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Explainable AI, in the context of autonomous systems, like self-driving cars, has drawn broad interests from researchers.
R. F. Tate, “Correlation between a discrete and a continuous variable. point-biserial correlation,” The Annals of Mathematical Statistics , vol. 25, no. 3, pp. 603–607, 1954. [Online]. Available: http://www.jstor.org/stable/2236844
1954
Earlier work this paper cites.
S. C. Johnson, “Hierarchical clustering schemes,” Psychometrika , vol. 32, no. 3, pp. 241–254, 1967
1967
Earlier work this paper cites.
J. Ramos et al. , “Using tf-idf to determine word relevance in document queries,” in Proceedings of the first instructional conference on machine learning , vol. 242. Piscataway, NJ, 2003, pp. 133–142
2003
Earlier work this paper cites.
R. Fuller, “Towards a general theory of driver behaviour,” Accident; analysis and prevention , vol. 37, no. 3, p. 461—472, May 2005. [Online]. Available: https://doi.org/10.1016/j.aap.2004.11.003
2004
Earlier work this paper cites.
J. Benesty, J. Chen, Y. Huang, and I. Cohen, “Pearson correlation coefficient,” in Noise reduction in speech processing . Springer, 2009, pp. 1–4
2009
Earlier work this paper cites.
B. Mok, M. Johns, K. J. Lee, D. Miller, D. Sirkin, P. Ive, and W. Ju, “Emergency, automation off: Unstructured transition timing for distracted drivers of automated vehicles,” in 2015 IEEE 18th international conference on intelligent transportation systems . IEEE, 2015, pp. 2458–2464
2015
Earlier work this paper cites.
J. Koo, J. Kwac, W. Ju, M. Steinert, L. Leifer, and C. Nass, “Why did my car just do that? explaining semi-autonomous driving actions to improve driver understanding, trust, and performance,” International Journal on Interactive Design and Manufacturing (IJIDeM) , vol. 9, no. 4, pp. 269–275, Nov 2015. [Online]. Available: https://doi.org/10.1007/s12008-014-0227-2
2015
Earlier work this paper cites.
M. Hengstler, E. Enkel, and S. Duelli, “Applied artificial intelligence and trust—the case of autonomous vehicles and medical assistance devices,” Technological Forecasting and Social Change , vol. 105, pp. 105–120, 2016
2016
Cited alongside, same era.
M. Hutson, “People don’t trust driverless cars. researchers are trying to change that,” 2017
2017
Cited alongside, same era.
B. Dominic, “Blameless driverless cars (and their consequences),” 2018. [Online]. Available: https://www.livemint.com/Opinion/DB7zd5kjJWib2OWkqbbuaM/Blameless-driverless-cars-and-their-consequences.html
2018
Cited alongside, same era.
L. H. Gilpin, D. Bau, B. Z. Yuan, A. Bajwa, M. Specter, and L. Kagal, “Explaining explanations: An overview of interpretability of machine learning,” in 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA) , 2018, pp. 80–89
2018
Cited alongside, same era.
D. Gunning, M. Stefik, J. Choi, T. Miller, S. Stumpf, and G.-Z. Yang, “Xai—explainable artificial intelligence,” Science Robotics , vol. 4, no. 37, 2019. [Online]. Available: https://robotics.sciencemag.org/content/4/37/eaay7120
2019
Later among the works it cites.
N. Du, J. Haspiel, Q. Zhang, D. Tilbury, A. K. Pradhan, X. J. Yang, and L. P. Robert, “Look who’s talking now: Implications of av’s explanations on driver’s trust, av preference, anxiety and mental workload,” Transportation Research Part C: Emerging Technologies , vol. 104, pp. 428 – 442, 2019. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0968090X18313640
2019
Later among the works it cites.
J. Glomsrud, A. Ødegårdstuen, A. Clair, and O. Smogeli, “Trustworthy versus explainable ai in autonomous vessels,” 09 2019
2019
Later among the works it cites.
Y. Xia, D. Zhang, J. Kim, K. Nakayama, K. Zipser, and D. Whitney, “Predicting driver attention in critical situations,” in Computer Vision – ACCV 2018 , C. Jawahar, H. Li, G. Mori, and K. Schindler, Eds. Cham: Springer International Publishing, 2019, pp. 658–674
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J. Kim, A. Rohrbach, T. Darrell, J. Canny, and Z. Akata, “Textual explanations for self-driving vehicles,” in The European Conference on Computer Vision (ECCV) , September 2018
2018
Cited alongside, same era.
J. Haspiel, N. Du, J. Meyerson, L. P. Robert Jr., D. Tilbury, X. J. Yang, and A. K. Pradhan, “Explanations and expectations: Trust building in automated vehicles,” in Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction , ser. HRI ’18. New York, NY, USA: Association for Computing Machinery, 2018, p. 119–120. [Online]. Available: https://doi.org/10.1145/3173386.3177057
2018
Cited alongside, same era.
K. Raats, V. Fors, and S. Pink, “Understanding trust in automated vehicles,” in Proceedings of the 31st Australian Conference on Human-Computer-Interaction , ser. OZCHI’19. New York, NY, USA: Association for Computing Machinery, 2019, p. 352–358. [Online]. Available: https://doi.org/10.1145/3369457.3369493
2019
Cited alongside, same era.
2019
Later among the works it cites.
E. Yurtsever, Y. Liu, J. Lambert, C. Miyajima, E. Takeuchi, K. Takeda, and J. H. L. Hansen, “Risky action recognition in lane change video clips using deep spatiotemporal networks with segmentation mask transfer,” 2019
2019
Later among the works it cites.
Wikipedia contributors, “Friedman test — Wikipedia, the free encyclopedia,” 2020, [Online; accessed 3-May-2020]. [Online]. Available: https://en.wikipedia.org/w/index.php?title=Friedman_test&oldid=951227618
2020
Closest in time.
Y. Shen, N. Wijayaratne, P. Du, S. Jiang, and K. Driggs-Campbell, “Autopreview: A framework for autopilot behavior understanding,” in Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems , ser. CHI EA ’21. New York, NY, USA: Association for Computing Machinery, 2021. [Online]. Available: https://doi.org/10.1145/3411763.3451591
2021
Closest in time.