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Rail track operators have traditionally used manual methods to construct train timetables. Creating a timetable can take several weeks, and so the process usually stops once the first feasible timetable has been found. It is suspected that this timetable is often far from optimal. Existing methods schedule track maintenance once the best train timetable has been determined and allow little or no adjustments to the timetable. This approach almost certainly produces suboptimal integrated solutions since the track maintenance schedule is developed with the imposition of the previously constructed train timetable. The research in this thesis considers operationally feasible methods to produce integrated train timetables and track maintenance schedules so that, when evaluated according to key performance criteria, the overall schedule is the best possible. This research was carried out as part of the Cooperative Research Centre for Railway Engineering and Technologies. We developed a method that uses a local search meta-heuristic called 'problem space search'. A fast dispatch heuristic repeatedly selects and moves a track possessor (train or maintenance task) through the network; this results in a single integrated schedule. This technique generates a collection of alternative feasible schedules by applying the dispatch heuristic to different sets of randomly perturbed data. The quality of the schedules is then evaluated. Thousands of feasible solutions can be found within minutes. We also formulated an integer programming model that selects a path for each train and maintenance task from a set of alternatives. If all possible paths are considered, then the best schedule found is guaranteed to be optimal. To reduce the size of the model, we explored a reduction technique called 'branch and price'. The method works on small example problems where paths are selected from a predetermined set, but the computation time and memory requirements mean that the method is not suitable for realistic problems. The main advantages of the problem space search method are generality and speed. We are able to model the operations of a variety of rail networks due to the representation of the problem. The generated schedules can be ranked with a user-defined objective measure. The speed at which we produce a range of feasible integrated schedules allows the method to be used in an operational setting, both to create schedules and to test different scenarios. A comparison with simulated current practice on a range of test data sets reveals improvements in total delay of up to 22%.

Rail track operators have traditionally used manual methods to construct train timetables. Creating a timetable can take several weeks, and so the process usually stops once the first feasible timetable has been found. It is suspected that this timetable is often far from optimal. Existing methods schedule track maintenance once the best train timetable has been determined and allow little or no adjustments to the timetable. This approach almost certainly produces suboptimal integrated solutions since the track maintenance schedule is developed with the imposition of the previously constructed train timetable. The research in this thesis considers operationally feasible methods to produce integrated train timetables and track maintenance schedules so that, when evaluated according to key performance criteria, the overall schedule is the best possible. This research was carried out as part of the Cooperative Research Centre for Railway Engineering and Technologies. We developed a method that uses a local search meta-heuristic called 'problem space search'. A fast dispatch heuristic repeatedly selects and moves a track possessor (train or maintenance task) through the network; this results in a single integrated schedule. This technique generates a collection of alternative feasible schedules by applying the dispatch heuristic to different sets of randomly perturbed data. The quality of the schedules is then evaluated. Thousands of feasible solutions can be found within minutes. We also formulated an integer programming model that selects a path for each train and maintenance task from a set of alternatives. If all possible paths are considered, then the best schedule found is guaranteed to be optimal. To reduce the size of the model, we explored a reduction technique called 'branch and price'. The method works on small example problems where paths are selected from a predetermined set, but the computation time and memory requirements mean that the method is not suitable for realistic problems. The main advantages of the problem space search method are generality and speed. We are able to model the operations of a variety of rail networks due to the representation of the problem. The generated schedules can be ranked with a user-defined objective measure. The speed at which we produce a range of feasible integrated schedules allows the method to be used in an operational setting, both to create schedules and to test different scenarios. A comparison with simulated current practice on a range of test data sets reveals improvements in total delay of up to 22%.

Railway traffic is one of the most used transportation methods in today's society both for freight transports and transportation of people. A necessity for this to function is that the tracks upon which the trains travel are functional. This includes both that the tracks have been constructed correctly and that the tracks have not experienced wear and tear to the level that their functionality is in jeopardy. This requires that the tracks are thoroughly maintained and thus a continuous knowledge about the state of the tracks is required. One way to obtain knowledge about the current track geometry is to measure the tracks using laser scanners to establish the tracks geographical position. This in turn leads to the possibility to notice changes in the tracks. These laser scanners can be mounted on trains or modified vehicles where they scan the tracks while the vehicle is moving along the tracks. However, the scanned points also have to be precisely located in a coordinate system so that they can be compared to the scanned geometry of the initial tracks. The precise locations can be acquired by using Global Navigation Satellite Systems (GNSS) along with Inertial Measurement Systems (INS) and odometers, which are then used as input in a Kalman filter. The GNSS and INS complement each other in a good way since INS have very high positional accuracy and a large temporal error while GNSS has an acceptable positional accuracy and no temporal error. In locations where there is sufficient GNSS availability, this method reaches positional accuracies around the low cm level. The aforementioned method does however struggle when there is subpar GNSS availability, for example in tunnels or in dense forests. This necessitates the use of additional data, and in this work the use of ground control points (GCP) have been examined. The GCPs have been implemented in simulated GNSS-free areas where a temporal distance of 2, 5, 10, 20 and 40 seconds between GCPs has been used. Based on these experiments, an estimated positional accuracy from 0.5 cm to 30 cm in GNSS-free environments has been acquired depending on the distance between points. The authors recommend an implementation of GCPs in a tightly coupled approach every 5-10 seconds to achieve a reliable positional precision on the mm-cm level. The disadvantages of GCPs are quite large since they have to be established and maintained, which costs a fair amount of money and time. It is therefore of utmost importance to minimize the need for GCPs. This can be accomplished either by using alternative solutions such as implementations of track alignment in the Kalman filter, but also by increasing the efficiency of the GCPs. The way that this thesis recommends this to be researched is to use the same GCPs multiple times by either using more advanced sensors for locating the GCPs or by increasing the number of sensors as well as spreading them out across the vehicle. / Tågtrafik är ett av de mest använda transportsätten idag vare sig det gäller godstransporter eller persontransporter. En nödvändighet för att detta ska fungera är att rälsen som tågen färdas på är funktionella. Detta inkluderar att rälsen är korrekt konstruerad, men även att rälsen inte har blivit skadade av bland annat kontinuerlig användning. Därmed behöver rälsen underhållas, och för att kunna göra det krävs kunskap om i vilket skick rälsen är. Ett sätt att införskaffa kunskap om rälsens skick är att mäta rälsen med hjälp av laserskanners. Dessa laserskanners kan monteras på tåg eller rälsanpassade fordon så att de kan mäta in rälsen samtidigt som fordonet färdas längs med rälsen. De inmätta punkterna måste emellertid även vara kända i ett koordinatsystem så att de kan jämföras med punkterna som mättes in när rälsen initialt skannades. Den precisa platsinformationen som krävs för detta kan införskaffas genom att använda Global Navigation Satellite Systems (GNSS) samt Inertial Measurement Systems (INS) och odometer, som sedan används som input i ett Kalmanfilter. GNSS och INS kompletterar varandra på ett bra vis eftersom INS har en väldigt hög platsnoggrannhet samt ett högt tidsberoende fel medan GNSS har relativt hög platsnoggrannhet och inget tidsberoende fel. Denna metod kan därmed nå noggrannheter runt cm-nivån när det är bra GNSS-förutsättningar. Metoden som beskrevs ovan fungerar emellertid inte bra när det är dåliga GNSS-förutsättningar, till exempel i tunnlar eller i täta skogar. Då behövs det annan data, och i detta arbete har användningen av kända punkter analyserats. De kända punkterna har implementerats under en sträcka med simulerad avsaknad av GNSS där ett tidsbaserat avstånd på 2, 5, 10, 20 och 40 sekunder mellan kända punkter har använts. Baserat på dessa experiment har en precision på 0,5 cm till 30 cm uppnåtts beroende på avståndet mellan de kända punkterna. Författarna rekommenderar att kända punkter ska implementeras i en tightly coupled beräkningsmetod var 5-10 sekund för att nå en noggrannhet på mm-cm nivå. Nackdelarna med kända punkter är däremot flertaliga eftersom de måste etableras och underhållas, vilket kräver både tid och pengar. Det är därför viktigt att minimera behovet av kända punkter. Det kan åstadkommas genom att till exempel implementera rälsdata i Kalmanfiltret, men även genom att öka effektiviteten i användandet av de kända punkterna. I det här arbetet rekommenderas det att undersöka hur det går att använda samma kända punkt flertalet gånger. Detta genom att antingen använda mer avancerade sensorer för att lokalisera de kända punkterna eller genom att öka antalet sensorer samt att sprida ut dem över fordonet.

The rate at which a railway track deteriorates depends on the response of the track under different static and repeated dynamic forces. These wheel/rail forces lead to imperfections in the rail surface and deviation in track geometry alignment. The wheel/rail forces are dependent upon the quality of maintenance of the characteristics of both train and track. If train components such as wheelsets and suspensions are maintained to a high standard, less dynamic forces are generated at the wheel/rail interface and less damage is caused over time. Therefore, the amount and cost of maintenance of track are reduced. However, there is little known about how the characteristics of train components affect time-dependent track degradation. Track degradation through deviation of track from its ideal position has the most effect on maintenance costs. Therefore, the present research aims to investigate this track degradation and improve understanding of the effects of train characteristics (such as train mass and speed, suspension stiffness and damping) on railway tracks. The research is conducted by looking into the relationship between wheel/rail forces and track degradation on one hand and between wheel/rail forces and train characteristics on the other hand, with the objective of assisting in managing vehicle/track interaction in order to minimise track degradation. This aim is achieved by investigating the above two relationships to attain the desired relationship between track degradation and train characteristics. The research focuses on wheel/rail vertical forces (both amplitudes and frequencies), vertical track alignment (longitudinal vertical profile), and rail head defects. The study started by collecting wheel/rail vertical forces data in addition to data on vertical track degradation under sustained traffic loads on a heavy haul railway section of track in Central Queensland. Also, five years of degradation and maintenance history data were collected on three other test sections of railway track under variety of traffic conditions and loads in Central Queensland. There were four main analyses of this data employed to probe the study. The first analysis was performed by examining the track degradation history data. The standard deviation method was used in this first analysis to acquire the rate of deterioration in terms of its relationship to track profile (roughness). The second analysis was accomplished by correlating the vertical wheel/rail forces to both vertical track profile and rail roughness using signal processing principles and a function know as coherence. The third analysis was carried out by using the computer simulation software NUCARS to obtain the link between wheel/rail forces and the deterioration of the vertical track profile. The fourth analysis was achieved by combining the results obtained from the above three analyses to acquire the rate of track deterioration in terms of its relationship to varying train characteristics. The first analysis mentioned above quantified the relationship between the level of roughness of the track and rate at which that roughness deteriorated. An important outcome of this relationship is that there is a threshold of roughness below which track deterioration is minimal. The track maintenance planners can now use that threshold for cost effective targeting of tamping activities. The correlation study between track roughness and wheel/rail forces using the coherence function found, surprisingly, that the overall deterioration of the track roughness, in the absence of frequencies of forces above 30 Hz, is due to the so-called quasi-static lower frequency oscillations of dynamic forces. This conclusion together with the relationship between vehicle characteristics and track forces, established in the analyses above, has significant implications for the design of wagon bogies and for charges track owners might levy on trains using their tracks. This research is part of a larger Rail CRC project 11/4 called 'Enhancing the Optimisation of Maintenance/Renewal' being carried out in the School of Urban Development in Queensland University of Technology.

Les travaux présentés dans ce manuscrit visent à développer des modèles de coût/performances pour améliorer les décisions de maintenance sur les infrastructures ferroviaires exploitées dans un environnement de plus en plus contraint: trafic accru, détérioration accélérée, temps de maintenance réduits. Les modèles de maintenance proposés sont construits à base de réseaux de Petri colorés ; ils sont animés par simulation de Monte Carlo pour estimer les performances (en termes de coût et de disponibilité) des politiques de maintenance considérées. Ils sont développés aux niveaux "composant" et "réseau", et plusieurs problèmes de maintenance différents sont étudiés. Au niveau "composant" (rail), des politiques de maintenance mettant en jeu différents niveaux d'information de surveillance sont comparées pour montrer l'intérêt de surveiller la détérioration graduelle du composant. L'effet de l'existence d'un délai de maintenance est également étudié pour les politiques conditionnelle et périodique. Au niveau système (ligne), une maintenance mettant en jeu différents types d'inspections complémentaires (automatique ou visuelle) est d'abord étudiée. On s'intéresse ensuite au cas de figure où l'évolution de la détérioration dépend du mode d'utilisation et de la charge de la voie : le problème de maintenance étudié vise alors à définir un réglage optimal des paramètres d'exploitation de la voie (vitesse limite) et de maintenance (délai d'intervention) / The aim of this thesis research work is to propose maintenance models for railways infrastructures that can help to make better maintenance decisions in the more constrained environment that the railway industry has to face, e.g. increased traffic loads, faster deterioration, longer maintenance planning procedures, shorter maintenance times. The proposed maintenance models are built using Coloured Petri nets; they are animated through Monte Carlo simulations to estimate the performance of the considered maintenance policies in terms of cost and availability. The maintenance models are developed both at the component and network levels, and several different maintenance problems are considered. At the rail component level, maintenance policies with different level of monitoring information (level of gradual deterioration vs binary working state) are compared to show the benefits of gathering monitoring information on the deterioration level. The effect of preventive maintenance delays is also investigated for both condition-based inspection policies and periodic inspection policies on a gradually deteriorating component. At the line level, a maintenance policy based on a two-level inspection procedure is first investigated. Then, considering the case when the deterioration process depends on the operation modes (normal vs limited speed), a maintenance optimization problem is solved to determine an optimal tuning of the repair delay and speed restriction