Systemarkitektur för presentation av geografiskinformation- Utredning av Informationssystem och produkter

Banverket Trafik has a responsibility to make sure that the companies who traffic the Swedish railroad have the correct information about the status of the railroad. One of Banverket Trafiks information systems (Opera) presents the train’s actual position on a map and provides the user with physical information about the trains. Due to increasing demands on the information systems, Banverket Trafik needs to update the present system architecture in order to manage the increasing demands on map graphics and map functions. This paper analysis the information system Opera on the basis of theory and support of methods and discuss problems and demands for Opera. Further we investigate three GIS products to se if they meet the demands. Information about the products was gathered from both supplier and independent users to get a just picture of the products potentials. This paper comprises a suggestion of new system architecture that meet these needs. The suggested system architecture is capable of handling the map graphics and the map’s functions of more than one information system. Hopefully more than one information system will use the suggested system architecture as a map service.

Extended local labor markets due to high speed trains : Visualization of estimations in the Swedish national travel demand forecasting tool, SAMPERS

Wider economic benefits resulting from extended geographical mobility is one argument for investments in high-speed rail. More specifically, the argument for high-speed trains in Sweden has been that they can help to further spatially extend labor market regions which in turn has a positive effect on growth and development. In this paper the aim is to cartographically visualize the potential size of the labor markets in areas that could be affected by possible future high-speed trains. The visualization is based on the forecasts of labor mobility with public transport made by the Swedish national mobility transport forecasting tool, SAMPERS, for two alternative high-speed rail scenarios. The analysis, not surprisingly, suggests that the largest impact of high-speed trains results in the area where the future high speed rail tracks are planned to be built. This expected effect on local labor market regions of high-speed trains could mean that possible regional economic development effects also are to be expected in this area. However, the results, in general, from the SAMPERS forecasts indicaterelatively small increases in local labor market potentials.

Elitidrottsproblem? : En kvalitativ studie om elitidrottares karriäravslutning

This paper used a qualitative technique from a social scientific perspective, a model based on Hewitt and his theory of the self-concept. The purpose of this study was to investigate why some elite athletes experience troublesome periods after their career ending. Interviews were performed with five elite athletes with varying experiences after career ending. The length of the elite athlete careers vary between 7 to 17 years. Two groups were made based upon experiences after career ending. Group 1 had experienced problems, for example suicide tendency, and group 2 had not. The result shows that a troublesome period can come up independently of career ending. The self-concept was investigated during the career and further different kind of variables which could affect the self as training and competition, social relations both before and after termination from sport. Result indicates that an individual in group 2 who has a high complexity in the self-concept based upon significant others outside the elite sport during the career copes with the new situation after career ending much better than group 1 who have not. To build up the self based only upon significant others in the elite sport seems to give expression in a strengthen self. Intensity in training and competition did not have a connection with a troublesome period after retirement from sport but it could prevent establishing contact with others outside the elite sport and reduce a high complexity in the self-concept. The result further shows that elite athletes who practise an individual sport trains in to a greater extent than elite athletes in a seasonal sport. Result also shows that practising a sport with one day off a week, contributes to better opportunities for developing a higher complexity in the self-concept. Suspicions has also rouse that practising an elite sport on the highest level can lead to extensive focusing that further leads to social isolation from individuals outside elite sport. To build up the self upon significant others outside elite sport during the career and keep in touch with significant others from elite sport after the career seems to be the key to avoid problems after the career ending. Suggestions about further investigations are made to see if medial exposure and status can affect the self.

Machine vision for the automatic classification of images acquired from Non-destructive tests

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Train Dispatching: Heuristic Optimization

Train dispatchers faces lots of challenges due to conflicts which causes delays of trains as a result of solving possible dispatching problems the network faces. The major challenge is for the train dispatchers to make the right decision and have reliable, cost effective and much more faster approaches needed to solve dispatching problems. This thesis work provides detail information on the implementation of different heuristic algorithms for train dispatchers in solving train dispatching problems. The library data files used are in xml file format and deals with both single and double tracks between main stations. The main objective of this work is to build different heuristic algorithms to solve unexpected delays faced by train dispatchers and to help in making right decisions on steps to take to have reliable and cost effective solution to the problems. These heuristics algorithms proposed were able to help dispatchers in making right decisions when solving train dispatching problems.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Mått för att mäta kodkvalitet undersystemutvecklingsprocessen

Viljan att hålla en hög kvalitet på den kod som skrivs vid utveckling av system och applikationerär inte något nytt i utvecklingsvärlden. Flera större företag använder sig av olika mått för attmäta kvaliteten på koden i sina system med målet att hålla en hög driftsäkerhet.Trafikverket är en statlig myndighet som ansvarar för driften av bland annat de system somhåller igång Sveriges järnvägsnät. Eftersom systemen fyller en viktig del i att säkra driften ochse till att tågpositioner, planering av avgångar och hantering av driftstörningar fungerar dygnetrunt för hela landet anser de att det är viktigt att sträva efter att hålla en hög kvalitet påsystemen.Syftet med det här examensarbetet var att ta reda på vilka mått som kan vara möjliga attanvända under systemutvecklingsprocessen för att mäta kvaliteten på kod och hur måtten kananvändas för att öka kvaliteten på IT-lösningar. Detta för att redan på ett tidigt stadie kunnamäta kvaliteten på den kod som skrivs i både befintliga och nyutvecklade system.Studien är en fallstudie som utfördes på Trafikverket, de olika måtten som undersöktes varcode coverage, nivån på maintainability index och antalet inrapporterade incidenter för varjesystem. Mätningar utfördes på sju av Trafikverkets system som i analysen jämfördes motantalet rapporterade incidenter. Intervjuer utfördes för att ge en bild över hur arbetssättet vidutveckling kan påverka kvaliteten. Genom litteraturstudier kom det fram ett mått som inte kundeanvändas praktiskt i det här fallet men är högst intressant, detta är cyclomatic complexity somfinns som en del av maintainability index men som även separat påverkar möjligheten att skrivaenhetstest.Resultaten av studien visar att måtten är användbara för ändamålet men bör inte användassom enskilda mått för att mäta kvalitet eftersom de fyller olika funktioner. Det är viktigt attarbetssättet runt utveckling genomförs enligt en tydlig struktur och att utvecklarna både harkunskap om hur man arbetar med enhetstest och följer kodprinciper för strukturen. Tydligakopplingar mellan nivån på code coverage och inflödet av incidenter kunde ses i de undersöktasystemen där hög code coverage ger ett lägre inflöde av incidenter. Ingen korrelation mellanmaintainability index och incidenter kunde hittas.

Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.