A value of prediction model to estimate optimal response time to threats for accident prevention

Tiantian Zhu, Stein Haugen, Yiliu Liu and Xue Yang

Reliability Engineering and System Safety, 2023, vol. 232, issue C

Abstract: This paper presents a novel value of (imperfect) prediction (VoP) model to estimate optimal response time to a threat that may result in an accident. The proposed VoP model is based on information value theory and considers both prediction accuracy and action failure probability over time. The optimal response time is dependent on parameters: the ratio between the accident cost and response action cost, accident probability, action failure probability, prediction performance, and response strategy (a series of sequential responses or a single response). A case study of iceberg management is presented to demonstrate the proposed approach; a sensitivity study is done to evaluate how optimal response time changes with those parameters. The case study show that it is reasonable to respond as early as possible if the threat can lead to a serious accident, while the response can be postponed when the potential consequence is moderate. In addition, the proposed VoP model is proven able to calculate accuracy requirements, thresholds for tolerating risk and acting precautionarily, and maximum investment in accident prevention. Imperfect prediction can lower risk acceptance threshold and higher the threshold of being precautionary; and it is reasonable to increase action cost.

Keywords: Response time; Decision time; Accident prediction; Prediction horizon; Value of prediction; Value of information; Accident prevention (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:232:y:2023:i:c:s0951832022006597

DOI: 10.1016/j.ress.2022.109044

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