Tactical driver lane change model using forward search

This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics, most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainly to accompany observations of the environment. This paper describes how uncertainly can be characterised for a vision system that locates coloured landmark in a typical laboratory environment. The paper describes a model of the uncertainly in segmentation, the internal camera model and the mounting of the camera on the robot. It =plains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainly model,

Dynamic visual features for audio-visual speaker verification

The cascading appearance-based (CAB) feature extraction technique has established itself as the state-of-the-art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we will demonstrate that the same steps taken to reduce static speaker and environmental information for the visual speech recognition application also provide similar improvements for visual speaker recognition. A further study is conducted comparing synchronous HMM (SHMM) based fusion of CAB visual features and traditional perceptual linear predictive (PLP) acoustic features to show that higher complexity inherit in the SHMM approach does not appear to provide any improvement in the final audio-visual speaker verification system over simpler utterance level score fusion.

Thomas Young's contribution to visual optics : the Bakerian lecture "On the mechanism of the eye"

Thomas Young (1773-1829) carried out major pioneering work in many different subjects. In 1800 he gave the Bakerian Lecture of the Royal Society on the topic of the “mechanism of the eye”: this was published in the following year (Young, 1801). Young used his own design of optometer to measure refraction and accommodation, and discovered his own astigmatism. He considered the different possible origins of accommodation and confirmed that it was due to change in shape of the lens rather than to change in shape of the cornea or an increase in axial length. However, the paper also dealt with many other aspects of visual and ophthalmic optics, such as biometric parameters, peripheral refraction, longitudinal chromatic aberration, depth-of-focus and instrument myopia. These aspects of the paper have previously received little attention. We now give detailed consideration to these and other less-familiar features of Young’s work and conclude that his studies remain relevant to many of the topics which currently engage visual scientists.

Mild systemic hypoxia and photopic visual field sensitivity

Purpose: Flickering stimuli increase the metabolic demand of the retina,making it a sensitive perimetric stimulus to the early onset of retinal disease. We determine whether flickering stimuli are a sensitive indicator of vision deficits resulting from to acute, mild systemic hypoxia when compared to standard static perimetry. Methods: Static and flicker visual perimetry were performed in 14 healthy young participants while breathing 12% oxygen (hypoxia) under photopic illumination. The hypoxia visual field data were compared with the field data measured during normoxia. Absolute sensitivities (in dB) were analysed in seven concentric rings at 1°, 3°, 6°, 10°, 15°, 22° and 30° eccentricities as well as mean defect (MD) and pattern defect (PD) were calculated. Preliminary data are reported for mesopic light levels. Results: Under photopic illumination, flicker and static visual field sensitivities at all eccentricities were not significantly different between hypoxia and normoxia conditions. The mean defect and pattern defect were not significantly different for either test between the two oxygenation conditions. Conclusion: Although flicker stimulation increases cellular metabolism, flicker photopic visual field impairment is not detected during mild hypoxia. These findings contrast with electrophysiological flicker tests in young participants that show impairment at photopic illumination during the same levels of mild hypoxia. Potential mechanisms contributing to the difference between the visual fields and electrophysiological flicker tests including variability in perimetric data, neuronal adaptation and vascular autoregulation, are considered. The data have implications for the use of visual perimetry in the detection of ischaemic/hypoxic retinal disorders under photopic and mesopic light levels.

Visual assessment of pedestrian crashes

Of the numerous factors that play a role in fatal pedestrian collisions, the time of day, day of the week, and time of year can be significant determinants. More than 60% of all pedestrian collisions in 2007 occurred at night, despite the presumed decrease in both pedestrian and automobile exposure during the night. Although this trend is partially explained by factors such as fatigue and alcohol consumption, prior analysis of the Fatality Analysis Reporting System database suggests that pedestrian fatalities increase as light decreases after controlling for other factors. This study applies graphical cross-tabulation, a novel visual assessment approach, to explore the relationships among collision variables. The results reveal that twilight and the first hour of darkness typically observe the greatest frequency of pedestrian fatal collisions. These hours are not necessarily the most risky on a per mile travelled basis, however, because pedestrian volumes are often still high. Additional analysis is needed to quantify the extent to which pedestrian exposure (walking/crossing activity) in these time periods plays a role in pedestrian crash involvement. Weekly patterns of pedestrian fatal collisions vary by time of year due to the seasonal changes in sunset time. In December, collisions are concentrated around twilight and the first hour of darkness throughout the week while, in June, collisions are most heavily concentrated around twilight and the first hours of darkness on Friday and Saturday. Friday and Saturday nights in June may be the most dangerous times for pedestrians. Knowing when pedestrian risk is highest is critically important for formulating effective mitigation strategies and for efficiently investing safety funds. This applied visual approach is a helpful tool for researchers intending to communicate with policy-makers and to identify relationships that can then be tested with more sophisticated statistical tools.

Semantic search and inferencing in health informatics

Consider a person searching electronic health records, a search for the term ‘cracked skull’ should return documents that contain the term ‘cranium fracture’. A information retrieval systems is required that matches concepts, not just keywords. Further more, determining relevance of a query to a document requires inference – its not simply matching concepts. For example a document containing ‘dialysis machine’ should align with a query for ‘kidney disease’. Collectively we describe this problem as the ‘semantic gap’ – the difference between the raw medical data and the way a human interprets it. This paper presents an approach to semantic search of health records by combining two previous approaches: an ontological approach using the SNOMED CT medical ontology; and a distributional approach using semantic space vector space models. Our approach will be applied to a specific problem in health informatics: the matching of electronic patient records to clinical trials.

Railway junction conflict resolution by local search method

This study investigates the application of local search methods on the railway junction traffic conflict-resolution problem, with the objective of attaining a quick and reasonable solution. A procedure based on local search relies on finding a better solution than the current one by a search in the neighbourhood of the current one. The structure of neighbourhood is therefore very important to an efficient local search procedure. In this paper, the formulation of the structure of the solution, which is the right-of-way sequence assignment, is first described. Two new neighbourhood definitions are then proposed and the performance of the corresponding local search procedures is evaluated by simulation. It has been shown that they provide similar results but they can be used to handle different traffic conditions and system requirements.

Decoupled image-based visual servoing for cameras obeying the unified projection model

This paper proposes a generic decoupled imagebased control scheme for cameras obeying the unified projection model. The scheme is based on the spherical projection model. Invariants to rotational motion are computed from this projection and used to control the translational degrees of freedom. Importantly we form invariants which decrease the sensitivity of the interaction matrix to object depth variation. Finally, the proposed results are validated with experiments using a classical perspective camera as well as a fisheye camera mounted on a 6-DOF robotic platform.

Attitude observability of a loosely-coupled GPS/Visual Odometry Integrated Navigation Filter

We present a novel method for integrating GPS position estimates with position and attitude estimates derived from visual odometry using a scheme similar to a classic loosely-coupled GPS/INS integration. Under such an arrangement, we derive the error dynamics of the system and develop a Kalman Filter for estimating the errors in position and attitude. Using a control-based approach to observability, we show that the errors in both position and attitude (including yaw) are fully observable when there is a component of acceleration perpendicular to the velocity vector in the navigation frame. Numerical simulations are performed to confirm the observability analysis.

The dynamic processes of visual, corporate, and organisational identity : an exploratory study

The purpose of this study is to contribute to the cross-disciplinary body of literature of identity and organisational culture. This study empirically investigated the Hatch and Schultz (2002) Organisational Identity Dynamics (OID) model to look at linkages between identity, image, and organisational culture. This study used processes defined in the OID model as a theoretical frame by which to understand the relationships between actual and espoused identity manifestations across visual identity, corporate identity, and organisational identity. The linking processes of impressing, mirroring, reflecting, and expressing were discussed at three unique levels in the organisation. The overarching research question of How does the organisational identity dynamics process manifest itself in practice at different levels within an organisation? was used as a means of providing empirical understanding to the previously theoretical OID model. Case study analysis was utilised to provide exploratory data across the organisational groups of: Level A - Senior Marketing and Corporate Communications Management, Level B - Marketing and Corporate Communications Staff, and Level C - Non-Marketing Managers and Employees. Data was collected via 15 in-depth interviews with documentary analysis used as a supporting mechanism to provide triangulation in analysis. Data was analysed against the impressing, mirroring, reflecting, and expressing constructs with specific criteria developed from literature to provide a detailed analysis of each process. Conclusions revealed marked differences in the ways in which OID processes occurred across different levels with implications for the ways in which VI, CI, and OI interact to develop holistic identity across organisational levels. Implications for theory detail the need to understand and utilise cultural understanding in identity programs as well as the value in developing identity communications which represent an actual rather than an espoused position.

User-web interactions : how wholistic/analytic web users search the web?

User-Web interactions have emerged as an important research in the field of information science. In this study, we examine extensively the Web searching performed by general users. Our goal is to investigate the effects of users’ cognitive styles on their Web search behavior in relation to two broad components: Information Searching and Information Processing Approaches. We use questionnaires, a measure of cognitive style, Web session logs and think-aloud as the data collection instruments. Our study findings show wholistic Web users tend to adopt a top-down approach to Web searching, where the users searched for a generic topic, and then reformulate their queries to search for specific information. They tend to prefer reading to process information. Analytic users tend to prefer a bottom-up approach to information searching and they process information by scanning search result pages.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Effect of simulated visual impairment on nighttime driving performance

PURPOSE: This study investigated the effects of simulated visual impairment on nighttime driving performance and pedestrian recognition under real-road conditions. METHODS: Closed road nighttime driving performance was measured for 20 young visually normal participants (M = 27.5 +/- 6.1 years) under three visual conditions: normal vision, simulated cataracts, and refractive blur that were incorporated in modified goggles. The visual acuity levels for the cataract and blur conditions were matched for each participant. Driving measures included sign recognition, avoidance of low contrast road hazards, time to complete the course, and lane keeping. Pedestrian recognition was measured for pedestrians wearing either black clothing or black clothing with retroreflective markings on the moveable joints to create the perception of biological motion ("biomotion"). RESULTS: Simulated visual impairment significantly reduced participants' ability to recognize road signs, avoid road hazards, and increased the time taken to complete the driving course (p < 0.05); the effect was greatest for the cataract condition, even though the cataract and blur conditions were matched for visual acuity. Although visual impairment also significantly reduced the ability to recognize the pedestrian wearing black clothing, the pedestrian wearing "biomotion" was seen 80% of the time. CONCLUSIONS: Driving performance under nighttime conditions was significantly degraded by modest visual impairment; these effects were greatest for the cataract condition. Pedestrian recognition was greatly enhanced by marking limb joints in the pattern of "biomotion," which was relatively robust to the effects of visual impairment.

Modelling web search behaviour : a user’s cognitive style perspective [Unpublished]

Many researchers have investigated and modelled aspects of Web searching. A number of studies have explored the relationships between individual differences and Web searching. However, limited studies have explored the role of users’ cognitive styles in determining Web searching behaviour. Current models of Web searching have limited consideration of users’ cognitive styles. The impact of users’ cognitive style on Web searching and their relationships are little understood or represented. Individuals differ in their information processing approaches and the way they represent information, thus affecting their performance. To create better models of Web searching we need to understand more about user’s cognitive style and their Web search behaviour, and the relationship between them. More rigorous research is needed in using more complex and meaningful measures of relevance; across a range of different types of search tasks and different populations of Internet users. The project further explores the relationships between the users’ cognitive style and their Web searching. The project will develop a model depicting the relationships between a user’s cognitive style and their Web searching. The related literature, aims and objectives and research design are discussed.