925 resultados para UAS Collision Avoidance


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With increasing rate of shipping traffic, the risk of collisions in busy and congested port waters is expected to rise. However, due to low collision frequencies it is difficult to analyze such risk in a sound statistical manner. This study aims at examining the occurrence of traffic conflicts in order to understand the characteristics of vessels involved in navigational hazards. A binomial logit model was employed to evaluate the association of vessel attributes and the kinematic conditions with conflict severity levels. Results show a positive association for vessels of small gross tonnage, overall vessel length, vessel height and draft with conflict risk. Conflicts involving a pair of dynamic vessels sailing at low speeds also have similar effects.

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With increasing rate of shipping traffic, the risk of collisions in busy and congested port waters is likely to rise. However, due to low collision frequencies in port waters, it is difficult to analyze such risk in a sound statistical manner. A convenient approach of investigating navigational collision risk is the application of the traffic conflict techniques, which have potential to overcome the difficulty of obtaining statistical soundness. This study aims at examining port water conflicts in order to understand the characteristics of collision risk with regard to vessels involved, conflict locations, traffic and kinematic conditions. A hierarchical binomial logit model, which considers the potential correlations between observation-units, i.e., vessels, involved in the same conflicts, is employed to evaluate the association of explanatory variables with conflict severity levels. Results show higher likelihood of serious conflicts for vessels of small gross tonnage or small overall length. The probability of serious conflict also increases at locations where vessels have more varied headings, such as traffic intersections and anchorages; becoming more critical at night time. Findings from this research should assist both navigators operating in port waters as well as port authorities overseeing navigational management.

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Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

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Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers exhibit safe behaviors. All the microscopic traffic simulation models include a car following model. This paper highlights the limitations of the Gipps car following model ability to emulate driver behavior for safety study purposes. A safety adapted car following model based on the Gipps car following model is proposed to simulate unsafe vehicle movements, with safety indicators below critical thresholds. The modifications are based on the observations of driver behavior in real data and also psychophysical notions. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time To Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against them. The results from simulation tests illustrate that the proposed model can predict the safety metrics better than the generic Gipps model. The outcome of this paper can potentially facilitate assessing and predicting traffic safety using microscopic simulation.

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Charitable organisations have remained exempt from income tax in Australia since the first comprehensive state income tax legislation in 18841 through to the current Income Tax Assessment Act 1977. The charitable exemption was also part of the English income tax legislation from its inception in 1799. The Federal Treasurer has released exposure draft legislation which seeks to remove taxation exemptions from some tax exempt organisations that perform any of their activities outside Australia or make trust distributions overseas. The proposed legislation is in response to alleged tax avoidance arrangements which involve tax exempt organisations and charitable trusts. The paper begins by describing the current charity tax exemption provisions under the Income Tax Assessment Act (ITAA). It then turns to tracing the background policy history of the amendments which appear to be at odds with the form and intent of the proposed provisions. The proposed amendments and their practical consequences are then closely scrutinised and found wanting in a number of respects. Alternative strategies are suggested to arrive at an equitable solution to the avoidance mischief.

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With the emergence of Unmanned Aircraft Systems (UAS) there is a growing need for safety standards and regulatory frameworks to manage the risks associated with their operations. The primary driver for airworthiness regulations (i.e., those governing the design, manufacture, maintenance and operation of UAS) are the risks presented to people in the regions overflown by the aircraft. Models characterising the nature of these risks are needed to inform the development of airworthiness regulations. The output from these models should include measures of the collective, individual and societal risk. A brief review of these measures is provided. Based on the review, it was determined that the model of the operation of an UAS over inhabited areas must be capable of describing the distribution of possible impact locations, given a failure at a particular point in the flight plan. Existing models either do not take the impact distribution into consideration, or propose complex and computationally expensive methods for its calculation. A computationally efficient approach for estimating the boundary (and in turn area) of the impact distribution for fixed wing unmanned aircraft is proposed. A series of geometric templates that approximate the impact distributions are derived using an empirical analysis of the results obtained from a 6-Degree of Freedom (6DoF) simulation. The impact distributions can be aggregated to provide impact footprint distributions for a range of generic phases of flight and missions. The maximum impact footprint areas obtained from the geometric template are shown to have a relative error of typically less than 1% compared to the areas calculated using the computationally more expensive 6DoF simulation. Computation times for the geometric models are on the order of one second or less, using a standard desktop computer. Future work includes characterising the distribution of impact locations within the footprint boundaries.

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The ability to perform autonomous emergency (forced) landings is one of the key technology enablers identified for UAS. This paper presents the flight test results of forced landings involving a UAS, in a controlled environment, and which was conducted to ascertain the performances of previously developed (and published) path planning and guidance algorithms. These novel 3-D nonlinear algorithms have been designed to control the vehicle in both the lateral and longitudinal planes of motion. These algorithms have hitherto been verified in simulation. A modified Boomerang 60 RC aircraft is used as the flight test platform, with associated onboard and ground support equipment sourced Off-the-Shelf or developed in-house at the Australian Research Centre for Aerospace Automation (ARCAA). HITL simulations were conducted prior to the flight tests and displayed good landing performance, however, due to certain identified interfacing errors, the flight results differed from that obtained in simulation. This paper details the lessons learnt and presents a plausible solution for the way forward.

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While frontline employees (FLEs) are known to bend the rules or act in non-conforming ways for customers, the phenomenon of FLEs over-servicing customers is not well understood. This paper proposes a behavioural concept termed customer-oriented deviance (COD) and a conceptual model of its key drivers. Using a qualitative study involving 22 in-depth interviews with FLEs, the analysis reveals three categories of COD behaviours: deviant service adaptation (DSA), deviant service communication (DSC), and deviant use of resources (DUR). The drivers of COD are categorised as individual (risk-taking, service aptitude, and pro-social moral values), situational (resource availability, social capita with customers, legitimacy of customer problems, and avoidance of hassles), and organisational (unconducive service climate and anticipated rewards). This paper contributes to understanding how and why FLEs over-service customers and extends current research by exploring multiple categories of behaviours within a services marketing context.

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Road traffic accidents can be reduced by providing early warning to drivers through wireless ad hoc networks. When a vehicle detects an event that may lead to an imminent accident, the vehicle disseminates emergency messages to alert other vehicles that may be endangered by the accident. In many existing broadcast-based dissemination schemes, emergency messages may be sent to a large number of vehicles in the area and can be propagated to only one direction. This paper presents a more efficient context aware multicast protocol that disseminates messages only to endangered vehicles that may be affected by the emergency event. The endangered vehicles can be identified by calculating the interaction among vehicles based on their motion properties. To ensure fast delivery, the dissemination follows a routing path obtained by computing a minimum delay tree. The multicast protocol uses a generalized approach that can support any arbitrary road topology. The performance of the multicast protocol is compared with existing broadcast protocols by simulating chain collision accidents on a typical highway. Simulation results show that the multicast protocol outperforms the other protocols in terms of reliability, efficiency, and latency.

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Vehicular safety applications, such as cooperative collision warning systems, rely on beaconing to provide situational awareness that is needed to predict and therefore to avoid possible collisions. Beaconing is the continual exchange of vehicle motion-state information, such as position, speed, and heading, which enables each vehicle to track its neighboring vehicles in real time. This work presents a context-aware adaptive beaconing scheme that dynamically adapts the beaconing repetition rate based on an estimated channel load and the danger severity of the interactions among vehicles. The safety, efficiency, and scalability of the new scheme is evaluated by simulating vehicle collisions caused by inattentive drivers under various road traffic densities. Simulation results show that the new scheme is more efficient and scalable, and is able to improve safety better than the existing non-adaptive and adaptive rate schemes.

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Rates of bicycle commuting currently hover around 1 - 2% in most Australian capital cities, although 17.8% of Australians report riding at least once per week. The most commonly stated reason for choosing not to ride a bicycle is fear of motorised vehicles. This paper sets out to examine the literature and offer a commentary regarding the role fear plays as a barrier to bicycle riding. The paper also provides an estimate of the relative risk of driving and riding, on a per trip basis. An analysis of the existing literature finds fear of motorised traffic to be disproportionate to actual levels of risk to bicycle riders. Moreover, the health benefits of bicycling outweigh the risks of collision. Rather than actual collisions forming the basis of people’s fear, it appears plausible that near collisions (which occur far more frequently) may be a significant cause for the exaggerated levels of fear associated with bicycle riding. In order to achieve the Australian Government’s goal of doubling bike riding participation, this review suggests it will be necessary to counter fear through the creation of a low risk traffic environment (both perceived and real), involving marketing/promotional campaigns and the development of a comprehensive bicycle infrastructure network and lower speed limits.

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Traffic safety studies mandate more than what existing micro-simulation models can offer as they postulate that every driver exhibits a safe behaviour. All the microscopic traffic simulation models are consisting of a car-following model and the Gazis–Herman–Rothery (GHR) car-following model is a widely used model. This paper highlights the limitations of the GHR car-following model capability to model longitudinal driving behaviour for safety study purposes. This study reviews and compares different version of the GHR model. To empower the GHR model on precise metrics reproduction a new set of car-following model parameters is offered to simulate unsafe vehicle conflicts. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time to Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against the generic versions of the GHR model. The results from simulation tests illustrate that the proposed model does predict the safety metrics better than the generic GHR model. Additionally it can potentially facilitate assessing and predicting traffic facilities’ safety using microscopic simulation. The new model can predict Near-miss rear-end crashes.

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Exceeding the speed limit and driving too fast for the conditions are regularly cited as significant contributing factors in traffic crashes, particularly fatal and serious injury crashes. Despite an extensive body of research highlighting the relationship between increased vehicle speeds and crash risk and severity, speeding remains a pervasive behaviour on Australian roads. The development of effective countermeasures designed to reduce the prevalence of speeding behaviour requires that this behaviour is well understood. The primary aim of this program of research was to develop a better understanding of the influence of drivers’ perceptions and attitudes toward police speed enforcement on speeding behaviour. Study 1 employed focus group discussions with 39 licensed drivers to explore the influence of perceptions relating to specific characteristics of speed enforcement policies and practices on drivers’ attitudes towards speed enforcement. Three primary factors were identified as being most influential: site selection; visibility; and automaticity (i.e., whether the enforcement approach is automated/camera-based or manually operated). Perceptions regarding these enforcement characteristics were found to influence attitudes regarding the perceived legitimacy and transparency of speed enforcement. Moreover, misperceptions regarding speed enforcement policies and practices appeared to also have a substantial impact on attitudes toward speed enforcement, typically in a negative direction. These findings have important implications for road safety given that prior research has suggested that the effectiveness of speed enforcement approaches may be reduced if efforts are perceived by drivers as being illegitimate, such that they do little to encourage voluntary compliance. Study 1 also examined the impact of speed enforcement approaches varying in the degree of visibility and automaticity on self-reported willingness to comply with speed limits. These discussions suggested that all of the examined speed enforcement approaches (see Section 1.5 for more details) generally showed potential to reduce vehicle speeds and encourage compliance with posted speed limits. Nonetheless, participant responses suggested a greater willingness to comply with approaches operated in a highly visible manner, irrespective of the corresponding level of automaticity of the approach. While less visible approaches were typically associated with poorer rates of driver acceptance (e.g., perceived as “sneaky” and “unfair”), participants reported that such approaches would likely encourage long-term and network-wide impacts on their own speeding behaviour, as a function of the increased unpredictability of operations and increased direct (specific deterrence) and vicarious (general deterrence) experiences with punishment. Participants in Study 1 suggested that automated approaches, particularly when operated in a highly visible manner, do little to encourage compliance with speed limits except in the immediate vicinity of the enforcement location. While speed cameras have been criticised on such grounds in the past, such approaches can still have substantial road safety benefits if implemented in high-risk settings. Moreover, site-learning effects associated with automated approaches can also be argued to be a beneficial by-product of enforcement, such that behavioural modifications are achieved even in the absence of actual enforcement. Conversely, manually operated approaches were reported to be associated with more network-wide impacts on behaviour. In addition, the reported acceptance of such methods was high, due to the increased swiftness of punishment, ability for additional illegal driving behaviours to be policed and the salutary influence associated with increased face-to-face contact with authority. Study 2 involved a quantitative survey conducted with 718 licensed Queensland drivers from metropolitan and regional areas. The survey sought to further examine the influence of the visibility and automaticity of operations on self-reported likelihood and duration of compliance. Overall, the results from Study 2 corroborated those of Study 1. All examined approaches were again found to encourage compliance with speed limits, such that all approaches could be considered to be “effective”. Nonetheless, significantly greater self-reported likelihood and duration of compliance was associated with visibly operated approaches, irrespective of the corresponding automaticity of the approach. In addition, the impact of automaticity was influenced by visibility; such that significantly greater self-reported likelihood of compliance was associated with manually operated approaches, but only when they are operated in a less visible fashion. Conversely, manually operated approaches were associated with significantly greater durations of self-reported compliance, but only when they are operated in a highly visible manner. Taken together, the findings from Studies 1 and 2 suggest that enforcement efforts, irrespective of their visibility or automaticity, generally encourage compliance with speed limits. However, the duration of these effects on behaviour upon removal of the enforcement efforts remains questionable and represents an area where current speed enforcement practices could possibly be improved. Overall, it appears that identifying the optimal mix of enforcement operations, implementing them at a sufficient intensity and increasing the unpredictability of enforcement efforts (e.g., greater use of less visible approaches, random scheduling) are critical elements of success. Hierarchical multiple regression analyses were also performed in Study 2 to investigate the punishment-related and attitudinal constructs that influence self-reported frequency of speeding behaviour. The research was based on the theoretical framework of expanded deterrence theory, augmented with three particular attitudinal constructs. Specifically, previous research examining the influence of attitudes on speeding behaviour has typically focussed on attitudes toward speeding behaviour in general only. This research sought to more comprehensively explore the influence of attitudes by also individually measuring and analysing attitudes toward speed enforcement and attitudes toward the appropriateness of speed limits on speeding behaviour. Consistent with previous research, a number of classical and expanded deterrence theory variables were found to significantly predict self-reported frequency of speeding behaviour. Significantly greater speeding behaviour was typically reported by those participants who perceived punishment associated with speeding to be less certain, who reported more frequent use of punishment avoidance strategies and who reported greater direct experiences with punishment. A number of interesting differences in the significant predictors among males and females, as well as younger and older drivers, were reported. Specifically, classical deterrence theory variables appeared most influential on the speeding behaviour of males and younger drivers, while expanded deterrence theory constructs appeared more influential for females. These findings have important implications for the development and implementation of speeding countermeasures. Of the attitudinal factors, significantly greater self-reported frequency of speeding behaviour was reported among participants who held more favourable attitudes toward speeding and who perceived speed limits to be set inappropriately low. Disappointingly, attitudes toward speed enforcement were found to have little influence on reported speeding behaviour, over and above the other deterrence theory and attitudinal constructs. Indeed, the relationship between attitudes toward speed enforcement and self-reported speeding behaviour was completely accounted for by attitudes toward speeding. Nonetheless, the complexity of attitudes toward speed enforcement are not yet fully understood and future research should more comprehensively explore the measurement of this construct. Finally, given the wealth of evidence (both in general and emerging from this program of research) highlighting the association between punishment avoidance and speeding behaviour, Study 2 also sought to investigate the factors that influence the self-reported propensity to use punishment avoidance strategies. A standard multiple regression analysis was conducted for exploratory purposes only. The results revealed that punishment-related and attitudinal factors significantly predicted approximately one fifth of the variance in the dependent variable. The perceived ability to avoid punishment, vicarious punishment experience, vicarious punishment avoidance and attitudes toward speeding were all significant predictors. Future research should examine these relationships more thoroughly and identify additional influential factors. In summary, the current program of research has a number of implications for road safety and speed enforcement policy and practice decision-making. The research highlights a number of potential avenues for the improvement of public education regarding enforcement efforts and provides a number of insights into punishment avoidance behaviours. In addition, the research adds strength to the argument that enforcement approaches should not only demonstrate effectiveness in achieving key road safety objectives, such as reduced vehicle speeds and associated crashes, but also strive to be transparent and legitimate, such that voluntary compliance is encouraged. A number of potential strategies are discussed (e.g., point-to-point speed cameras, intelligent speed adaptation. The correct mix and intensity of enforcement approaches appears critical for achieving optimum effectiveness from enforcement efforts, as well as enhancements in the unpredictability of operations and swiftness of punishment. Achievement of these goals should increase both the general and specific deterrent effects associated with enforcement through an increased perceived risk of detection and a more balanced exposure to punishment and punishment avoidance experiences.

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Research interest in pedestrian behaviour spans the retail industry, emergency services, urban planners and other agencies. Most models to simulate and model pedestrian movement can be distinguished on the basis of geographical scale, from the micro-scale movement of obstacle avoidance, through the meso-scale of individuals planning multi-stop shopping trips, up to the macro-scale of overall flow of masses of people between places. In this paper, route-choice decision-making model is devised for modelling passengers flow in airport terminal. A set of devised advanced traits of passengers is firstly proposed. Advanced traits take into account a passenger’s cognitive preferences and demonstrate underlying motivations of route-choice decisions. Although the activities of passengers are normally regarded as stochastic and sometimes unpredictable, real scenarios of passenger flows are basically feasible to be compared with virtual simulations in terms of tactical route-choice decision-making. Passengers in the model are as intelligent agents who possess a bunch of initial basic traits and are categorized into five distinguish groups in terms of routing preferences. Route choices are consecutively determined by inferring current advanced traits according to the utility matrix.