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The nature of explanations provided by an explainable AI algorithm has been a topic of interest in the explainable AI and human-computer interaction community.
M. R. Endsley, “Situation models: An avenue to the modeling of mental models,” in
2000
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,”
2015
Earlier work this paper cites.
M. M. Davidson, M. S. Butchko, K. Robbins, L. W. Sherd, and S. J. Gervais, “The mediating role of perceived safety on street harassment and anxiety,”
2016
Earlier work this paper cites.
A. Dosovitskiy, G. Ros, F. Codevilla, A. Lopez, and V. Koltun, “CARLA: An open urban driving simulator,” in
2017
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S. Khastgir, S. Birrell, G. Dhadyalla, and P. Jennings, “Calibrating trust through knowledge: Introducing the concept of informed safety for automation in vehicles,”
2018
Earlier work this paper cites.
R. Guidotti, A. Monreale, S. Ruggieri, F. Turini, F. Giannotti, and D. Pedreschi, “A survey of methods for explaining black box models,”
2018
Earlier work this paper cites.
A. Kunze, S. J. Summerskill, R. Marshall, and A. J. Filtness, “Conveying Uncertainties using Peripheral Awareness Displays in the Context of Automated Driving,” in
2019
Earlier work this paper cites.
A. Kunze, S. J. Summerskill, R. Marshall, and A. J. Filtness, “Automation Transparency: Implications of Uncertainty Communication for Human-Automation Interaction and Interfaces,”
2019
Earlier work this paper cites.
M. Eiband, D. Buschek, A. Kremer, and H. Hussmann, “The Impact of Placebic Explanations on Trust in Intelligent Systems,” in
2019
Earlier work this paper cites.
C. Hewitt, I. Politis, T. Amanatidis, and A. Sarkar, “Assessing public perception of self-driving cars: The autonomous vehicle acceptance model,” in
2019
Earlier work this paper cites.
T. Ha, S. Kim, D. Seo, and S. Lee, “Effects of explanation types and perceived risk on trust in autonomous vehicles,”
2020
Cited alongside, same era.
M. Colley, C. Bräuner, M. Lanzer, M. Walch, M. Baumann, and E. Rukzio, “Effect of Visualization of Pedestrian Intention Recognition on Trust and Cognitive Load,” in
2020
Cited alongside, same era.
P. Wintersberger, H. Nicklas, T. Martlbauer, S. Hammer, and A. Riener, “Explainable automation: Personalized and Adaptive UIs to Foster Trust and Understanding of Driving Automation Systems,” in
2020
Cited alongside, same era.
N. Dillen, M. Ilievski, E. Law, L. E. Nacke, K. Czarnecki, and O. Schneider, “Keep Calm and Ride Along: Passenger Comfort and Anxiety as Physiological Responses to Autonomous Driving Styles,” in
2020
Cited alongside, same era.
J. Terken and B. Pfleging, “Toward shared control between automated vehicles and users,”
M. Colley, B. Eder, J. O. Rixen, and E. Rukzio, “Effects of Semantic Segmentation Visualization on Trust, Situation Awareness, and Cognitive Load in Highly Automated Vehicles,” in
2021
Later among the works it cites.
S. Anjomshoae, D. Omeiza, and L. Jiang, “Context-based image explanations for deep neural networks,”
2021
Later among the works it cites.
R. Bin Issa, M. Das, M. S. Rahman, M. Barua, M. K. Rhaman, K. S. N. Ripon, and M. G. R. Alam, “Double deep Q-learning and faster R-Cnn-based autonomous vehicle navigation and obstacle avoidance in dynamic environment,”
2021
Later among the works it cites.
S. M. Faas, J. Kraus, A. Schoenhals, and M. Baumann, “Calibrating Pedestrians’ Trust in Automated Vehicles: Does an Intent Display in an External HMI Support Trust Calibration and Safe Crossing Behavior?,” in
2021
Later among the works it cites.
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2020
Cited alongside, same era.
H. Liu, T. Hirayama, and M. Watanabe, “Importance of instruction for pedestrian-automated driving vehicle interaction with an external human machine interface: Effects on pedestrians’ situation awareness, trust, perceived risks and decision making,” in
2021
Cited alongside, same era.
T. Schneider, J. Hois, A. Rosenstein, S. Ghellal, D. Theofanou-Fülbier, and A. R. Gerlicher, “ExplAIn Yourself! Transparency for Positive UX in Autonomous Driving,” in
2021
Cited alongside, same era.
D. Omeiza, K. Kollnig, H. Webb, M. Jirotka, and L. Kunze, “Why Not Explain? Effects of Explanations on Human Perceptions of Autonomous Driving,” in
2021
Cited alongside, same era.
D. Omeiza, H. Web, M. Jirotka, and L. Kunze, “Towards Accountability: Providing Intelligible Explanations in Autonomous Driving,” in
2021
Cited alongside, same era.
2021
Cited alongside, same era.
2022
Later among the works it cites.
D. Omeiza, S. Anjomshoae, H. Webb, M. Jirotka, and L. Kunze, “From Spoken Thoughts to Automated Driving Commentary: Predicting and Explaining Intelligent Vehicles’ Actions,” in
2022
Later among the works it cites.
S. Buijsman, “Defining explanation and explanatory depth in XAI,”
2022
Later among the works it cites.
M. Colley, M. Rädler, J. Glimmann, and E. Rukzio, “Effects of Scene Detection, Scene Prediction, and Maneuver Planning Visualizations on Trust, Situation Awareness, and Cognitive Load in Highly Automated Vehicles,”
2022
Later among the works it cites.
G. Silvera, A. Biswas, and H. Admoni, “DReyeVR: Democratizing Virtual Reality Driving Simulation for Behavioural & Interaction Research,” in
2022
Later among the works it cites.
F. Quansah, J. E. Hagan Jr, F. Sambah, J. B. Frimpong, F. Ankomah, M. Srem-Sai, M. Seibu, R. S. K. Abieraba, and T. Schack, “Perceived safety of learning environment and associated anxiety factors during COVID-19 in Ghana: Evidence from physical education practical-oriented program,”
2022
Later among the works it cites.