; and Kendall, A. 2021 · 2021
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Bevdet: High-performance multi-camera 3d object detection in bird-eye-view
Huang, J.; Huang, G.; Zhu, Z.; Ye, Y.; and Du, D. 2021 · 2021
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Object dgcnn: 3d object detection using dynamic graphs
Wang, Y.; and Solomon, J. M. 2021 · 2021
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Center-based 3d object detection and tracking
Yin, T.; Zhou, X.; and Krahenbuhl, P. 2021 · 2021
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Wang, M.; Wang, Z.; Talbot, J.; Gerdes, J. C.; and Schwager, M. 2019 · 2019
Cited alongside, same era.
Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D
Philion, J.; and Fidler, S. 2020 · 2020
Cited alongside, same era.
Pv-rcnn: Point-voxel feature set abstraction for 3d object detection
Shi, S.; Guo, C.; Jiang, L.; Wang, Z.; Shi, J.; Wang, X.; and Li, H. 2020 · 2020
Cited alongside, same era.
Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching
Zhang, L.; Ding, W.; Chen, J.; and Shen, S. 2020 · 2020
Cited alongside, same era.
Voxel r-cnn: Towards high performance voxel-based 3d object detection
Deng, J.; Shi, S.; Li, P.; Zhou, W.; Zhang, Y.; and Li, H. 2021 · 2021
Cited alongside, same era.
Epsilon: An efficient planning system for automated vehicles in highly interactive environments
Ding, W.; Zhang, L.; Chen, J.; and Shen, S. 2021 · 2021
Cited alongside, same era.
PowerBEV: A Powerful Yet Lightweight Framework for Instance Prediction in Bird’s-Eye View
Li, P.; Ding, S.; Chen, X.; Hanselmann, N.; Cordts, M.; and Gall, J. 2023a
Cited in the paper.
Akan, A. K.; and Güney, F. 2022 · 2022
Later among the works it cites.
Chen, D.; and Krähenbühl, P. 2022 · 2022
Later among the works it cites.
Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers
Li, Z.; Wang, W.; Li, H.; Xie, E.; Sima, C.; Lu, T.; Qiao, Y.; and Dai, J. 2022 · 2022
Later among the works it cites.
Effective adaptation in multi-task co-training for unified autonomous driving
Liang, X.; Wu, Y.; Han, J.; Xu, H.; Xu, C.; and Liang, X. 2022 · 2022
Later among the works it cites.
Beverse: Unified perception and prediction in birds-eye-view for vision-centric autonomous driving
Zhang, Y.; Zhu, Z.; Zheng, W.; Huang, J.; Huang, G.; Zhou, J.; and Lu, J. 2022 · 2022
Later among the works it cites.
Planning-oriented autonomous driving
Hu, Y.; Yang, J.; Chen, L.; Li, K.; Sima, C.; Zhu, X.; Chai, S.; Du, S.; Lin, T.; Wang, W.; et al. 2023 · 2023
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