HCI International 2023 – Late Breaking Papers

This report seeks to understand the topic of occupational ergonomics through a comprehensive bibliometric analysis and systematic literature review. To conduct this analysis, three primary key terms were utilized across a variety of online databases where data was collected and analyzed through the lens of engagement, trend, cluster, and word cloud analyses. Using appropriate quantitative and qualitative research tools, inferences and conclusions are developed to better understand the industries in which occupational ergonomics plays a role, identify risks, and provide strategic recommendations in prevent future injury. From the analyses performed, findings include increasing understanding and engagement with workplace ergonomic related keywords, as seen in Figs. 5 and 6. Additionally, organizations and employees are becoming more aware of industry-standard terms including ergonomics, musculoskeletal disorder/disease, risk, and more as seen through an increased cluster frequency in Figs. 11 and 12. This project also highlights ongoing and future potentials for research in this area of study.

Ergonomics is a critical factor in the design of transportation vehicles, as it can significantly impact comfort, safety, and overall user experience. This study aims to conduct a systematic review of the current literature on the topic of ergonomics in transportation vehicles and to perform an in-depth RAMSIS analysis of the design optimization process. The study will explore the various factors driving the importance of ergonomics in transportation vehicles and the initiatives being undertaken to address this challenge. The review will also examine the role of human factors and ergonomics (HFE) and human-computer interaction (HCI) communities in developing user-centered design methodologies, advanced interfaces, and simulation tools for transportation systems. Furthermore, the study will analyze the use of RAMSIS software in evaluating the ergonomics of transportation vehicle designs and optimizing the design process for enhanced comfort and safety. The systematic review will be based on a comprehensive search of relevant databases and will include both qualitative and quantitative studies. The study findings will provide valuable insights into the current state of research on ergonomics in transportation vehicles and will highlight the importance of design optimization for enhancing comfort and safety.

Advancements in technology over the past few decades have led to rapid changes in manufacturing and process industries. This industry-wide shift towards automation and digitization is better known as Industry 4.0, or the fourth industrial revolution. As new Industry 4.0 technologies are adopted and “smart factories” become commonplace, the impact on the health and safety of manufacturing workers needs to be understood. The aim of this systematic review is to understand how Industry 4.0 technologies can be integrated without introducing new risks to worker health and safety through a literature review and database, content, and co-citation analyses. The literature analysis revealed publications analyzing connections between Industry 4.0 and worker health and safety, however, as an emerging field, relevant studies and publications are limited. More funding and research into the relationship between Industry 4.0 and worker OHS will be critical to the advancement, implementation, and acceptance of new technologies. Future research should likely concentrate on establishing concepts that incorporate human factors considerations into the design of integrated safety systems.

Human error is inevitable to some degree, though in many cases it can lead to a significant risk of human injury or illness. Because of this, designers and engineers need to be aware of many considerations to ensure that their products and processes are safe. To do this, they must consider human error throughout the lifecycle, including design, manufacturing, and product in use. Especially as technology advances and processes become more optimized, risk potential should be studied and analyzed before an incident can occur. Simulation and human modeling tools provide essential information to improve products and reduce risks. This paper discusses the importance of understanding and reducing human error through a systematic review of the topic and through exemplifying one of many tools, RAMSIS, that aids in analyzing such risk. Specifically, the tool is used to study user interaction with a vehicle, which can help designers identify potential areas of concern that could lead to unsafe driving conditions.

This literature review examines the emerging field of wearable technologies and their impact on various industries, including healthcare, fitness, and ergonomics. Using advanced research techniques such as CiteSpace, VOS Viewer, and Scite.ai, we identified the most relevant and current information on wearable technologies. The review reveals that wearable technologies are becoming increasingly popular due to their potential to enhance human health and well-being. Wearable devices can monitor a range of health metrics such as heart rate, sleep quality, and physical activity, helping individuals to better understand and manage their health. Additionally, wearable technologies are being used in various industries to improve performance and productivity. Furthermore, the review highlights the importance of job design in the implementation of wearable technologies. The integration of wearable technologies in the workplace can enhance job performance and improve employee well-being, but it also requires careful consideration of job design to avoid potential negative impacts on job autonomy, privacy, and work-life balance. Overall, this literature review underscores the potential benefits of wearable technologies and the need for further research to fully realize their potential in improving human health and well-being and enhancing workplace productivity. The review also highlights the importance of considering job design when implementing wearable technologies in the workplace.

This study utilizes ergonomics principles and RAMSIS software to optimize the analysis of driver posture in the sweeper cabin and constructs 18 different Chinese human body models of varying genders and sizes. Firstly, parameters such as H30 and H-point X-axis travel (L95) are determined based on vehicle type, platform, and benchmark vehicle data. Seat back angle, ankle comfort angle, and seat slide rail inclination are also set. Subsequently, RAMSIS software is employed to create a 3D model for simulating driver posture, and the cabin layout is optimized based on human comfort evaluation results. Next, spatial and reachability analyses are conducted to ensure that components such as the steering wheel and operating handles are within reach. Finally, evaluators are organized to conduct subjective evaluations of the driving cabin to verify the effectiveness of the optimization scheme. Through simulation analysis and subjective evaluation, the final optimization scheme is determined to be “steering wheel position moved back by 30 mm and raised by 10 mm” and “seat slide rail moved forward by 25 mm.” This scheme improves the comfort of drivers with different heights and sitting heights during driving, thus meeting the driving requirements of the vast majority of people. This study provides valuable references for the ergonomics design of sweeper cabins and demonstrates the accuracy of RAMSIS simulation results.

Work-related health and safety hazards affect adults with mobility-limiting disabilities disproportionately more than non-disabled adults. Conditions that expose adults with disabilities to greater health and safety risk include employers failing to implement effective workplace ergonomic adaptations and hiring discrimination leading to unstable employment. A systematic review and bibliometric analysis were conducted to evaluate the sources of work-related hazards for workers with mobility-limiting disabilities, the impact of exposure to those hazards, hazard mitigations with design, and measures of mitigation effectiveness. Bibliometric methods implemented included textual concept analysis and scientific mapping of co-citation analysis, and key articles were selected for detailed review. Two key sources of hazards identified are (1) the work environment (workstation, work tools, and interaction with people and machines) and (2) hazards related to employment (transportation to work, safe clothing, and unemployment). Human factors engineering and Digital Human Modeling are two existing design approaches implemented to address these hazards. Design solutions include ergonomic workstations, prosthetics for performing tasks, and robotic devices. The primary measures of mitigation effectiveness are participation in the workplace and safety. Despite existing design solutions, there is still a need to mitigate work-related hazards for physically disabled people. There is a growing demand for innovation as employment rates continue to improve for adults with disabilities.

This study looks at the importance of ergonomics in transportation as well as the contributions of the human factors and ergonomics (HFE), human computer interface (HCI), and safety-related organizations to this critical area of focus. The study provides an outline of the problems with transportation ergonomics, such as the physical and mental tiredness caused by extended travel, subpar infrastructure, and distracted driving. It considers how these concerns impact the safety, efficiency, and sustainability of transportation systems as well as how industrial engineering, HFE, HCI, and safety groups are addressing these issues. The paper focuses on the contributions made by these communities in identifying ergonomic concerns, developing plans for risk reduction, and developing technology that enhances the effectiveness and safety of transportation. The findings show that even while significant progress has been made in addressing ergonomics-related transportation challenges, more research and development are still needed to ensure that transportation systems meet user needs and promote sustainability and safety. The research provides a helpful overview of the importance of ergonomics in transportation and the contributions made by many groups in addressing this significant area of concern, highlighting the necessity of developing transportation systems that prioritize passenger safety, comfort, and productivity. A review of many studies found that incorporating ergonomics into transportation design can significantly reduce accidents, fatigue, and musculoskeletal issues among commuters and transportation workers.

Musculoskeletal disorders (MSDs) represent a cross-cutting problem among healthcare workers; particular attention should be given to surgeons who are involved in mentally and physically demanding tasks. This work aimed to propose a multi-parametric ergonomic approach able to exploit different wearable devices to estimate cervical discomfort and the muscular fatigue sustained by an otolaryngology (ENT) surgeon during the execution of laryngeal surgeries. The proposed protocol includes the use of both inertial measurement units (IMUs) and surface electromyography (EMG) probes to monitor head movement and muscle activation during the surgical procedures. IMUs were placed on the forehead and at the C7 level, while EMG probes were positioned on relevant bilateral upper body muscles involved in the surgical tasks. Data analysis encompassed the extraction and examination of flexion/extension, bending, and axial rotation joint angles and EMG signals were scrutinized to assess muscle activation and fatigue. The proposed protocol was preliminary validated involving one expert surgeon, who realized 28 surgeries, employing either a conventional microscope or an advanced exoscope; the setup was well-tolerated, with only minor discomfort reported. The protocol effectively captured detailed information regarding head movement and muscle activation patterns throughout the surgeries, revealing notable features in surgical approaches. The ergonomic assessment protocol provides a solid foundation for future investigations and the development of tailored surgical training programs aimed at mitigating the risk of MSDs among surgeons.

Ergonomics in transportation is an essential area of research with the potential to enhance the safety and comfort of many individuals. By incorporating ergonomic principles into transportation systems, they can become safer, more comfortable, and more efficient. In this paper, a bibliometric analysis and systematic review are conducted to identify trends and areas of interest within the field. Leading authors and leading institutions are identified. Co-occurrence and co-citation analyses are performed. Word clouds are generated from relevant literature. Data was first exported from sources such as Scopus, Google Scholar, Web of Science, Dimensions, and Harzing’s Publish or Perish. The data was then analyzed with a variety of tools including VOSviewer, CiteSpace, BibExcel, Vicinitas, and MAXQDA. A brief procedure for conducting content analyses in each tool is provided. Potential future work is identified and discussed. Overall, the use of various bibliometric analysis tools is demonstrated for use in a systematic literature review and the importance of incorporating ergonomic principles into transportation systems is discussed.

RAMSIS is a highly realistic and time-efficient software tool that is designed to support manufacturers in improving customer satisfaction by finding design flaws and hence, improving the well-being of the customer. In this paper, the need for continuous redesigning of the passenger cabin in automobiles is discussed. A new design of a car is tested by seating a manikin inside and simulating its optimal posture for the given constraints of the car and manikin. The applied method is a digital simulation of the human interacting with the passenger cabin interior. The demonstration was performed on RAMSIS a CAD-based simulation tool. In this work, Furthermore, this study explores multiple discussion points such as the benefits and future applications of the software, results of the simulation, and how obstacles or limitations could be resolved. In this project, the following analyses are conducted: discomfort analysis, reach analysis, max-size backseat-passenger calculation, obstructive vision, and reflective vision. One main result is the incompleteness of the car design in terms of ergonomic design. Additionally, many of the conducted analyses showed significant ergonomic design faults for the current design. Lastly, future work extending the RAMSIS analysis is explored.

A flight simulator is a device that replicates the experience of flying an aircraft realistically, without actually leaving the ground. It consists of a cockpit with various systems and instruments that simulate the flight environment through the use of augmented reality. Augmented reality is a technology that overlays virtual elements onto the real world, enhancing the user's perception and interaction with their environment in real time. Flight simulators have been identified as valuable tools to provide safe and cost-effective ways to train pilots and simulate emergencies. This form of augmented reality can improve safety training by allowing the trainees, or pilots, to visualize and interact with potential hazards in a controlled environment, which can help them understand and retain safety procedures. By doing a bibliometric analysis, we conducted a deep dive into the uses of flight simulators and how it impacts flight training and engineering design.

Active mobility, such as biking, faces a common challenge in Swedish municipalities due to the lack of adequate lighting during the dark winter months. Insufficient lighting infrastructure hinders individuals from choosing bicycles, despite the presence of well-maintained bike paths and a willingness to cycle. To address this issue, a project has been undertaken in the Swedish municipality of Skara for an alternative lighting solution using drones. A series of tests have been conducted based on drone prototypes developed for the selected bike paths. Participants were invited to cycle in darkness illuminated by drone lighting and share their mobility preferences and perception. This paper summarizes the users’ perception of drone lighting as an alternative to fixed lighting on bike paths, with a special focus on the impact on travel habits and the perceived sense of security and comfort. Most participants were regular cyclists who cited bad weather, time, and darkness as significant factors that deterred them from using bicycles more frequently, reducing their sense of security. With drone lighting, the participants appreciated the illumination’s moonlight-like quality and its ability to enhance their sense of security by illuminating the surroundings. On the technology side, they gave feedback on reducing the drone’s sound and addressing lighting stability issues. In summary, the test results showcase the potential of drone lighting as a viable alternative to traditional fixed lighting infrastructure, offering improved traffic safety, sense of security, and comfort. The results show the feasibility and effectiveness of this innovative approach, supporting transformation towards active and sustainable mobility, particularly in regions facing lighting challenges.

To date the air transportation system has been developed with the incremental introduction of new technology and with highly experienced air transport pilots and air traffic controllers overseeing flight operations. Thus, we currently have one of the safest commercial aviation systems in the world. General Aviation (GA) in the United States, however, has not always followed the same cautious and monitored approach to implementation; consequently, the GA safety record does not meet the high standards of commercial aviation. Recently, a new system known as Urban Air Mobility (UAM), is attracting considerable interest and investment from industry and government agencies. UAM refers to a system of passenger and small-cargo air transportation vehicles within an urban area with the goal of reducing the number of times we need to use our cars, thus improving urban traffic by moving people and cargo from crowded single passenger vehicles on our roads to personal and on-demand air vehicles. These UAM vehicles will be small and based on electric, Vertical-Take-Off-and-Landing (eVTOL) systems. A significant component of UAM is offloading of flight-management responsibilities from human pilots to newly-developed autonomy. Currently, over 100 UAM vehicles are either in development or production. Most, if not all, have a goal of fully autonomous vehicle operations, but fully autonomous flying vehicles are not expected in the near future. Therefore, we are developing concepts for UAM vehicles that will be easy to fly and/or manage by operators with minimal pilot training. In this paper we will discuss our human-automation teaming approach to develop an easy-to-operate VTOL aircraft, and some of the fly-by-wire technology needed to stabilize the vehicle so that a simple ecological mental model of the flying task can be implemented. We will discuss the requirements for a stability augmentation system that must be developed to support our simple pilot input model, and also present design guidelines and requirements based on a pilot input and management model. Finally, our approach to vehicle development will involve considerable operator testing and evaluation: improving pilot model, inceptors, displays and also work on a plan for how a UAM vehicle can be integrated with terminal area air traffic control airspace with minimal impact on controller workload.

Bicycles as a transport mode, has many advantages to improve quality of urban life for carbon less cities, traffic congestion reduction and good for resident’s health. Despite these advantages, the number of new cyclists does not increase in cities with low cycling maturity. There is a large percent of residents interested but concerned about safety to cycling in urban streets. We developed an experiment with images simulating a cyclist’s route in an urban road intersection to evaluate the level of safety perception in different types of cycling infrastructure. Three variables were studied: traffic density, cycleway types and intersection designs. A set of images was shown to 300 individuals online who rated each image in a four-point scale related to their perception of safety. Safety perception was higher for: low traffic density, painted cyclist lane and separation of cyclists from traffic. The simple presence of colored markings increased the safety perception relatedly with no design in the intersection environment. The more complex studied intersection design increased even more the safety perception. Naturally, the interventions of cycle design that include specific measures for cyclists needs increase not only the level of their safety perceived, but the likelihood of using bicycles. The complex design (Dutch model safety intersection design) is a good approach to increase security awareness. In conclusion, there is a clear interaction between the visual design on roads and the cyclist, this interaction has a positive effect on the perception of safety and to improve cycling.

Artificial intelligence is growing fast, and it is becoming important due to advances that allow complex algorithms or software to be used in transportation. AI technologies are beneficial for all kinds of industries, including transportation. The development of AI in transportation engineering for autonomous vehicle (AV) control is a rapidly growing field. The introduction of AVs on the market, along with the development of related technologies, will have a potential impact not only on the automotive industry but also on urban transport systems, new mobility-related businesses will emerge, whereas existing ones will have to adapt to changes. However, there are also challenges associated with AI in transportation, including safety concerns, cybersecurity threats, and job displacement.Surely technology can be a useful tool in promoting safety, but its effectiveness may depend on factors such as interactivity, equipment complexity, and adaptation of social behavior. System safety is the application of technical and managerial skills to the systematic, forward-looking identification, and control of hazards throughout the life cycle of a system like an AI [24]. In this paper a systematic literature review of the Safety of Artificial Intelligence and Transportation was performed by searching the keywords on the SCOPUS, Web of Science, and Google Scholar through Harzing software, many papers related to AI and transportation were explored. Searches were refined and led to VOS viewer to analyze the connection between authors and what papers come under similar topics. Next was a thorough analysis of engagements, which was done through Twitter trend analysis which collaborates a further justification of research into this topic. Overall, the findings from the systematic analyses of the four articles selected from various databases, including Google Scholar, SpringerLink, and ResearchGate, two chapters from Rogers L. Brauer’s book Safety and Health for Engineers, Third Edition and David L. Goetsch Occupational Safety and Health for Technologists, Engineers, and Managers, 9th Edition with three more articles derived from the co-citation analysis led to interesting discoveries in integrating AI into transportation systems, with AI mitigating some risks while new ones come up which points to the importance of funding for future work into analyzing AI in systems, to increase sustainability, while mitigating AI's risks.

In all social studies and research, the involvement of users and citizens is fundamental in order to build products and carry out research that truly considers the user at the centre of construction and definition of the research process.But what are the different strategies used to keep users involved throughout the entire research? And what are the best engagement strategies for their involvement? Obviously, there is not a single answer to this question, but the engagement strategies depend on the characteristics of the users to be reached and the objectives to be achieved.In this article, a literature review on this topic will be presented and the main engagement strategies that are used for user engagement will be described and analysed. This investigation of the literature will constitute the basis of the research methodologies that will be followed within the SINFONICA project, a EU-funded project that foresees co-creation and co-design processes using effective engagement methodologies that foster the exchange of visions and knowledge involving citizens and relevant stakeholders.

This paper takes performs a review and reappraisal discussion on safety pertaining to battery electric vehicles. This is in response to the various pressures to advance the technology used to power battery electric vehicles to a safe state. A variety of bibliometric and co-citation tools are used to source references and relevant sources. Other tools are used to understand how the topic is trending and growing, and how it compares to other well-established and safety-related topics. These tools and their results are discussed. Graphs of leading authors and leading countries are presented, to show who is doing this work and where. The topic is tied back into the course, emphasizing the safety aspects, and getting a base level understanding of what the hazards created are. This leads to the future work section, where the National Science Foundation website is explored to see if there are grants being awarded to further this research.

Due to advances in artificial intelligence (AI), humans are increasingly facing algorithm-generated content in everyday applications. To avoid threads to the system’s transparency and trustworthiness, the approach of explainable AI (XAI) will play an important role when designing these systems tied to the needs and characteristics of their end-users. Our work investigates explanation strategies for AI-based adaptive in-vehicle systems from a human-centered point of view. We present two explanation concepts: one interactive and one text-based approach. The concepts were evaluated and compared in a real-world driving study with 36 participants. The aim is to assess whether interactive engagement with explanations fosters the system’s understandability and the user’s mental model. Our results did not show significant differences between the concepts. Both groups performed well when assessing their mental model after experiencing the explanation concept. However, we found significant decreases in the mental model when measuring it again after participants experienced the prototypical adaptations of the system during the test drive.

This paper explores the impact of COVID-19 on public transportation systems through a bibliometric analysis, systematic review, and reappraisal. A systematic review analyzes literature, identifies trends, and provides comprehensive insights. Metadata from Harzing’s Publish or Perish via Scopus is utilized, with analysis conducted using tools like MAXQDA’s Wordcloud, VOS Viewer for visualization, BibExcel, Citespace, and Mendeley for referencing. The study aims to comprehensively assess the existing literature, including publishing trends, research areas, and identifying knowledge gaps. It evaluates the quality of research and offers suggestions for future studies. The analysis reveals a significant increase in COVID-19 and transportation research since the pandemic’s start, particularly in 2020 and 2021. Key themes identified include the pandemic’s impact on public transportation, the effectiveness of health and safety measures, and the role of technology in mitigating the spread of the virus. The assessment also highlights research gaps, such as the need for studies on the long-term effects of the pandemic on transportation systems and its implications for social equity. This bibliometric study, systematic review, and reassessment provide valuable insights for current transportation research. The findings can guide future projects and assist policymakers in developing effective strategies to minimize the pandemic’s impact on transportation infrastructures.

Emotion is a significant factor that affects driving performance. To prevent accidents caused by drivers’ emotions, it is important to understand the effect of emotion on driving performance. Many studies have used subjective evaluation methods to evaluate the effects of emotions on driving performance. However, these methods require direct questioning of the subject, which can be difficult to evaluate during driving. Furthermore, it is still unclear how positive emotions affect driving performance, especially on lane-keeping performance. Therefore, this study aims to objectively examine the effect of positive emotions on driving performance using physiological indexes. In the experiment, participants were asked to drive both with and without induced positive emotions via music stimuli. We collected electroencephalograph (EEG) and heart rate variability (HRV) data and offset from the lane position during driving. We used EEG and HRV indexes to evaluate arousal and comfort levels and compared how different positive emotions affect lane-keeping performance. Sixteen students participated in the experiment. The results showed higher RMSSD, lower β/α, and smaller the standard deviation of lateral position (SDLP) in the music condition. These results suggest that music induces a more relaxed emotional state. Furthermore, positive emotions, such as relaxation, can lead to better driving performance. However, future studies should focus more on how to induce emotions and the difficulty of driving tasks.

Public attitudes and intentions are crucial for successful technological innovation, such as automated vehicles (AVs). To effectively advance the development and future evolution of AVs, it is crucial to comprehensively understand individuals’ perceptions of autonomous driving. However, traditional survey methods using structured questionnaires may limit respondents’ ability to express themselves freely. To address this limitation, we employ Natural Language Processing (NLP) techniques to analyze consumers’ opinions and attitudes towards AVs as shared on social media platforms. Through Python programming, we collected and analyzed consumer comments from leading Chinese social media platforms (Sina Weibo, TikTok) and automotive social media platforms (Autohome Inc.) between June 2020 and April 2023, totaling 120,486 comments. Leveraging advanced text mining techniques such as Dynamic topic models (DTM), sentiment analysis, and semantic network analysis based on Pointwise mutual information (PMI) algorithms, we investigate the evolution of public perception regarding AVs over the past three years. Our findings unveil a predominant negative sentiment towards AVs, with discernible shifts in sentiment coinciding with major AV-related social events. Furthermore, we explore the reasons behind users’ negative attitudes and identify potential factors contributing to the distrust of autonomous driving. These findings provide valuable guidance to public agencies, automobile manufacturers, and technology companies, enhancing their understanding of the adoption of AVs.

Automated vehicles relieve drivers’ physical and cognitive load from driving and enable them to freely perform non-driving related tasks (NDRTs), which is promising to free modern citizens from the cost of the daily car-driving commute. Today, what NDRTs drivers are willing to perform and the reasons why they are willing to perform remain unclear, hindering the design of in-vehicle services. To fill this gap, we interviewed 15 drivers with driving experience in L2 automated cars to explore their preferred NDRTs during commutes in various levels of automation and why these tasks were performed. We classified four typical groups of NDRTs that can be performed during a commute, and the results indicated that drivers’ preferred NDRTs change with the automation level of cars and the digital devices they use. We further revealed 11 reasons why drivers are willing to perform certain NDRTs, and these reasons were categorized into the drivers’ needs and habits, the NDRT features, and the driving conditions. The findings of this study extend the understanding of user behaviors when commuting in automated cars, which will guide the design of non-driving related services for autonomous driving.

Each individual has become a mobile smart sensor under the supporting conditions of Artificial Intelligence, Big Data, Internet of Everything, Location Based Services and other technologies, which provide technical support for the research on user activity and behavior at a fine scale. Meanwhile, traditional product design methods are no longer applicable to the Smart Product-Service System Design with autonomous vehicles as the medium. Changes have occurred from product design to service system design of smart products and their composition, from intuition-based design to data-driven design, from human-machine design to relational design between service participants and smart bodies and smart service systems, and from styling design to experience design. It is required to integrate design thinking and smart mobility so as to explore methods and tools for terminal smart design, network smart design and cloud smart design.

There is not yet sufficient knowledge on how people want to be driven in a highly automated vehicle. Many studies suggest that automated vehicles should drive like a human driver, e.g. moving to the right edge of the lane when meeting oncoming traffic. To generate naturally looking trajectory behaviour, more detailed studies on manual driving are necessary. The authors report on a driving simulator study investigating twelve different oncoming traffic scenarios. 46 subjects experienced scenarios with variations in type of vehicle (trucks, cars), quantity (one, two) and position (with/without lateral offset) – each on a lane 3.00 m or on 2.75 m wide respectively. Results show that subjects react to oncoming traffic by veering to the right edge of the lane. We also found that quantity, type, and position of oncoming vehicles influence manual driving behaviour. Trucks and vehicles with lateral offset to the road centre lead to greater reactions and hence to more lateral distance between the ego and the oncoming vehicle. From this study on manual driving, we recommend an adaptive autonomous driving style which adjusts its trajectory behaviour on type and position of oncoming vehicles. Thus, our results help to design an accepted and trusted trajectory behaviour for highly automated vehicles.

This paper investigates participants’ perceptions and preferences regarding different cooperative intervention features for automated driving with level 2 driving automation. The experiment conducted involved 40 participants. A Kano questionnaire and a semi-standardized interview were employed to collect participants’ feedback on features for interventions in different maneuvers (e.g., initiating a lane change) and parameter settings (e.g., changing target speed). The results revealed a positive influence of most features on user satisfaction. Certain features were rated as essential requirements, while others were perceived as exciting additions. The response distributions show a high variance, indicating the existence of multiple user groups with different needs. The interviews conducted subsequently to the experiment provide qualitative insights, emphasizing the significance of implementation and the varying relevance between different maneuver and parameter interventions regarding satisfaction. The findings contribute to the design of experience-oriented human-machine interfaces (HMIs) in automated driving, highlighting the importance of cooperative features. The results can be used to prioritize the integration of distinct features. Future research should consider larger and more diverse samples to further enhance generalizability.

User experience (UX) evaluation can improve product quality, which has been confirmed in many studies. In recent years, the Chinese government has continued to promote the digitalization, intelligence and standardization of automobiles and the high-quality development of the intelligent automobile industry. However, there is still space for progress in production standardization and quality standardization, and mechanisms have not yet been designed to comprehensively measure the UX of intelligent vehicles. Therefore, the purpose of this paper is to develop a comprehensive framework for the evaluation of UX in intelligent vehicle human-machine interface (HMI) from the perspective of literature research and industry research. The framework was determined after a review of related literatures to analysis and summary existing evaluation approaches and was analyzed and organized according to the following components: UX evaluation object, the type of evaluation performer, HMI UX metrics, the most frequently applied evaluation methods, and UX influence factors. Through this method, it is possible for developers to obtain the theoretical knowledge and practical experience required for the evaluation of UX of HMI of intelligent vehicles, to carry out the evaluation to ensure the consistency of product quality, and then promote the high-quality development of the intelligent vehicle industry.

To understand how crowdsourced data is being used to boost transportation safety and efficiency, this study uses bibliometric analysis and data mining tools to draw insights from the body of academic literature regarding prominent authors and sub-topics, while identifying key articles that provide foundational knowledge. Results are shown in the form of descriptive figures created in software tools useful for bibliometric analysis. Insights from these figures and articles found related to the topic present an opportunity for review and reappraisal of the use of crowdsourced data in transportation. A review of recent and well-established literature shows that crowdsourced data represents an emerging opportunity for designers and policymakers interested in improving the safety of transportation systems where technology can be leveraged to uncover data continuously being collected by everyday users through popular apps like Strava and Waze.

Based on the review of research methods in the design field, it can be found that the KJ method is heavily used in the information induction stage of user research, but the KJ method has the disadvantage of subjectivity in the clustering process. Quantitative research characteristics of the AHP method through weight calculation can effectively overcome the subjectivity of the KJ method, so the KJ method is combined with the AHP method to form a bottom-up exogenous innovation integration method. In this paper, the method is applied to the research on the topic of community new energy vehicle charging service designs in line with the current era, and outputs a set of service design for community new energy vehicle charging based on user needs research.

The topic of road safety modeling by applying artificial intelligence has been aroused in the research field. The purpose of this study was to explore artificial intelligence enhancing road safety using bibliometric analyses. The data sources were collected from three databases: Scopus, ProQuest, and Web of Science. Numerous analysis tools were applied to visualize the trends and get meaningful outcomes, such as MaxQDA, Vicinitas, Scopus, etc. The measures of analysis were shown in five individual analysis results which include content, co-citation, keyword, trend, and statistical analysis. Statistical analysis was performed by ANOVA to distinguish the significant predictors in publication yields with interpretation. The recent trend in artificial intelligence and road safety has increased in the field of research. All analysis and findings are shown in the analysis section. We briefly mention the future work area ideas in various aspects of the study.

Many in the academic community find claims made about the virtuous nature of smart cities dumbfounding. In that sense left not only bewildered by the claims which academics make about the virtues of smart cities, but the audacious nature of the expectations advocates of them as developments based on the future internet also harbour. In surveying the foundations of smart cities as developments based on the future internet, this paper shall address the bewilderment over the claims made about the virtues of smart cities by academics and audacious nature of the expectations the IEA, IRENA, UN, WB and WHO now also harbour of them as developments based on the future internet. In rendering both the virtues of smart cities and audacious nature of them as future internet-based developments, the paper shall reveal how cities can be smart in developing the future internet as a basis to meet the social challenge adapting to climate change poses. This shall go some way to close a gap that has opened in the past decade over the foundations of smart cities by reporting on the results of a case-study into the metrics of future internet-based developments. Those metrics that provide smart cities with a system of measurements which link the informatics of digital technologies to data management platforms and connect the infrastructures of future internet-based developments to the management of natural resources. To the management of natural resources as environments that in turn relate the energetic of climate change adaptation strategies to a metabolic which serves to green the intellectual capital of urban and regional innovation systems. Green the intellectual capital of urban and regional innovation systems and qualify whether in meeting the social challenge SDG7 poses this keeps 1.5 alive.

When architects design a space and want to provoke reactions of surprise, relaxation, sadness, or excitement in users, how they combine the architectural characteristics of form, materials or light will influence these emotional reactions. The possibility of combining architectural elements is so vast and complex that it requires constant study and testing by the architect to achieve the reaction, sensation, or emotion he is trying to produce. This article results from preambular research that aims to create a methodological working framework that allows the development of a continuous study of the systematic relationship between different architectural features and emotional responses. As a main result, the proposed framework allows for obtaining emotional reactions related to architectural spaces, obtained through biosensors or self-report surveys, which feed the inference engine developed through the Kansei method. It is expected that the compilation of future studies based on this framework can be consulted as a guide or as an inspiration to read the built/designed spaces and/or open new possibilities and perspectives of spaces and architectural forms in the relationship with the human being. In the end, a comic narrative synthesizes the content of this article visually, having Le Corbusier as the main character.

Owing to high efficiency and high performance controllability, permanent magnet synchronous motors (PMSM) are being considered for various robotic applications including the Articulated Robots. PMSM drive includes a position/speed sensor for self synchronous control. Sensorless operation refers to the possibility of removing the afore-mentioned position/speed sensor to increase the robustness of the system and improve the reliability against sensor failures. This requires speed/position estimation for closed loop control. Extended Kalman filter (EKF) is a viable option as an observer owing to its noise rejection characteristics, ease in tuning the observer and the recursive algebraic nature of the algorithm which translates to real time hardware implementability. This paper proposes sensorless PMSM drive for robotic applications, with the dual perspective of improving the control and estimation aspects of the drive. A modification to the speed controller of Proportional+Integral (PI controller) type is proposed, wherein the overshoot in speed is drastically reduced without the necessity of including the Differential control. Likewise, a Proportional+Differential (PD) type is proposed for position control, with a suggestion to reduce the peak overshoot in position response. An adaptive Kalman filter is proposed to improve the estimation of speed/position, to achieve a high performance closed loop controlled PMSM drive.

Artificial Intelligent (AI) and Internet of Things (IoT) will provide novel solutions in the area of public spaces design if the designers could understand how these technologies can be best utilized. This study aims to address the question, “How can practitioners be supported in applying AI and IoT technologies in the early design process of smart public spaces?” In order to answer the question, the author developed a framework includes three categories and 48 technologies that can be utilized in smart public spaces design. A focus group was run to evaluate the feasibility. The evaluation suggests that the framework can be used as design stimuli in the concept design phase. At the end, the paper discusses the usage and iteration direction for the framework.

Public facilities are necessary to our daily lives, but not everyone will have a positive experience using them in open spaces, particularly those with different abilities. Affordance theory has brought more attention to people with different disabilities. The interaction between persons with different disabilities and public facilities in open spaces is observed and analyzed as part of this paper's investigation of the connection between affordance and user behavior. This paper presents a user experience framework based on affordance that reveals the interaction between users and artifacts from the perspective of affordance and makes recommendations for inclusive public design to promote user experience in open spaces, drawing on the literature on affordance and user experience.

Low-carbon economy and zero-carbon cities are a systematic social transformation that is taking place worldwide. As we all know, the key to the generation and reduction of carbon is to change the production mode. In urban development, we should take the path of green development. For each of us, the carbon dioxide produced by eating, wearing and living will leave “footprints” on the earth. Although “low carbon” is no longer a new concept for many people, we still need to make more efforts from recognition to action. Internationally, Singapore first proposed the "Smart City 2015" plan in 2006, followed by IBM's new concept of “Smart Earth” in 2008, which set off a boom in the construction of global smart cities at that time. Japan, which followed closely, put forward the “I-Japan” smart city plan, and South Korea also put forward the “U-City” smart city outline. In this situation, the United States, the European Union and other countries also quickly put forward corresponding smart city construction concepts for pilot. Therefore, smart city construction has become a new round of global development direction, and its strategic and cutting-edge nature is self-evident. It can be said that whoever takes the lead in planning and building smart cities in the future can lead a new round of development.

As the textile industry in China is heavily polluted, this study explores the design of a smart sewing device for recycling used clothing based on multi-modal Interaction to create a fun way to collect used clothing, for users who have a need to recycle and a desire to transform used clothing. User needs for online and offline services are identified through the KANO model user needs analysis. With the analysis of the user’s channel characteristics and the operating tasks of the smart sewing device, the quantitative requirements of the user VACP channel resources for different operating interfaces of the smart sewing device are obtained, and specific design strategies are proposed to guide the completion of the design practice. Furthermore, product iterations and optimizations are carried out based on the feedback results to initially validate the effectiveness of multi-modal Interaction mechanisms in VACP theory for the design of smart sewing devices.

In recognition, high-quality green space can maintain the sustainable development of cities and promote health and well-being for the most significant possible people, regardless of age, ability, and circumstances. Improving the inclusiveness of urban parks can promote a positive user experience and social equity for different user groups, especially vulnerable people. Using green spaces in Guangzhou as a case study, this paper investigates human behavior in green spaces. It identifies barriers and opportunities for creating inclusive urban parks. A general integrated green space framework for inclusion and user experience is proposed. The result shows that the disparity in the quality of urban would lead to different experiences for users. The paper concludes by making some recommendations for researchers, urban planners, and policymakers to formulate specific planning and guidance for providing more inclusive green spaces and consider ways to improve the quality of green spaces that respond to the varying needs of different user groups.

This research focuses on developing a wearable device that aims to enhance problem-solving and communication abilities within the context of Industry 4.0. The wearable is being developed in the Continental Advanced Antenna, and it allows operators to notify material shortages on the manufacturing line and helps minimize workflow disturbance. The wearable gives a list of missing materials using context-aware computing, allowing operators to identify and prioritize the missing item quickly. We used the Quick and Dirty usability testing approach to ensure the device’s usability and efficacy, allowing quick feedback and iterative modifications throughout the development process. Experienced consultants of project participated initial tests on the device and found that it has the potential to improve efficiency and communication in an industrial setting. However, further testing involving end users is necessary to optimize the device for the unique demands of the production environment. This paper offers valuable insights into the lessons learned from the project and proposes potential future research directions.

Digital citizen science projects have become globally popular in the last decade, with mobile platforms and devices engaging people in observing environmental phenomena. Youth participation in citizen science has been regarded as an opportunity to learn about science within the context of education, and they can better understand scientific processes and methods and gain self-efficacy, motivation, and responsible behavior by refining inquiry-based learning with the research paradigm of citizen science known as “citizen inquiry.” This study investigates how user-centered design contributes to designing a digital citizen inquiry mobile application, Plastic Detectives, for young citizen inquirers to create an effective method of monitoring plastic, raising awareness about plastic pollution at the societal level. The Plastic Detectives mobile application was developed using the design life cycle model. One hundred twenty-eight participants, from elementary school to university students, contributed to the user-centered Plastic Detectives’ app development in three research periods. The life cycle model application ensures that consumers are involved in the design and that the process is appropriately planned and tested. Semi-structured interviews, focus groups, and investigative record data have been used to identify the efficacy of the development. According to the findings, young participants positively accepted the digital citizen inquiry technology. They were satisfactory regarding contextual data sharing, task monitoring, expeditious selection, recording-to-sharing experience flow, positive social tasks, and visual affordance. The findings reveal successful mechanisms for the design of effective and sustainable citizen inquiry communities, as well as methods for their maintenance.

Recent advancements in mobile robot research have resulted in the development of precise robot control tools, while information technology research has focused on the Internet of Things (IoT) in the context of the fourth industrial revolution. This study evaluates a user interface designed for remote control of the Crowbot BOLT robot. This robot utilizes the ESP32 board and is controlled through the M5Stack Core2 kit with a touch screen. The user interface offers two modes of operation: touch-based buttons for movement control and gyroscope control based on the M5Stack’s angular position. Communication between the robot and the user interface is established using the MQTT protocol through the ThingSpeak server, allowing control from any location with a line of sight and internet connectivity. Operation data is collected by recording control orders and measuring sending times, while user acceptance is evaluated using an IoT-based technology acceptance model. The results indicate the need for remote control response time improvement and reveal low scores in perceived usefulness and influence social. In conclusion, the study demonstrates the feasibility of remote control of a mobile robot using the MQTT protocol, providing valuable insights for similar applications and considering user recommendations for future enhancements and system expansion.

This paper proposes a novel obstacle detection system optimized for mobile platforms. The system uses a long-short step Recurrent Neural Network (RNN) for optical flow estimation in various speed scenarios, combined with a global direction filter that filters out background noise, resulting in more robust and accurate obstacle detection. The system is designed to maximize processing speed and resource efficiency on mobile platforms. Performance is demonstrated on own-collected YouTube videos, achieving a precision rate of 95.2%, recall rate of 94.3%, and a frame rate of 75 FPS, surpassing state-of-the-art optical flow techniques. The proposed method is also evaluated on a real robot platform, demonstrating robust performance in detecting and avoiding obstacles of varying sizes and speeds under different lighting and noise conditions. Overall, the proposed system offers a reliable and efficient solution for obstacle detection and avoidance on mobile platforms, with high confidence in obstacle detection and avoidance in various real-world scenarios.

In order to deal with increasingly frequent accidents caused during underpass flooding, it is required to develop traffic control equipment that can stop vehicle traffic in a quick and effective way. In this research, design requirements for underpass traffic control equipment were clarified through literature review, analysis of existing equipment, and user research focused on road management authorities in Japan and China. Preliminary results of this work led to widening the scope of required functionality beyond stopping traffic, in order to include assistive functions such as traffic redirecting and warning. Based on this finding, the design proposal is composed by two main elements: a fixed barricade and a set of mobile assistive devices. At the present state of design development, a qualitative validation was carried out by applying questionnaires and conducting interviews with road managers. From an overall perspective, the proposal was positively evaluated. Specifically, characteristics such as efficiency, usage space, cost and aesthetic appealing were highlighted, while theft, safety enhancing and visibility were identified as points for future improvement.