Assessment Concept for TrustVehicles

Clement, Philipp; Danzinger, Herbert; Quinz, Philipp; Hillbrand, Bernhard; Hartavi, Ahu Ece; Kasikci, Kübra Zehra

doi:10.1007/978-3-030-60861-3_6

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…The scenarios are scheduled automatically from the test automation service once the SSQT is completed. The ten scenarios are divided into the following 4 clusters (scenarios with similar use case [56]), which are also shown in Figure 4.…”

Section: Scenariosmentioning

confidence: 99%

“…Each scenario is conducted in high driving automation mode (SAE level 4-no need for driver intervention, but still possible) [1], see also Figure 1, while the participants were tasked with observing the vehicle behaviour and the environment and providing their subjective feedback. The scenario clusters are designed in the same environment [56]. Their AD parameters differ so that two driving modes are available: sporty or comfortable.…”

Section: Scenariosmentioning

confidence: 99%

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Enhancing Acceptance and Trust in Automated Driving trough Virtual Experience on a Driving Simulator

et al. 2022

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As vehicle driving evolves from human-controlled to autonomous, human–machine interaction ensures intuitive usage as well as the feedback from vehicle occupants to the machine for optimising controls. The feedback also improves understanding of the user satisfaction with the system behaviour, which is crucial for determining user trust and, hence, the acceptance of the new functionalities that aim to improve mobility solutions and increase road safety. Trust and acceptance are potentially the crucial parameters for determining the success of autonomous driving deployment in wider society. Hence, there is a need to define appropriate and measurable parameters to be able to quantify trust and acceptance in a physically safe environment using dependable methods. This study seeks to support technical developments and data gathering with psychology to determine the degree to which humans trust automated driving functionalities. The primary aim is to define if the usage of an advanced driving simulator can improve consumer trust and acceptance of driving automation through tailor-made studies. We also seek to measure significant differences in responses from different demographic groups. The study employs tailor-made driving scenarios to gather feedback on trust, usability and user workload of 55 participants monitoring the vehicle behaviour and environment during the automated drive. Participants’ subjective ratings are gathered before and after the simulator session. Results show a significant increase in trust ensuing the exposure to the driving automation functionalities. We quantify this increase resulting from the usage of the driving simulator. Those less experienced with driving automation show a higher increase in trust and, therefore, profit more from the exercise. This appears to be linked to the demanded participant workload, as we establish a link between workload and trust. The findings provide a noteworthy contribution to quantifying the method of evaluating and ensuring user acceptance of driving automation. It is only through the increase of trust and consequent improvement of user acceptance that the introduction of the driving automation into wider society will be a guaranteed success.

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Section: Scenariosmentioning

confidence: 99%

Section: Scenariosmentioning

confidence: 99%

Enhancing Acceptance and Trust in Automated Driving trough Virtual Experience on a Driving Simulator

et al. 2022

Self Cite

View full text Add to dashboard Cite

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Measuring trust in automated driving using a multi-level approach to human factors

Clement

Danzinger

Veledar

et al. 2021

2021 24th Euromicro Conference on Digital System Design (DSD)

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As the driving is shifting towards automation, the maximization of related benefits would profit from improved user acceptance of the new technology. Studies suggest a strong connection between acceptance and trust in technical solutions. We investigate the improvement of user trust to driving automation through demonstrations that carried on a sophisticated driving simulator. The study correlates subjective data with objective psycho-physiological measurements. The multi-factorial and multivariate analysis of variance investigates the influence of learning effects and pre-experience with ADAS on trust. Results show improvement in trust through user interaction with a human-machine interface of the demonstrated AD system, hence illustrating the relevance of human-centered development processes. The conclusion is supported by the observation of driver cardiac signals.

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Assessment Concept for TrustVehicles

Cited by 2 publications

References 8 publications

Enhancing Acceptance and Trust in Automated Driving trough Virtual Experience on a Driving Simulator

Enhancing Acceptance and Trust in Automated Driving trough Virtual Experience on a Driving Simulator

Measuring trust in automated driving using a multi-level approach to human factors

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