Travel Choice Analysis under Metro Emergency Context: Utility? Regret? Or Both?

With the continuous expansion of the network scale and increasing of passengers, metro emergencies such as operational equipment failure are happening more frequently. Due to the narrow space and crowds of people, metro emergencies always have more of an impact than road traffic emergencies. In order to adopt appropriate measures to ensure passenger safety and avoid risks, we need to get a better understanding of passengers’ travel choice behaviors under emergencies. Most of the existing research studies related to travel choice behaviors took the random utility maximization (RUM) principle for granted, but failed to realize the potential of different decision-making processes and changes to the decision-making environment. In this research, we aim to analyze metro passengers’ travel choice behaviors under metro network emergency contexts. Based on the data collected from a survey about travel choices under metro emergencies in the Guangzhou Metro, we compared the performances of models that follow the RUM and random regret minimization (RRM) principles, and established a hybrid RUM-RRM model as well as a nested logit model following RRM (NL-RRM) to estimate the effects of various factors on passengers’ travel choice behaviors. Comparisons illustrate that the hybrid model and NL-RRM model can improve model fit, and the combination of RUM and RRM outperforms either of them respectively.

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Computer Says I Don’t Know: An Empirical Approach to Capture Moral Uncertainty in Artificial Intelligence

Minds and Machines ◽

10.1007/s11023-021-09556-9 ◽

2021 ◽

Author(s):

Andreia Martinho ◽

Maarten Kroesen ◽

Caspar Chorus

Keyword(s):

Decision Making ◽

Latent Class ◽

Choice Model ◽

Choice Data ◽

Moral Uncertainty ◽

Choice Analysis ◽

Uncertain Model ◽

Decision Making Processes ◽

Core Idea ◽

Number Of Classes

AbstractAs AI Systems become increasingly autonomous, they are expected to engage in decision-making processes that have moral implications. In this research we integrate theoretical and empirical lines of thought to address the matters of moral reasoning and moral uncertainty in AI Systems. We reconceptualize the metanormative framework for decision-making under moral uncertainty and we operationalize it through a latent class choice model. The core idea being that moral heterogeneity in society can be codified in terms of a small number of classes with distinct moral preferences and that this codification can be used to express moral uncertainty of an AI. Choice analysis allows for the identification of classes and their moral preferences based on observed choice data. Our reformulation of the metanormative framework is theory-rooted and practical in the sense that it avoids runtime issues in real time applications. To illustrate our approach we conceptualize a society in which AI Systems are in charge of making policy choices. While one of the systems uses a baseline morally certain model, the other uses a morally uncertain model. We highlight cases in which the AI Systems disagree about the policy to be chosen, thus illustrating the need to capture moral uncertainty in AI systems.

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Theorizing hit-and-run: A study of driver decision-making processes after a road traffic collision

Criminology & Criminal Justice ◽

10.1177/1748895817740173 ◽

2017 ◽

Vol 19 (1) ◽

pp. 45-61

Author(s):

Matt Hopkins ◽

Sally Chivers

Keyword(s):

Decision Making ◽

Rational Choice ◽

Road Traffic ◽

Analytical Framework ◽

Decision To Leave ◽

Rational Decision Making ◽

Choice Decision ◽

Road Traffic Collision ◽

Decision Making Processes ◽

Hit And Run

Explanations for driver decisions to hit-and-run have largely been based around a rational choice perspective that suggests drivers consider the expected costs of reporting a collision against the benefits of leaving the scene. Although such an explanation appears plausible, previous research has largely focused upon identifying contributory or contextual factors through analysis of quantitative datasets rather than engaging with drivers in order to understand how they make the decision to ‘run’. This article explores the application of the rational choice perspective to hit-and-run driving. First, it develops an analytical framework based upon the rational choice decision-making process put forward by Tay et al. in 2008. Second, through analysis of 52 interviews with offenders, it examines how drivers structure the decision to leave the scene. Third, a typology of drivers is developed that illustrates that hit-and-run is not always based upon rational decision making. Finally, the article concludes with some implications for further research and the prevention of hit-and-run collisions.

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Cognitive Processing of Miscommunication in Interactive Listening: An Evaluation of Listener Indecision and Cognitive Effort

Journal of Speech Language and Hearing Research ◽

10.1044/2020_jslhr-20-00128 ◽

2021 ◽

pp. 1-17

Author(s):

Jennifer M. Roche ◽

Arkady Zgonnikov ◽

Laura M. Morett

Keyword(s):

Decision Making ◽

Cognitive Processing ◽

Language Processing ◽

Cognitive Effort ◽

Mouse Tracking ◽

Computer Mouse ◽

Decision Making Processes ◽

Computer Mouse Tracking ◽

Listening Task ◽

Processing Effort

Purpose The purpose of the current study was to evaluate the social and cognitive underpinnings of miscommunication during an interactive listening task. Method An eye and computer mouse–tracking visual-world paradigm was used to investigate how a listener's cognitive effort (local and global) and decision-making processes were affected by a speaker's use of ambiguity that led to a miscommunication. Results Experiments 1 and 2 found that an environmental cue that made a miscommunication more or less salient impacted listener language processing effort (eye-tracking). Experiment 2 also indicated that listeners may develop different processing heuristics dependent upon the speaker's use of ambiguity that led to a miscommunication, exerting a significant impact on cognition and decision making. We also found that perspective-taking effort and decision-making complexity metrics (computer mouse tracking) predict language processing effort, indicating that instances of miscommunication produced cognitive consequences of indecision, thinking, and cognitive pull. Conclusion Together, these results indicate that listeners behave both reciprocally and adaptively when miscommunications occur, but the way they respond is largely dependent upon the type of ambiguity and how often it is produced by the speaker.

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“It's Not Humanly Possible to Do Everything”: Perspectives on Intervention Decision-Making Processes of Parents of Children with Autism Spectrum Disorders

Perspectives on Language Learning and Education ◽

10.1044/lle22.1.13 ◽

2015 ◽

Vol 22 (1) ◽

pp. 13-21 ◽

Cited By ~ 5

Author(s):

Erinn Finke ◽

Kathryn Drager ◽

Elizabeth C. Serpentine

Keyword(s):

Decision Making ◽

Individualized Education Program ◽

Children With Autism ◽

Autism Spectrum ◽

Sources Of Information ◽

Individual Decision ◽

Decision Making Processes ◽

Spectrum Disorders ◽

Interview Methodology ◽

Communication Interventions

Purpose The purpose of this investigation was to understand the decision-making processes used by parents of children with autism spectrum disorder (ASD) related to communication-based interventions. Method Qualitative interview methodology was used. Data were gathered through interviews. Each parent had a child with ASD who was at least four-years-old; lived with their child with ASD; had a child with ASD without functional speech for communication; and used at least two different communication interventions. Results Parents considered several sources of information for learning about interventions and provided various reasons to initiate and discontinue a communication intervention. Parents also discussed challenges introduced once opinions of the school individualized education program (IEP) team had to be considered. Conclusions Parents of children with ASD primarily use individual decision-making processes to select interventions. This discrepancy speaks to the need for parents and professionals to share a common “language” about interventions and the decision-making process.

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