Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases
Autonomy is being increasingly used in domains like maritime, aviation, medical, and civil domains. Nevertheless, at the current autonomy level, human takeover in the human–autonomy interaction process (HAIP) is still critical for safety. Whether humans take over relies on situation awareness (SA) a...
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MDPI AG
2025-01-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/1/158 |
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| author | Shengkui Zeng Qidong You Jianbin Guo Haiyang Che |
| author_facet | Shengkui Zeng Qidong You Jianbin Guo Haiyang Che |
| author_sort | Shengkui Zeng |
| collection | DOAJ |
| description | Autonomy is being increasingly used in domains like maritime, aviation, medical, and civil domains. Nevertheless, at the current autonomy level, human takeover in the human–autonomy interaction process (HAIP) is still critical for safety. Whether humans take over relies on situation awareness (SA) about the correctness of autonomy decisions, which is distorted by human anchoring and omission bias. Specifically, (i) anchoring bias (tendency to confirm prior opinion) causes the imperception of key information and miscomprehending correctness of autonomy decisions; (ii) omission bias (inaction tendency) causes the overestimation of predicted loss caused by takeover. This paper proposes a novel HAIP safety assessment method considering effects of the above biases. First, an SA-based takeover decision model (SAB-TDM) is proposed. In SAB-TDM, SA perception and comprehension affected by anchoring bias are quantified with the Adaptive Control of Thought-Rational (ACT-R) theory and Anchoring Adjustment Model (AAM); behavioral utility prediction affected by omission bias is quantified with Prospect Theory. Second, guided by SAB-TDM, a dynamic Bayesian network is used to assess HAIP safety. A case study on autonomous ship collision avoidance verifies effectiveness of the method. Results show that the above biases mutually contribute to seriously threaten HAIP safety. |
| format | Article |
| id | doaj-art-f5656f57ca434773b9de27a432ac6993 |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-f5656f57ca434773b9de27a432ac69932025-01-24T13:37:04ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-01-0113115810.3390/jmse13010158Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission BiasesShengkui Zeng0Qidong You1Jianbin Guo2Haiyang Che3School of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaSchool of Reliability and Systems Engineering, Beihang University, Beijing 100191, ChinaAutonomy is being increasingly used in domains like maritime, aviation, medical, and civil domains. Nevertheless, at the current autonomy level, human takeover in the human–autonomy interaction process (HAIP) is still critical for safety. Whether humans take over relies on situation awareness (SA) about the correctness of autonomy decisions, which is distorted by human anchoring and omission bias. Specifically, (i) anchoring bias (tendency to confirm prior opinion) causes the imperception of key information and miscomprehending correctness of autonomy decisions; (ii) omission bias (inaction tendency) causes the overestimation of predicted loss caused by takeover. This paper proposes a novel HAIP safety assessment method considering effects of the above biases. First, an SA-based takeover decision model (SAB-TDM) is proposed. In SAB-TDM, SA perception and comprehension affected by anchoring bias are quantified with the Adaptive Control of Thought-Rational (ACT-R) theory and Anchoring Adjustment Model (AAM); behavioral utility prediction affected by omission bias is quantified with Prospect Theory. Second, guided by SAB-TDM, a dynamic Bayesian network is used to assess HAIP safety. A case study on autonomous ship collision avoidance verifies effectiveness of the method. Results show that the above biases mutually contribute to seriously threaten HAIP safety.https://www.mdpi.com/2077-1312/13/1/158human–autonomy interactionsafety assessmentsituation awarenesstakeover decisionanchoring biasomission bias |
| spellingShingle | Shengkui Zeng Qidong You Jianbin Guo Haiyang Che Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases Journal of Marine Science and Engineering human–autonomy interaction safety assessment situation awareness takeover decision anchoring bias omission bias |
| title | Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases |
| title_full | Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases |
| title_fullStr | Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases |
| title_full_unstemmed | Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases |
| title_short | Situation Awareness-Based Safety Assessment Method for Human–Autonomy Interaction Process Considering Anchoring and Omission Biases |
| title_sort | situation awareness based safety assessment method for human autonomy interaction process considering anchoring and omission biases |
| topic | human–autonomy interaction safety assessment situation awareness takeover decision anchoring bias omission bias |
| url | https://www.mdpi.com/2077-1312/13/1/158 |
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