Specific Feedback Matters - The Role of Specific Feedback in the Development of Trust in Automated Driving Systems

2019 ◽  
Author(s):  
Aaron Edelmann ◽  
Stefan Stumper ◽  
Tibor Petzoldt
Keyword(s):  
Automated Driving ◽  
Specific Feedback

scholarly journals PRECISION OF VISUAL LOCALIZATION USING DYNAMIC GROUND CONTROL POINTS

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 363-370
Author(s):  
P. Trusheim ◽  
C. Heipke
Keyword(s):  
Rapid Development ◽  
Sliding Window ◽  
Bundle Adjustment ◽  
Ground Control ◽  
Visual Localization ◽  
Control Points ◽  
Automated Driving ◽  
Sliding Windows ◽  
Ground Control Points

Abstract. Localization is one of the first steps in navigation. Especially due to the rapid development in automated driving, a precise and reliable localization becomes essential. In this paper, we report an investigation of the usage of dynamic ground control points (GCP) in visual localization in an automotive environment. Instead of having fixed positions, dynamic GCPs move together with the camera. As a measure of quality, we employ the precision of the bundle adjustment results. In our experiments, we simulate and investigate different realistic traffic scenarios. After investigating the role of tie points, we compare an approach using dynamic GCPs to an approach with static GCPs to answer the question how a comparable precision can be reached for visual localization. We show, that in our scenario, where two dynamic GCPs move together with a camera, similar results are indeed obtained to using a number of static GCPs distributed over the whole trajectory. In another experiment, we take a closer look at sliding window bundle adjustments. Sliding windows make it possible to work with an arbitrarily large number of images and to still obtain near real-time results. We investigate this approach in combination with dynamic GCPs and vary the no. of images per window.

“One Size Does Not Fit All”: Revisiting Team Feedback Theories From a Cultural Dimensions Perspective

2020 ◽  
Vol 45 (2) ◽  
pp. 252-309 ◽  
Author(s):  
Catherine Gabelica ◽  
Vitaliy Popov
Keyword(s):  
Individual Differences ◽  
Intercultural Communication ◽  
Cultural Dimensions ◽  
Critical Component ◽  
Culturally Informed ◽  
Individual Perception ◽  
Specific Feedback ◽  
Heterogeneous Teams ◽  
Feedback Responses

Feedback is a critical component of teamwork regulation. Research underscores the importance of feedback processes for its effectiveness in teams and further notes how individual differences can affect these processes. Nonetheless, few have theorized on the cultural dimensions associated with feedback to specify how these can attenuate such processes. We contend that research can be advanced by specifying how cultural dimensions may shape individual perception and processing of feedback and team processing of feedback in homogeneous and heterogeneous teams with respect to cultural dimensions. To address this foundational question, we review and integrate the literature on feedback in teams and culture in teams by (a) incorporating the role of culture in team feedback models, (b) discussing how cultural dimensions could influence the perception and processing of feedback, and (c) highlighting important directions for future inquiries at the intersection of feedback and cultural theories. We discuss the links between cultural dimensions derived from the field of intercultural communication and feedback behaviors and processes and provide propositions concerning culturally informed differences in specific feedback responses at individual and team levels.

scholarly journals Tell Them How They Did: Feedback on Operator Performance Helps Calibrate Perceived Ease of Use in Automated Driving

2019 ◽  
Vol 3 (2) ◽  
pp. 29 ◽  
Author(s):  
Yannick Forster ◽  
Sebastian Hergeth ◽  
Frederik Naujoks ◽  
Josef Krems ◽  
Andreas Keinath
Keyword(s):  
Driving Simulator ◽  
Ease Of Use ◽  
Use Case ◽  
Perceived Ease Of Use ◽  
Automated Driving ◽  
Human Machine Interfaces ◽  
Level 3 ◽  
Level 2 ◽  
Over Time

The development of automated driving will profit from an agreed-upon methodology to evaluate human–machine interfaces. The present study examines the role of feedback on interaction performance provided directly to participants when interacting with driving automation (i.e., perceived ease of use). In addition, the development of ratings itself over time and use case specificity were examined. In a driving simulator study, N = 55 participants completed several transitions between Society of Automotive Engineers (SAE) level 0, level 2, and level 3 automated driving. One half of the participants received feedback on their interaction performance immediately after each use case, while the other half did not. As expected, the results revealed that participants judged the interactions to become easier over time. However, a use case specificity was present, as transitions to L0 did not show effects over time. The role of feedback also depended on the respective use case. We observed more conservative evaluations when feedback was provided than when it was not. The present study supports the application of perceived ease of use as a diagnostic measure in interaction with automated driving. Evaluations of interfaces can benefit from supporting feedback to obtain more conservative results.

scholarly journals Communications and Driver Monitoring Aids for Fostering SAE Level-4 Road Vehicles Automation

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 228 ◽  
Author(s):  
Felipe Jiménez ◽  
José Naranjo ◽  
Sofía Sánchez ◽  
Francisco Serradilla ◽  
Elisa Pérez ◽  
...  
Keyword(s):  
Decision Making ◽  
Cooperative Systems ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Road Vehicles ◽  
Driver Monitoring ◽  
Level 3 ◽  
Assistance Systems ◽  
Level 2

Road vehicles include more and more assistance systems that perform tasks to facilitate driving and make it safer and more efficient. However, the automated vehicles currently on the market do not exceed SAE level 2 and only in some cases reach level 3. Nevertheless, the qualitative and technological leap needed to reach level 4 is significant and numerous uncertainties remain. In this sense, a greater knowledge of the environment is needed for better decision making and the role of the driver changes substantially. This paper proposes the combination of cooperative systems with automated driving to offer a wider range of information to the vehicle than on-board sensors currently provide. This includes the actual deployment of a cooperative corridor on a highway. It also takes into account that in some circumstances or scenarios, pre-set or detected by on-board sensors or previous communications, the vehicle must hand back control to the driver, who may have been performing other tasks completely unrelated to supervising the driving. It is thus necessary to assess the driver’s condition as regards retaking control and to provide assistance for a safe transition.

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