Exploratory MCDA for handling deep uncertainties: the case of intelligent speed adaptation implementation
Exploratory MCDA for handling deep uncertainties: the case of intelligent speed adaptation implementation
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处理深度不确定性的探索性 MCDA：智能速度自适应实施案例
DOI：
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发表时间：
2010
期刊：
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通讯作者：
D. B. Agusdinata
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文献类型：
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作者：
J. V. D. Pas;W. Walker;V. Marchau;G. P. V. Wee;D. B. Agusdinata
有时候，专家、决策者和分析师面临的政策问题涉及到很大的不确定性。当（1）对未来的了解不足以预测系统的未来变化时，（2）没有足够的知识来使用适当的模型来估计结果，和/或（3）没有足够的知识来了解利益相关者当前分配给各种标准或将来分配的权重。本文提出了一种MCDA方法，它被称为探索性多准则决策分析（EMCDA），以处理深度不确定性的条件。EMCDA基于探索性建模，这是一种建模方法，允许政策分析师探索关于未来世界的多种假设（使用不同的后果模型，不同的情景和不同的权重）。可以从这种方法中受益的政策问题的一个例子是改善交通安全的创新决策。为了提高交通安全性，人们对智能速度自适应（伊萨）寄予厚望，ISA是一种支持驾驶员保持适当速度的车载系统。然而，军事和民防资源部关于伊萨的不同研究在伊萨的实际安全效益估计数和利益攸关方（如汽车工业）提供伊萨的意愿方面得出了不同的结果。EMCDA的伊萨的实施的应用程序表明，它是可能的情况下进行MCDA的深度不确定性。考虑到完整的不确定性空间的全面分析表明，最佳政策是为年轻驾驶员（小于24岁）强制实施伊萨系统，限制他们驾驶速度超过限速。基于不同的假设，分析还表明，伊萨政策不应该针对老年驾驶员。版权所有© 2010约翰威利父子有限公司.
Sometimes experts, decisionmakers, and analysts are confronted with policy problems that involve deep uncertainty. Such policy problems occur when (1) the future is not known well enough to predict future changes to the system, (2) there is not enough knowledge regarding the appropriate model to use to estimate the outcomes, and/or (3) there is not enough knowledge regarding the weights stakeholders currently assign to the various criteria or will assign in the future. This paper presents an MCDA approach developed to deal with conditions of deep uncertainty, which is called Exploratory Multi-Criteria Decision Analysis (EMCDA). EMCDA is based on exploratory modelling, which is a modelling approach that allows policy analysts to explore multiple hypotheses about the future world (using different consequence models, different scenarios, and different weights). An example of a policy problem that can benefit from this methodology is decision making on innovations for improving traffic safety. In order to improve traffic safety, much is expected from Intelligent Speed Adaptation (ISA), an in-vehicle system that supports the driver in keeping an appropriate speed. However, different MCDA studies on ISA give different results in terms of the estimates of real-world safety benefits of ISA and the willingness of stakeholders (e.g. the automotive industry) to supply ISA. The application of EMCDA to the implementation of ISA shows that it is possible to perform an MCDA in situations of deep uncertainty. A full analysis taking into account the complete uncertainty space shows that the best policy is to make mandatory an ISA system for young drivers (less than 24 years of age) that restricts them from driving faster than the speed limit. Based on different assumptions, the analysis also shows that ISA policies should not target older drivers. Copyright © 2010 John Wiley & Sons, Ltd.