Pedestrian vision and collision avoidance behavior: investigation of the information process space of pedestrians using an eye tracker

This study investigates the Information Process Space (IPS) of pedestrians, which has been widely used in microscopic pedestrian movement simulation models. IPS is a conceptual framework to define the spatial extent within which all objects are considered as potential obstacles for each pedestrian when computing where to move next. The particular focus of our study was identifying the size and shape of IPS by examining observed gaze patterns of pedestrians. A series of experiments was conducted in a controlled laboratory environment, in which up to 4 participants walked on a platform at their natural speed. Their gaze patterns were recorded by a head-mounted eye tracker and walking paths by laser-range-scanner–based tracking systems at the frequency of 25Hz. Our findings are threefold: pedestrians pay much more attention to ground surfaces to detect immediate potential environmental hazards than fixating on obstacles; most of their fixations fall within a cone-shape area rather than a semicircle; and the attention paid to approaching pedestrians is not as high as that paid to static obstacles. These results led to an insight that the structure of IPS should be re-examined by researching directional characteristics of pedestrians’ vision

Potential Explosive Device on a Commuter Train: What drives train drivers to deviate from the security procedure?

Explosives pose a major threat to urban metro rail systems. Train drivers are therefore expected to regularly perform security procedures in response to reports of suspicious items on the train. This study was conducted to develop a multi-factorial account of deviation from one such security procedure by train drivers. By analysing data from focus group interviews with 30 train drivers, observation in a rail simulator, actual cab rides, and training material four major themes emerged to explain why drivers may deliberately deviate from following normative procedures designed by their managers. This included perceived pressure from safety and service goals, stress and fatigue during peak hours of operation, and workload created by security tasks. The results are organised in a succinct model that draws a link between drivers’ perceived pressure from multiple goals, and the changing driving conditions in which they perform. The study proposes ways for managers of urban commuter rail networks to understand the pressures that their drivers face in performing security tasks that are not part of their conventional job profile. The findings can inform changes in training methods, encourage drivers to discuss their reasons for deliberate rule violation, and support the design of security procedures more likely to be implemented

Mapping social vulnerability to flood hazard in Norfolk, England

In this paper, we present a method to assess social vulnerability through the creation of an Open Source Vulnerability Index (OS-VI). The OS-VI provides context to environmental hazards and allows NGOs and local agencies to better tailor services and provide targeted pre-emptive vulnerability reduction and resilience-building programmes. A deductive indicator-based approach is utilised to incorporate a wide range of vulnerability indicators known to influence vulnerability. Unlike many vulnerability indices, the OS-VI incorporates flood risk as well as the loss of capabilities and the importance of key services (health facilities and food stores) through the measurement of accessibility when determining an area's level of social vulnerability. The index was developed using open-source mapping and analysis software and is composed completely of open-source data from national data sets. The OS-VI was designed at the national level, with data for all proxy indicators available across the entirety of England and Wales. For this paper, a case study is presented concerned with one English county, Norfolk

Combining machine learning with computational hydrodynamics for prediction of tidal surge inundation at estuarine ports

Accurate forecasts of extreme storm surge water levels are vital for operators of major ports. Existing regional tide-surge models perform well at the open coast but their low spatial resolution makes their forecasts less reliable for ports located in estuaries. In December 2013, a tidal surge in the North Sea with an estimated return period of 760 years partially flooded the Port of Immingham in the Humber estuary, on the UK east coast. Damage to critical infrastructure caused several weeks of disruption to vital supply chains and highlighted a need for additional forecasting tools to supplement national surge warnings. In this paper, we show that Artificial Neural Networks (ANNs) can generate better short-term forecasts of extreme water levels at estuarine ports. Using Immingham as a test case, an ANN is configured to simulate the tidal surge residual using an input vector that includes observations of surge at distant tide gauges in NW Scotland, wind and atmospheric pressure, and the predicted astronomical tide at Immingham. The forecast surge time-series, combined with the astronomical tide, provides a boundary condition for a local high-resolution 2D hydrodynamic model that predicts flood extent and damage potential across the port. Although the forecasting horizon of the ANN is limited, 6 to 24 hour forecasts at Immingham achieve an accuracy comparable to or better than the UK national tide-surge model and at far less computational cost. Use of a local rather than a larger regional hydrodynamic model means that potential inundation can be simulated very rapidly at high spatial resolution. Validation against the 2013 surge shows that the hybrid ANN-hydrodynamic model generates realistic flood extents that can inform port resilience planning

Weak antiferromagnetism of J_eff=1/2 band in bilayer iridate Sr3Ir2O7

The antiferromagnetic structure of Sr3Ir2O7, the bilayer analogue of a spin-orbital Mott insulator Sr2IrO4, was revealed by resonant magnetic x-ray diffraction. Contrasting intensities of the magnetic diffraction at the Ir LIII and LII edges show a Jeff=1/2 character of the magnetic moment as is argued in Sr2IrO4. The magnitude of moment, however, was found to be smaller than that of Sr2IrO4 by a factor of 5-6, implying that Sr3Ir2O7 is no longer a Mott insulator but a weak antiferromagnet. An evident change of the temperature dependence of the resistivity at TN, from almost temperature-independent resistivity to insulating, strongly suggests that the emergent weak magnetism controls the charge gap. The magnetic structure was found to be an out-of-plane collinear antiferromagnetic ordering in contrast to the inplane canted antiferromagnetism in Sr2IrO4, originating from the strong bilayer antiferromagnetic coupling

Spin dynamics and antiferromagnetic order in PrBa2Cu4O8 studied by Cu nuclear respnance

Results of the nuclear resonance experiments for the planar Cu sites in PrBa2Cu4O8 are presented. The NMR spectrum at 1.5 K in zero magnetic field revealed an internal field of 6.1 T, providing evidence for an antiferromagnetic order of the planar Cu spins. This confirms that the CuO2 planes are insulating, therefore, the metallic conduction in this material is entirely due to the one-dimensional zigzag Cu2O2 chains. The results of the spin-lattice relaxation rates measured by zero field NQR above 245 K in the paramagnetic state are explained by the theory for a Heisenberg model on a square lattice.Comment: 4 pages, 2 figure

Pseudogap Induced Antiferromagnetic Spin Correlation in High-Temperature Superconductors

The pseudogap phenomena observed on cuprate high temperature superconductors are investigated based on the exact diagonalization method on the finite cluster t-J model. The results show the presence of the gap-like behavior in the temperature dependence of various magnetic properties; the NMR relaxation rate, the neutron scattering intensity and the static susceptibility. The calculated spin correlation function indicates that the pseudogap behavior arises associated with the development of the antiferromagnetic spin correlation with decreasing the temperature. The numerical results are presented to clarify the model parameter dependence, that covers the realistic experimental situation. The effect of the next-nearest neighbor hopping $t'$ is also studied.Comment: 7 pages, Revtex, with 10 eps figures, to appear in J. Phys. Soc. Jpn. (Vol. 70, No. 1

Exploring the nature of visual fixations on other pedestrians

How we look at other people may affect conclusions drawn about the effect of changes in lighting when this task needs to be done after dark. This paper reports further analysis of the distance and duration of fixation on other pedestrians, updating a previous review by considering a greater number of fixations and by examining the influence on these of other characteristics such as the relative direction of travel. This analysis provides further support for a tendency to fixate others at a distance of 15 m and for a duration of 500 ms

The sensitivity of the vortex filament method to different reconnection models

We present a detailed analysis on the effect of using different algorithms to model the reconnection of vortices in quantum turbulence, using the thin-filament approach. We examine differences between four main algorithms for the case of turbulence driven by a counterflow. In calculating the velocity field we use both the local induction approximation (LIA) and the full Biot-Savart integral. We show that results of Biot-Savart simulations are not sensitive to the particular reconnection method used, but LIA results are.Comment: 9 pages, 9 figure