890 resultados para endogenous risk perception


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Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

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Post-earthquake fire (PEF) is considered one of the most high risk and complicated problems affecting buildings in urban areas and can cause even more damage than the earthquake itself. However, most standards and codes ignore the implications of PEF and so buildings are not normally designed with PEF in mind. What is needed is for PEF factors to be routinely scrutinized and codified as part of the design process. A systematic application is presented as a means of mitigating the risk of PEF in urban buildings. This covers both existing buildings, in terms of retrofit solutions, and those yet to be designed, where a PEF factor is proposed. To ensure the mitigation strategy meets the defined criteria, a minimum time is defined – the safety guaranteed time target – where the safety of the inhabitants in a building is guaranteed.

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A bioeconomic model was developed to evaluate the potential performance of brown tiger prawn stock enhancement in Exmouth Gulf, Australia. This paper presents the framework for the bioeconomic model and risk assessment for all components of a stock enhancement operation, i.e. hatchery, grow-out, releasing, population dynamics, fishery, and monitoring, for a commercial scale enhancement of about 100 metric tonnes, a 25% increase in average annual catch in Exmouth Gulf. The model incorporates uncertainty in estimates of parameters by using a distribution for the parameter over a certain range, based on experiments, published data, or similar studies. Monte Carlo simulation was then used to quantify the effects of these uncertainties on the model-output and on the economic potential of a particular production target. The model incorporates density-dependent effects in the nursery grounds of brown tiger prawns. The results predict that a release of 21 million 1 g prawns would produce an estimated enhanced prawn catch of about 100 t. This scale of enhancement has a 66.5% chance of making a profit. The largest contributor to the overall uncertainty of the enhanced prawn catch was the post-release mortality, followed by the density-dependent mortality caused by released prawns. These two mortality rates are most difficult to estimate in practice and are much under-researched in stock enhancement.

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It has been shown that active control of locomotion increases accuracy and precision of nonvisual space perception, but psychological mechanisms of this enhancement are poorly understood. The present study explored a hypothesis that active control of locomotion enhances space perception by facilitating crossmodal interaction between visual and nonvisual spatial information. In an experiment, blindfolded participants walked along a linear path under one of the following two conditions: (1) They walked by themselves following a guide rope; and (2) they were led by an experimenter. Subsequently, they indicated the walked distance by tossing a beanbag to the origin of locomotion. The former condition gave participants greater control of their locomotion, and thus represented a more active walking condition. In addition, before each trial, half the participants viewed the room in which they performed the distance perception task. The other half remained blindfolded throughout the experiment. Results showed that although the room was devoid of any particular cues for walked distances, visual knowledge of the surroundings improved the precision of nonvisual distance perception. Importantly, however, the benefit of preview was observed only when participants walked more actively. This indicates that active control of locomotion allowed participants to better utilize their visual memory of the environment for perceiving nonvisually encoded distance, suggesting that active control of locomotion served as a catalyst for integrating visual and nonvisual information to derive spatial representations of higher quality.

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Engineering design processes are necessary to attain the requisite standards of integrity for high-assurance safety-related systems. Additionally, human factors design initiatives can provide critical insights that parameterise their development. Unfortunately, the popular perception of human factors as a “forced marriage” between engineering and psychology often provokes views where the ‘human factor’ is perceived as a threat to systems design. Some popular performance-based standards for developing safety-related systems advocate identifying and managing human factors throughout the system lifecycle. However, they also have a tendency to fall short in their guidance on the application of human factors methods and tools, let alone how the outputs generated can be integrated in to various stages of the design process. This case study describes a project that converged engineering with human factors to develop a safety argument for new low-cost railway level crossing technology for system-wide implementation in Australia. The paper enjoins the perspectives of a software engineer and cognitive psychologist and their involvement in the project over two years of collaborative work to develop a safety argument for low-cost level crossing technology. Safety and reliability requirements were informed by applying human factors analytical tools that supported the evaluation and quantification of human reliability where users interfaced with the technology. The project team was confronted with significant challenges in cross-disciplinary engagement, particularly with the complexities of dealing with incongruences in disciplinary language. They were also encouraged to think ‘outside the box’ as to how users of a system interpreted system states and ehaviour. Importantly, some of these states, while considered safe within the boundary of the constituent systems that implemented safety-related functions, could actually lead the users to engage in deviant behaviour. Psychology explained how user compliance could be eroded to levels that effectively undermined levels of risk reduction afforded by systems. Linking the engineering and psychology disciplines intuitively, overall safety performance was improved by introducing technical requirements and making design decisions that minimized the system states and behaviours that led to user deviancy. As a commentary on the utility of transdisciplinary collaboration for technical specification, the processes used to bridge the two disciplines are conceptualised in a graphical model.