Change in dynamic visual acuity (DVA) by pupil dilation

OBJECTIVE: This study was conducted to assess dynamic visual acuity (DVA) under pupil dilation. BACKGROUND: Pupil dilation may negatively affect driving performance. METHODS: Thirty healthy young adults (mean age 29.4 years) with pupil dilation participated in this study as the Mydrin P group. In addition to them, 15 healthy young adults (mean age 28.5 years) without pupil dilation were enrolled as the control group. DVA was measured binocularly with free-head viewing at 0, 30, 60, 120, and 360 min after mydriatic drop instillation in both eyes. Pupil size was measured at each time. RESULTS: In the Mydrin P group, DVA significantly improved at 30, 60, and 120 min (ANOVA; p < .01) but returned to the predilation level at 360 min (ANOVA; p = .61). Pupil size changed from 4.1 to 7.8 mm (ANOVA; p < .01) at 30 min after the instillation, and this level was maintained up to 120 min but returned to normal within 360 min. In the control group, DVA did not significantly change at all measured times (ANOVA; p > .9). DVA was significantly (p < .05) correlated with the pupil size at all measured times. CONCLUSION: The improvement in DVA was related to the enlargement of the pupil. This study suggests that the pupil size is one factor that may affect DVA. APPLICATION: Potential applications of this study include useful information to assess the effect of pupil dilation on driving performance.     

Occlusion as a measure for visual workload: an overview of TNO occlusion research in car driving

A process-oriented approach by systematically studying driver performance, distraction, and workload is the way to go for assessing safety effects of new telematics applications in vehicles. These systems may strive for drivers' attention and possibly lead to distraction from the primary task. Visual occlusion techniques appear to be an effective means of studying drivers' visual information processing performance. Studies to illustrate this include identifying the minimum visual information drivers need for driving (asking for visual information) and the evaluation of driver support systems such as heading control and adaptive cruise control with respect to visual workload. In other applications the occlusion technique is used to exclude 'visual array' information from the optic flow field. The temporary exclusion of part of the visual field of view was applied in evaluating the effects of different types of driver's side rearview mirrors.     

Using mutual information for appearance-based visual path following

In this paper we propose a new way to achieve a navigation task (visual path following) for a non-holonomic vehicle. We consider an image-based navigation process. We show that it is possible to navigate along a visual path without relying on the extraction, matching and tracking of geometric visual features such as keypoint. The new proposed approach relies directly on the information (entropy) contained in the image signal. We show that it is possible to build a control law directly from the maximization of the shared information between the current image and the next key image in the visual path. The shared information between those two images is obtained using mutual information that is known to be robust to illumination variations and occlusions. Moreover the generally complex task of features extraction and matching is avoided. Both simulations and experiments on a real vehicle are presented and show the possibilities and advantages offered by the proposed method.     

A model and a solution algorithm for the car pooling problem with pre-matching information

Most past car pooling studies have focused on the to-work problem (from different origins to a common destination) or the return-from-work problem (from the same origin to different destinations). Pre-matching information, including the carpool partners and the route/schedule for each previously participating vehicle, have rarely been considered. As a result, there has not yet been a suitable method/model developed for solving practical many-to-many car pooling problem with multiple vehicle and person types, as well as pre-matching information, that occur in real-world. In this study we strive to make up this lack by employing a time–space network flow technique to develop a model for this type of car pooling problem with pre-matching information (CPPPMI). The model is formulated as an integer multiple commodity network flow problem. A solution algorithm, based on Lagrangian relaxation and a heuristic for the upper bound solution, is developed to solve the model. To test how well the model and the solution algorithm may be applied to real-world, numerical tests are performed with several problem instances randomly generated based upon data reported from a past study carried out in northern Taiwan. The test results show the effectiveness of the proposed model and solution algorithm.     

Integration of information model (IDEF1) with function model (IDEFO) for CIM information systems design

In this paper a methodology is proposed for the integration of IDEFI with IDEF0, allowing an IDEFI model to be generated easily from the corresponding IDEFO model. The methodology involves: (1) the principle for the integration of IDEFI with IDEFO based on the concepts of IDEF methods; (2) the new requirements for IDEFO diagrams at the relative bottom levels to meet the prerequisites for the integration of IDEF models; (3) the development of a knowledge-based system (KBIDEF) for the integration of the IDEFI model with its corresponding IDEFO model; (4) the design of two databases: object-oriented IDEF0 and IDEFI databases, three libraries: Entity Class Library, Relation Class Library and Domain Relation Class Library and two knowledge bases: Relation Analysis Knowledge Base and Domain Knowledge Base for CIM information system design. Finally, the paper suggests some areas for future work.     

On the information content of multiple view angle (MVA) images

This paper examines the potential to distinguish land cover types in digital images acquired at several different sensor view angles with respect to a fixed area on the Earth's surface. Images recorded by an airborne multispectral scanner over an area of arable farmland are used to generate four such multipleview-angle (MVA) datasets: each consists of data obtained at six sensor view angles in a single spectral waveband: green (0.52-0.605 mu m), red (0.63-0.69 mu m), near-infrared (0.76-0.90 mu m), and middle infrared (1.55-1.75 mu m), respectively.The data are initially presented in the form of single-band MVA false-colour composite images. These are used to illustrate the extent to which different surface materials can be distinguished visually in MVA data. The concept of MVA (cf.,multispectral) feature space is then introduced and the separability of different land cover types within it is explored. It is suggested that single-band MVA data contain two main components of statistical variance directional and spectral . Their relative contributions to the total statistical variance in single-band MVA data is assessed using linear correlation analysis and principal components analysis (PCA). It is shown that while the spectral component tends to dominate in all wavebands, particularly in the near-infrared, the directional component nevertheless provides an important means of distinguishing certain cover types. The implications of these findings are discussed in relation to the parameters used in current bidirectional reflectance distribution function (BDRF) models and the development of 'angular indices' for vegetation monitoring (cf., traditional multispectral vegetation indices).     

An evolutionary tuned driving system for virtual car racing games: The AUTOPIA driver

This work presents a driving system designed for virtual racing situations. It is based on a complete modular architecture capable of automatically driving a car along a track with or without opponents. The architecture is composed of intuitive modules, with each one being responsible for a basic aspect of car driving. Moreover, this modularity of the architecture will allow us to replace or add modules in the future as a way to enhance particular features of particular situations. In the present work, some of the modules are implemented by means of hand‐designed driving heuristics, whereas modules responsible for adapting the speed and direction of the vehicle to the track's shape, both critical aspects of driving a vehicle, are optimized by means of a genetic algorithm that evaluates the performance of the controller in four different tracks to obtain the best controller in a large number of situations; the algorithm also penalizes controllers that go out of the track, lose control, or get damaged. The evaluation of the performance is done in two ways. First, in runs with and without adversaries over several tracks. And second, the architecture was submitted as a participant to the 2010 Simulated Car Racing Competition, which in end won laurels. © 2012 Wiley Periodicals, Inc.     

A visual language compiler for information retrieval by visualreasoning

When a database increases in size, retrieving the data becomes a major problem. An approach based on data visualization and visual reasoning is described. The main idea is to transform the data objects and present sample data objects in a visual space. The user can use a visual language to incrementally formulate the information retrieval request in the visual space. A prototype system is described with the following features: (1) it is built on top of the SIL-ICON visual language compiler and therefore can be customized for different application domains; (2) it supports a fuzzy icon grammar to define reasonable visual sentences; (3) it incorporates a semantic model of the database for fuzzy visual query translation; and (4) it incorporates a VisualNet which stores the knowledge learned by the system in its interaction with the user so that the VisualReasoner can adapt its behavior     

Convergence adoption model (CAM) in the context of a smart car service

This study proposes the convergence adoption model (CAM) in the context of a smart car service. The unique characteristics of convergence technology demand the incorporation of compatibility judgment, task-technology-fit (TTF) and the effect of visual design to fully understand users' adoption intention. The results of our study indicate that the compatibility with past experiences with existing and comparable technologies is indeed a critical factor affecting perceived ease-of-use, usefulness, and enjoyment of convergence technology. TTF is found to directly influence the adoption intention and mediate the effect of perceived usefulness and enjoyment on the adoption intention. Finally, the results show that visual attractiveness of the interface design enhances the evaluation of the key constructs of our model, such as compatibility judgment, perceived enjoyment, and adoption intention of convergence technology.     

Hardware for visual information: Displays and systems

A review of hardware for visual purposes, which is broadly classified into light emitters (CRTs, alphanumeric VDUs and television displays) and light controllers (eidophors, cathodochromic tubes, photochromatic displays and liquid crystals), is presented. It includes sections on constrained-format, head-mounted and solid-state displays, soft and hard copy, including printers and plotters, and interaction methods.     

Pipeline following by visual servoing for Autonomous Underwater Vehicles

A nonlinear image-based visual servo control approach for pipeline following of fully-actuated Autonomous Underwater Vehicles (AUV) is proposed. It makes use of the binormalized Plücker coordinates of the pipeline borders detected in the image plane as feedback information while the system dynamics are exploited in a cascade manner in the control design. Unlike conventional solutions that consider only the system kinematics, the proposed control scheme accounts for the full system dynamics in order to obtain an enlarged provable stability domain. Control robustness with respect to model uncertainties and external disturbances is reinforced using integral corrections. Robustness and efficiency of the proposed approach are illustrated via both realistic simulations and experimental results on a real AUV.     

Topic Tomographies (TopTom): a visual approach to distill information from media streams

In this paper we present Top Tom, a digital platform whose goal is to provide analytical and visual solutions for the exploration of a dynamic corpus of user‐generated messages and media articles, with the aim of i) distilling the information from thousands of documents in a low‐dimensional space of explainable topics, ii) cluster them in a hierarchical fashion while allowing to drill down to details and stories as constituents of the topics, iii) spotting trends and anomalies. Top Tom implements a batch processing pipeline able to run both in near‐real time with time stamped data from streaming sources and on historical data with a temporal dimension in a cold start mode. The resulting output unfolds along three main axes: time, volume and semantic similarity (i.e. topic hierarchical aggregation). To allow the browsing of data in a multiscale fashion and the identification of anomalous behaviors, three visual metaphors were adopted from biological and medical fields to design visualizations, i.e. the flowing of particles in a coherent stream, tomographic cross sectioning and contrast‐like analysis of biological tissues. The platform interface is composed by three main visualizations with coherent and smooth navigation interactions: calendar view, flow view, and temporal cut view. The integration of these three visual models with the multiscale analytic pipeline proposes a novel system for the identification and exploration of topics from unstructured texts. We evaluated the system using a collection of documents about the emerging opioid epidemics in the United States.     

Implementing an analytic model for customer information control systems (CICS)

In most installations, it is important that response time consistently meets negotiated service levels for online, interactive systems. As a result, the capacity planning and performance management disciplines have become important functions to these installations. This paper discusses one of the tools used in capacity planning. Initial methods of capacity planning ranged from “seat of the pants” analysis to complex trending techniques. Because it is often necessary to take into account not only the growth pattern of various capacity indicators, but also the interrelationship of these indicators, analytic queuing models have become an accepted method of analysis in the computer measurement arena. The analytic queuing model discussed in this paper is a mathematic representation of the physical parts of a computer system. It is important to note that such an analytic model can only evaluate a finite number of elements or pieces of the system. As a result, when actual measured values are compared with those calculated by the model (the process of model validation) discrepancies can result because of elements that are not explicitly represented in the model. Many of the influences that are not represented by the mathematic model can be removed by tuning the system to remove bottlenecks. When using a model for capacity planning, it is assumed that the data used to develop the model are derived from a system that is “moderately tuned.” A moderately tuned system is one in which the majority of the bottlenecks or other influences not represented by the model have been removed. When the model is used to predict the responsiveness and throughput of the system into the future, it is assumed that any negative influences not represented in the model will be removed in a timely fashion. In this paper, we will review the impact of such tuning issues on attempts to validate the model against actual data. The analytic model discussed in this paper is for IBMs Customer Information Control System (CICS). The model was published in 1982 in the IBM Systems Journal. In the following sections, we will review the model that was presented in the IBM Systems Journal, present extensions required to implement the model for MVS systems, and discuss the aspects of CICS performance that are not represented by analytic models based on traditional SMF and RMF data.     

A visual discomfort recognition model based on the fusion of multisource information

An experiment was performed to explore the influence of image attributes (white level, black level, color saturation, and sharpness) on visual discomfort, with measurements of the subjective questionnaire, eye movement, and electrocardiogram. The objective and subjective results showed that these image attributes influenced visual discomfort significantly. A visual discomfort recognition model based on Dempster–Shafer evidence theory was proposed according to the experiment results. With multiple features and weighting coefficients, the model could recognize visual discomfort states well.     

面向智能驾驶的平行视觉感知：基本概念、框架与应用

目的 视觉感知技术是智能车系统中的一项关键技术,但是在复杂挑战下如何有效提高视觉性能已经成为智能驾驶领域的重要研究内容。本文将人工社会（artificial societies）、计算实验（computational experiments）和平行执行（parallel execution）构成的ACP方法引入智能驾驶的视觉感知领域,提出了面向智能驾驶的平行视觉感知,解决了视觉模型合理训练和评估问题,有助于智能驾驶进一步走向实际应用。方法 平行视觉感知通过人工子系统组合来模拟实际驾驶场景,构建人工驾驶场景使之成为智能车视觉感知的“计算实验室”;借助计算实验两种操作模式完成视觉模型训练与评估;最后采用平行执行动态优化视觉模型,保障智能驾驶对复杂挑战的感知与理解长期有效。结果 实验表明,目标检测的训练阶段虚实混合数据最高精度可达60.9%,比单纯用KPC（包括：KITTI（Karlsruhe Institute of Technology and Toyota Technological Institute）,PASCAL VOC（pattern analysis,statistical modelling and computational learning visual object classes）和MS COCO（Microsoft common objects in context））数据和虚拟数据分别高出17.9%和5.3%;在评估阶段相较于基准数据,常规任务（-30°且垂直移动）平均精度下降11.3%,环境任务（雾天）平均精度下降21.0%,困难任务（所有挑战）平均精度下降33.7%。结论 本文为智能驾驶设计和实施了在实际驾驶场景难以甚至无法进行的视觉计算实验,对复杂视觉挑战进行分析和评估,具备加强智能车在行驶过程中感知和理解周围场景的意义。     

Job satisfaction and visual display unit (VDU) usage: an explanatory model

Abstract

This study explores the relationship between job salisfaction and the daily usage of visual display units (VDUs). A negative correlation is found to exist between job satisfaction and utilization of the VDU. Workers who have utilized the VDU alone for data entry were more satisfied with their jobs than those workers who had used the key punch for data entry and then switched to the VDU, although they said they preferred the VDU over the key punch. The following model was found to be statistically significant:

Job satisfaction =f(-VDU Usage + Supervisor intervention+ Team membership+ job utility—performance of the task)     

Job satisfaction and visual display unit (VDU) usage: an explanatory model

This study explores the relationship between job salisfaction and the daily usage of visual display units (VDUs). A negative correlation is found to exist between job satisfaction and utilization of the VDU. Workers who have utilized the VDU alone for data entry were more satisfied with their jobs than those workers who had used the key punch for data entry and then switched to the VDU, although they said they preferred the VDU over the key punch. The following model was found to be statistically significant:

Job satisfaction =f(-VDU Usage + Supervisor intervention+ Team membership+ job utility—performance of the task)     

The gap between design intent and user response: identifying typical and novel car design elements among car brands for evaluating visual significance

This paper identifies correlations of design intent and user response to stylistic recognition of 23 car brands, with an emphasis on visual aesthetics. By evaluating car exterior designs based on shape similarities, it is possible to find the distributions of the typical design elements and novel design elements. These can then be compared with looking probabilities on design elements observed from eye tracking experiments to conduct a Design Intent Analysis. We have identified that the participants’ viewing patterns are related to the degree of shape similarities of particular design elements such as the front bumper, side silhouette, and side front fender. We observed no significance in regard to subjects’ looking probabilities in relation to design intent of the other 16 design elements. Thus, the design intent of the car brands does not correlate with the user responses. The contribution of this paper is twofold: providing systematic measures and promoting practical possibilities for design quantification. The design field relies heavily on expert knowledge; an empirical understanding of designer intent and user response therefore can provide quantifiable insight to automobile companies. Based on our findings, companies could investigate how creating unique designs may not always be good strategies for improving design qualities, brand recognition or even purchase intent. Companies can efficiently and strategically manage design costs, which are directly related to the manufacturing cost.     

Perception,information processing and modeling: Critical stages for autonomous driving applications

Over the last decades, the development of Advanced Driver Assistance Systems (ADAS) has become a critical endeavor to attain different objectives: safety enhancement, mobility improvement, energy optimization and comfort. In order to tackle the first three objectives, a considerable amount of research focusing on autonomous driving have been carried out. Most of these works have been conducted within collaborative research programs involving car manufacturers, OEM and research laboratories around the world. Recent research and development on highly autonomous driving aim to ultimately replace the driver's actions with robotic functions. The first successful steps were dedicated to embedded assistance systems such as speed regulation (ACC), obstacle collision avoidance or mitigation (Automatic Emergency Braking), vehicle stability control (ESC), lane keeping or lane departure avoidance. Partially automated driving will require co-pilot applications (which replace the driver on his all driving tasks) involving a combination of the above methods, algorithms and architectures. Such a system is built with complex, distributed and cooperative architectures requiring strong properties such as reliability and robustness. Such properties must be maintained despite complex and degraded working conditions including adverse weather conditions, fog or dust as perceived by sensors. This paper is an overview on reliability and robustness issues related to sensors processing and perception. Indeed, prior to ensuring a high level of safety in the deployment of autonomous driving applications, it is necessary to guarantee a very high level of quality for the perception mechanisms. Therefore, we will detail these critical perception stages and provide a presentation of usable embedded sensors. Furthermore, in this study of state of the art of recent highly automated systems, some remarks and comments about limits of these systems and potential future research ways will be provided. Moreover, we will also give some advice on how to design a co-pilot application with driver modeling. Finally, we discuss a global architecture for the next generation of co-pilot applications. This architecture is based on the use of recent methods and technologies (AI, Quantify self, IoT …) and takes into account the human factors and driver modeling.