A decision-making rule for modeling travelers’ route choice behavior based on cumulative prospect theory

Xu, Hongli; Zhou, Jing; Xu, Wei

doi:10.1016/j.trc.2010.05.009

Cited by 177 publications

(75 citation statements)

References 23 publications

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“…Parameter values that are consistent with the experimental results are: α = β = 0.88, λ = 2.25, γ + = 0.61, γ − = 0.69. Abdellaoui [36] and Xu et al [37] also conducted experiments that studied these parameter values, and obtained similar results.…”

Section: Calculation Of Gain and Lossmentioning

confidence: 63%

Environmentally Friendly Supplier Selection Using Prospect Theory

et al. 2017

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This paper proposes an optimal selection method to address the real-world problem of environmentally friendly supplier selection, based on prospect theory. This study adopted the manufacturer's point of view, and considered the manufacturer's psychological and behavioral factors in the process of choosing suppliers. The first step was to build supplier-selection indexes for manufacturers. Then, the study assessed the attribute of manufacturer expectations as a reference point. Next, index gains and losses were evaluated against the expectation reference point, yielding a payoff matrix and loss matrix. Finally, the study used prospect theory to calculate the comprehensive prospect value of each supplier; comprehensive prospect values were sorted in descending order to help manufacturers make the best choice.

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Section: Calculation Of Gain and Lossmentioning

confidence: 63%

Environmentally Friendly Supplier Selection Using Prospect Theory

et al. 2017

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“…Some researchers 27,28 have conducted framework studies of this combined method in the commuter trip condition, but few real-world applications exist because of unsolved obstacles involved, such as setting a reference point for loss evaluation and a probabilistic cost description for the choice branches. Although exogenous reference point [29][30][31][32] and endogenous one 33 of CPT are proposed in route-choice model of commuter trip condition, they cannot directly be copied in evacuation. People have no prior knowledge to determine even the rough arrival time at the evacuation destination, which is different to the researches in commuter trip.…”

Section: Consistency Analysis Of Evacuees' Risk Attitude and Cptmentioning

confidence: 99%

Risk-based stochastic evacuation routing strategy under dynamic probabilistic route cost information

Huang

Zheng

Ren

2017

Advances in Mechanical Engineering

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Traffic information is rather helpful to travelers in the non-recurrent traffic incident such as emergency evacuation. Unfortunately, the most concerned information-intersection traffic signal-cannot be directly shown on the medium, for example, variable message sign, because of its large size and incomprehensible content. Thus, this article mines the signal data as well as queue length to generate a well-understood content named probabilistic route delay. In addition, this article combines both route delays and real-time travel time to obtain minimal dynamic route cost. These delays and costs are components of dynamic probabilistic route cost for information provision. Based on the conveyed dynamic probabilistic route cost information, a revised logit model is used to depict evacuees' stochastic route-choice behavior, wherein a risk-based prospect value instead of the expected value is found to be a better choice in the non-random fixed utility. This risk-based stochastic evacuation routing strategy can generate more actual flow if it is compared to single prospect-value-based risky strategy or expected-value-based stochastic strategy. A case study on the evacuation of Nanjing Olympic Center is used to apply the risk-based stochastic evacuation routing strategy. A major contribution lies in that the proposed dynamic probabilistic route cost information and the risk-based stochastic evacuation routing strategy are effectively integrated. This integration can be used to determine variable message sign information or optimize signal timings, which would serve for the most efficient evacuation.

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“…For example, Reference [5] modelled a taxi service system in urban areas, taking into account the taxi drivers' knowledge of the transportation network from their day-to-day experience. Reference [6] found that driver's travel experience as well as a renewal of all acquirable traffic information that can assist in confirming the reference points in road network have influence on the route choice of the next trip. Reference [7] presented an experiential approach to compute optimal paths, in which path-planning was supported by a flexible road network hierarchy using the experience of taxi drivers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…With respect to learning feature, some researchers mentioned above proved that taxi drivers have the characteristics of learning, which means that they will update their traffic information from their day-to-day experience and use the information in route choice of the next trip [5,6]. Besides taxi related studies there are also some researchers who modelled the learning process of other travel behaviours.…”

Section: Literature Reviewmentioning

confidence: 99%