964 resultados para Traffic Conflict Techniques
Resumo:
Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.
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It is well-established that prolonged exposure to workplace conflict, as a work stressor, is linked to physical illness and psychological dysfunction in employees (see Spector and Jex, 1998; Romanov, Appelberg, Honkasalo, and Koskenvuo, 1996; Skogstad, Einarsen, Torsheim, Aasland, and Hetland, 2007). In addition to the negative implications for physiological and psychological health, workplace conflict has been shown to influence employee behaviors that have consequences for organizational effectiveness (e.g., turnover and impaired performance; see Bowling and Beehr, 2006; De Dreu and Weingart, 2003). Further, research suggests that managers spend approximately 20 percent of their time managing conflict (Thomas, 1992; Baron, 1989). There also are substantial financial implications associated with workplace conflict. For example, in the United Kingdom, costs at the national level for sickness absence and replacement costs has been estimated to be close to £2 billion per annum (Hoel, Sparks, and Cooper, 2001).
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What has Mime got to do with Corporate Communication? As a professional Mime artist on both stage and screen for more than 25 years, the author has been adapting and applying the techniques of Mime to the corporate communication context over a number of years, coaching corporate CEO’s, Executives and Managers, representing both public and private sector corporations and organisations. This unusual inter-contextual skill transfer is the subject of both a book and series of VODCasts by the author (currently in the final stages of completion), which form part of the author’s Doctoral Research and from which this paper is substantially drawn. The author’s professional background is multi-disciplinary – encompassing theatre, television, media, music, tertiary education and corporate training contexts. It is also inter-disciplinary – concerned with the commonality of different artistic mediums and forms and how, where and why these professional disciplines: intersect; interact, and inform each other – and therefore how they support each other - rather than losing creative/professional opportunities because of areas where they might conflict. This paper examines in particular the physicality of presentation and communication – beyond ‘generic’ body-language analysis. It involves the analysis, manipulation and stylisation of human physicality to support and enhance individual inter-professional communication, and how mime performance skills specifically, inform that process. This paper discusses:- • how mime skills clarify and enhance inter-professional communication. • what adaptations need to be applied in that context • getting a ‘performance’ from ‘non-performers’
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Bauxite refinery residues are derived from the Bayer process by the digestion of crushed bauxite in concentrated caustic at elevated temperatures. Chemically, it comprises, in varying amounts (depending upon the composition of the starting bauxite), oxides of iron and titanium, residual alumina, sodalite, silica, and minor quantities of other metal oxides. Bauxite residues are being neutralised by seawater in recent years to reduce the alkalinity in bauxite residue, through the precipitation of hydrotalcite-like compounds and some other Mg, Ca, and Al hydroxide and carbonate minerals. A combination of X-ray diffraction (XRD) and vibrational spectroscopy techniques, including mid-infrared (IR), Raman, near-infrared (NIR), and UV-Visible, have been used to characterise bauxite residue and seawater neutralised bauxite residue. Both the ferrous (Fe2+) and ferric (Fe3+) ions within bauxite residue can be identified by their characteristic NIR bands, where ferrous ions produce a strong absorption band at around 9000 cm-1, while ferric ions produce two strong bands at 25000 and 14300 cm-1. The presence of adsorbed carbonate and hydroxide anions can be identified at around 5200 and 7000 cm-1, respectively, attributed to the 2nd overtone of the 1st fundamental overtones observed in the mid-IR spectra. The complex bands in the Raman and mid-IR spectra around 3500 cm-1 are assigned to the OH stretching vibrations of the various oxides present in bauxite residue, and water. The combination of carbonate and hydroxyl units and their fundamental overtones give rise to many of the features of the NIR spectra.
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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.
Resumo:
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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Traffic state estimation in an urban road network remains a challenge for traffic models and the question of how such a network performs remains a difficult one to answer for traffic operators. Lack of detailed traffic information has long restricted research in this area. The introduction of Bluetooth into the automotive world presented an alternative that has now developed to a stage where large-scale test-beds are becoming available, for traffic monitoring and model validation purposes. But how much confidence should we have in such data? This paper aims to give an overview of the usage of Bluetooth, primarily for the city-scale management of urban transport networks, and to encourage researchers and practitioners to take a more cautious look at what is currently understood as a mature technology for monitoring travellers in urban environments. We argue that the full value of this technology is yet to be realised, for the analytical accuracies peculiar to the data have still to be adequately resolved.
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This thesis investigates the impacts of variable speed limit on motorway speed variation and headway distribution. Initiative techniques of traffic flow categorisation study contribute in analysing the effects of variable speed limit on various traffic states. The project focuses on the speed harmonisation impacts within and across lanes as well as the uniformity of headway spread in the application of variable speed limit.
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Recurrence relations in mathematics form a very powerful and compact way of looking at a wide range of relationships. Traditionally, the concept of recurrence has often been a difficult one for the secondary teacher to convey to students. Closely related to the powerful proof technique of mathematical induction, recurrences are able to capture many relationships in formulas much simpler than so-called direct or closed formulas. In computer science, recursive coding often has a similar compactness property, and, perhaps not surprisingly, suffers from similar problems in the classroom as recurrences: the students often find both the basic concepts and practicalities elusive. Using models designed to illuminate the relevant principles for the students, we offer a range of examples which use the modern spreadsheet environment to powerfully illustrate the great expressive and computational power of recurrences.
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We first classify the state-of-the-art stream authentication problem in the multicast environment and group them into Signing and MAC approaches. A new approach for authenticating digital streams using Threshold Techniques is introduced. The new approach main advantages are in tolerating packet loss, up to a threshold number, and having a minimum space overhead. It is most suitable for multicast applications running over lossy, unreliable communication channels while, in same time, are pertain the security requirements. We use linear equations based on Lagrange polynomial interpolation and Combinatorial Design methods.
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With nine examples, we seek to illustrate the utility of the Renormalization Group approach as a unification of other asymptotic and perturbation methods.
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For the renewable energy sources whose outputs vary continuously, a Z-source current-type inverter has been proposed as a possible buck-boost alternative for grid-interfacing. With a unique X-shaped LC network connected between its dc power source and inverter topology, Z-source current-type inverter is however expected to suffer from compounded resonant complications in addition to those associated with its second-order output filter. To improve its damping performance, this paper proposes the careful integration of Posicast or three-step compensators before the inverter pulse-width modulator for damping triggered resonant oscillations. In total, two compensators are needed for wave-shaping the inverter boost factor and modulation ratio, and they can conveniently be implemented using first-in first-out stacks and embedded timers of modern digital signal processors widely used in motion control applications. Both techniques are found to damp resonance of ac filter well, but for cases of transiting from current-buck to boost state, three-step technique is less effective due to the sudden intermediate discharging interval introduced by its non-monotonic stepping (unlike the monotonic stepping of Posicast damping). These findings have been confirmed both in simulations and experiments using an implemented laboratory prototype.
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Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.
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This paper proposes a combination of source-normalized weighted linear discriminant analysis (SN-WLDA) and short utterance variance (SUV) PLDA modelling to improve the short utterance PLDA speaker verification. As short-length utterance i-vectors vary with the speaker, session variations and phonetic content of the utterance (utterance variation), a combined approach of SN-WLDA projection and SUV PLDA modelling is used to compensate the session and utterance variations. Experimental studies have found that a combination of SN-WLDA and SUV PLDA modelling approach shows an improvement over baseline system (WCCN[LDA]-projected Gaussian PLDA (GPLDA)) as this approach effectively compensates the session and utterance variations.