105 resultados para Railroad trains.


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When arranging a place to meet in Brisbane, it has become almost second nature to say, “I’ll meet you outside Hungry Jack’s,” which is located in Queen Street Mall. In Melbourne, the common saying is, “I’ll meet you under the clocks,” which refers to the row of clocks above the main entrance to Flinders Street Railway Station. The saying “I’ll meet you under the clocks” is loaded with memory and history for most Melbournians—from WWII farewells to after school meetings. The clocks, and the station, have become part of the symbolic culture of the city. A feature of these two sites is the diversity of people who arrange to meet there, ranging from business people, tourists, teenagers, lovers, families to local schoolchildren. These two spaces cross boundaries of exclusion and enable people to feel as though they belong the city. While it seems appropriate for people to arrange to meet at a railway station, it is interesting that many people who meet at Flinders Street Station do not travel by train to arrive there: some walk; some take the tram and then walk; others arrive by bus. Similarly, most of the many people who arrange to meet outside Hungry Jack’s in Brisbane do not intend to enter the store...

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In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. The sugarcane transport system is very complex and uses daily schedules, consisting of a set of locomotives runs, to satisfy the requirements of the mill and harvesters. The total cost of sugarcane transport operations is very high; over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. Efficient schedules for sugarcane transport can reduce the cost and limit the negative effects that this system can have on the raw sugar production system. There are several benefits to formulating the train scheduling problem as a blocking parallel-machine job shop scheduling (BPMJSS) problem, namely to prevent two trains passing in one section at the same time; to keep the train activities (operations) in sequence during each run (trip) by applying precedence constraints; to pass the trains on one section in the correct order (priorities of passing trains) by applying disjunctive constraints; and, to ease passing trains by solving rail conflicts by applying blocking constraints and Parallel Machine Scheduling. Therefore, the sugarcane rail operations are formulated as BPMJSS problem. A mixed integer programming and constraint programming approaches are used to describe the BPMJSS problem. The model is solved by the integration of constraint programming, mixed integer programming and search techniques. The optimality performance is tested by Optimization Programming Language (OPL) and CPLEX software on small and large size instances based on specific criteria. A real life problem is used to verify and validate the approach. Constructive heuristics and new metaheuristics including simulated annealing and tabu search are proposed to solve this complex and NP-hard scheduling problem and produce a more efficient scheduling system. Innovative hybrid and hyper metaheuristic techniques are developed and coded using C# language to improve the solutions quality and CPU time. Hybrid techniques depend on integrating heuristic and metaheuristic techniques consecutively, while hyper techniques are the complete integration between different metaheuristic techniques, heuristic techniques, or both.

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Children and the environment cover a broad, interdisciplinary field of research and practice. The social sciences often use the word “environment” to mean the social, political, or economic context of children’s lives, but this bibliography covers physical settings. It focuses on a place-based scale that children can see, hear, taste, smell, touch, and navigate: not large, abstract scales such as national identities or population dynamics, or small scales such as environmental impacts on genes or cell functions. Attention to the everyday settings of children’s lives grew in the 18th century, when Romantic literature introduced the theme of children and nature. In the 19th century, concern for children’s welfare included an interest in conditions for children in burgeoning industrial cities, and justifications for early streetcar and railroad suburbs included claims that they would save children from the dangers of cities and provide the healthful benefits of natural surroundings. In the 20th century, academic disciplines developed different lines of inquiry about the impact of the physical environment on children and how children relate to places: ethnographic studies of children in different parts of the world in the fields of anthropology and geography; sociological studies of different populations of children in different settings; educational research on the learning opportunities that different school and out-of-school settings afford; medical research to understand disease vectors and the impact of pollutants on children; and efforts in the field of environment and behavior research more broadly, to understand how built and designed environments affect children physically, cognitively, socially, and emotionally. At the beginning of the 21st century, children and the environment is an active area of inquiry seeking to understand rapidly changing conditions for children as the world urbanizes, opportunities for free play outdoors and independent mobility erode in many parts of the world, media environments consume more of children’s time, and awareness grows that children need opportunities to contribute to creating sustainable societies.

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There is consistent evidence showing that driver behaviour contributes to crashes and near miss incidents at railway level crossings (RLXs). The development of emerging Vehicle-to-Vehicle and Vehicle-to-Infrastructure technologies is a highly promising approach to improve RLX safety. To date, research has not evaluated comprehensively the potential effects of such technologies on driving behaviour at RLXs. This paper presents an on-going research programme assessing the impacts of such new technologies on human factors and drivers’ situational awareness at RLX. Additionally, requirements for the design of such promising technologies and ways to display safety information to drivers were systematically reviewed. Finally, a methodology which comprehensively assesses the effects of in-vehicle and road-based interventions warning the driver of incoming trains at RLXs is discussed, with a focus on both benefits and potential negative behavioural adaptations. The methodology is designed for implementation in a driving simulator and covers compliance, control of the vehicle, distraction, mental workload and drivers’ acceptance. This study has the potential to provide a broad understanding of the effects of deploying new in-vehicle and road-based technologies at RLXs and hence inform policy makers on safety improvements planning for RLX.

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Recently updated information has raised a concern over not only the existing cost-ineffective design method but also the unrealistic analysis mode of railroad prestressed concrete sleepers. Because of the deficient knowledge in the past, railway civil engineers have been mostly aware of the over-conservative design methods for structural components in any railway track, which rely on allowable stresses and material strength reductions. Based on a number of proven experiments and field data, it is believed that the concrete sleepers which complied with the allowable stress concept possess unduly untapped fracture toughness. A collaborative research project run by the Australian Cooperative Research Centre for Railway Engineering and Technologies (RailCRC) was initiated to ascertain the reserved capacity of Australian railway prestressed concrete sleepers designed using the existing design code. The findings have led to the development of a new limit states design concept. This briefing highlights the conventional and the new limit states design philosophies and their implication to both the railway and the public community.

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This paper describes an innovative platform that facilitates the collection of objective safety data around occurrences at railway level crossings using data sources including forward-facing video, telemetry from trains and geo-referenced asset and survey data. This platform is being developed with support by the Australian rail industry and the Cooperative Research Centre for Rail Innovation. The paper provides a description of the underlying accident causation model, the development methodology and refinement process as well as a description of the data collection platform. The paper concludes with a brief discussion of benefits this project is expected to provide the Australian rail industry.

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Travelling by public transport is usually regarded as boring and uninteresting. Refraining from talking to the stranger next to you may be due to limitations that are self-imposed and further corroborated by social expectations and cultural norms that govern behaviour in public space. Our design research into passenger interactions on board of urban commuter trains has informed the development of the TrainRoulette prototype – a mobile app for situated, real-time chats between train passengers. We study the impact of our design intervention on shaping perceptions of the train journey experience. Moreover, we are interested in the implications of such ICT-mediated interactions within train journeys for stimulating social offline interactions and new forms of passenger engagement.

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Modern trains with different axle configurations, speeds and loads are used in railway networks. As a result, one of the most important questions of the mangers involved in bridge managements systems (BMS) is how these changes affect the structural behavior of the critical components of the railway bridges. Although researchers have conducted, many investigations on the dynamic effects of the moving loads on bridges, the influence of the changes in the speed of the train on the demand by capacity ratios of the different critical components of the bridge have not yet been properly studied. This study is important, because different components with different capacities and roles for carrying loads in the structure may be affected differently. To investigate the above phenomenon in this research, a structural model of a simply supported bridge is developed. It will be verified that the dynamic behavior of this bridge is similar to a group of railway bridges in Australia. Demand by capacity ratios of the critical components of the bridge, when it is subjected to a train load with different speeds will be calculated. The results show that the effect of increase or decrease of speed should not be underestimated. The outcome is very significant as it is contrary to what is currently expected, i.e. by reducing the speed of the train, the demand by capacity ratio of components may increase and make the bridge unsafe for carrying live load.

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In Australia, and elsewhere, the movement of trains on long-haul rail networks is usually planned in advance. Typically, a train plan is developed to confirm that the required train movements and track maintenance activities can occur. The plan specifies when track segments will be occupied by particular trains and maintenance activities. On the day of operation, a train controller monitors and controls the movement of trains and maintenance crews, and updates the train plan in response to unplanned disruptions. It can be difficult to predict how good a plan will be in practice. The main performance indicator for a train service should be reliability - the proportion of trains running the service that complete at or before the scheduled time. We define the robustness of a planned train service to be the expected reliability. The robustness of individual train services and for a train plan as a whole can be estimated by simulating the train plan many times with random, but realistic, perturbations to train departure times and segment durations, and then analysing the distributions of arrival times. This process can also be used to set arrival times that will achieve a desired level of robustness for each train service.

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The Bluetooth technology is being increasingly used to track vehicles throughout their trips, within urban networks and across freeway stretches. One important opportunity offered by this type of data is the measurement of Origin-Destination patterns, emerging from the aggregation and clustering of individual trips. In order to obtain accurate estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. These issues mainly stem from the use of the Bluetooth technology amongst drivers, and the physical properties of the Bluetooth sensors themselves. First, not all cars are equipped with discoverable Bluetooth devices and the Bluetooth-enabled vehicles may belong to some small socio-economic groups of users. Second, the Bluetooth datasets include data from various transport modes; such as pedestrian, bicycles, cars, taxi driver, buses and trains. Third, the Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be extracted from the data. Finally, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold. We first give a comprehensive overview of the aforementioned issues. Further, we propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data. We postulate that the methods introduced by this paper are the first crucial steps that need to be followed in order to compute accurate Origin-Destination matrices in urban road networks.

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Collisions between pedestrians and vehicles continue to be a major problem throughout the world. Pedestrians trying to cross roads and railway tracks without any caution are often highly susceptible to collisions with vehicles and trains. Continuous financial, human and other losses have prompted transport related organizations to come up with various solutions addressing this issue. However, the quest for new and significant improvements in this area is still ongoing. This work addresses this issue by building a general framework using computer vision techniques to automatically monitor pedestrian movements in such high-risk areas to enable better analysis of activity, and the creation of future alerting strategies. As a result of rapid development in the electronics and semi-conductor industry there is extensive deployment of CCTV cameras in public places to capture video footage. This footage can then be used to analyse crowd activities in those particular places. This work seeks to identify the abnormal behaviour of individuals in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM), Full-2D HMM and Spatial HMM to model the normal activities of people. The outliers of the model (i.e. those observations with insufficient likelihood) are identified as abnormal activities. Location features, flow features and optical flow textures are used as the features for the model. The proposed approaches are evaluated using the publicly available UCSD datasets, and we demonstrate improved performance using a Semi-2D Hidden Markov Model compared to other state of the art methods. Further we illustrate how our proposed methods can be applied to detect anomalous events at rail level crossings.

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A technique for analysing exhaust emission plumes from unmodified locomotives under real world conditions is described and applied to the task of characterizing plumes from railway trains servicing an Australian shipping port. The method utilizes the simultaneous measurement, downwind of the railway line, of the following pollutants; particle number, PM2.5 mass fraction, SO2, NOx and CO2, with the last of these being used as an indicator of fuel combustion. Emission factors are then derived, in terms of number of particles and mass of pollutant emitted per unit mass of fuel consumed. Particle number size distributions are also presented. The practical advantages of the method are discussed including the capacity to routinely collect emission factor data for passing trains and to thereby build up a comprehensive real world database for a wide range of pollutants. Samples from 56 train movements were collected, analyzed and presented. The quantitative results for emission factors are: EF(N)=(1.7±1)×1016 kg-1, EF(PM2.5)= (1.1±0.5) g·kg-1, EF(NOx)= (28±14) g·kg-1, and EF(SO2 )= (1.4±0.4) g·kg-1. The findings are compared with comparable previously published work. Statistically significant (p<α, α=0.05) correlations within the group of locomotives sampled were found between the emission factors for particle number and both SO2 and NOx.

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Improving safety at rail level crossings is an important part of both road and rail safety strategies. While low in number, crashes between vehicles and trains at level crossings are catastrophic events typically involving multiple fatalities and serious injuries. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles with eye and head tracking, provide researchers with the opportunity to further understand driver behaviour at such crossings in ways not previously possible. This paper describes a study conducted to further understand the factors that shape driver behaviour at rail level crossings using instrumented vehicles. Twenty-two participants drove an On-Road Test Vehicle (ORTeV) on a predefined route in regional Victoria with a mix of both active (flashing lights with/without boom barriers) and passively controlled (stop, give way) crossings. Data collected included driving performance data, head checks, and interview data to capture driver strategies. The data from an integrated suite of methods demonstrated clearly how behaviour differs at active and passive level crossings, particularly for inexperienced drivers. For example, the head check data clearly show the reliance and expectancies of inexperienced drivers for active warnings even when approaching passively controlled crossings. These studies provide very novel and unique insights into how level crossing design and warnings shape driver behaviour.

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Aim Collisions between trains and pedestrians are the most likely to result in severe injuries and fatalities when compared to other types of rail crossing accidents. Currently, there is a growing emphasis towards developing effective interventions designed to reduce the prevalence of train–pedestrian collisions. This paper reviews what is currently known regarding the personal and environmental factors that contribute to train–pedestrian collisions, particularly among high-risk groups. Method Studies that reported on the prevalence and characteristics of pedestrian accidents at railway crossings up until June 2012 were searched in electronic databases. Results Males, school children and older pedestrians (and those with disabilities) are disproportionately represented in fatality databases. However, a main theme to emerge is that little is known about the origins of train–pedestrian collisions (especially compared to train–vehicle collisions). In particular, whether collisions result from engaging in deliberate violations versus making decisional errors. This subsequently limits the corresponding development of effective and targeted interventions for high-risk groups as well as crossing locations. Finally, it remains unclear what combination of surveillance and deterrence-based and education-focused campaigns are required to produce lasting reductions in train–pedestrian fatality rates. This paper provides direction for future research into the personal and environmental origins of collisions as well as the development of interventions that aim to attract pedestrians’ attention and ensure crossing rules are respected.

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Every year a number of pedestrians are struck by trains resulting in death and serious injury. While much research has been conducted on train-vehicle collisions, very little is currently known about the aetiology of train-pedestrian collisions. To date, scant research has been undertaken to investigate the demographics of rule breakers, the frequency of deliberate violation versus error making and the influence of the classic deterrence approach on subsequent behaviours. Aim This study aimed to to identify pedestrians’ self-reported reasons for engaging in violations at crossing, the frequency and nature of rule breaking and whether the threat of sanctions influence such events. Method A questionnaire was administered to 511 participants of all ages. Results Analysis revealed that pedestrians (particularly younger groups) were more likely to commit deliberate violations rather than make crossing errors e.g., mistakes. The most frequent reasons given for deliberate violations were participants were running late and did not want to miss their train or participants believed that the gate was taking too long to open so may be malfunctioning. In regards to classical deterrence, an examination of the perceived threat of being apprehended and fined for a crossing violation revealed participants reported the highest mean scores for swiftness of punishment, which suggests they were generally aware that they would receive an “on the spot” fine. However, the overall mean scores for certainty and severity of sanctions (for violating the rules) indicate that the participants did not perceive the certainty and severity of sanctions as very high. This paper will further discuss the research findings in regards to the development of interventions designed to improve pedestrian crossing safety.