Traction power system simulation in electrified railways

Electricity has been the major source of power in most railway systems. Reliable, efficient and safe power distribution to the trains is vitally important to the overall quality of railway service. Like any large-scale engineering system, design, operation and planning of traction power systems rely heavily on computer simulation. This paper reviews the major features on modelling and the general practices for traction power system simulation; and introduces the development of the latest simulation approach with discussions on simulation results and practical applications. Remarks will also be given on the future challenges on traction power system simulation.

Train control to reduce delays upon service disturbances at railway junctions

Train delay is one of the most important indexes to evaluate the service quality of the railway. Because of the interactions of movement among trains, a delayed train may conflict with trains scheduled on other lines at junction area. Train that loses conflict may be forced to stop or slow down because of restrictive signals, which consequently leads to the loss of run-time and probably enlarges more delays. This paper proposes a time-saving train control method to recover delays as soon as possible. In the proposed method, golden section search is adopted to identify the optimal train speed at the expected time of restrictive signal aspect upgrades, which enables the train to depart from the conflicting area as soon as possible. A heuristic method is then developed to attain the advisory train speed profile assisting drivers in train control. Simulation study indicates that the proposed method enables the train to recover delays as soon as possible in case of disturbances at railway junctions, in comparison with the traditional maximum traction strategy and the green wave strategy.

An investigation of commuter exposure to ultrafine particles in Sydney

Commuting in various transport modes represents an activity likely to incur significant exposure to traffic emissions. This study investigated the determinants and characteristics of exposure to ultrafine (< 100 nm) particles (UFPs) in four transport modes in Sydney, with a specific focus on exposure in automobiles, which remain the transport mode of choice for approximately 70% of Sydney commuters. UFP concentrations were measured using a portable condensation particle counter (CPC) inside five automobiles commuting on above ground and tunnel roadways, and in buses, ferries and trains. Determinant factors investigated included wind speed, cabin ventilation (automobiles only) and traffic volume. The results showed that concentrations varied significantly as a consequence of transport mode, vehicle type and ventilation characteristics. The effects of wind speed were minimal relative to those of traffic volume (especially heavy diesel vehicles) and cabin ventilation, with the latter proving to be a strong determinant of UFP ingress into automobiles. The effect of ~70 minutes of commuting on total daily exposure was estimated using a range of UFP concentrations reported for several microenvironments. A hypothetical Sydney resident commuting by automobile and spending 8.5 minutes of their day in the M5 East tunnel could incur anywhere from a lower limit of 3-11% to an upper limit of 37-69% of daily UFP exposure during a return commute, depending on the concentrations they encountered in other microenvironments, the type of vehicle they used and the ventilation setting selected. However, commute-time exposures at either extreme of the values presented are unlikely to occur in practice. The range of exposures estimated for other transport modes were comparable to those of automobiles, and in the case of buses, higher than automobiles.

Investigation into the transport, behaviour and deposition of combustion aerosols from transport sources

The deterioration of air quality is a significant issue in large and growing cities. This work investigates particulate emissions from transport, the largest source of air pollution in cities today. Emitters such as busy roads and diesel trains are investigated, with specific reference to the evolution of particles over time and distance. Diesel trains are investigated as an alternative to road traffic in investigating evolutionary processes. Higher emissions and solitary sources mean that the emitted plume can be observed over time in a single location. These results represent the first investigation of the evolution of fine and ultrafine aerosol particles from this type of source. Aerosols near a busy road are investigated, with the result that a dependence of total number concentration on distance from the road is shown to be related to the fragmentation of nanoparticle clusters. Local meteorological conditions are also monitored and humidity is shown to vary with distance from the road in a nonmonotonic way. Particles from a busy road were also examined using a scanning electron microscope, with the intention of understanding the make up of the emitted aerosol plume. It was determined that due to significant surface behaviour post-deposition, this method of analysis could not directly classify airborne pollutants. Some interesting results were obtained however, particularly in terms of composite particles and the analysis of deposited patterns. This thesis introduces new work in terms of the analysis of diesel train particulate emissions, as well as adding further evidence towards the fragmentation process of aerosol evolution in both background concentrations and emitted aerosol plumes.

Modelling and analysis of the crush zone of a typical Australian passenger train

In this paper, a three-dimensional nonlinear rigid body model has been developed for the investigation of the crashworthiness of a passenger train using the multibody dynamics approach. This model refers to a typical design of passenger cars and train constructs commonly used in Australia. The high-energy and low-energy crush zones of the cars and the train constructs are assumed and the data are explicitly provided in the paper. The crash scenario is limited to the train colliding on to a fixed barrier symmetrically. The simulations of a single car show that this initial design is only applicable for the crash speed of 35 km/h or lower. For higher speeds (e.g. 140 km/h), the crush lengths or crush forces or both the crush zone elements will have to be enlarged. It is generally better to increase the crush length than the crush force in order to retain the low levels of the longitudinal deceleration of the passenger cars.

Modeling train delays in urban networks

The reliability of urban passenger trains is a critical performance measure for passenger satisfaction and ultimately market share. A delay to one train in a peak period can have a severe effect on the schedule adherence of other trains. This paper presents an analytically based model to quantify the expected positive delay for individual passenger trains and track links in an urban rail network. The model specifically addresses direct delay to trains, knock-on delays to other trains, and delays at scheduled connections. A solution to the resultant system of equations is found using an iterative refinement algorithm. Model validation, which is carried out using a real-life suburban train network consisting of 157 trains, shows the model estimates to be on average within 8% of those obtained from a large scale simulation. Also discussed, is the application of the model to assess the consequences of increased scheduled slack time as well as investment strategies designed to reduce delay.

City meeting places: Brisbane's Hungry Jack's and Melbourne's Flinders Street Station

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...

Scheduling techniques to optimise rail operations

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.

Methodology to assess safety effects of future Intelligent Transport Systems on railway level crossings

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.

An innovative information gathering and data analysis platform for railway level crossing safety data

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.

TrainRoulette : promoting situated in-train social interaction between passengers

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.

Susceptibility of the critical structural components of railway bridges to the changes in train speed

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.

Estimating the robustness of long-haul train plans

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.

Towards the retrieval of accurate OD matrices from Bluetooth data : lessons learned from 2 years of data

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.

Detecting anomalous events at railway level crossings

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.