{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:49:35Z","timestamp":1767318575865,"version":"3.48.0"},"publisher-location":"Cham","reference-count":65,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032123916","type":"print"},{"value":"9783032123923","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T00:00:00Z","timestamp":1767312000000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>As air travel grows, increasing demand for pilots and ATC operators requires greater automation. Autonomous systems can help manage traffic, reduce crew sizes, and enable a transition from dual pilot operations (DPO) to reduced crew (RCO), single pilot (SiPO), or full autonomy. A major challenge is ensuring effective human-autonomy teaming. Depending on the scenario, humans may delegate tasks, work alongside automation, or interact with artificial pilots. Independent of the scenario, autonomous systems should help reduce workload and avoid increases in pilot stress. Similarly, trust and reliability are essential\u2014without them, automation may be underutilized, leading to errors. Further, clear communication and decision-making are crucial, and autonomy levels must align with operational needs, balancing automation efficiency with human oversight. With respect to SiPO, support systems must address pilot incapacitation due to workload, fatigue, or health issues to ensure safety. This paper explores the transition from current operations to future autonomous paradigms, considering cases of partial and full autonomy. It examines key technologies, human-autonomy teaming, and cognitive methods to assess different models. The review provides insights into automation\u2019s role in future operations, analysing various configurations, autonomy levels, and their impact on human operators to determine optimal aviation strategies.<\/jats:p>","DOI":"10.1007\/978-3-032-12392-3_4","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:45:15Z","timestamp":1767318315000},"page":"54-73","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Safe Return-to-Land Operations in Future Cockpits: An Analysis of Cases and Mitigation Technologies"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7191-8781","authenticated-orcid":false,"given":"Andrew","family":"Fuchs","sequence":"first","affiliation":[]},{"given":"Carmen","family":"Bejarano","sequence":"additional","affiliation":[]},{"given":"Adrien","family":"Metge","sequence":"additional","affiliation":[]},{"given":"Sara","family":"Ruano","sequence":"additional","affiliation":[]},{"given":"Jose Manuel","family":"Cordero","sequence":"additional","affiliation":[]},{"given":"Andr\u00e9s","family":"Perillo","sequence":"additional","affiliation":[]},{"given":"Paris","family":"Vaiopoulos","sequence":"additional","affiliation":[]},{"given":"Ginevra","family":"Fedrizzi","sequence":"additional","affiliation":[]},{"given":"Anna Giulia","family":"Vicario","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","first-page":"2937","DOI":"10.1016\/j.promfg.2015.07.948","volume":"3","author":"MT Koltz","year":"2015","unstructured":"Koltz, M.T., et al.: An investigation of the harbor pilot concept for single pilot operations. Procedia Manuf. 3, 2937\u20132944 (2015)","journal-title":"Procedia Manuf."},{"key":"4_CR2","unstructured":"Matessa, M., Strybel, T., Vu, K., Battiste, V., Schnell, T.: Concept of operations for RCO SPO (No. ARC-E-DAA-TN44254). National Aeronautics and Space Administration, United States (2017)"},{"key":"4_CR3","doi-asserted-by":"crossref","unstructured":"Lachter, J., Brandt, S.L., Battiste, V., Ligda, S.V., Matessa, M., Johnson, W.W.: Toward single pilot operations: developing a ground station. In: Proceedings of the International Conference on Human-Computer Interaction in Aerospace (2014)","DOI":"10.1145\/2669592.2669685"},{"key":"4_CR4","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1109\/TTS.2020.3014395","volume":"1","author":"T Gillespie","year":"2020","unstructured":"Gillespie, T., Hailes, S.: Assignment of legal responsibilities for decisions by autonomous cars using system architectures. IEEE Trans. Technol. Soc. 1, 148\u2013160 (2020)","journal-title":"IEEE Trans. Technol. Soc."},{"key":"4_CR5","doi-asserted-by":"publisher","unstructured":"Li, X., Wu, X., Zhao, Y., Li, Y.: Perceptual risk-aware adaptive responsibility sensitive safety for\u00a0autonomous driving. In: Indulska, M., Reinhartz-Berger, I., Cetina, C., Pastor, O. (eds.) CAiSE 2023, pp. 33\u201349. LNCS, vol. 13901. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-34560-9_3","DOI":"10.1007\/978-3-031-34560-9_3"},{"key":"4_CR6","doi-asserted-by":"publisher","first-page":"16181","DOI":"10.1109\/TITS.2024.3420959","volume":"25","author":"W Huang","year":"2024","unstructured":"Huang, W., Liu, H., Huang, Z., Lv, C.: Safety-aware human-in-the-loop reinforcement learning with shared control for autonomous driving. IEEE Trans. Intell. Transp. Syst. 25, 16181\u201316192 (2024)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"4_CR7","doi-asserted-by":"publisher","first-page":"93293","DOI":"10.1109\/ACCESS.2023.3300423","volume":"11","author":"F Gao","year":"2023","unstructured":"Gao, F., Luo, C., Shi, F., Chen, X., Gao, Z., Zhao, R.: Online safety verification of autonomous driving decision-making based on dynamic reachability analysis. IEEE Access 11, 93293\u201393309 (2023)","journal-title":"IEEE Access"},{"key":"4_CR8","first-page":"367","volume":"237","author":"S Thomas","year":"2023","unstructured":"Thomas, S., Groth, K.M.: Toward a hybrid causal framework for autonomous vehicle safety analysis. Proc. Inst. Mech. Eng. Part O J. Risk Reliab. 237, 367\u2013388 (2023)","journal-title":"Proc. Inst. Mech. Eng. Part O J. Risk Reliab."},{"key":"4_CR9","doi-asserted-by":"publisher","unstructured":"Boujezza, H., Boubakri, A.: A new redundant intelligent architecture to\u00a0improve the\u00a0operational safety of\u00a0autonomous vehicles. In: Barolli, L. (ed.) AINA 2024. LNDECT, vol. 199, pp. 140\u2013152. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-57840-3_13","DOI":"10.1007\/978-3-031-57840-3_13"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Morales-Alvarez, W., Sipele, O., L\u00e9beron, R., Tadjine, H.H., Olaverri-Monreal, C.: Automated driving: a literature review of the take over request in conditional automation. Electronics 9 (2020)","DOI":"10.3390\/electronics9122087"},{"key":"4_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2021.102231","volume":"73","author":"D Mukherjee","year":"2022","unstructured":"Mukherjee, D., Gupta, K., Chang, L.H., Najjaran, H.: A survey of robot learning strategies for human-robot collaboration in industrial settings. Robot. Comput. Integr. Manuf. 73, 102231 (2022)","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"4_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2022.102510","volume":"81","author":"S Li","year":"2023","unstructured":"Li, S., et al.: Proactive human\u2013robot collaboration: mutual-cognitive, predictable, and self-organising perspectives. Robot. Comput. Integr. Manuf. 81, 102510 (2023)","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Valori, M., et al.: Validating safety in human\u2013robot collaboration: standards and new perspectives. Robotics 10 (2021)","DOI":"10.3390\/robotics10020065"},{"key":"4_CR14","unstructured":"EASA: EASA Artificial Intelligence Roadmap 2.0. EASA (2023)"},{"key":"4_CR15","unstructured":"EASA: Annual Safety Review 2024. EASA (2024)"},{"key":"4_CR16","unstructured":"E. I. G. o. P. T. (IGPT): EASA Automation Policy: Bridging Design and Training Principles. EASA (2013)"},{"key":"4_CR17","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1109\/3468.844354","volume":"30","author":"R Parasuraman","year":"2000","unstructured":"Parasuraman, R., Sheridan, T.B., Wickens, C.D.: A model for types and levels of human interaction with automation. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 30, 286\u2013297 (2000)","journal-title":"IEEE Trans. Syst. Man Cybern. Part A Syst. Hum."},{"key":"4_CR18","unstructured":"EASA: EASA Concept Paper: Guidance for Level 1 & 2 machine learning applications. A deliverable of the EASA AI Roadmap. EASA (2024)"},{"key":"4_CR19","doi-asserted-by":"crossref","unstructured":"Klaproth, O.W., Vernaleken, C., Krol, L.R., Halbruegge, M., Zander, T.O., Russwinkel, N.: Tracing pilots\u2019 situation assessment by neuroadaptive cognitive modeling. Front. Neurosci. 14 (2020)","DOI":"10.3389\/fnins.2020.00795"},{"key":"4_CR20","doi-asserted-by":"publisher","first-page":"122113","DOI":"10.1109\/ACCESS.2021.3108438","volume":"9","author":"H Chen","year":"2021","unstructured":"Chen, H., Liu, S., Pang, L., Wanyan, X., Fang, Y.: Developing an improved ACT-R model for pilot situation awareness measurement. IEEE Access 9, 122113\u2013122124 (2021)","journal-title":"IEEE Access"},{"key":"4_CR21","unstructured":"Rabinowitz, N., Perbet, F., Song, F., Zhang, C., Eslami, S.A., Botvinick, M.: Machine theory of mind. In: International Conference on Machine Learning (2018)"},{"key":"4_CR22","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1016\/j.tics.2004.10.001","volume":"8","author":"AM Leslie","year":"2004","unstructured":"Leslie, A.M., Friedman, O., German, T.P.: Core mechanisms in \u2018theory of mind.\u2019 Trends Cogn. Sci. 8, 528\u2013533 (2004)","journal-title":"Trends Cogn. Sci."},{"key":"4_CR23","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1017\/S0140525X00076512","volume":"1","author":"D Premack","year":"1978","unstructured":"Premack, D., Woodruff, G.: Does the chimpanzee have a theory of mind? Behav. Brain Sci. 1, 515\u2013526 (1978)","journal-title":"Behav. Brain Sci."},{"key":"4_CR24","doi-asserted-by":"crossref","unstructured":"Fuchs, A., Passarella, A., Conti, M.: Modeling, replicating, and predicting human behavior: a survey. ACM Trans. Auton. Adapt. Syst. 18 (2023)","DOI":"10.1145\/3580492"},{"key":"4_CR25","doi-asserted-by":"publisher","unstructured":"Tchio, G.C.T., Courtemanche, MA., Tato, A.A.N., Nkambou, R., Psych\u00e9, V.: Integrating an ontological reference model of piloting procedures in ACT-R cognitive architecture to simulate piloting tasks. In: Frasson, C., Mylonas, P., Troussas, C. (eds.) ITS 2023. LNCS, vol. 13891, pp. 183\u2013194. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-32883-1_16","DOI":"10.1007\/978-3-031-32883-1_16"},{"key":"4_CR26","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/s10111-014-0292-0","volume":"17","author":"W-M Roth","year":"2015","unstructured":"Roth, W.-M., Mavin, T.J., Munro, I.: How a cockpit forgets speeds (and speed-related events): toward a kinetic description of joint cognitive systems. Cogn. Technol. Work 17, 279\u2013299 (2015)","journal-title":"Cogn. Technol. Work"},{"key":"4_CR27","doi-asserted-by":"publisher","unstructured":"Tamkodjou Tchio, G.C., Nkambou, R., Tato Nyamen, A.A., Psych\u00e9, V.: Handling of\u00a0abnormal aircraft takeoff procedures: cognitive modeling of\u00a0an\u00a0ACT-R synthetic pilot integrating an\u00a0ontological reference model. In: Mylonas, P., Kardaras, D., Caro, J. (eds.) NiDS 2024. LNNS, vol. 1170, pp. 448\u2013461. Springer, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-73344-4_38","DOI":"10.1007\/978-3-031-73344-4_38"},{"key":"4_CR28","doi-asserted-by":"publisher","first-page":"24871","DOI":"10.1007\/s12144-022-03430-2","volume":"42","author":"Z Zheng","year":"2023","unstructured":"Zheng, Z., Gao, S., Su, Y., Chen, Y., Wang, X.: Cognitive load-induced pupil dilation reflects potential flight ability. Curr. Psychol. 42, 24871\u201324881 (2023)","journal-title":"Curr. Psychol."},{"key":"4_CR29","unstructured":"Brams, S., Ziv, G., Levin, O., Wagemans, J., Williams, A.M., Helsen, W.F.: Brain, gaze behavior and perceptual-cognitive skills in aviation: what is yet to be studied? In: Proceedings of the 1st International Workshop on Eye-Tracking in Aviation (ETAVI 2020) (2020)"},{"key":"4_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.apergo.2022.103838","volume":"105","author":"E van Weelden","year":"2022","unstructured":"van Weelden, E., Alimardani, M., Wiltshire, T.J., Louwerse, M.M.: Aviation and neurophysiology: a systematic review. Appl. Ergon. 105, 103838 (2022)","journal-title":"Appl. Ergon."},{"key":"4_CR31","unstructured":"Vogl, J., Delgado-Howard, C., Plummer, H., McAtee, A., Hayes, A., Aura, C., Onge, P.S.: A literature review of applied cognitive workload assessment in the aviation domain. US Army Aeromedical Research Laboratory (2023)"},{"key":"4_CR32","doi-asserted-by":"crossref","unstructured":"Martinez-Marquez, D., Pingali, S., Panuwatwanich, K., Stewart, R.A., Mohamed, S.: Application of eye tracking technology in aviation, maritime, and construction industries: a systematic review. Sensors 21 (2021)","DOI":"10.3390\/s21134289"},{"key":"4_CR33","doi-asserted-by":"crossref","unstructured":"Wilson, J.C., Nair, S., Scielzo, S., Larson, E.C.: Objective measures of cognitive load using deep multi-modal learning: a use-case in aviation. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5 (2021)","DOI":"10.1145\/3448111"},{"key":"4_CR34","unstructured":"Roscoe, A.H., Ellis, G.A.: A subjective rating scale for assessing pilot workload in flight: a decade of practical use (1990)"},{"key":"4_CR35","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/THMS.2021.3116115","volume":"52","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Sun, Y., Zhang, Y.: Evolutionary game and collaboration mechanism of human-computer interaction for future intelligent aircraft cockpit based on system dynamics. IEEE Trans. Hum. Mach. Syst. 52, 87\u201398 (2022)","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"key":"4_CR36","first-page":"S15","volume":"73","author":"GA Boy","year":"2022","unstructured":"Boy, G.A., Morel, C.: The machine as a partner: Human-machine teaming design using the PRODEC method. Work 73, S15\u2013S30 (2022)","journal-title":"Work"},{"key":"4_CR37","doi-asserted-by":"publisher","DOI":"10.1088\/1757-899X\/1024\/1\/012105","volume":"1024","author":"C Dormoy","year":"2021","unstructured":"Dormoy, C., Andr\u00e9, J.-M., Pagani, A.: A human factors\u2019 approach for multimodal collaboration with cognitive computing to create a human intelligent machine team: a review. IOP Conf. Ser. Mater. Sci. Eng. 1024, 012105 (2021)","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"4_CR38","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1177\/00081256231211020","volume":"66","author":"V Kolbj\u00f8rnsrud","year":"2024","unstructured":"Kolbj\u00f8rnsrud, V.: Designing the intelligent organization: six principles for human-AI collaboration. Calif. Manag. Rev. 66, 44\u201364 (2024)","journal-title":"Calif. Manag. Rev."},{"key":"4_CR39","doi-asserted-by":"crossref","unstructured":"Caldwell, S., et al.: An agile new research framework for hybrid human-AI teaming: trust, transparency, and transferability. ACM Trans. Interact. Intell. Syst. 12 (2022)","DOI":"10.1145\/3514257"},{"key":"4_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2021.104600","volume":"109","author":"K Ogunsina","year":"2022","unstructured":"Ogunsina, K., DeLaurentis, D.: Enabling integration and interaction for decentralized artificial intelligence in airline disruption management. Eng. Appl. Artif. Intell. 109, 104600 (2022)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"4_CR41","doi-asserted-by":"publisher","first-page":"7786","DOI":"10.1109\/JIOT.2022.3229746","volume":"10","author":"H Xu","year":"2022","unstructured":"Xu, H., Fan, Y., Li, W., Zhang, L.: Wireless distributed consensus for connected autonomous systems. IEEE Internet Things J. 10, 7786\u20137799 (2022)","journal-title":"IEEE Internet Things J."},{"key":"4_CR42","doi-asserted-by":"crossref","unstructured":"Hashemi, S.M., Botez, R.M., Ghazi, G.: Blockchain PoS and PoW consensus algorithms for airspace management application to the UAS-S4 Eh\u00e9catl. Algorithms 16 (2023)","DOI":"10.3390\/a16100472"},{"key":"4_CR43","doi-asserted-by":"crossref","unstructured":"Paul, S., Patterson, S., Varela, C.A.: Collaborative situational awareness for conflict-aware flight planning. In: 2020 AIAA\/IEEE 39th Digital Avionics Systems Conference (DASC) (2020)","DOI":"10.1109\/DASC50938.2020.9256620"},{"key":"4_CR44","doi-asserted-by":"crossref","unstructured":"Xu, Z., Li, Y., Feng, C., Zhang, L.: Exact fault-tolerant consensus with voting validity. In: 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2023)","DOI":"10.1109\/IPDPS54959.2023.00089"},{"key":"4_CR45","unstructured":"Hung, F., et al.: Intention-based behavioral anomaly detection (2019)"},{"key":"4_CR46","doi-asserted-by":"crossref","unstructured":"Oh, M.-h., Iyengar, G.: Sequential anomaly detection using inverse reinforcement learning. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, New York, NY, USA (2019)","DOI":"10.1145\/3292500.3330932"},{"key":"4_CR47","doi-asserted-by":"publisher","unstructured":"Suck, S., Fortmann, F.: Aircraft pilot intention recognition for advanced cockpit assistance systems. In: Schmorrow, D., Fidopiastis, C. (eds.) AC 2016, Part II. LNCS, vol. 9744, pp. 231\u2013240. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-39952-2_23","DOI":"10.1007\/978-3-319-39952-2_23"},{"key":"4_CR48","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1518\/001872095779049543","volume":"37","author":"MR Endsley","year":"1995","unstructured":"Endsley, M.R.: Toward a theory of situation awareness in dynamic systems. Hum. Factors J. Hum. Factors Ergon. Soc. 37, 32\u201364 (1995)","journal-title":"Hum. Factors J. Hum. Factors Ergon. Soc."},{"key":"4_CR49","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1518\/001872095779064555","volume":"37","author":"MR Endsley","year":"1995","unstructured":"Endsley, M.R., Kiris, E.O.: The out-of-the-loop performance problem and level of control in automation. Hum. Factors J. Hum. Factors Ergon. Soc. 37, 381\u2013394 (1995)","journal-title":"Hum. Factors J. Hum. Factors Ergon. Soc."},{"key":"4_CR50","doi-asserted-by":"publisher","unstructured":"Rose, A.M.: Acquisition and retention of skills. In: McMillan, G.R., Beevis, D., Salas, E., Strub, M.H., Sutton, R., Van Breda, L. (eds.) Applications of Human Performance Models to System Design, pp. 419\u2013426. Springer, Boston (1989). https:\/\/doi.org\/10.1007\/978-1-4757-9244-7_30","DOI":"10.1007\/978-1-4757-9244-7_30"},{"key":"4_CR51","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1080\/1463922021000054335","volume":"5","author":"DB Kaber","year":"2004","unstructured":"Kaber, D.B., Endsley, M.R.: The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task. Theor. Issues Ergon. Sci. 5, 113\u2013153 (2004)","journal-title":"Theor. Issues Ergon. Sci."},{"key":"4_CR52","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1177\/001872089303500203","volume":"35","author":"A Kirlik","year":"1993","unstructured":"Kirlik, A.: Modeling strategic behavior in human-automation interaction: why an \u201caid\u201d can (and should) go unused. Hum. Factors J. Hum. Factors Ergon. Soc. 35, 221\u2013242 (1993)","journal-title":"Hum. Factors J. Hum. Factors Ergon. Soc."},{"key":"4_CR53","doi-asserted-by":"crossref","unstructured":"Chen, J.Y.C., Barnes, M.J., Harper-Sciarini, M.: Su-pervisory control of multiple robots: human-performance issues and user-interface design. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 41, 435\u2013454 (2011)","DOI":"10.1109\/TSMCC.2010.2056682"},{"key":"4_CR54","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1518\/155534308X284417","volume":"2","author":"R Parasuraman","year":"2008","unstructured":"Parasuraman, R., Sheridan, T.B., Wickens, C.D.: Situation awareness, mental workload, and trust in automation: viable, empirically supported cognitive engineering constructs. J. Cogn. Eng. Decis. Mak. 2, 140\u2013160 (2008)","journal-title":"J. Cogn. Eng. Decis. Mak."},{"key":"4_CR55","doi-asserted-by":"crossref","unstructured":"Woods, D.D., Cook, R.I.: Incidents \u2013 markers of resilience or brittleness? In: Hollnagel, E., Woods, D.D., Leveson, N. (eds.) Resilience Engineering, 1st edn., pp. 69\u201376. CRC Press (2017)","DOI":"10.1201\/9781315605685-10"},{"key":"4_CR56","unstructured":"Woods, D.D., Sarter, N.B., Sarter, I.N., Amalberti, R.: Learning from automation surprises and \u201cgoing sour\u201d accidents\u201d"},{"key":"4_CR57","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2022.107574","volume":"140","author":"MR Endsley","year":"2023","unstructured":"Endsley, M.R.: Supporting human-AI teams: transparency, explainability, and situation awareness. Comput. Hum. Behav. 140, 107574 (2023)","journal-title":"Comput. Hum. Behav."},{"key":"4_CR58","doi-asserted-by":"crossref","unstructured":"Alcorn, M.A., et al.: Strike (with) a pose: neural networks are easily fooled by strange poses of familiar objects. arXiv (2019)","DOI":"10.1109\/CVPR.2019.00498"},{"key":"4_CR59","unstructured":"Pearl, J., Mackenzie, D.: The Book of Why: The New Science of Cause and Effect, First Trade Paperback Edition ed. Basic Books, New York (2020)"},{"key":"4_CR60","doi-asserted-by":"publisher","first-page":"1521","DOI":"10.1007\/s11948-017-9975-2","volume":"24","author":"A Howard","year":"2018","unstructured":"Howard, A., Borenstein, J.: The ugly truth about ourselves and our robot creations: the problem of bias and social inequity. Sci. Eng. Ethics 24, 1521\u20131536 (2018)","journal-title":"Sci. Eng. Ethics"},{"key":"4_CR61","unstructured":"Littman, M.L., et al.: Gathering strength, gathering storms: the one hundred year study on artificial intelligence (AI100) 2021 study panel report. arXiv (2022)"},{"key":"4_CR62","doi-asserted-by":"crossref","unstructured":"Chen, J.Y., Procci, K., Boyce, M., Wright, J., Garcia, A., Barnes, M.: Situation Awareness-Based Agent Transparency: Fort (2014)","DOI":"10.21236\/ADA600351"},{"key":"4_CR63","doi-asserted-by":"publisher","first-page":"3017","DOI":"10.1016\/j.promfg.2015.07.846","volume":"3","author":"SL Brandt","year":"2015","unstructured":"Brandt, S.L., Lachter, J., Battiste, V., Johnson, W.: Pilot situation awareness and its implications for single pilot operations: analysis of a human-in-the-loop study. Procedia Manuf. 3, 3017\u20133024 (2015)","journal-title":"Procedia Manuf."},{"key":"4_CR64","unstructured":"Endsley, M.R., Farley, T.C., Jones, W.M., Midkiff, A.H., Hansman, R.J.: Situation awareness information requirements for commercial airline pilots"},{"key":"4_CR65","doi-asserted-by":"crossref","unstructured":"Endsley, M.R., Rodgers, M.D.: Situation awareness information requirements for en route air traffic control (406512004-001) (1994)","DOI":"10.1037\/e406512004-001"}],"container-title":["Lecture Notes in Computer Science","HCI International 2025 \u2013 Late Breaking Papers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-12392-3_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:45:18Z","timestamp":1767318318000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-12392-3_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032123916","9783032123923"],"references-count":65,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-12392-3_4","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gothenburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sweden","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2025.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}