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The purpose of the study was to explore how property management companies view of Building Information Modeling (BIM) as a working method in property management process, and to explore the companies efforts at BIM in terms of the level of detail on BIM object implementation in property management. The study includes both companies that have and do not have contributions in BIM. The exploration was aimed at two companies and their varying ways of working to inform the needs of BIM in property management. The purpose of the study was also to give a clear picture of how BIM tools should be defined in the management process. The work was used of qualitative methods to answer the questions first consisted of a literature review, interviews and case study. The case study was about BIM implementation in New Karolinska Solna. The result showed that the definition of BIM in property management companies is not clear yet. The companies have intended to use BIM, but they are not there yet, there should be a type of requirements list that works with planning and production and benefit from using BIM in the property management. According to respondents, most of the common reasons why BIM was not used were because the approach of the tool. There is no proper structure or common working method of how the tool would be applied. Many literature sources including respondents claimed that BIM seemed good and have a good potential to be the future work process. BIM leads to improved work environment, improved sustainability development, good marketing, increased quality in work, time savings, and improved project management. As a suggestion as to how BIM could be implemented, it can be described in a few steps, which is status analysis, identify the benefits of BIM, start implementing on a smaller scale, follow up continuously, improve and expand the work and last but not least Integrate information. The conclusions that can be drawn from the results and literature study were that BIM can improve the quality management of the properties, but it is important to find a reasonable level of BIM implementation as well as a suitable detail level of BIM-model.

Syfte: Examensarbetet syftar till att undersöka var företagsverksamheter inom trafiksäkerhet och tillfällig trafikledning kan tillämpa visuell artificiell intelligens (AI) för att uppnå en säkrare, miljövänligare och mer kostnadseffektiv verksamhet. 

Frågeställningar: “Hur kan tillämpning av visuell artificiell intelligens användas för identifiering av temporära skyddsanordningar vid vägarbeten?”; “Hur kan tillämpning av visuell artificiell intelligens användas för identifiering av personlig skyddsutrustning vid vägarbeten?”; och “Vilka förändringar kan ske gällande företagsverksamhetens säkerhet, kostnader och koldioxidutsläpp vid tillämpningen av visuell artificiell intelligens vid vägarbeten?”.

Metod: Denna studie utfördes med en abduktiv ansats och en mixad forskningsdesign. Där en teoretisk referensram utifrån vetenskapliga artiklar och en empiriinsamling bestående av en fallstudie, intervjuer med anställda, och beräkningar baserat på data från fallföretaget analyserades för att besvara studiens frågeställningar.

Slutsats: Genom att adressera utmaningarna och utnyttja möjligheterna som teknologin erbjuder kan AI-kameror vara ett värdefullt verktyg för att främja en säkrare och mer hållbar arbetsmiljö vid vägarbeten samt en mer gynnsam verksamhet. Genom att tillämpa visuell artificiell intelligens, för att identifiera korrekt användning av personlig skyddsutrustning vid vägarbeten och kombinera det med manuella inspektioner, kan säkerheten för arbetare förbättras och korrekt användning av personlig skyddsutrustning (PPE) säkerställas. Slutligen indikerar studien att tillämpning av visuell artificiell intelligens vid vägarbeten har potential att förbättra säkerheten för arbetare, trafikanter och civilpersoner runtom, minska kostnaderna för företagen och minska miljöpåverkan genom minskade koldioxidutsläpp.

The different material layers as part of a road construction fill all a function so theroad becomes durable, safe, comfortable and aesthetically pleasing. Recently, anew group of construction materials started to play an important role in roadconstruction – geosynthetics.

This thesis addresses the two most common types ofgeosynthetics used in modern road construction, namely geogrids and geotextiles.The most common use of geogrids is reinforcement of poor subgrade by usinggeogrid soil reinforcement, which occurs when road material particles wedge inthe geogrid’s mesh. Geotextiles act partly as a barrier that prevents the finermaterial in the below ground from being mixed with coarser upper material andalso act as a load spreader.Road contractors often face a choice of whether geogrids and/or geotextiles areappropriate in a particular road project and also how much profit the choice mightbring. This phase in the tender calculation process is the intended scope of thisthesis.

The thesis deals with both the "hard" cost-function aspects and the "softer" values e.g. ecology and social aspects. To facilitate the comparison, a comparative modelwas developed. The comparison is done for two different cases: Case A – roadconstruction on the bank and Case B – road construction in hill cutting. In Case A “with geogrid”, the amount of trenching becomes smaller due to saving ofreinforcement layer thickness.The completed cost comparison indicates an opportunity for significant savings forroad contractors that choose to strengthen the road’s superstructure with geogrid. In Case A “with geotextile”, no trenching saving is likely, but instead, bearingcapacity improvement is a long term financial gain. An estimated cost for Case B “hill cutting road”, is approximately SEK 600 000 which is less than the cheapestcase i.e. Case A “with geogrid”. After the use of geogrids, the function changes are as following:

• Traffic load distribution on the terrace has increased and lateral landmovements have reduced
• Filling material density has increased due to geogrid wedging mechanism
• Frictional resistance has increased due to the fact that pavement materialparticles have been extended due to geogrid’s wedging mechanism
• Superstructure’s total thickness has been reduced due reinforcement layerthickness’s reduction

After the use of geogrids, the function changes are as following:

• The composition and function of the road pavement and terrace materialremains intact. (The words "remains intact" run true to the concept of"functional change" but in this case, it is meant that the materialcomposition and function could have been worse if not properly chosengeotextile was added to the design).
• The scenario "gritty mud" is avoided if the geotextile has been enteredcorrectly with the right overlap.

Results concerning the ecological aspects show that the trenching reduction due touse of geogrids leads to fewer ground motion, lesser soil degradation and fewerenvironmental harmful emissions because the use of road construction equipmentdeclines. Reduced distribution excavation thanks to geotextiles leads to both thesame advantages as in the sentence above and partly to the fact that the amount ofmaterials that need become deposited decreases. In addition, the risk ofgroundwater lowering due to artificial drainage ditch is minimized. The road'stotal life cycle is extended, which contributes to reducing the environmentalimpacts arising from road repair and construction of a new road if the old onestops fulfilling its function. Degradation of geogrids and geotextiles is notenvironmentally harmful, but takes a long time in natural conditions, which meansthat in practice, the use must be documented and taken care of (regarding finalcombustion in a prudent manner).Regarding social sustainability, the following conclusion could be drawn: a roadthat has a higher carrying capacity leads to higher traffic safety due to minimalsubsidence, track formation and cracking. Road safety is seen by citizens not onlyas something that the private motorists are responsible for but also something thatroad authorities should consider when planning for a socially sustainable society.Another conclusion is road maintenance frequency and hereby the taxpayers' longtermeconomic gain. The road extended total life cycle contributes to the reductionof road repairs and new construction of roads. In other words, it is not just “oneroad construction company” that wins economically by minimizing their warrantywork.

The discussion concerns the cases where geosynthetics are not economicallyoptimal bearing capacity choice, such as solid rock cutting or a stretch of roadwhich has weaker parties but for which, a filling material yet compensates for theexcavated. The report concludes with a special discussion of the Swedishgeosynthetics research. The geosynthetics industry is controlled by private actors(developers, manufacturers and others) and contractors who do not like releasinginformation that might reduce their competitiveness. Therefore, the independentresearcher’s role has been quite weak and mostly reduced to “play ‘catch-up’insofar as investigating the nuances of how geosynthetics work "(Koerner, 2005). Another reason for the lack of reports on geosynthetics benefit is the long term asa sharp research project takes to plan, implement, control and evaluate. WhilstTrafikverket’s and local municipalities’ play the leading role in the Swedish roadconstruction industries, it should be in their interest to start taking geosyntheticsmore seriously by implementing credible tests and full scale trials and publishpractically applicable documents based on objective tests of structures containing geosynthetics.

I storstadsområden i Sverige blir det allt vanligare att bygga överdäckningar. Överdäckningar är ett storstadsfenomen och är betydligt vanligare internationellt. I Västerås stad kan det vara aktuellt med en överdäckning i samband med stadsbyggnadsprojektet ”3B”, Bygga Bort Barriärer. Stadsbyggnadsprojektets mål är att utveckla stationsområdet och bygga bort järnvägen, för att kunna länka ihop Västerås centrum med den nya stadsdelen och Mälaren. För att uppfylla detta mål och förbättra stationsområdet kan en överdäckning vara en bra lösning. Detta examensarbete ska utreda om en överdäckning kan genomföras i Västerås och studera de faktorer som påverkar en eventuell överdäckning.

Examensarbetet begränsades till det utmarkerade spårområdet i ÖP64, stationsområdet i Västerås stad, där överdäckning kan prövas. Fokus lades på risk- och säkerhetsaspekter, miljöaspekter och stads- och landskapsbild. Empiriska studien genomfördes med hjälp av kvalitativa arkiv- och intervjuanalyser baserade på tre fallstudier. Resultatet utmynnade i en fördjupning inom problematiken samt framställandet av en modell.

Det finns inget tydligt fastställt regelverk som gäller för överdäckning vilket medför att planarbetet blir komplicerat. Tolkning av lagar som gäller för tunnlar och broar görs i nuläget, vilket öppnar för subjektiva bedömningar. I planarbetet är det tydligt att riskhanteringen är den viktigaste faktorn att beakta samt den mest problematiska. Denna styrs av farligt gods och avgör hur komplicerad riskhanteringen blir. Vid farligt gods är det explosiva och brandfarliga ämnen som medför stora skador på överdäckningen som kan leda till kollaps.

Resultatet av fördjupningen visar att en överdäckning är möjlig och uppfyller de uppsatta mål för stationsområdet, men den samhällsekonomiska nyttan måste bedömas vara värd den ökade investeringen.

Nyckelord: Överdäckning, bygga bort barriärer, intunnling, riskhantering, buller, farligt gods 

The power distribution system is the final link to transfer the electrical energy to the individual customers. It is distributed in a complex technical grid but is associated with the majority of all outages occurring. Improving its reliability is an efficient way to reduce the effects of outages.

A common way of improving the reliability is by designing loop structures containing two connected feeders separated by a section point. The location of the section point will decide how the system structure is connected and its level of reliability. By finding the optimal location, an improved reliability may be accomplished.

This Master’s thesis has developed a method of finding optimized section points locations in a primary distribution system in order to improve its reliability. A case study has been conducted in a part of Mälarenergi Elnät’s distribution system with the objective of developing an algorithm in MATLAB able to generate the optimal section points in the area. An analytical technique together with a method called Failure Modes and Effect Analysis (FMEA) as preparatory step, was used to simulate the impact of outages in various components based on historical data and literature reviews. Quantifying the impact was made by calculating the System Average Interruption Duration Index (SAIDI) and the Expected Cost (ECOST) which represented the reliability from a customer- and a socio-economic perspective.

Using an optimization routine based on a Greedy algorithm an improvement of the reliability was made possible. The result of the case study showed a possible improvement of 28% on SAIDI and 41% on ECOST if optimizing the location of section points. It also indicated that loop structures containing mostly industry-, trade- and service-sectors may improve ECOST considerably by having a relocated section point.

The analysis concluded that based on the considerable improvement the case study showed, a distribution system could be highly benefitted by optimizing the location of section points. The created algorithm may provide a helpful tool well representative for such a process in a cost-effective way. Applying it into a full size system was considered being possible but it would first require some additional improvements of reliability inputs and to resolve some fundamental issues like rated current in lines and geographical distances to substations. 

The growing urgency of climate change has led to growth in the electrification technology field, where batteries have emerged as an essential role in the renewable energy transition, supporting the implementation of environmentally friendly technologies such as smart grids, energy storage systems, and electric vehicles. Battery cell degradation is a common occurrence indicating battery usage. Optimizing lithium-ion battery degradation during operation benefits the prediction of future degradation, minimizing the degradation mechanisms that result in power fade and capacity fade. This degree project aims to investigate battery degradation prediction based on capacity using deep learning methods. Through analysis of battery degradation and health prediction for lithium-ion cells using non-destructive techniques. Such as electrochemical impedance spectroscopy obtaining ECM and three different deep learning models using multi-channel data. Additionally, the AI models were designed and developed using multi-channel data and evaluated performance within MATLAB. The results reveal an increased resistance from EIS measurements as an indicator of ongoing battery aging processes such as loss o active materials, solid-electrolyte interphase thickening, and lithium plating. The AI models demonstrate accurate capacity estimation, with the LSTM model revealing exceptional performance based on the model evaluation with RMSE. These findings highlight the importance of carefully managing battery charging processes and considering factors contributing to degradation. Understanding degradation mechanisms enables the development of strategies to mitigate aging processes and extend battery lifespan, ultimately leading to improved performance.

Tar asphalt containing harmful pollutants has been in our roads for a long time before its harmfulness was discovered in the 1970s. Prior to 1973 in Sweden, tar asphalt was a common repair material when repairing roads. A lot of the documentation of where repairs have been made prior to 1973 have disappeared over time. This means that if a road that existed before 1973 is to be rebuilt, the road must be environmentally invented for the presence of tar asphalt. The purpose of this degree project is to examine the methods that the consultant company ÅF uses today to identify tar asphalt in projects. To identify these methods a literature study has been made, analysis of past projects of ÅF and interviews with personnel of the company. An important problem that was identified is related to the field tests that are quite uncertain and can only identify quite high levels of pollutants in the asphalt. Further improvements for how to solve it would be implementing lab analysis of all samples on road projects where the margin for error is smaller. For all smaller or medium sized projects, a more cost-efficient method using mainly field tests as they use today appear the best solution.

Detecting lane markings in road scenes poses a significant challenge due to their intricate nature, which is susceptible to unfavorable conditions. While lane markings have strong shape priors, their visibility is easily compromised by varying lighting conditions, adverse weather, occlusions by other vehicles or pedestrians, road plane changes, and fading of colors over time. The detection process is further complicated by the presence of several lane shapes and natural variations, necessitating large amounts of high-quality and diverse data to train a robust lane detection model capable of handling various real-world scenarios. In this paper, we present a novel self-supervised learning method termed Contrastive Learning for Lane Detection via Cross-Similarity (CLLD) to enhance the resilience and effectiveness of lane detection models in real-world scenarios, particularly when the visibility of lane markings are compromised. CLLD introduces a novel contrastive learning (CL) method that assesses the similarity of local features within the global context of the input image. It uses the surrounding information to predict lane markings. This is achieved by integrating local feature contrastive learning with our newly proposed operation, dubbed cross-similarity. The local feature CL concentrates on extracting features from small patches, a necessity for accurately localizing lane segments. Meanwhile, cross-similarity captures global features, enabling the detection of obscured lane segments based on their surroundings. We enhance cross-similarity by randomly masking portions of input images in the process of augmentation. Extensive experiments on TuSimple and CuLane benchmark datasets demonstrate that CLLD consistently outperforms state-of-the-art contrastive learning methods, particularly in visibility-impairing conditions like shadows, while it also delivers comparable results under normal conditions. When compared to supervised learning, CLLD still excels in challenging scenarios such as shadows and crowded scenes, which are common in real-world driving.