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Autonomous driving has advanced significantly due to sensors, machine learning, and artificial intelligence improvements.
P. C. Wason and J. S. B. Evans, “Dual processes in reasoning?,”
1974
Earlier work this paper cites.
Carnegie Mellon University, The Robotics Institute, 1992
R. C. Coulter · 1992
Earlier work this paper cites.
S. Epstein, “Cognitive-experiential self-theory of personality,”
2003
Earlier work this paper cites.
S. Thrun, M. Montemerlo, H. Dahlkamp, D. Stavens, A. Aron, J. Diebel, P. Fong, J. Gale, M. Halpenny, G. Hoffmann,
2006
Earlier work this paper cites.
D. Kahneman, “Fast and slow thinking,”
2011
Earlier work this paper cites.
J. S. B. Evans and K. E. Stanovich, “Dual-process theories of higher cognition: Advancing the debate,”
2013
Earlier work this paper cites.
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun, “Carla: An open urban driving simulator,” in
2017
Earlier work this paper cites.
I. Loshchilov and F. Hutter, “Decoupled weight decay regularization,”
2017
Earlier work this paper cites.
F. Codevilla, E. Santana, A. M. López, and A. Gaidon, “Exploring the limitations of behavior cloning for autonomous driving,” in
2019
Earlier work this paper cites.
D. Chen, B. Zhou, V. Koltun, and P. Krähenbühl, “Learning by cheating,” in
2020
Earlier work this paper cites.
Z. Liu, H. Jiang, H. Tan, and F. Zhao, “An overview of the latest progress and core challenge of autonomous vehicle technologies,” in
2020
Earlier work this paper cites.
C. Raffel, N. Shazeer, A. Roberts, K. Lee, S. Narang, M. Matena, Y. Zhou, W. Li, and P. J. Liu, “Exploring the limits of transfer learning with a unified text-to-text transformer,”
2020
Earlier work this paper cites.
T. Yin, X. Zhou, and P. Krahenbuhl, “Center-based 3d object detection and tracking,” in
2021
Earlier work this paper cites.
K. Chitta, A. Prakash, and A. Geiger, “Neat: Neural attention fields for end-to-end autonomous driving,” in
2021
Earlier work this paper cites.
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
Earlier work this paper cites.
D. Chen, V. Koltun, and P. Krähenbühl, “Learning to drive from a world on rails,” in
2021
Earlier work this paper cites.
Z. Li, W. Wang, H. Li, E. Xie, C. Sima, T. Lu, Y. Qiao, and J. Dai, “Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,” in
2022
Earlier work this paper cites.
J.-B. Alayrac, J. Donahue, P. Luc, A. Miech, I. Barr, Y. Hasson, K. Lenc, A. Mensch, K. Millican, M. Reynolds, R. Ring, E. Rutherford, S. Cabi, T. Han, Z. Gong, S. Samangooei, M. Monteiro, J. Menick, S. Borgeaud, A. Brock, A. Nematzadeh, S. Sharifzadeh, M. Binkowski, R. Barreira, O. Vinyals, A. Zisserman, and K. Simonyan, “Flamingo: a visual language model for few-shot learning,”
2022
Earlier work this paper cites.
2022
Earlier work this paper cites.
K. Chitta, A. Prakash, B. Jaeger, Z. Yu, K. Renz, and A. Geiger, “Transfuser: Imitation with transformer-based sensor fusion for autonomous driving,”
2022
Earlier work this paper cites.
P. Wu, X. Jia, L. Chen, J. Yan, H. Li, and Y. Qiao, “Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline,”
2022
Earlier work this paper cites.
Z. Liu, H. Tang, A. Amini, X. Yang, H. Mao, D. L. Rus, and S. Han, “Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation,” in
2023
Earlier work this paper cites.
Wayve, “Lingo-1: Exploring natural language for autonomous driving,” 2023
2023
Cited alongside, same era.
Y. Ma, Y. Cao, J. Sun, M. Pavone, and C. Xiao, “Dolphins: Multimodal language model for driving,”
2023
Cited alongside, same era.
X. Li, Y. Bai, P. Cai, L. Wen, D. Fu, B. Zhang, X. Yang, X. Cai, T. Ma, J. Guo,
2023
Cited alongside, same era.
2023
Cited alongside, same era.
J. Mao, J. Ye, Y. Qian, M. Pavone, and Y. Wang, “A language agent for autonomous driving,”
2023
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
2023
Later among the works it cites.
H. Shao, L. Wang, R. Chen, H. Li, and Y. Liu, “Safety-enhanced autonomous driving using interpretable sensor fusion transformer,” in
2023
Later among the works it cites.
Y. Hu, J. Yang, L. Chen, K. Li, C. Sima, X. Zhu, S. Chai, S. Du, T. Lin, W. Wang,
2023
Later among the works it cites.
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
2023
Later among the works it cites.
Y. Peng, J. Han, Z. Zhang, L. Fan, T. Liu, S. Qi, X. Feng, Y. Ma, Y. Wang, and S.-C. Zhu, “The tong test: Evaluating artificial general intelligence through dynamic embodied physical and social interactions,”
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Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
W.-L. Chiang, Z. Li, Z. Lin, Y. Sheng, Z. Wu, H. Zhang, L. Zheng, S. Zhuang, Y. Zhuang, J. E. Gonzalez, I. Stoica, and E. P. Xing, “Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,” March 2023
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Cited alongside, same era.
2023
Later among the works it cites.
S. Gildert and G. Rose, “Building and testing a general intelligence embodied in a humanoid robot,”
2023
Later among the works it cites.
F. Dou, J. Ye, G. Yuan, Q. Lu, W. Niu, H. Sun, L. Guan, G. Lu, G. Mai, N. Liu,
2023
Later among the works it cites.
B. Zhang, J. Zhu, and H. Su, “Toward the third generation artificial intelligence,”
2023
Later among the works it cites.
Z. Xi, W. Chen, X. Guo, W. He, Y. Ding, B. Hong, M. Zhang, J. Wang, S. Jin, E. Zhou,
2023
Later among the works it cites.
Y. Liu, F. Wu, Z. Liu, K. Wang, F. Wang, and X. Qu, “Can language models be used for real-world urban-delivery route optimization?,”
2023
Later among the works it cites.
2023
Later among the works it cites.
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H. Liu, C. Li, Q. Wu, and Y. J. Lee, “Visual instruction tuning,”
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D. Fu, X. Li, L. Wen, M. Dou, P. Cai, B. Shi, and Y. Qiao, “Drive like a human: Rethinking autonomous driving with large language models,” in
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E. Sachdeva, N. Agarwal, S. Chundi, S. Roelofs, J. Li, M. Kochenderfer, C. Choi, and B. Dariush, “Rank2tell: A multimodal driving dataset for joint importance ranking and reasoning,” in
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