Cross-generational acceptance of and interest in advanced vehicle technologies: A nationwide survey

The number of older drivers on the roadways is increasing; at the same time, technology in the automotive environment is rapidly evolving. To investigate the potential impact of these converging changes, this study used a cross-generational approach to compare driver attitudes toward advanced automotive technologies. Approximately 1000 drivers between the ages of 18 and 85 located across the United States responded to a survey about their opinions regarding general technology, advanced in-vehicle technology, and near-horizon connected vehicle systems. Participant responses were categorized using a generational construct, sorting responses not only by age but by shared life experiences (e.g. economic circumstances, involvement in wartime activities, cultural movements, etc.). The oldest generation (the “Silent” generation) exhibited the least interest in and comfort with advanced technology, although they owned and used advanced in-vehicle technology at approximately the same rates as the two middle generations. The youngest generation (the “Millennial” generation) was most likely to be interested in and comfortable with technology, but was least likely to own vehicles with advanced technology. All participants expressed interest in safety-related connected vehicle systems, but less so in infotainment applications. Reservations regarding data security and system cost were shared across generations. These findings are framed in the context of an aging population with unique driving and vehicle needs, and provide information that may assist both with vehicle technology design aspects and the proposed large-scale implementation of connected vehicle systems, including considerations for seniors and emphasis on safety systems and data security.     

A feature based comparison of pen and swipe based signature characteristics

Dynamic Signature Verification (DSV) is a biometric modality that identifies anatomical and behavioral characteristics when an individual signs their name. Conventionally signature data has been captured using pen/tablet apparatus. However, the use of other devices such as the touch-screen tablets has expanded in recent years affording the possibility of assessing biometric interaction on this new technology.To explore the potential of employing DSV techniques when a user signs or swipes with their finger, we report a study to correlate pen and finger generated features. Investigating the stability and correlation between a set of characteristic features recorded in participant’s signatures and touch-based swipe gestures, a statistical analysis was conducted to assess consistency between capture scenarios.The results indicate that there is a range of static and dynamic features such as the rate of jerk, size, duration and the distance the pen traveled that can lead to interoperability between these two systems for input methods for use within a potential biometric context. It can be concluded that this data indicates that a general principle is that the same underlying constructional mechanisms are evident.     

ELM-HTM guided bio-inspired unsupervised learning for anomalous trajectory classification

Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose a new bio-inspired learning model for a single-class classifier to detect abnormality in video object trajectories. The method uses a simple but dynamic extreme learning machine (ELM) and hierarchical temporal memory (HTM) together referred to as ELM-HTM in an unsupervised way to learn and classify time series patterns. The method has been tested on trajectory sequences in traffic surveillance to find abnormal behaviors such as high-speed, unusual stops, driving in wrong directions, loitering, etc. Experiments have also been performed with 3D air signatures captured using sensors and used for biometric authentication(forged/genuine). The results indicate a significant gain over training time and classification accuracy. The proposed method outperforms in predicting long-time patterns by observing small steps with an average accuracy gain of 15% as compared to the state-of-the-art HTM. The method has applications in detecting abnormal activities in videos by learning the movement patterns as well as in biometric authentication.     

Societal and Ethical Implications of Anti-Spoofing Technologies in Biometrics

Biometric identification is thought to be less vulnerable to fraud and forgery than are traditional forms of identification. However biometric identification is not without vulnerabilities. In a ‘spoofing attack’ an artificial replica of an individual’s biometric trait is used to induce a system to falsely infer that individual’s presence. Techniques such as liveness-detection and multi-modality, as well as the development of new and emerging modalities, are intended to secure biometric identification systems against such threats. Unlike biometrics in general, the societal and ethical issues raised by spoofing and anti-spoofing techniques have not received much attention. This paper examines these issues.     

Intersection crossing assist system: Transition from a road-side to an in-vehicle system

Due to high vehicle velocities rural intersections have a disproportionately high rate of fatalities. The current study examines the transition from an infrastructure-based rural intersection crossing assist system to one located inside a vehicle. Moreover, we investigate the efficacy of the in-vehicle system. Three different designs of the assist system were examined regarding their impact on driving performance and applicability to varying age groups and visibility conditions. These designs differed in terms of their complexity based on the amount of information that drivers received about the intersection traffic. Seventy-two older and younger participants divided into the three design groups crossed a busy rural intersection in a simulated environment. Drivers completed four blocks of trials in which the presence of the assist system and visibility conditions (limited, clear) were counterbalanced. When presented with the assist system drivers were less likely to accept a smaller gap, especially under low-visibility conditions. The design of the assist system that resulted in the best overall intersection crossing performance was also the most informative about the traffic. Older drivers exhibited some benefits from the presence of the assist system, although not to the same extent as the younger drivers. The results suggest that some infrastructure-based assist or information display systems could successfully be transitioned to inside a vehicle.     

An abstract dynamic access control architecture

This paper presents an abstract architecture capturing the most essential characteristics of security architectures for the kind of access control required in multi-agent systems. A security architecture is usually component based; it is dynamically extensible, reflective, and should be able to support a variety of policy strategies and enforcement mechanisms. Therefore, in designing and implementing such an architecture, it is important to accurately describe its structure, components, and their interactions; and we should also provide support for verifying properties that the architecture must satisfy. The abstract Dynamic Access Control Architecture, or DACA, we propose provides the flexibility to express several complex characteristics abstractly, ultimately resulting in a more structured foundation for implementing security architectures for access control.     

Cognitive solutions for security and cryptography

This paper describes the new security solutions based on cognitive approaches and new computing paradigm called cognitive cryptography. This new security area establish a new generation of computational methods and security systems, focused on creation intelligent cryptographic algorithms and security protocols using cognitive information processing approaches. Such systems are designed for semantic evaluation of encrypted data, and allow to select the most appropriate techniques of its encryption. This paper presents a possible application of such techniques for different security tasks like authentication, secret sharing, secure data management etc. Additionally, some cryptographic solutions inspired by biological models will be presented.     

Ethical and methodological aspects of medical computer data bases and knowledge bases

Ethical problems are related to computer data bases, containing data on individuals and groups of persons, as well as to computer knowledge bases, containing general rules and elements of expert systems.In the present essay the following conclusions are made regarding computer data bases: privacy, security, and confidentiality of medical computer data bases should be ensured. This duty should rest with physicians in hospitals. The principle of informed consent should be applied to gathering information which is to be stored and processed by computers. Information stored in computer data bases should not be used for purposes for which the subjects (patients as well as personnel) have not given their consent. In order to decrease the possibility of misuses of medical data bases containing information on individuals, these registers should not be linked to other central data bases.     

Influence of traffic conditions on driver behavior before making a right turn at an intersection: Analysis of driver behavior based on measured data on an actual road

This paper describes an investigation of the influence of the position of a forward vehicle and following vehicle on the onset of driver preparatory behavior before making a right turn at an intersection. Four experimental vehicles with various sensors and a driving recorder system were developed to measure driver behavior before making a right turn at a specific intersection on a public road. The experimental term was eight weeks to collect data on natural driving maneuvers. The relationships between the remaining distances to the center of the intersection when releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal and the relative distances from the forward and following vehicles were analyzed based on the measured data. The time it took to reach the center of the turn and the driving speed when each behavioral event occurred were also evaluated from the viewpoint of the relative position between the driver’s vehicle and the leading or following vehicles. The results suggest that the drivers approached the target intersection in a car-following condition, and that the positions of the front and rear vehicles and the vehicle velocity influence the onset location and timing of releasing the accelerator pedal and covering the brake pedal. Drivers began to decelerate closer to the center of the intersection when they approached the intersection close to a leading or following vehicle at a reduced driving speed. However, these influences were not reflected in the turn signal operation, indicating that drivers intend to make a right turn at a constant location while approaching a target intersection and that intention appears in the turn signal activation. The findings of this observational study imply that the method of providing route guidance instruction, in which the traffic conditions surrounding the driver’s vehicle are taken into consideration, is effective in reducing driver errors in receiving instruction and following the correct route. The results also indicate that measuring and accumulating different behavioral indices based on traffic conditions contribute to determining the criteria for the presentation timing just before reaching the intersection, which can assist drivers in preparing to make a right turn at a usual location. Driver decelerating maneuvers are used while driving without leading or following vehicles and while driving with a lead and/or following vehicle at long range, and driver turn signal operations are used when approaching an intersection under close car-following conditions.     

Containment in theory and practice

Abstract

This article selects the term ‘containment’ as a vehicle for an exploration of multi-professional work and communication in the general practice setting. The term was selected because of its widespread use by and relevance to the different professionals who work in general practice. It is sufficiently elastic to be applied to one-to-one work between patients and GPs, counsellors, nurses or complementary therapists, and to a multi-professional teamwork process.

The exploration of the concept in use at Marylebone Health Centre is complicated by the multi-professional nature of the team and then-wide range of belief systems and language groups. In the process of exploring the term, members of the team had to cope with their discovery that it was being used in contradictory ways. They decided that a new and more grounded definition in shared and ordinary (nonprofessional) language was needed, if the term were to become a vehicle for inter-professional collaboration and if unhelpful, anti-task social defences were to be minimised.     

Investigating the potential of EDA data from biometric wearables to inform inclusive design of the built environment

This paper presents a pilot of a method which measures quantitative biometric data to understand the emotional response of people to their physical environment. The aim of the audit method is to address the problem of lack of accessibility of public buildings for those with hidden disabilities. People with invisible disabilities such as Autistic Spectrum Disorders (ASD, Autism) sometimes feeling forced to withdraw from public spaces and communities and unfamiliar or busy environments such as art galleries can be particularly problematic (Amaze, 2018). As part of the Audit, data is collected using a wearable biometric device that is mapped against internal location. In this study the EDA (Electrodermal Activity) Audit was trialed with participants with ASD at a public art gallery in UK. The results reveal that participants with ASD experienced a greater increase in stress level compared to the neurotypical control participants. Areas where noticeable ‘peaks’ of stress were recorded usually had a restricted view or required human interaction. Comparison of GSR (Galvanic Skin Response) data with questionnaire information gathered before and after visiting the gallery also implies that the participants with ASD were less able to articulate their emotional response to spaces. We discuss the development of an EDA Audit method that could provide knowledge to help designers envision spaces that are more inclusive.     

情节模拟对预期伴侣反应性及依恋安全感的影响

当依恋对象不在身边时, 个体可以通过内部表征的方式通达依恋对象的可得与反应性, 获得依恋安全感。然而, 现有研究对内部表征通达途径的考察忽略了情节模拟的作用。该研究采用实验组控制组前后测设计, 考察是否可以通过依恋相关的情节模拟通达依恋对象的可得与反应性, 帮助个体获得依恋安全感。研究招募正处于恋爱关系中且恋爱时长超过6个月的大学生46名。前测评定依恋相关的困境情境; 3天后实验组被试进行依恋相关的情节模拟任务, 控制组被试进行情境结果的撰写任务, 并再次对情境进行评定。结果发现, 相比于控制组, 情节模拟组预期伴侣的反应性和依恋安全感有更大提升。以上的研究结果表明, 依恋相关的情节模拟可以通达伴侣可得与反应性并帮助个体获得依恋安全感。     

Whispering gallery mode sensor for phase transformation and solidification studies

Whispering gallery mode (WGM) sensors are created by coupling a dielectric microresonator with the evanescent field of an optical fiber. Since the sensor is created by two separate entities, most of the existing studies are limited to using them in fluid environments, such as air or water, for the ease of manipulation and placement in the optimum configuration. This work is focused on studying the possibility of using WGM sensors inside a solid material. The sensor is immersed in water, which is cooled to solid state and the sensor survival is monitored. In subsequent studies, three remelting cycles are carried out and temperature measurements are obtained through the sensor. The sensor output is calibrated with the temperature data obtained from a thermocouple. The results show that a linear relationship exists between temperature and WGM shift, which enables application of these sensors in temperature measurement. Considering that the sensitivity of WGM sensors is very high (10^?6 N force and 10^?5 K temperature), they can be used for high resolution studies on solidification in cryogenic environments.     

Icy roads and urban environments. Passenger experiences in autonomous vehicles in Finland

This study focused on identifying customerś real-life experiences, perceptions and feelings about travelling in different autonomous vehicles and in various operating conditions in Finland in 2018. Quantitative convenience sample (n = 141) were collected from passengers travelling on an autonomous shuttle bus in Helsinki. Qualitative data (n = 70) were gathered by interviewing passengers of a driverless shuttle bus in Helsinki and passengers of an autonomous car in winter conditions in Lapland. This research was first one which included passengers’ real-life experiences after using autonomous vehicles in winter conditions. We applied the Theory of Planned Behaviour. The research questions were (a) What beliefs about outcomes and evaluation of outcomes do passengers have and carry out when they travel in an autonomous vehicle, irrespective of vehicle type or operating conditions? (b) What key factors influence people’s positive or negative attitudes towards autonomous vehicles? (c) What key factors could induce people to use autonomous vehicles? The quantitative data were analysed by nonparametric Kruskal-Wallis H test and qualitative data by inductive content analysis. According to the results, trust, safety and security were the main factors influencing people’s positive attitudes towards using autonomous vehicles. Results from passengers travelling in heavy winter conditions indicate that winter conditions do not significantly influence passengers’ attitudes towards using autonomous vehicles. There were no significant differences between gender regarding passengers’ perceptions of traffic safety, personal security and emergency management. However, younger passengers felt their personal security on board to be significantly better than older and students their possibilities to act in a case of emergency significantly better than employed people.     

Automation of Stress Recognition Using Subjective or Objective Measures

Automation of stress recognition involves collecting stress-reflecting data and then using a computational technique to estimate the stress level corresponding to that data. With the advent of objective sensors or mobile context measurement, automated stress recognition revolves around and is restricted to only these measures. Traditional subjective questionnaires and self-reports, though highly reliable, have been bounded to only clinical settings, without extending their scope to general population and natural environments. This review discusses some widely used questionnaires for measuring stress which can prove to be equally efficient to their conventional paper-based application when computerized. A summary on highly accepted objective measures of stress, including physiological, behavioural and contextual data, is provided next. Past research work using these subjective and objective measures for automatically recognizing stress is also reviewed. A comparative analysis of questionnaires and objective measures is conducted, which helped in highlighting significant advantages and disadvantages of the measures. Use of reports or questionnaires for automating stress recognition is suggested, owing to improved costs, high reliability and user trust.     

‘Do-It-Yourself’ Healthcare? Quality of Health and Healthcare Through Wearable Sensors

Wearable sensors are an integral part of the new telemedicine concept supporting the idea that Information Technologies will improve the quality and efficiency of healthcare. The use of sensors in diagnosis, treatment and monitoring of patients not only potentially changes medical practice but also one’s relationship with one’s body and mind, as well as the role and responsibilities of patients and healthcare professionals. In this paper, we focus on knowledge assessment of the online communities of Fitbit (a commercial wearable device) and the Quantified Self movement. Through their online forums, we investigate how users’ knowledge claims, shared experiences and imaginations about wearable sensors interrogate or confirm the narratives through which they are introduced to the publics. Citizen initiatives like the Quantified Self movement claim the right to ‘own’ the sensor generated data. But how these data can be used through traditional healthcare systems is an open question. More importantly, wearable sensors trigger a social function that is transformative of the current idea of care and healthcare, focused on sharing, socialising and collectively reflecting about individual problems. Whether this is aligned with current policy making about healthcare, whose central narrative is focused on efficiency and productivity, is to be seen.     

The intelligence community and the war on terror: the role of behavioral science

The United States intelligence community has been under intense scrutiny from both inside and outside in the aftermath of September 11. Post mortem assessments of intelligence breakdowns may judge the events as more predictable than was in fact the actual reality. In a troubled world, when threats to national security can materialize very quickly, the intelligence community must be able to effectively and swiftly develop and implement plans to prevent further terrorist attacks on the homeland. Numerous scenarios need to be considered for the management of crisis situations. Intelligence actions must make it more difficult for terrorists to strike at their targets. The war on terror must confront a new generation of enemies who threaten to attack the United States with weapons of mass destruction. This essay will focus on the role of behavioral science and how related reforms within the intelligence community could improve its capability to respond to a huge challenge.     

PsychoPro 2.0: Using multidimensional scaling to examine the perceptual categorization of race

Recently, researchers examining cognitive mechanisms involved in the detection of racial markers have been using psychophysics to examine perceptual thresholds delineating race using a program called PsychoPro (MacLin, MacLin, Peterson, Chowdhry, & Joshi, 2009). PsychoPro allows researchers to collect data using facial stimuli morphed along a racial continuum with psychophysical methodology. PsychoPro 2.0 was updated so researchers could collect paired-comparison data that can then be analyzed using multidimensional scaling (MDS). MDS allows researchers to examine the perceptions of racial boundaries along perceptual dimensions not bounded by the stimulus continuum, by having the observer make paired comparisons to racial stimuli based on their perceived similarity. Results indicate that ratings were made on the basis of at least six different racial dimensions that suggest the emergence of a third race not represented by the original morph starting images. Details of the software, the new paired-comparison feature and its relevance in psychophysical studies in general and racial categorization in particular are presented.     

Real-time detection of drivers’ texting and eating behavior based on vehicle dynamics

With rapid advancement in cellphones and intelligent in-vehicle technologies along with driver’s inclination to multitasking, crashes due to distracted driving had become a growing safety concern in our road network. Some previous studies attempted to detect distracted driving behaviors in real-time to mitigate their adverse consequences. However, these studies mainly focused on detecting either visual or cognitive distractions only, while most of the real-life distracting tasks involve driver’s visual, cognitive, and physical workload, simultaneously. Additionally, previous studies frequently used eye, head, or face tracking data, although current vehicles are not commonly equipped with technologies to acquire such data. Also those data are comparatively difficult to acquire in real-time during traffic monitoring operations. To address the above issues, this study focused on developing algorithms for detecting distraction tasks that involve simultaneous visual, cognitive, and physical workload using only vehicle dynamics data. Specifically, algorithms were developed to detect driving behaviors under two distraction tasks – texting and eating. Experiment was designed to include the two distracted driving scenarios and a control with multiple runs for each. A medium fidelity driving simulator was used for acquiring vehicle dynamics data for each scenario and each run. Several data mining techniques were explored in this study to investigate their performance in detecting distraction. Among them, the performance of two linear (linear discriminant analysis and logistic regression) and two nonlinear models (support vector machines and random forests) is reported in this article. Random forests algorithms had the best performance, which detected texting and eating distraction with an accuracy of 85.38% and 81.26%, respectively. This study may provide useful guidance to successful development and implementation of distracted driver detection algorithms in connected vehicle environment, as well as to auto manufacturers interested in integrating distraction detection systems in their vehicles.