Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Autonomous vehicles operate in real time traffic scenarios and aim to reach their destination from their source in the most efficient manner possible. Research in mobile robotics provides a variety of sophisticated means with which to plan the path of these vehicles. Conversely professional human drivers usually drive using instinctive means, which enables them to reach their goal almost optimally whilst still obeying all traffic laws. In this paper we propose the use of fuzzy logic for novel motion planning. The planner is generated using an evolutionary algorithm which resembles the learning stage of professional drivers. Whether to overtake or not, is a decision which affects one’s driving and the decision is made using some deliberation. We further extend the approach to perform decision making regarding overtaking for all vehicles. Further we coordinate the motion of the vehicles at a traffic crossing to avoid any potential jam or collision. Experimental results prove that by using this approach we have been able to make the vehicles move in an optimal manner in a variety of scenarios

Determining SUSY model parameters and masses at the LHC using cross-sections, kinematic edges and other observables.

We address the problem of mass measurements of supersymmetric particles at the Large Hadron Collider, using the ATLAS detector as an example. By using Markov Chain sampling techniques to combine standard measurements of kinematic edges in the invariant mass distributions of decay products with a measurement of a missing $p_T$ cross-section, we show that the precision of mass measurements at the LHC can be dramatically improved, even when we do not assume that we have measured the kinematic endpoints precisely, or that we have identified exactly which particles are involved in the decay chain causing the endpoints. The generality of the technique is demonstrated in a preliminary investigation of a non-universal SUGRA model, in which we relax the requirements of mSUGRA by breaking the degeneracy of the GUT scale gaugino masses. The model studied is compatible with the WMAP limits on dark matter relic density

R-C-P Method: An Autonomous Volume Calculation Method Using Image Processing and Machine Vision

Machine vision and image processing are often used with sensors for situation awareness in autonomous systems, from industrial robots to self-driving cars. The 3D depth sensors, such as LiDAR (Light Detection and Ranging), Radar, are great invention for autonomous systems. Due to the complexity of the setup, LiDAR may not be suitable for some operational environments, for example, a space environment. This study was motivated by a desire to get real-time volumetric and change information with multiple 2D cameras instead of a depth camera. Two cameras were used to measure the dimensions of a rectangular object in real-time. The R-C-P (row-column-pixel) method is developed using image processing and edge detection. In addition to the surface areas, the R-C-P method also detects discontinuous edges or volumes. Lastly, experimental work is presented for illustration of the R-C-P method, which provides the equations for calculating surface area dimensions. Using the equations with given distance information between the object and the camera, the vision system provides the dimensions of actual objects

Redefining the patient-carer model at end of life.

CONTEXT: While the patient-carer dyad has been broadly described, there is little exploration of patient-carer models in use. AIM: To explore types of patient-carer models in use for those with advanced and progressive disease. METHODS: Qualitative interviews were undertaken with patients at risk of dying in the next year and their carers across three sites (residential care home, medical assessment unit, general medical unit). Thematic analysis was undertaken. RESULTS: Four patient-carer models were identified. In these, the provision of care and of coordination of care services were important areas and organised differently across the patient, the carer, and alternative sources of support. CONCLUSION: A 'one size fits all' patient-carer model is outdated and a new understanding of different types of patient-carer models are required to fully inform care delivered at end of life

Proactivity Toward Workplace Safety Improvement: An Investigation of Its Motivational Drivers and Organizational Outcomes

Initiating a safety oriented change - or safety initiative - is conceptually distinct from other forms of safety participation and safety citizenship behaviour, yet little attention has been given to its performance outcomes or its motivational antecedents. An initial study with a sample composed of middle managers (N = 86) showed that safety initiative predicted objective improvement actions six months later, whereas, showing differential validity, safety compliance predicted the implementation of monitoring actions. Two subsequent studies focused on motivational antecedents. First, using a sample of team leaders (N = 295), we tested a higher-order structure of proactive motivation that incorporates three domains: “can do”, “reason to” and future orientation. Second, in a longitudinal study of chemical work operators (N = 188), after checking for the influence of potential confounds (past behaviours; accidents experience; perceived risk), we showed that safety initiative was predicted only by proactive motivation. Instead, safety compliance was found to be associated with affective commitment and scrupulousness, whereas safety helping was found to be associated with affective commitment. Self-reported behaviours were validated against rater assessments. This study supports the importance of distinguishing safety initiative from other safety behaviours, indicating how to create an organizational context supporting a proactive management of workplace safety

Mathematical Modelling of Chemical Diffusion through Skin using Grid-based PSEs

A Problem Solving Environment (PSE) with connections to remote distributed Grid processes is developed. The Grid simulation is itself a parallel process and allows steering of individual or multiple runs of the core computation of chemical diffusion through the stratum corneum, the outer layer of the skin. The effectiveness of this Grid-based approach in improving the quality of the simulation is assessed

Measuring sparticle masses in non-universal string inspired models at the LHC

We demonstrate that some of the suggested five supergravity points for study at the LHC could be approximately derived from perturbative string theories or M-theory, but that charge and colour breaking minima would result. As a pilot study, we then analyse a perturbative string model with non-universal soft masses that are optimised in order to avoid global charge and colour breaking minima. By combining measurements of up to six kinematic edges from squark decay chains with data from a new kinematic variable, designed to improve slepton mass measurements, we demonstrate that a typical LHC experiment will be able to determine squark, slepton and neutralino masses with an accuracy sufficient to permit an optimised model to be distinguished from a similar standard SUGRA point. The technique thus generalizes SUSY searches at the LHC

Search strategies for top partners in composite Higgs models

We consider how best to search for top partners in generic composite Higgs models. We begin by classifying the possible group representations carried by top partners in models with and without a custodial $SU(2)\times SU(2) \rtimes \mathbb{Z}_2$ symmetry protecting the rate for $Z \rightarrow b\overline{b}$ decays. We identify a number of minimal models whose top partners only have electric charges of $\frac{1}{3}, \frac{2}{3},$ or $\frac{4}{3}$ and thus decay to top or bottom quarks via a single Higgs or electroweak gauge boson. We develop an inclusive search for these based on a top veto, which we find to be more effective than existing searches. Less minimal models feature light states that can be sought in final states with like-sign leptons and so we find that 2 straightforward LHC searches give a reasonable coverage of the gamut of composite Higgs models.BG acknowledges the support of the Science and Technology Facilities Council, the In- stitute for Particle Physics Phenomenology, and King’s College, Cambridge and thanks R. Contino and R. Rattazzi for discussions. DS acknowledges the support of the Science and Technology Facilities Council, as well as Emmanuel College, Cambridge, and thanks O.Matsedonskyi for FeynRules help. TM thanks C. Lester for discussions on mass variables.This is the final version. It was first published by Springer at http://link.springer.com/article/10.1007%2FJHEP08%282014%29171

Remote Aerial Mapping Spectrometer

According to the EPA, harmful algal blooms may occur more frequently in coastal areas like the Chesapeake Bay due to warming waters and increased nutrient pollution. Algal blooms cause aquatic dead zones which damage the ecosystem and can produce toxins which are dangerous to animals and humans. Continual environmental monitoring is required to research algal blooms and to prevent harm to residents and industries. We researched technologies to locate harmful algal blooms and found spectroscopic remote surveying an effective approach. A material’s wavelength-dependent reflectance reveals its material composition. Unfortunately, existing methods which can map spectral characteristics are lacking. Field researchers with handheld spectrometers may analyze nearby vegetation’s identity and health but surveying a large area is time-consuming. Alternatively, hyperspectral cameras mounted to aircraft and satellites can gather data from a wide region but are cost prohibitive for local studies and provide limited spatial resolution. We designed a spectral mapping sensor payload for mounting on unmanned aerial vehicles. The Remote Aerial Mapping Spectrometer (RAMS) adapts to any aircraft able to carry its low weight because it is self-powered and includes all necessary sensors. It scans its surroundings with a laser rangefinder and spectrometer with a long-focus lens. RAMS monitors the orientation of its sensor package and computes a three-dimensional map of nearby material signatures. This graphical representation of localized spectra will assist in charting harmful algal blooms but also monitor forests threatened by invasive species and provide pinpoint agricultural analytics. RAMS makes environmental data richer and more cost-effective than current techniques.https://scholarscompass.vcu.edu/capstone/1191/thumbnail.jp