Modeling heterogeneous risk-taking behavior in route choice
Modeling heterogeneous risk-taking behavior in route choice
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DOI：
10.1016/j.tra.2011.04.009
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发表时间：
2011
影响因子：
6.4
通讯作者：
Xing Wu;Y. Nie
中科院分区：
文献类型：
--
作者：
Xing Wu;Y. Nie
基于随机优势理论，提出了一种建模路径选择中异质风险行为的统一方法。在效用最大化的框架下，一阶、二阶和三阶随机优势（FSD、SSD、TSD）分别与不满足、风险厌恶和破产厌恶相联系.不同风险偏好的出行者可以选择的路径可以从相应的SD-容许路径中获得，SD-容许路径可以使用一般动态规划来生成。本文还分析了基于SD的方法与其他考虑风险行为的路径选择模型之间的关系。这些路径选择模型采用了多种可靠性指标，这往往使问题的最佳路径难以找到。我们表明，这些可靠性指标的最佳路径往往属于三个SD-容许路径集之一。这一发现不仅为这些路线选择模型提供了与SD理论相一致的冒险行为的解释，而且还通过SD-容许路径集提供了一种统一的计算可行的解决方案，这些路径集通常很小，可以在不必枚举所有路径的情况下生成。提出了一种通用的标签校正算法来生成FSD、SSD和TSD可接受路径，并进行了数值实验来测试该算法并验证分析结果。
This paper proposes a unified approach to modeling heterogonous risk-taking behavior in route choice based on the theory of stochastic dominance (SD). Specifically, the first-, second-, and third-order stochastic dominance (FSD, SSD, TSD) are respectively linked to insatiability, risk-aversion and ruin-aversion within the framework of utility maximization. The paths that may be selected by travelers of different risk-taking preferences can be obtained from the corresponding SD-admissible paths, which can be generated using general dynamic programming. This paper also analyzes the relationship between the SD-based approach and other route choice models that consider risk-taking behavior. These route choice models employ a variety of reliability indexes, which often make the problem of finding optimal paths intractable. We show that the optimal paths with respect to these reliability indexes often belong to one of the three SD-admissible path sets. This finding offers not only an interpretation of risk-taking behavior consistent with the SD theory for these route choice models, but also a unified and computationally viable solution approach through SD-admissible path sets, which are usually small and can be generated without having to enumerate all paths. A generic label-correcting algorithm is proposed to generate FSD-, SSD-, and TSD-admissible paths, and numerical experiments are conducted to test the algorithm and to verify the analytical results.