Cooperation and the Role of Autonomy in Automated Driving

2018 ◽  
pp. 1-27 ◽  
Author(s):  
Gina Wessel ◽  
Eugen Altendorf ◽  
Constanze Schreck ◽  
Yigiterkut Canpolat ◽  
Frank Flemisch
Keyword(s):  
Automated Driving

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.

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.

scholarly journals Transitions Between Highly Automated and Longitudinally Assisted Driving: The Role of the Initiator in the Fight for Authority

2020 ◽  
pp. 001872082094618 ◽  
Author(s):  
Davide Maggi ◽  
Richard Romano ◽  
Oliver Carsten
Keyword(s):  
Road Safety ◽  
Driving Simulator ◽  
Cruise Control ◽  
Automated Driving ◽  
Safety Issues ◽  
The Road ◽  
Operational Design ◽  
Level 3 ◽  
Driving Task

Objective A driving simulator study explored how drivers behaved depending on their initial role during transitions between highly automated driving (HAD) and longitudinally assisted driving (via adaptive cruise control). Background During HAD, drivers might issue a take-over request (TOR), initiating a transition of control that was not planned. Understanding how drivers behave in this situation and, ultimately, the implications on road safety is of paramount importance. Method Sixteen participants were recruited for this study and performed transitions of control between HAD and longitudinally assisted driving in a driving simulator. While comparing how drivers behaved depending on whether or not they were the initiators, different handover strategies were presented to analyze how drivers adapted to variations in the authority level they were granted at various stages of the transitions. Results Whenever they initiated the transition, drivers were more engaged with the driving task and less prone to follow the guidance of the proposed strategies. Moreover, initiating a transition and having the highest authority share during the handover made the drivers more engaged with the driving task and attentive toward the road. Conclusion Handover strategies that retained a larger authority share were more effective whenever the automation initiated the transition. Under driver-initiated transitions, reducing drivers’ authority was detrimental for both performance and comfort. Application As the operational design domain of automated vehicles (Society of Automotive Engineers [SAE] Level 3/4) expands, the drivers might very well fight boredom by taking over spontaneously, introducing safety issues so far not considered but nevertheless very important.

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