Dynamics of Trust in Automation and Interactive Decision Making during Driving Simulation Tasks

As technological advancements and lowered costs make self-driving cars available to more people, it becomes important to understand the dynamics of human-automation interactions for safety and efficacy. We used a dynamical approach to examine data from a previous study on simulated driving with an automated driving assistant. To maximize effect size in this preliminary study, we focused the current analysis on the two lowest and two highest-performing participants. Our visual comparisons were the utilization of the automated system and the impact of perturbations. Low-performing participants toggled and maintained reliance either on automation or themselves for longer periods of time. Decision making of high-performing participants was using the automation briefly and consistently throughout the driving task. Participants who displayed an early understanding of automation capabilities opted for tactical use. Further exploration of individual differences and automation usage styles will help to understand the optimal human-automation-team dynamic and increase safety and efficacy.

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Pedagogical Considerations in Teaching Implicit Bias

International Journal of Bias Identity and Diversities in Education ◽

10.4018/ijbide.2020010103 ◽

2020 ◽

Vol 5 (1) ◽

pp. 46-63

Author(s):

Lisa Bloom ◽

Candy J. Noltensmeyer ◽

Sur Ah Hahn ◽

Charmion B. Rush ◽

Pamela Heidlebaugh-Buskey ◽

...

Keyword(s):

Decision Making ◽

Undergraduate Students ◽

Implicit Bias ◽

Teaching And Research ◽

Self Perceptions ◽

Preliminary Study ◽

Everyday Realities ◽

The Impact ◽

Bias And Discrimination

This project is part of a larger study examining the impact of an interactive lesson on implicit bias designed to help undergraduate students understand how implicit bias affects everyday realities and develop strategies for countering the effects of implicit bias in both personal and professional decisions. This portion of the project focuses on students' experiences with discrimination and strategies to address bias. Results from this preliminary study are promising as students' self-perceptions are explored and may assist instructors with pedagogical decision making for teaching topics such as bias and discrimination. Limitations of the study and implications for future teaching and research are discussed.

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Joint Decision Making and Cooperative Driver-Vehicle Interaction during Critical Driving Situations

i-com ◽

10.1515/icom-2016-0033 ◽

2016 ◽

Vol 15 (3) ◽

Cited By ~ 5

Author(s):

Eugen Altendorf ◽

Gina Weßel ◽

Marcel Baltzer ◽

Yigiterkut Canpolat ◽

Frank Flemisch

Keyword(s):

Decision Making ◽

Complex Task ◽

Automated Driving ◽

Joint Decision ◽

Vehicle System ◽

Human Driver ◽

Automation Systems ◽

Driving Task ◽

Common Goals ◽

The Individual

AbstractIn automated driving, the human driver and an automation form a joint human-machine system. In this system, each partner has her own individual cognitive as well as perceptual processes, which enable them to perform the complex task of driving. On different layers of the driving task, both, drivers and automation systems, assess the situation and derive action decisions. Although the processes can be divided between human and machine, and are sometimes very elaborate, the outcome should be a joint one because it affects the entire driver-vehicle system. In this paper, the individual processes for decision-making are defined and a framework for joint decision-making is proposed. Joint decision-making relies on common goals and norms of the two subsystems, human and automation, and evolves with experience.

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Automated driving on public roads: Experiences in real traffic

it - Information Technology ◽

10.1515/itit-2015-0010 ◽

2015 ◽

Vol 57 (4) ◽

Cited By ~ 4

Author(s):

Oliver Pink ◽

Jan Becker ◽

Sören Kammel

Keyword(s):

System Design ◽

Use Cases ◽

Automated Driving ◽

Robust Implementation ◽

Technical Realization ◽

Driving Task ◽

High Level ◽

The Impact ◽

Highly Automated Driving ◽

Country Specific

AbstractAutomated driving on public roads is affected by many foreseeable and unforeseeable driving situations. Depending on the driving task, the environmental and road conditions, and the behavior of other drivers, different actions have to be taken. This paper provides a high-level overview of the development of highly automated driving systems and illustrates challenging situations and use cases. We outlined the impact of these use cases on system design, key technologies, and their technical realization for a highly automated driving system. Furthermore, the paper demonstrates how certain aspects of the system design as well as their implementation are country specific and how continuous testing is required for robust implementation of the functionalities.

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Quota Women Are Threatening to Men

Swiss Journal of Psychology ◽

10.1024/1421-0185/a000195 ◽

2017 ◽

Vol 76 (3) ◽

pp. 107-116 ◽

Cited By ~ 4

Author(s):

Klea Faniko ◽

Till Burckhardt ◽

Oriane Sarrasin ◽

Fabio Lorenzi-Cioldi ◽

Siri Øyslebø Sørensen ◽

...

Keyword(s):

Decision Making ◽

Organizational Performance ◽

Gender Stereotypes ◽

Perceived Threat ◽

Preferential Treatment ◽

Public Sector Employees ◽

Different Types ◽

Low Levels ◽

Women In Decision Making ◽

The Impact

Abstract. Two studies carried out among Albanian public-sector employees examined the impact of different types of affirmative action policies (AAPs) on (counter)stereotypical perceptions of women in decision-making positions. Study 1 (N = 178) revealed that participants – especially women – perceived women in decision-making positions as more masculine (i.e., agentic) than feminine (i.e., communal). Study 2 (N = 239) showed that different types of AA had different effects on the attribution of gender stereotypes to AAP beneficiaries: Women benefiting from a quota policy were perceived as being more communal than agentic, while those benefiting from weak preferential treatment were perceived as being more agentic than communal. Furthermore, we examined how the belief that AAPs threaten men’s access to decision-making positions influenced the attribution of these traits to AAP beneficiaries. The results showed that men who reported high levels of perceived threat, as compared to men who reported low levels of perceived threat, attributed more communal than agentic traits to the beneficiaries of quotas. These findings suggest that AAPs may have created a backlash against its beneficiaries by emphasizing gender-stereotypical or counterstereotypical traits. Thus, the framing of AAPs, for instance, as a matter of enhancing organizational performance, in the process of policy making and implementation, may be a crucial tool to countering potential backlash.

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