Addressing Driver Disengagement and Proper System Use: Human Factors Recommendations for Level 2 Driving Automation Design

2021 ◽  
pp. 155534342098312
Author(s):  
Alexandra S. Mueller ◽  
Ian J. Reagan ◽  
Jessica B. Cicchino
Keyword(s):  
Human Factors ◽  
Data Driven ◽  
Management Systems ◽  
Design Domain ◽  
Proper System ◽  
Operational Design ◽  
System Use ◽  
Level 2

Level 2 driving automation has the potential to reduce crashes; however, there are known risks when using these systems, particularly as they relate to drivers becoming disengaged from driving. This paper provides data-driven recommendations for Level 2 driving automation design using the best currently available methods to encourage driver engagement and communicate where and how a system can safely be used. Our recommendations pertaining to driver engagement concern driver management systems that monitor the driver for signs of disengagement and return the driver to the loop using a multimodal escalation process with attention reminders, countermeasures for sustained noncompliance to the attention reminders, and proactive methods for keeping drivers engaged with respect to driver-system interactions and system functionality considerations. We also provide guidance on how the operational design domain (ODD), driver responsibilities, and system limitations should be communicated and how these systems must be self-limited within the ODD. In addition, we discuss the benefits and limitations of training to emphasize the importance of making these systems intuitive to all users, regardless of training, to ensure proper use. These recommendations should be applied as a whole, because selectively adhering to only some may inadvertently exacerbate the dangers of driver disengagement.

scholarly journals Shipping Accidents Dataset: Data-Driven Directions for Assessing Accident’s Impact and Improving Safety Onboard

Data ◽  
2021 ◽  
Vol 6 (12) ◽  
pp. 129
Author(s):  
Panagiotis Panagiotidis ◽  
Kyriakos Giannakis ◽  
Nikolaos Angelopoulos ◽  
Angelos Liapis
Keyword(s):  
Human Factors ◽  
Human Error ◽  
Historical Data ◽  
Critical Factor ◽  
Data Driven ◽  
Management Systems ◽  
Weather Data ◽  
Incident Management ◽  
Unstructured Information ◽  
Safety Procedures

Recent tragic marine incidents indicate that more efficient safety procedures and emergency management systems are needed. During the 2014–2019 period, 320 accidents cost 496 lives, and 5424 accidents caused 6210 injuries. Ideally, we need historical data from real accident cases of ships to develop data-driven solutions. According to the literature, the most critical factor to the post-incident management phase is human error. However, no structured datasets record the crew’s actions during an incident and the human factors that contributed to its occurrence. To overcome the limitations mentioned above, we decided to utilise the unstructured information from accident reports conducted by governmental organisations to create a new, well-structured dataset of maritime accidents and provide intuitions for its usage. Our dataset contains all the information that the majority of the marine datasets include, such as the place, the date, and the conditions during the post-incident phase, e.g., weather data. Additionally, the proposed dataset contains attributes related to each incident’s environmental/financial impact, as well as a concise description of the post-incident events, highlighting the crew’s actions and the human factors that contributed to the incident. We utilise this dataset to predict the incident’s impact and provide data-driven directions regarding the improvement of the post-incident safety procedures for specific types of ships.

scholarly journals Analysis of ATO System Operation Scenarios Based on UPPAAL and the Operational Design Domain

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 503
Author(s):  
Zicong Meng ◽  
Tao Tang ◽  
Guodong Wei ◽  
Lei Yuan
Keyword(s):  
High Speed ◽  
Test Case ◽  
Design Domain ◽  
System Operation ◽  
High Speed Railway ◽  
Functional Specification ◽  
Operational Design ◽  
Train Operation ◽  
System Requirements ◽  
Automatic Train Operation

With the gradual maturity of the automatic train operation (ATO) system in subways, its application scope has also expanded to the high-speed railway field. Considering that the ATO system is still in the early stages of operation, it will take time to fully mature, and definite specifications of the requirements for system operation have not yet been formed. This paper presents the operational design domain (ODD) of the high-speed railway ATO system and proposes a scenario analysis method based on the operational design domain to obtain the input conditions of the system requirements. The article models and verifies the scenario of the linkage control of the door and platform door based on the UPPAAL tools and extracts the input and expected output of the system requirements of the vehicle ATO system. Combined with the input conditions of the system requirements, the system requirements of the vehicle ATO in this scenario are finally obtained, which provides a reference for future functional specification generation and test case generation.

scholarly journals Content Management Systems Performance and Compliance Assessment Based on a Data-Driven Search Engine Optimization Methodology

Information ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 259
Author(s):  
Ioannis Drivas ◽  
Dimitrios Kouis ◽  
Daphne Kyriaki-Manessi ◽  
Georgios Giannakopoulos
Keyword(s):  
Search Engine ◽  
Common Knowledge ◽  
Organizational Structures ◽  
Content Management ◽  
Data Driven ◽  
Management Systems ◽  
Search Engine Optimization ◽  
Optimization Methodology ◽  
Content Management Systems ◽  
The Web

While digitalization of cultural organizations is in full swing and growth, it is common knowledge that websites can be used as a beacon to expand the awareness and consideration of their services on the Web. Nevertheless, recent research results indicate the managerial difficulties in deploying strategies for expanding the discoverability, visibility, and accessibility of these websites. In this paper, a three-stage data-driven Search Engine Optimization schema is proposed to assess the performance of Libraries, Archives, and Museums websites (LAMs), thus helping administrators expand their discoverability, visibility, and accessibility within the Web realm. To do so, the authors examine the performance of 341 related websites from all over the world based on three different factors, Content Curation, Speed, and Security. In the first stage, a statistically reliable and consistent assessment schema for evaluating the SEO performance of LAMs websites through the integration of more than 30 variables is presented. Subsequently, the second stage involves a descriptive data summarization for initial performance estimations of the examined websites in each factor is taking place. In the third stage, predictive regression models are developed to understand and compare the SEO performance of three different Content Management Systems, namely the Drupal, WordPress, and custom approaches, that LAMs websites have adopted. The results of this study constitute a solid stepping-stone both for practitioners and researchers to adopt and improve such methods that focus on end-users and boost organizational structures and culture that relied on data-driven approaches for expanding the visibility of LAMs services.

Teaming with Technology at the TSA: Practical Methods for Enhancing Human Performance with Automation in Operational Environments

2018 ◽  
Vol 62 (1) ◽  
pp. 639-640
Author(s):  
Kristopher Korbelak ◽  
Jeffrey Dressel ◽  
David Band ◽  
Jennifer Blanchard
Keyword(s):  
Human Factors ◽  
Human Performance ◽  
Automated Systems ◽  
Operational Environment ◽  
Cognitive Constraints ◽  
Organizational Influence ◽  
Transportation Security Administration ◽  
System Use ◽  
Discussion Panel ◽  
System Characteristics

Automated systems are not only commonplace but often are a necessity to complete highly specialized tasks across many operational environments. The Transportation Security Administration (TSA) aims to enhance human performance and increase safety through the acquisition and implementation of various types of automated systems. The Human Performance Branch (HPB) at TSA supports this aim through research on human factors that influence interactions with automation. Knowledge gained from HPB efforts informs TSA of the automated systems that will best suit worker needs, how to integrate these systems into the general workflow, and the relevant human factors that will support proper system use and, ultimately, enhance human performance. This discussion panel reviews a theoretical framework the TSA can use to guide assessment of multiple drivers of human performance in a consistent and standardized fashion as well as several TSA projects investigating three categories of human factors known to influence performance with automation – human (i.e., individual differences, cognitive constraints), context (e.g., organizational influence, environment), and system characteristics (e.g., type of automation) – and how those factors can be accounted for in the operational environment.

Electronic Medication Management Systems: Analysis of Enhancements to Reduce Errors and Improve Workflow

2021 ◽  
Vol 12 (05) ◽  
pp. 1049-1060
Author(s):  
Madaline Kinlay ◽  
Lai Mun Rebecca Ho ◽  
Wu Yi Zheng ◽  
Rosemary Burke ◽  
Ilona Juraskova ◽  
...  
Keyword(s):  
Medication Errors ◽  
Systems Analysis ◽  
Continuous Monitoring ◽  
Medication Management ◽  
Electronic System ◽  
Management Systems ◽  
Safety Risks ◽  
System Use ◽  
Changes Over Time ◽  
Over Time

Abstract Background Electronic medication management (eMM) has been shown to reduce medication errors; however, new safety risks have also been introduced that are associated with system use. No research has specifically examined the changes made to eMM systems to mitigate these risks. Objectives To (1) identify system-related medication errors or workflow blocks that were the target of eMM system updates, including the types of medications involved, and (2) describe and classify the system enhancements made to target these risks. Methods In this retrospective qualitative study, documents detailing updates made from November 2014 to December 2019 to an eMM system were reviewed. Medication-related updates were classified according to “rationale for changes” and “changes made to the system.” Results One hundred and seventeen updates, totaling 147 individual changes, were made to the eMM system over the 4-year period. The most frequent reasons for changes being made to the eMM were to prevent medication errors (24% of reasons), optimize workflow (22%), and support “work as done” on paper (16%). The most frequent changes made to the eMM were options added to lists (14% of all changes), extra information made available on the screen (8%), and the wording or phrasing of text modified (8%). Approximately a third of the updates (37%) related to high-risk medications. The reasons for system changes appeared to vary over time, as eMM functionality and use expanded. Conclusion To our knowledge, this is the first study to systematically review and categorize system updates made to overcome new safety risks associated with eMM use. Optimization of eMM is an ongoing process, which changes over time as users become more familiar with the system and use is expanded to more sites. Continuous monitoring of the system is necessary to detect areas for improvement and capitalize on the benefits an electronic system can provide.

Towards a Specified Operational Design Domain for a Safe Remote Driving of Trains

2021 ◽  
Author(s):  
Abhimanyu Tonk ◽  
Abderraouf Boussif ◽  
Julie Beugin ◽  
Simon Collart-Dutilleul
Keyword(s):  
Design Domain ◽  
Operational Design ◽  
Remote Driving

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.

Post Macondo Safety and Regulatory Issues: Human Factors From an Organizational Development and Senior Management Perspective

2013 ◽  
Author(s):  
Philip Grossweiler ◽  
David Costello ◽  
Kevin Graham
Keyword(s):  
Risk Management ◽  
Human Factors ◽  
Organizational Development ◽  
Nuclear Power ◽  
Management Practices ◽  
Safety Management ◽  
National Research Council ◽  
Management Systems ◽  
Safety Management Systems ◽  
Cost Center

Regulations governing the safety of drilling and offshore production operations have changed since the Macondo spill. This paper suggests management level perspectives on the nexus of human factors and safety management systems including an overview of ideas from: Congressional Testimony; the Bipartisan Policy Center inputs to the Presidents Commission on the Spill; the National Academy of Engineering and National Research Council Deepwater Horizon Report, and workshops and initiatives by RPSEA (Research Partnership to Secure Energy for America), SPE, and ASME. The value of benchmarks from risk management practices from the aviation, nuclear power, and financial community are also discussed. The paper will also consider questions as to what management might consider reducing risk and treating risk management as not just a cost center, but as a way to integrate safety management systems into improving corporate performance for all stakeholders. Paper published with permission.

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