A digital-driving system for smart vehicles

In the wake of the computer and information technology revolutions, vehicles are undergoing dramatic changes in their capabilities and how they interact with drivers. Although some vehicles can decide to either generate warnings for the human driver or control the vehicle autonomously, they must usually make these decisions in real time with only incomplete information. So, human drivers must still maintain control over the vehicle. I sketch a digital driving behavior model. By simulating and analyzing driver behavior during different maneuvers such as lane changing, lane following, and traffic avoidance, researchers participating in the Beijing Institute of Technology's digital-driving project will be able to examine the possible correlations or causal relations between the smart vehicle, IVISs, the intelligent road-traffic-information network, and the driver. We aim to successfully demonstrate that a digital-driving system can provide a direction for developing human-centered smart vehicles.     

Drivers of mobile payment acceptance: The impact of network externalities

Mobile payment is an attractive option that has recently boomed because of the advent of smart phones and their applications. Despite the great potential of such technology in simplifying our lives, its uptake remains limited. As the technology acceptance fails to meet expectations, this study aims at providing a better understanding of the factors influencing mobile payment acceptance. Through an empirical investigation that couples the traditional technology acceptance factors with “network externalities” effect. This study hypothesized that performance expectancy, effort expectancy; social influence, trust, and network externality are major factors that influence the intention to use mobile payment. Results indicated that while the traditional acceptance drivers still impact customers’ willingness to adopt mobile payment, network externalities was the most influential driver of mobile payment acceptance. Results also failed to support the influence of effort expectancy. Conclusions and future work propositions are stated at the end.     

Human–Vehicle Cooperation in Automated Driving: A Multidisciplinary Review and Appraisal

ABSTRACT

To draw a comprehensive and cohesive understanding of human–vehicle cooperation in automated driving, a review is made on key studies in human–robot interaction and human factors. Throughout this article, insight is provided into how human drivers and vehicle systems interplay and influence each other. The limitations of technology-centered taxonomies of automation are discussed and the benefits of accounting for human agents are examined. The contributions of machine learning to automated driving and how critical models in human-system cooperation can inform the design of a more symbiotic relationship between driver and vehicle are investigated. Challenges in the human element to enable the safe introduction of road automation are also discussed. Particularly, the unintended consequences of vehicle automation on driver’s workload, situation awareness and trust are examined, and the social interactions between driver, vehicle, and other road users are investigated. This review will help professionals shape future directions for safer and more efficient and effective human–vehicle cooperation.     

Modeling vehicle–pedestrian interactions outside of crosswalks

Pedestrian and driver behaviors as well as their interactions, are essential in planning, designing and operating highway facilities. Pedestrian crossing outside of a marked or unmarked crosswalk (i.e. jaywalking), is one of those pedestrian behaviors that may highly affect safety and operations. Unlike permissible crossings at crosswalks, jaywalking events are not often anticipated by drivers, which may result in less driver reaction time and different vehicle operation dynamics. It is important to understand pedestrian crossing behavior outside of crosswalks, as well as driver yielding behavior towards them. To date, limited quantitative and behavioral research has been conducted to investigate this interaction or simulate it microscopically. This paper aims to explore both pedestrian jaywalking behavior (gap acceptance and speeds) and the corresponding driver reactions (yielding behavior) for modeling the vehicle–pedestrian interactions (VPI) outside the crosswalks in a micro-simulation environment. The study also quantifies the differences between vehicle–jaywalker and vehicle-permissible crossing. An observational study and an instrumented vehicle study were conducted on the campus of the University of Florida to collect data from pedestrian and driver perspectives, respectively.Crossing speed, yield acceptance and delay of jaywalking crossings and permissible crossings were observed in the study and these attributed can be used for replicating pedestrian operations in simulators. Moreover, behaviors of driver approaching jaywalkers versus pedestrians crossing at designated crosswalks were compared on the basis of yield rates, and vehicle speed profiles. Vehicle yield dynamics were analyzed to model the driver reactions towards jaywalkers. Lastly, it was found that the locations of jaywalking events are highly concentrated and influenced by the crossing environment, such as pedestrian and vehicular volume, bus stops presence and crossing distance.This paper establishes several quantitative relationships describing interactions between pedestrians crossing outside of crosswalks and approaching drivers, which provide the basis and assumptions for modeling such interactions in a micro-simulation environment for traffic operational analyses.     

The Effects of Vibration Patterns of Take-Over Request and Non-Driving Tasks on Taking-Over Control of Automated Vehicles

Automated vehicles offer the possibility of significantly increasing traffic safety, mobility, and driver comfort, and reducing congestion and fuel emissions. Current automation technology, however, remains imperfect, and in certain situations, automation will still require the driver to suspend non-driving tasks and take back control of the automated vehicle in a limited period of time. During automated driving, drivers engaged in non-driving tasks (e.g., reading, taking a nap) may not perceive the visual or auditory take-over request in a timely nor accurate manner. Therefore, it is necessary to explore the potential of tactile warning further. This study investigates the effects of vibration patterns of take-over requests (six vibration patterns with different orders of the vibration location) and various realistic non-driving tasks (six non-driving tasks: reading, typing, watching videos, playing games, taking a nap, and monitoring the driving scenario on the driving simulator) on driver take-over behavior, and driver trust and acceptance of automated vehicles. Across all non-driving tasks, the fastest response time was observed with Vibration Pattern 5 (order of the vibration location: back–back–seat–seat). The shortest response time and largest minimum time-to-collision (TTC) also were observed when drivers took back control of the vehicle after monitoring the driving scenario. No interaction effects between vibration patterns and non-driving tasks were observed. Potential applications of the results of designing take-over requests in automated vehicles are discussed.     

“Human” Problems in Semi-Autonomous Vehicles: Understanding Drivers’ Reactions to Off-Nominal Scenarios

ABSTRACT

Research related to autonomous vehicles and to their implications for human-machine interactions is on the rise. Advanced Driver Assistance Systems have become increasingly popular in vehicles currently deployed on the market, making researchers wonder about potential risks in case of technology failures for drivers that become accustomed to the use of such technology. To further our understanding of such concern, this work looks at the currently available data from autonomous vehicles field testing that has been carried out in California from 2014 to 2017. Our examination includes both qualitative and quantitative analyses, respectively, based on (i) the type of response in terms of control takeover in off-nominal scenarios that led to collisions involving autonomous vehicles; and (ii) the time to takeover after disengagements of the autonomous technology that acts as “brain” of the vehicle, with the request to the human driver to regain control of the vehicle. Our findings include expected values for the response time, discussion of factors that affect dispersion, presentation of how to determine trust and experience effects in the data, as well as a careful comparison with state-of-the-art literature on the topic.     

Traffic flow harmonization in expressway merging

Steering a vehicle is a task increasingly challenging the driver in terms of mental resources. Reasons for this include the increasing volume of road traffic and a rising quantity of road signs, traffic lights, and other distractions at the roadside (such as billboards), to name a few. The application of Advanced Driver Assistance Systems, in particular if taking advantage of Ambient Intelligence (AmI) technology, can help to increase the perceptivity of a driver, leading as a direct consequence to more relaxed mental stress of the same. One situation where we see potential in the application of such a system are merging areas on the expressway where two or more varying traffic streams converge into a single one. In order to reduce cognitive liabilities (in this work expressed as panic or anger), drivers are exposed to while merging, we have developed two behavioral rules. The first (“increased range of perception”) enables drivers to change early upstream into a spare lane, allowing the merging traffic to join into mainline traffic at reduced conflicts, the second (“inter-car distance management” in the broader area of merging) provide drivers with recommendations of when and how to change lanes at the best. From a technical point of view, the “VibraSeat” a in-house developed car seat with integrated tactile actuators, is used for delivering information about perception range and inter-car distances to the driver in a way that does not stress his/her mental capabilities. To figure out possible improvements in its application in real traffic and at a meaningful scale, cellular automaton–based simulation of a specific section of Madrid expressway M30 was performed. Results from the data-driven simulation experiments on the true to scale model indicate that AmI technology has the potential to increase road throughput or average driving speed and furthermore to decrease the panic of drivers while merging into an upper (the main) lane.     

Citizen Science: New Research Challenges for Human–Computer Interaction

Citizen science broadly describes citizen involvement in science. Citizen science has gained significant momentum in recent years, brought about by widespread availability of smartphones and other Internet and communications technologies (ICT) used for collecting and sharing data. Not only are more projects being launched and more members of the public participating, but more human–computer interaction (HCI) researchers are focusing on the design, development, and use of these tools. Together, citizen science and HCI researchers can leverage each other’s skills to speed up science, accelerate learning, and amplify society’s well-being globally as well as locally. The focus of this article is on HCI and biodiversity citizen science as seen primarily through the lens of research in the author’s laboratory. The article is framed around five topics: community, data, technology, design, and a call to save all species, including ourselves. The article ends with a research agenda that focuses on these areas and identifies productive ways for HCI specialists, science researchers, and citizens to collaborate. In a nutshell, while species are disappearing at an alarming rate, citizen scientists who document species’ distributions help to support conservation and educate the public. HCI researchers can empower citizen scientists to dramatically increase what they do and how they do it.     

Latest developments for “system‐on‐glass” displays using low‐temperature poly‐Si TFTs

Abstract— A 2.3‐in.‐diagonal QVGA‐formatted “System‐On‐Glass” display has been developed by using low‐temperature poly‐Si TFT‐LCD technology. This display fully integrates 6‐bit RGB digital interface drivers as well as all the power supply circuitry to drive the LCD, which requires neither external driver ICs nor power‐supply ICs. This paper discusses the newly developed TFT circuit technologies used in this LCD. The development trend of the “System‐On‐Glass” display is also reviewed.     

Utilization of Visual Information Perception Characteristics to Improve Classification Accuracy of Driver’s Visual Search Intention for Intelligent Vehicle

Understanding and predicting a driver’s behaviors in a vehicle is a prospective function embedded in a smart car. Beyond the patterns of observable behaviors, driver’s intention could be identified based on goal-driven behaviors. A computational model to classify driver intention in visual search which is finding a target with one’s eyes as moving selective attention across a search field, could improve the level of intelligence that a smart car could demonstrate. To develop a computational cognitive that explains the underlying cognitive process and reproduces drivers’ behaviors, particular parameters in human cognitive process should be specified. In this study, 2 issues are considered as influential factors on a driver’s eye movements: a driver’s visual information processing characteristics (VIPCs) and the purpose of visual search. To assess an individual’s VIPC, 4 psychological experiments—Donders’s reaction time, mental rotation, signal detection, and Stroop experiments—were utilized. Upon applying k-means clustering method, 114 drivers were divided into 9 driver groups. To investigate the influence of task goal on a driver’s eye movement, driving simulation was conducted to collect a driver’s eye movement data under the given purpose of visual search (perceptual and cognitive tasks). The empirical data showed that there were significant differences in a driver’s oculomotor behavior, such as response time, average fixation time, and average glance duration between the driver groups and the purposes of visual search. The effectiveness of using VIPC for grouping drivers was tested with task goal classification model by comparing the models’ performance when drivers were grouped by typical demographic data such as gender. Results show that grouping based on VIPC improves accuracy and stability of prediction of the model on a driver’s intention underlying visual search behaviors. This study would benefit future studies focusing on personalization and adaptive interfaces in the development of smart car.     

Context-sensitive distraction warnings – Effects on drivers׳ visual behavior and acceptance

In this study, we investigated the effects of context-sensitive distraction warnings on drivers׳ in-car glance behaviors and acceptance. The studied prototype warning application functions on a smart phone. The novelty of the application is its proactive and context-sensitive approach to the adjustment of warning thresholds according to the estimated visual demands of the driving situation ahead. In our study, novice and experienced drivers conducted in-car tasks with a smart phone on a test track with and without the warnings. The application gave a warning if the driver׳s gaze was recognized to remain on the smart phone over a situation-specific threshold time, or if the driver was approaching a high-demand part of the track (an intersection or a tight curve). Glance metrics indicated a significant increasing effect of the warnings on glance time on road while multitasking. The effect varied between 5% and 30% increase depending on the in-car task. A text message reading task was the most visually demanding activity and indicated the greatest effect of the warnings on glance time on road. Driving experience did not have an effect on the efficiency of the warnings. The proposed gaze tracking with current smart phone technology proved to be highly unreliable in varying lighting conditions. However, the findings suggest that location-based proactive distraction warnings of high-demanding driving situations ahead could help all drivers in overcoming the inability to evaluate situational demands while interacting with complex in-car tasks and to place more attention on the road. Furthermore, survey results indicate that it is possible to achieve high levels of trust, perceived usefulness, and acceptance with these kinds of context-sensitive distraction warnings for drivers.     

Real-time EEG-based emotion monitoring using stable features

In human–computer interaction (HCI), electroencephalogram (EEG) signals can be added as an additional input to computer. An integration of real-time EEG-based human emotion recognition algorithms in human–computer interfaces can make the users experience more complete, more engaging, less emotionally stressful or more stressful depending on the target of the applications. Currently, the most accurate EEG-based emotion recognition algorithms are subject-dependent, and a training session is needed for the user each time right before running the application. In this paper, we propose a novel real-time subject-dependent algorithm with the most stable features that gives a better accuracy than other available algorithms when it is crucial to have only one training session for the user and no re-training is allowed subsequently. The proposed algorithm is tested on an affective EEG database that contains five subjects. For each subject, four emotions (pleasant, happy, frightened and angry) are induced, and the affective EEG is recorded for two sessions per day in eight consecutive days. Testing results show that the novel algorithm can be used in real-time emotion recognition applications without re-training with the adequate accuracy. The proposed algorithm is integrated with real-time applications “Emotional Avatar” and “Twin Girls” to monitor the users emotions in real time.     

Human factors and road safety. Overview of research at the University of Michigan Transportation Research Institute between 1977 and 1986

This article presents a brief overview of the research performed at tge Human Factors Division of The University of Michigan Transportation Research Institute between 1977 and 1986. The focus of the research has been on human factors (ergonomics) aspects of road safety. Specifically, the research has dealt with the following issues: vehicle headlighting, vehicle rear lighting and signalling, vehicle displays and controls, vehicle components, conspicuity of vehicles, legibility of traffic signs and licence plates, driver reaction time, driver performance, stopping sight distance, driver seated position, individual differences (drivers with disabilities, older drivers), methods for measuring blood alcohol concentration, societal violence and traffic accidents, cross-cultural comparison of driver risk-perception, and theoretical issues.     

Exploring Design Guidelines of Using User-Centered Design in Gamification Development: A Delphi Study

Gamification has become an increasingly important trend in the field of human–computer interaction (HCI) design. Applying the idea of user-centered design (UCD) in gamification is drawing more and more attention as the gamification design theoretical frameworks referencing UCD have been proposed. However, questions like “How should a gamification project be developed with specific UCD methods?” and “What design guidelines could be applied in the practice of using UCD in gamification project?” remain unanswered. We hereby conducted a Delphi study to explore design guidelines for using UCD in gamification development with knowledge from practice. The Delphi panel recruited for this study included 20 experienced gamification designers, who produced 28 initial guideline items in the pre-Delphi round. After three rounds of addition, modification, and deletion, 35 design guidelines were ultimately identified. Among these, 31 were found process-oriented and in line with the classic UCD processes and the rest four were about collecting feedback from the design user participants. The author discovered that some of the design guidelines showed consistency with existing theoretical frameworks or design principles about gamification and UCD, and meanwhile, some appeared to be different from the known gamification design knowledge. The research results extended and complemented current gamification design field by providing maneuverable guides and a better overall understanding of how to conduct a gamification project with UCD for gamification researchers and practitioners. In addition, by using the Delphi method in the field of gamification, this study provided a reference to future research in HCI design which needed to draw lessons from practical knowledge.     

Understanding Usability and User Experience of Web-Based 3D Graphics Technology

As Web-based interactive 3D graphics (Web 3D), popularly referred to as Virtual Reality, continue to become more affordable, research and development groups in various fields have been adopting Web 3D technology. In addition to simulation of 3D content, the ability to instantly display alternative looks has been recognized as an innovative way to improve communication in such fields as product design, architecture, and e-commerce. Despite substantial adoption of Web 3D, how and how much the technology benefits target users as well as the providers who choose to adapt the Web 3D technology are not well understood. Previous research has established that interactive 3D graphics provide users with unique human–computer interaction (HCI). However, little is known about how users experience the Web 3D graphics technology and how user–system interaction contributes to system usability. The purpose of this study is to build new knowledge of the user experience with interactive-3D graphics systems used for product demonstration. By testing the impact of the technology on the user–system interaction and usability and comparing this impact with that of conventional two-dimensional (2D) graphics, this study tries to better understand the Web 3D technology from an interdisciplinary view of technology acceptance, sense of presence, and HCI. The study investigated how system usability is affected by HCI in the context of a furniture-style preference survey. The results of the study display the clear advantage for Web 3D for usability and show that perceived usefulness and sense of presence both mediate the effect of the technology treatment on the usability outcomes. The contribution of this study is that it includes empirical data to show how Web 3D benefits users when adopted in the context of a product demonstration and how the advantage is obtained through the user's interaction with the Web 3D technology.     

A controllable and accountable state-oriented Card-Aided Firewall

This paper proposes a new approach, named Card-Aided Firewall (CAF) that combines the simplified firewall and the state-oriented smart card technologies to construct a controllable and accountable Internet access framework. The idea suggests that a client computer, protected by a light-weight firewall, could establish diversified authenticated communication channels, controlled and accounted by “legal” states of the smart card.The program of a smart card is state-oriented or a state machine, which defines a chain of events involving various state transitions. The “legal” states of a smart card program are defined to be legal to communicate with surfing targets. A predefined Access Control List (ACL), stored in the same card, is necessary. An ACL is a sequential list of permit or deny statements that apply to addresses or upper-layer protocols. The proposed firewall decides acceptance or rejection messages by matching the current state of the card program and the ACL. In addition, a complete surfing account for tracing back is recorded. It is a by-product of the smart card authentication.The proposed Card-Aided Firewall framework is implemented to demonstrate its effectiveness. The implementation is done at the driver level. It keeps up with the high line speed. The driver takes 39K bytes and works well with other firewalls. The average packet processing time of the CAF driver is 31.74 μs. On the premise of secure authentication within the smart card, the Card-Aided Firewall would facilitate various rapidly growing applications in campus cards, family cards, and employee cards, etc. that require accurate controllability and accountability in the surfing boundary.     

Design of informatics-based services in manufacturing industries: case studies using large vehicle-related databases

Numerous companies in manufacturing industries have “servitized” their value propositions to address issues on product commoditization and sustainability. A key component of servitization is informatics, which transforms product and customer data into information for customers. In this study, informatics-based service is defined as a type of service wherein informatics is crucial to customer value creation. Despite the importance of this concept, studies on the design of informatics-based services in manufacturing industries are rare. This paper reports on two case studies on such designs. Informatics-based services have been designed for a major Korean automobile manufacturer and the Korea Transportation Safety Authority (TS) based on their large vehicle-related databases. The first case study with the automobile manufacturer aims to design vehicle operations and health management services for passenger vehicle drivers while the second study with TS focuses on the design of driving safety enhancement services for commercial vehicle (i.e., bus, taxi, and truck) drivers. Based on the case studies, this paper discusses various aspects of informatics-based service design in manufacturing industries. This study would assist researchers and practitioners in designing new informatics-based services and contribute to promoting and inspiring research on intelligent services in manufacturing industries under the current information economy.     

Highly Automated Driving Impact on Drivers’ Gaze Behaviors during a Car-Following Task

ABSTRACT

The ever-increasing degree of automation in vehicles, with drivers delegating part of the manual driving task to automation, sets new research questions in terms of human–machine cooperation. Manual steering requires drivers to gaze at a distant road sections to ensure that the vehicle follows the road curvature and at a near road sections to maintain the vehicle within the lane limits. In this experiment, gaze behaviors engaged under highly automated driving (HAD) and manual driving conditions were compared. The results show a critical decrease of the number of gazes at the near road sections for the HAD condition compared to the manual driving condition. Two human-based highly automated “driving styles” were also compared, but did not translate into significant gaze behaviors modifications. Finally, no after-effect of the HAD was found on subsequent manual driving.     

Hybrid gaming environments: keeping the human in the loop within the Internet of things

This paper discusses the issues and realization of hybrid gaming environments that allow human users to utilize ubiquitous computing technology in order to provide novel interaction experiences. The paper first discusses recent trends in human–computer interaction and the emerging application domain of hybrid gaming that is realized with tangible user interfaces and smart artifacts. Then, the field of hybrid games is discussed and analyzed in more detail through the thorough discussion of a conceptual model for hybrid games. Finally, the concrete realization of the hybrid game “In search for the Amulet” is presented as an example for the emerging field of hybrid games.     

An evidential fusion approach for activity recognition in ambient intelligence environments

With the growing emergence of ambient intelligence, ubiquitous computing, sensor networks and wireless networking technologies, “ubiquitous networked robotics” is becoming an active research domain of intelligent autonomous systems. It targets new innovative applications in which robotic systems will become part of these networks of artifacts to provide novel capabilities and various assistive services anywhere and anytime, such as healthcare and monitoring services for elderly in Ambient Assisted Living (AAL) environments. Situation recognition, in general, and activity recognition, in particular, provide an added value on the contextual information that can help the ubiquitous networked robot to autonomously provide the best service that meet the needs of the elderly. Dempster–Shafer theory of evidence and its derivatives are an efficient tool to handle uncertainty and incompleteness in smart homes and ubiquitous computing environments. However, their combination rules yield counter-intuitive results in high conflicting activities. In this paper, we propose a new approach to support conflict resolution in activity recognition in AAL environments. This approach is based on a new mapping for conflict evidential fusion to increase the efficiency and accuracy of activity recognition. It gives intuitive interpretation for combining multiple sources in all conflicting situations. The proposed approach, evaluated on a real world smart home dataset, achieves 78% of accuracy in activity recognition. The obtained results outperform those obtained with the existing combination rules.