scholarly journals Mode Awareness and Automated Driving—What Is It and How Can It Be Measured?

Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 277 ◽  
Author(s):  
Christina Kurpiers ◽  
Bianca Biebl ◽  
Julia Mejia Hernandez ◽  
Florian Raisch
Keyword(s):  
Gold Standard ◽  
Automated Driving ◽  
Active System ◽  
Operational Design ◽  
Automation Systems ◽  
Study Results ◽  
Level 3 ◽  
No Gold Standard ◽  
Level 2 ◽  
Initial Instruction

In SAE (Society of Automotive Engineers) Level 2, the driver has to monitor the traffic situation and system performance at all times, whereas the system assumes responsibility within a certain operational design domain in SAE Level 3. The different responsibility allocation in these automation modes requires the driver to always be aware of the currently active system and its limits to ensure a safe drive. For that reason, current research focuses on identifying factors that might promote mode awareness. There is, however, no gold standard for measuring mode awareness and different approaches are used to assess this highly complex construct. This circumstance complicates the comparability and validity of study results. We thus propose a measurement method that combines the knowledge and the behavior pillar of mode awareness. The latter is represented by the relational attention ratio in manual, Level 2 and Level 3 driving as well as the controllability of a system limit in Level 2. The knowledge aspect of mode awareness is operationalized by a questionnaire on the mental model for the automation systems after an initial instruction as well as an extensive enquiry following the driving sequence. Further assessments of system trust, engagement in non-driving related tasks and subjective mode awareness are proposed.

scholarly journals The Relationship of Rates and Causes of Stillbirth to Obstetric Facility Level

Doctor Ru ◽  
2020 ◽  
Vol 19 (8) ◽  
pp. 61-65
Author(s):  
M.Ya. Kamilova ◽  
◽  
P.A. Dzhonmakhmadova ◽  
F.R. Ishan-Khodzhaeva ◽  
◽  
...  
Keyword(s):  
Fetal Death ◽  
Labor And Delivery ◽  
Study Objective ◽  
Study Materials ◽  
Perinatal Audit ◽  
Study Results ◽  
Level 3 ◽  
Facility Level ◽  
Relationship Of ◽  
Level 2

Study Objective: To compare the rates and causes of stillbirth in level 2 and 3 obstetric institutions. Study Design: This was a retrospective group study. Materials and Methods: Statistical data and labor and delivery histories of women who experienced stillbirth and were admitted to obstetric facilities (two level 2 facilities and one level 3 facility) between January and June 2019 were reviewed. Retrospective analysis was done of their labor and delivery histories, and the cases of stillbirth were clinically analyzed, using the ReCoDe classification. Study Results: The frequency of stillbirth was higher in the level 3 hospital. Irrespective of the level of hospital, mortality in the antenatal period dominated (four out of six cases in the level 2 facilities and 104 out of 129 in the level 3 facility); it was more often due to congenital malformations in the level 2 facilities and to intrauterine growth restriction (IUGR) or placental insufficiency in the level 3 facility. In the level 3 hospital, the most common causes of intranatal fetal death included maternal (pre-eclampsia and extragenital diseases) and fetal (IUGR) disorders that developed before labor. The risk factors for stillbirth were inadequate quality of medical services and factors related to the woman or family, such as late registration for prenatal care, non-compliance with doctors’ recommendations, etc. Conclusion: The actual causes, as established in this study, of negligence leading to stillbirth demonstrate that there is potential for reducing perinatal mortality. Keywords: stillbirth, antenatal and intranatal fetal death, ReCoDe classification, causes of stillbirth, perinatal audit.

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.

Is Driving Automation Used as Intended? Real-World Use of Partially Automated Driving Systems and their Safety Consequences

2021 ◽  
pp. 036119812110271
Author(s):  
Hyungil Kim ◽  
Miao Song ◽  
Zachary Doerzaph
Keyword(s):  
Real World ◽  
Transportation Safety ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Secondary Tasks ◽  
Driving Experience ◽  
Novel Technology ◽  
Automation Systems ◽  
Depth Analysis ◽  
Level 2

Advanced driver assistance systems with SAE Level 2 automated capabilities have entered the vehicle marketplace. Such driving automation systems (DASs) have the potential to fundamentally change the driving experience through automated lateral and longitudinal vehicle control. However, drivers may not use DASs as intended because of their misunderstanding of the systems’ capabilities and limitations. Moreover, the real-world use and effects of this novel technology on transportation safety are largely unknown. To investigate driver interactions with driving automation, the study examined existing naturalistic driving data collected from 50 participants who drove personally owned vehicles with Level 2 DASs for 12 months. It was found that 47 out of 235 safety-critical events (SCEs) involved DAS use. An in-depth analysis of 47 SCEs revealed that people misused DASs in 57% of SCEs (e.g., engaged in secondary tasks, used the systems not on highways or with hands off the wheel). During 13% of SCEs, the systems neither reacted to the situation nor warned the driver. A post-study survey showed that the participants found DASs useful and usable. However, the greater the positive attitude toward DAS features, the more participants felt comfortable engaging in secondary tasks. This is a potential unintended side effect of Level 2 DASs given that they still rely on the human driver’s supervision. This study also captured some scenarios where DASs did not meet driver expectations in typical driving situations, such as approaching stopped vehicles and negotiating curves. The findings may inform the development of human-machine interfaces and training programs to reduce the unintended use of DASs and their safety consequences.

Peripheral Monitoring of Traffic in Conditionally Automated Driving

2018 ◽  
Vol 62 (1) ◽  
pp. 1828-1832 ◽  
Author(s):  
Jonas Radlmayr ◽  
Karin Brüch ◽  
Kathrin Schmidt ◽  
Christine Solbeck ◽  
Tristan Wehner
Keyword(s):  
Situation Awareness ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Active System ◽  
Subject Design ◽  
Level 3 ◽  
Driving Task

Conditionally automated vehicles (level 3) allow drivers to engage in visual, non-driving related tasks (NDRTs) while the automation is active. System limits require drivers to reengage in the dynamic driving task in take-over situations. If the NDRT is visually engaging, situation awareness (SA) necessary for a successful take-over can decrease. This study analyzed, if the SA of drivers increases while monitoring the surrounding traffic peripherally. A semi-transparent balloon game in the head-up display operationalized the engagement into a visual NDRT with the possibility of peripheral monitoring. In addition, participants without the possibility of monitoring due to simulated heavy fog (second group) were tested along with a third group that could monitor surroundings self-determined without a NDRT. The between-subject design included 57 participants. Results showed that self-determined monitoring leads to higher situation awareness compared to peripheral monitoring and no monitoring. This did not result in better take-over performances.

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.

scholarly journals Does Adaptive Mode Transition Contribute to Better Driver Intervention in Highly Automated Driving?

2019 ◽  
Vol 63 (1) ◽  
pp. 287-291
Author(s):  
Huiping Zhou ◽  
Makoto Itoh ◽  
Satoshi Kitazaki
Keyword(s):  
Driving Simulator ◽  
Mode Transition ◽  
Automated Driving ◽  
Automated Control ◽  
Human Driver ◽  
Level 3 ◽  
Level Transition ◽  
Verbal Messages ◽  
Level 2 ◽  
Highly Automated Driving

This paper presents an adaptive mode (level) transition in highly combined driving automation in which the mode of a system could adaptively shift to any level including SAE level 3 (conditional automation, CA) to level 2 (partial automation) based on the driving environment. We show the effects of the adaptive transition on the take over of car control by a human driver and driving behavior after intervention when the system issues a response to intervene. A driving simulator experiment is conducted to collect data during the transition from automated control to manual driving in three scenes: obstacle on a driving lane, blurred lane mark, and stopped car ahead. Results indicate that the interventions of drivers who experience the adaptive transition are delayed in comparison to those who experience only the fixed transition. The adaptive transition is conducive for drivers to stop the car for preventing a potential collision with a stopped car ahead. Owing to the adaptive transition, drivers perceive a critical hazard after taking over car control and provide a rapid response. In addition, during the adaptive transition, drivers prefer verbal messages to the simple “beeping” message.

scholarly journals Analyzing the Importance of Driver Behavior Criteria Related to Road Safety for Different Driving Cultures

2020 ◽  
Vol 17 (6) ◽  
pp. 1893 ◽  
Author(s):  
Danish Farooq ◽  
Sarbast Moslem ◽  
Rana Faisal Tufail ◽  
Omid Ghorbanzadeh ◽  
Szabolcs Duleba ◽  
...  
Keyword(s):  
Hierarchical Structure ◽  
Traffic Safety ◽  
Traffic Accidents ◽  
Driver Behavior ◽  
Analytic Hierarchy ◽  
Safety Issues ◽  
Study Results ◽  
Level 3 ◽  
Hierarchy Process ◽  
Level 2

Driver behavior has been considered as the most critical and uncertain criteria in the study of traffic safety issues. Driver behavior identification and categorization by using the Fuzzy Analytic Hierarchy Process (FAHP) can overcome the uncertainty of driver behavior by capturing the ambiguity of driver thinking style. The main goal of this paper is to examine the significant driver behavior criteria that influence traffic safety for different traffic cultures such as Hungary, Turkey, Pakistan and China. The study utilized the FAHP framework to compare and quantify the driver behavior criteria designed on a three-level hierarchical structure. The FAHP procedure computed the weight factors and ranked the significant driver behavior criteria based on pairwise comparisons (PCs) of driver’s responses on the Driver Behavior Questionnaire (DBQ). The study results observed “violations” as the most significant driver behavior criteria for level 1 by all nominated regions except Hungary. While for level 2, “aggressive violations” is observed as the most significant driver behavior criteria by all regions except Turkey. Moreover, for level 3, Hungary and Turkey drivers evaluated the “drive with alcohol use” as the most significant driver behavior criteria. While Pakistan and China drivers evaluated the “fail to yield pedestrian” as the most significant driver behavior criteria. Finally, Kendall’s agreement test was performed to measure the agreement degree between observed groups for each level in a hierarchical structure. The methodology applied can be easily transferable to other study areas and our results in this study can be helpful for the drivers of each region to focus on highlighted significant driver behavior criteria to reduce fatal and seriously injured traffic accidents.

scholarly journals Automated Driving: A Literature Review of the Take over Request in Conditional Automation

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2087
Author(s):  
Walter Morales-Alvarez ◽  
Oscar Sipele ◽  
Régis Léberon ◽  
Hadj Hamma Tadjine ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Transition Process ◽  
Future Research ◽  
Automated Driving ◽  
Driving Dynamic ◽  
Dynamic Task ◽  
Emergency Situations ◽  
Operational Design ◽  
Level 3 ◽  
Guidelines And Standards ◽  
Attention Level

In conditional automation (level 3), human drivers can hand over the Driving Dynamic Task (DDT) to the Automated Driving System (ADS) and only be ready to resume control in emergency situations, allowing them to be engaged in non-driving related tasks (NDRT) whilst the vehicle operates within its Operational Design Domain (ODD). Outside the ODD, a safe transition process from the ADS engaged mode to manual driving should be initiated by the system through the issue of an appropriate Take Over Request (TOR). In this case, the driver’s state plays a fundamental role, as a low attention level might increase driver reaction time to take over control of the vehicle. This paper summarizes and analyzes previously published works in the field of conditional automation and the TOR process. It introduces the topic in the appropriate context describing as well a variety of concerns that are associated with the TOR. It also provides theoretical foundations on implemented designs, and report on concrete examples that are targeted towards designers and the general public. Moreover, it compiles guidelines and standards related to automation in driving and highlights the research gaps that need to be addressed in future research, discussing also approaches and limitations and providing conclusions.

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