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- Figalova, Nikol, et al.
(författare)
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An extension of the human-factors methodological toolbox for human-AV interaction design research : Deliverable 1.4 in the EC ITN project SHAPE-IT
- 2023
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Early state researchers (ESRs) of the SHAPE-IT project have committed to exploring innovative methods to ensure driving safety during interactions between human and Automated Vehicles (AVs). In this deliverable, insights of ESRs span a broad spectrum of methodologies, from experimental methods, including psychophysiological measures, Virtual Reality/Augmented Reality (VR/AR) applications, and transparency assessments, to human-AV interaction models, with vehicle-pedestrian model and vehicle-cyclist model, and lastly the long-term effects. New types of interactions between humans and AVs need to be evaluated during the systems’ development to ensure that requirements of safety, acceptance, and efficiency are met before they are introduced to the market. Since innovative concepts require great cost and effort for their realization, it is necessary to ascertain whether the expected effects will be achieved. Many of the systems’ ergonomic requirements can be considered using experimental methods based on theoretical knowledge. This proposal outlines different aspects for empirical investigations related to the interaction between human and AV. It is important to mention that different human roles need to be considered inside (passenger or driver) and outside/around (VRU) the AV. The research aspects range from cognitive processes (perception and decision), via motion behavior, to learning and behavioral adaptation. This requires that dedicated methods with clear, consistent definitions be refined or developed. One example is the usage of virtual reality to investigate the complex interaction processes between AVs and VRUs in a safe and controllable setting as an alternative to field trials. Also, different AV communication strategies can be implemented in VR quicker and with reduced effort compared to hardware setups or experimental cars. Further methods are physiological measurements, different types of driving simulation and long-term behavioral study approaches. In their combination the different methods represent a toolbox of methodological approaches to analyze and evaluate different aspects of automated driving realizations. This deliverable presents a collection of recommended experimental approaches that address complex questions using advanced measurement equipment and statistical approaches, and their successful application within the SHAPE-IT project.
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| 2. |
- Figalova, Nikol, et al.
(författare)
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Methodological Framework for Modelling and Empirical Approaches (Deliverable D1.1 in the H2020 MSCA ITN project SHAPE-IT)
- 2021
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The progress in technology development over the past decades, both with respect to software and hardware, offers the vision of automated vehicles as means of achieving zero fatalities in traffic. However, the promises of this new technology – an increase in road safety, traffic efficiency, and user comfort – can only be realized if this technology is smoothly introduced into the existing traffic system with all its complexities, constraints, and requirements. SHAPE- IT will contribute to this major undertaking by addressing research questions relevant for the development and introduction of automated vehicles in urban traffic scenarios. Previous research has pointed out several research areas that need more attention for a successful implementation and deployment of human-centred vehicle automation in urban environments. In SHAPE-IT, for example, a better understanding of human behaviour and the underlying psychological mechanisms will lead to improved models of human behaviour that can help to predict the effects of automated systems on human behaviour already during system development. Such models can also be integrated into the algorithms of automated vehicles, enabling them to better understand the human interaction partners’ behaviours. Further, the development of vehicle automation is much about technology (software and hardware), but the users will be humans and they will interact with humans both inside and outside of the vehicle. To be successful in the development of automated vehicles functionalities, research must be performed on a variety of aspects. Actually, a highly interdisciplinary team of researchers, bringing together expertise and background from various scientific fields related to traffic safety, human factors, human-machine interaction design and evaluation, automation, computational modelling, and artificial intelligence, is likely needed to consider the human-technology aspects of vehicle automation. Accordingly, SHAPE-IT has recruited fifteen PhD candidates (Early Stage Researchers – ESRs), that work together to facilitate this integration of automated vehicles into complex urban traffic by performing research to support the development of transparent, cooperative, accepted, trustworthy, and safe automated vehicles. With their (and their supervisors’) different scientific background, the candidates bring different theoretical concepts and methodological approaches to the project. This interdisciplinarity of the project team offers the unique possibility for each PhD candidate to address research questions from a broad perspective – including theories and methodological approaches of other interrelated disciplines. This is the main reason why SHAPE-IT has been funded by the European Commission’s Marie Skłodowska-Curie Innovative Training Network (ITN) program that is aimed to train early state researchers in multidisciplinary aspects of research including transferable skills. With the unique scope of SHAPE-IT, including the human-vehicle perspective, considering different road-users (inside and outside of the vehicle), addressing for example trust, transparency, and safety, and including a wide range of methodological approaches, the project members can substantially contribute to the development and deployment of safe and appreciated vehicle automation in the cities of the future. To achieve the goal of interdisciplinary research, it is necessary to provide the individual PhD candidate with a starting point, especially on the different and diverse methodological approaches of the different disciplines. The empirical, user-centred approach for the development and evaluation of innovative automated vehicle concepts is central to SHAPE- IT. This deliverable (D1.1 “Methodological Framework for Modelling and Empirical Approaches”) provides this starting point. That is, this document provides a broad overview of approaches and methodologies used and developed by the SHAPE-IT ESRs during their research. The SHAPE-IT PhD candidates, as well as other researchers and developers outside of SHAPE-IT, can use this document when searching for appropriate methodological approaches, or simply get a brief overview of research methodologies often employed in automated vehicle research. The first chapter of the deliverable shortly describes the major methodological approaches to collect data relevant for investigating road user behaviour. Each subchapter describes one approach, ranging from naturalistic driving studies to controlled experiments in driving simulators, with the goal to provide the unfamiliar reader with a broad overview of the approach, including its scope, the type of data collected, and its limitations. Each subchapter ends with recommendations for further reading – literature that provide much more detail and examples. The second chapter explains four different highly relevant tools for data collection, such as interviews, questionnaires, physiological measures, and as other current tools (the Wizard of Oz paradigm and Augmented and Virtual Reality). As in the first chapter this chapter provides the reader with information about advantages and disadvantages of the different tools and with proposed further readings. The third chapter deals with computational models of human/agent interaction and presents in four subchapters different modelling approaches, ranging from models based on psychological mechanisms, rule-based and artificial intelligence models to simulation models of traffic interaction. The fourth chapter is devoted to Requirements Engineering and the challenge of communicating knowledge (e.g., human factors) to developers of automated vehicles. When forming the SHAPE-IT proposal it was identified that there is a lack of communication of human factors knowledge about the highly technical development of automated vehicles. This is why it is highly important that the SHAPE-IT ESRs get training in requirement engineering. Regardless of the ESRs working in academia or industry after their studies it is important to learn how to communicate and disseminate the findings to engineers. The deliverable ends with the chapter “Method Champions”. Here the expertise and association of the different PhD candidates with the different topics are made explicit to facilitate and encourage networking between PhDs with special expertise and those seeking support, especially with regards to methodological questions.
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| 3. |
- Abe, K., et al.
(författare)
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J-PARC Neutrino Beamline Upgrade Technical Design Report
- 2019
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Rapport (refereegranskat)abstract
- In this document, technical details of the upgrade plan of the J-PARC neutrino beamline for the extension of the T2K experiment are described. T2K has proposed to accumulate data corresponding to 2×1022 protons-on-target in the next decade, aiming at an initial observation of CP violation with 3σ or higher significance in the case of maximal CP violation. Methods to increase the neutrino beam intensity, which are necessary to achieve the proposed data increase, are described.
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| 4. |
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| 5. |
- Merat, Natasha, et al.
(författare)
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An Overview of Interfaces for Automated Vehicles (inside/outside) (Deliverable D2.1 in the H2020 MSCA ITN project SHAPE-IT)
- 2021
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This Deliverable starts with a short overview of the design principles and guidelines developed for current Human Machine Interfaces (HMIs), which are predominantly developed for manually driven vehicles, or those with a number of Advanced Driver Assistance Systems (ADAS), at SAE Levels 0 and 1 (SAE, 2018). It then provides an overview of how the addition of more capable systems, and the move to higher levels of vehicle automation, is changing the role the human inside an Automated Vehicle (AV), and the ways in which future automated vehicles at higher levels of automation (SAE level 4 and 5) must communicate with other road users, in the absence of an “in charge” human driver. It is argued that such changes in the role of the driver, and more transfer of control to the AV and its different functionalities, means that there will be more emphasis on the roles and responsibilities of HMIs for future AVs. In parallel, the multifaceted nature of these HMI, presented from different locations, both in and outside the vehicles, using a variety of modalities, and engaging drivers in a two-way interaction, means that a new set of design guidelines are required, to ensure that the humans interacting with AVs (inside and outside the vehicle) are not distracted and overloaded, that they remain situation aware and understand the capabilities and limitations of the system, having the right mental model of system capabilities and their responsibilities, as responsible road users, at all times Following a summary of suggested frameworks and design principles which highlight the significant change needed for new AV HMIs, an overview of results from studies investigating human interaction with internal (or iHMIs), and external (or eHMIs), is provided, with examples of new and innovative methods of communication between humans and their vehicles. The Deliverable then provides a summary of the innovative approaches that will be tackled by the ESRs of the project, which focus on factors such as use of AI and AR for future design of more intuitive and transparent HMI, studying how HMI can support the long term interaction of humans with AVs, and the use of neuroergonomic methods for developing safer HMIs. The Deliverable concludes by summarising how each ESR’s project contributes to the development of HMIs for future AVs.
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| 6. |
- Merat, Natasha, et al.
(författare)
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Design guidelines for acceptable, transparent, and safe AVs in urban environments : Deliverable 2.6 in the EC ITN project SHAPE-IT
- 2023
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This Deliverable summarises the work of ESRs 1, 5, 7 and 12 of the SHAPE-IT project that considered how a range of human states such as attention, fatigue and mental workload are affected by SAE Level 2 and 3 automated vehicles (AVs), when compared to manual driving, and what this means for AV and road safety. The studies also consider how AV safety and acceptance can increase with Human Machine Interface (HMI) transparency, and what factors contribute to the improvement of this transparency. An investigation of what aspects of an AV’s HMIs, its driving environment and driving style, contribute to the perceived safety, comfort and trust for its users is provided, and new methods and frameworks for enhancing these states are introduced. By considering how human factors concepts and knowledge should be embraced by software developers and AV engineers, ESRs 8 and 15 highlight the importance of a multidisciplinary approach to AV development. Finally, the work of ESR2 focuses on how AV trust, acceptance, and transparency changes with prolonged and repeated use of AVs, emphasising that successful deployment of AVs must embrace human factors knowledge during all stages of AV development. This work also highlights that as long as AVs require human interaction and intervention, including a diverse user group, and ensuring the appropriate level of trust is built at each stage of the interaction, will improve the correct and safe use of AVs.
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| 7. |
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| 8. |
- Svensson, Tommy, 1970, et al.
(författare)
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CELTIC CP5-026 WINNER+, D1.9 Final Innovation Report
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This deliverable is the final innovation report from the innovation workpackage in WINNER+. The document describes the latest innovations and their assessment as well as summarizes the innovations developed in the work package during the project. We analyze the suitability of these innovations as technology enablers for improving current systems, in particular IMT Advanced and beyond.
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