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  • 1.
    Almlof, Erik
    et al.
    KTH Royal Inst Technol.
    Zhao, Xiaoyun
    Dalarna University, School of Information and Engineering, Microdata Analysis. KTH Royal Inst Technol.
    Pernestal, Anna
    KTH Royal Inst Technol.
    Jenelius, Erik
    KTH Royal Inst Technol, Div Transport Planning, Stockholm, Sweden..
    Nybacka, Mikael
    KTH Royal Inst Technol.
    Frameworks for assessing societal impacts of automated driving technology2022In: Transportation planning and technology (Print), ISSN 0308-1060, E-ISSN 1029-0354, Vol. 45, no 7, p. 545-572Article in journal (Refereed)
    Abstract [en]

    Numerous studies have studied the impacts of automated driving (AD) technology on e.g. accident rates or CO2 emissions using various frameworks. In this paper we present an overview of previous frameworks used for societal impacts and review their advantages and limitations. Additionally, we introduce the Total Impact Assessment (TIA) framework developed by the Swedish Transport Administration and use this framework to evaluate three scenarios for AD bus services in Stockholm. We conclude that the reviewed frameworks cover different aspects of AD technology, and that e.g. cybersecurity and biodiversity are areas largely neglected. Furthermore, most frameworks assume effects to be homogenous, when there may be large variation in e.g. perceived security. The TIA framework does not manage to include all societal aspects of AD technology, but has great benefits and manages to provide important insights of the societal impacts of AD technology, especially how effects may wary for different actors.

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  • 2.
    Andersson, Julia
    et al.
    Dalarna University, School of Information and Engineering.
    Liedström, Matilda
    Dalarna University, School of Information and Engineering.
    Effekten av olika logistiklösningar: En studie kring fördelar och nackdelar med tredjepartslogistik och inbärning till ett projekt i Dalarna2021Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Within the construction industry the advantages of looking at the logistics todifferent projects has been acknowledged during the past couple of years.This study has been written in collaboration with Skanska Sverige AB. Thepurpose of the study is to, in different ways, examine what advantages anddisadvantages there are in using the logistics solutions terminalization (also knownto be a part of Third Party Logistics) and inside delivery to a specific project inDalarna, Sweden. This project is a remodeling project of a school with studentsfrom six to sixteen years old. Within the school area new parts of the school isbuilt while students are located in the yet existent buildings. This infer thatstudents move around the construction sites daily. The study also involves thirdparty people and how these people feel about the large transports connected to theproject. The inside delivery utility is then discussed based on the securityexperience within and around the construction site along with the economic andecological perspective of the service.The methods used in this study are interviews with three people of the projectmanagement, one person that works with logistics at the company, the headmasterof the younger students, skilled workers and third party people. Furthermore afield study is done that includes measurements and observations. As a close,calculations are done to determine if a economical profitability could be possibleby using inside delivery.Results from the study show how the logistics solutions terminalization and insidedelivery is looked at within Skanska today. Here, the advantages anddisadvantages with the different services are displayed from the perspectives of thepeople who were interviewed. The results from the measurements from the fieldstudy presents how many third party people that move adjacent to the two activeconstruction sites when the school day begins. The calculations show that it iseconomically beneficial to use inside delivery after the end of the workday whileused with terminalization.Conclusions of the study indicate that there are no overall solutions regarding howthe logistics must be used in different projects. If there is a possibility to use terminalization in the area where the project is situated, this, along with insidedelivery, is a good alternative for the project.

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  • 3.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Distance measure and the p-median problem in rural areas2015In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 226, no 1, p. 89-99Article in journal (Refereed)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region with a sparse, heterogeneous network and a non-symmetric distribution of the population. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (1-100 facilities). We find that the network distance give as good a solution as the travel-time network. The Euclidean distance gives solutions some 4-10 per cent worse than the network distances, and the solutions tend to deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

  • 4.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography.
    A compelling argument for the gravity p-median model2013In: European Journal of Operational Research, ISSN 0377-2217, E-ISSN 1872-6860, Vol. 226, no 3, p. 658-660Article in journal (Refereed)
    Abstract [en]

    The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population always travels to the nearest facility. Drezner and Drezner (2006, 2007) provide three arguments on why this assumption might be incorrect, and they introduce the extended gravity p-median model to relax the assumption. We favour the gravity p-median model, but we note that in an applied setting, the three arguments are incomplete. In this communication, we point at the existence of a fourth compelling argument for the gravity p-median model.

  • 5.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics. HUI Research, Stockholm.
    The effect on CO2 emissions of taxing truck distance in retail transports2017In: Transportation Research Part A: Policy and Practice, ISSN 0965-8564, E-ISSN 1879-2375, Vol. 97, p. 47-54Article in journal (Refereed)
    Abstract [en]

    To finance transportation infrastructure and to address social and environmental negative externalities of road transports, several countries have recently introduced or consider a distance based tax on trucks. In competitive retail and transportation markets, such tax can be expected to lower the demand and thereby reduce CO2 emissions of road transports. However, as we show in this paper, such tax might also slow down the transition towards e-tailing. Considering that previous research indicates that a consumer switching from brick-and-mortar shopping to e-tailing reduces her CO2 emissions substantially, the direction and magnitude of the environmental net effect of the tax is unclear. In this paper, we assess the net effect in a Swedish regional retail market where the tax not yet is in place. We predict the net effect on CO2 emissions to be positive, but off-set by about 50% because of a slower transition to e-tailing.

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  • 6.
    Carling, Kenneth
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Meng, Xiangli
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rudholm, Niklas
    Dalarna University, School of Technology and Business Studies, Economics.
    The effects of taxing truck distance on CO2 emissions from transports in retailing2015Report (Other academic)
    Abstract [en]

    To finance transportation infrastructure and to address social and environmental negative externalities of road transports, several countries have recently introduced or consider a distance based tax on trucks. In the competitive retail market such tax can be expected to lower the demand and thereby reduce CO2 emissions of road transports. However, as we show in this paper, such tax might also slow down the transition towards e-tailing. Considering that previous research indicates that a consumer switching from brick-and-mortar shopping to e-tailing reduces her CO2 emissions substantially, the direction and magnitude of the environmental net effect of the tax is unclear. In this paper, we assess the net effect in a Swedish regional retail market where the tax not yet is in place. We predict the net effect on CO2 emissions to be positive, but off-set by about 50% because of a slower transition to e-tailing.

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  • 7. Cordi, Ilja
    et al.
    Leden, Lars
    Luleå tekniska universitet, Arkitektur och vatten.
    Ranhagen, Ulf
    Luleå tekniska universitet, Arkitektur och vatten.
    FoU-plan trafikteknik: inriktningsplan för FoU inom integrerad fysisk samhällsplanering och trafiksäkerhet1999Report (Other academic)
  • 8.
    Dominic, Chris
    et al.
    University of Gävle.
    Olsmats, Carl
    Dalarna University, School of Information and Engineering, Industrial Engineering and Management.
    Life-Centered Concurrent Packaging Design: Integrating Packaging, Product, Logistics Process and Supply Chain2023In: Diid - Disegno Industriale Industrial Design, ISSN 1594-8528, Vol. 12, no 79Article in journal (Refereed)
    Abstract [en]

    Using a life-centered packaging design approach in the context of packaging applications for consumer goods, this paper presents a conceptual model for the concurrent development of packaging, product, logistics process, and supply chain (SC). The objective is to enhance the understanding of packaging logistics and logistics management in SCs and to identify current packaging logistics issues in the SC. The four-dimensional concurrent engineering (4DCE) framework, based on the alignment of and interaction between SC, logistics, packaging, and product, is used to increase overall SC efficiency. The model is applied and tested via three case studies within different industries. The results indicate improved understanding and knowledge-sharing between SC actors, with collaborative efforts leading to an increased overall SC performance.

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  • 9.
    Espegren, Yanina
    et al.
    Dalarna University, School of Technology and Business Studies, Business Administration and Management.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Olsmats, Carl
    Dalarna University, School of Technology and Business Studies, Industrial Engineering and Management.
    Smart online grocery delivery and peri-urbanconsumers’ attitudes2018Report (Other academic)
    Abstract [en]

    Purpose: To explore consumers’ attitudes towards e-commerce, in particular online grocery shopping, and its delivery in non-dense areas for the purpose of designing smart last-mile solutions.

    Approach: The state-of-the-art of smart e-commerce delivery in dense areas was identified by a review of the literature. It was expected that this knowledge could be transferred to non-dense areas. This prediction was examined and explored further by making use of four focus groups recruited in a Swedish mid-sized town.

    Findings: Respondents were generally positive towards e-commerce, although mixed attitudes were found with regard to online grocery shopping. Further, the willingness to pay for flexible, smart and sustainable delivery was low, with a notable exception for local produce.

    Originality: The knowledge acquired and solution developed in dense areas is not readily transferred to non-dense areas. There is scope for developing new Business Models for the supply chain of local produce. For the prototype testing and roll-out of smart e-commerce delivery platforms, the online local produce market is recommended.

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  • 10.
    Etuk, Mfon
    et al.
    Dalarna University, School of Information and Engineering.
    Mihai, Radu Ștefan
    Dalarna University, School of Information and Engineering.
    Exploring the use of mobile warehouses in midsized urban and rural regions for last-mile transportation2023Independent thesis Advanced level (degree of Master (Two Years)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Abstract: Efficient last-mile transportation is a continuous difficulty for businesses, particularly in e-commerce, necessitating the development of creative solutions. This thesis investigates the use of mobile warehouses in mid-sized urban and rural areas to help with this problem. The study begins by emphasizing the importance offlawless delivery as well as the role of warehouses in supply chains. Mobile warehouses emerge as a possible solution, addressing constraints related to these regions' low population density, purchasing power, and market dynamics. The methodology includes a review of the literature on mobile warehouse solutions and the introduction of a generalized cost function model for estimating last-mile logistics costs. The model, which is adaptable to different vehicle types, is applied to Dalarna County in Sweden, considering delivery routes and stops. The findings spotlight the efficacy of mobile warehouses, notably mobile trucks, for last-mile delivery in Dalarna County. Interpretation of results from simulation scenarios emphasizes the importance of route optimization. While the study acknowledges its limitations, it underscores the potential benefits of adopting mobile warehouses, both in practical and theoretical terms. These findings resonate as valuable insights for businesses and the logistics industry, especially in the dynamic landscape of e-commerce. The study illuminates the way forward, emphasizing the critical role of adaptive, geography-specific solutions, such as mobile warehouses, in enhancing last-mile delivery efficiency.

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  • 11.
    Fleyeh, Hasan
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Traffic Signs Color Detection and Segmentation in Poor Light Conditions2005In: Machine Vision Applications (MVA2005), Tsukuba Science City, 2005Conference paper (Refereed)
    Abstract [en]

    This paper presents a new algorithm for color detection and segmentation of road signs in poor light conditions. The images were taken by a digital camera mounted in a car. The RGB channels of the digital images were enhanced separately by histogram equalization, and then a color constancy algorithm was applied to extract the true colors of the sign. The resultant image was then converted into HSV color space, and segmented to extract the colors of the road signs. The method was tested on outdoor images in different poor light conditions such as fog and snow, and they show high robustness. This project is part of the research taking place at Dalarna University - Sweden in the field of the Intelligent Transport Systems (ITS).

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  • 12.
    Hallenberg, Josefin
    et al.
    Dalarna University, School of Technology and Business Studies, Industrial Engineering and Management.
    Bergström, Jonas
    Dalarna University, School of Technology and Business Studies, Industrial Engineering and Management.
    Konceptet mobilitet som tjänst: Viktiga kompetenser och möjliga utmaningar vid vidareutvecklingen av MaaS i Sverige.2016Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Transport and travel is necessary for our society to function. Today, the privately owned car stands for more than half of all personal trips in Sweden. In the last couple of years researchers have highlighted the idea that personal transport is facing a paradigm shift, which means a reduction in the use and dependent of the privately owned car and an increased focus on individuals buying their Mobility as a Service (MaaS). MaaS is described as an integrated mix of different mobility services which are arranged in the form of customized mobility packages to the customer. These mobility packages can be compared to a mobile phone subscription, which includes various mobility services, such as train, bus, subway, taxi, carpool, etc. in various amounts depending on the individual's changing needs. The individual can take care of their own travel planning, booking and payment via an app in their smartphone. What distinguish MaaS from other mobility services is that the customer can travel from door-to-door instead of a predefine station to another.

    There have been various Maas projects around the world in order to increase understanding of the concept of MaaS, there is still a lot of unanswered questions and researchers would like to see more studies in the field, in order to find factors that are important and vital to the concept MaaS.

    The aim of the thesis is to: Discuss some competences that may be significant for the further development of the concept Maas in Sweden and discuss potential challenges that may arise at further development of the concept MaaS in Sweden.

    This study is based on previous research and experiences and thoughts on the concept MaaS from various stakeholders with knowledge and experience of the concept.

    This study has an abductive approach. Primary data were obtained through qualitative semistructured interviews with eight people who have knowledge and experience of the Maas.

    The main conclusions in this study is that the competences that are most important in the development of MaaS is collaborative skills and competences required to create an attractive mobility package based on customer needs.

    One challenge identified in this study is the challenge of creating individualized mobility package in which different types of mobility services are integrated. Another challenge can arise when public and private organizations collaborate and when new organizations enter the transport network and try to cooperate with the established organizations

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  • 13.
    Hägerby, Daniel
    et al.
    Dalarna University, School of Technology and Business Studies, Energy and Environmental Technology.
    Karlsson, Mikael
    HVV.
    V2G backup Skid-VM 20152012Report (Other academic)
    Abstract [sv]

    2015 kommer Skid-VM att hållas i Falun. TV-bolagen kräver redundant kraft som standard för denna typ av arrangemang. Detta sköts normalt med dieselgeneratorer och eventuellt UPS:er. För att utreda detaljerna kring, och möjligheterna med, att ersätta några eller alla dieselgeneratorer med elkraft från elfordon, har en förstudie gjorts under 2011.

    Denna studie tittat djupare på några sätt att göra detta. Slutsatsen är att tekniken finns och är mogen nog att klara uppgiften, men intresset hos fordonstillverkarna är svagt.

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  • 14.
    Jansson, Kjell
    et al.
    KTH.
    Algers, Staffan
    KTH.
    Lang, Harald
    KTH.
    Larsen, Odd
    KTH.
    Mortazavi, Reza
    KTH.
    Bates, John
    KTH.
    Daly, Andrew
    KTH.
    Descriptive and theory report for “Towards a model for long distance passenger travel in the context of infrastructure and public transport planning”2013Report (Other academic)
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  • 15.
    Jomaa, Diala
    et al.
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Dougherty, Mark
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Yella, Siril
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Edvardsson, Karin
    Dalarna University, School of Technology and Business Studies, Construction.
    Effectiveness of trigger speed of vehicle-activated signs on mean and standard deviation of speed2016In: Journal of Transportation Safety and Security, ISSN 1943-9962, Vol. 8, no 4, p. 293-309Article in journal (Refereed)
    Abstract [en]

    Excessive or inappropriate speeds are a key factor in traffic fatalities and crashes. Vehicle-activated signs (VASs) are therefore being extensively used to reduce speeding to increase traffic safety. A VAS is triggered by an individual vehicle when the driver exceeds a speed threshold, otherwise known as trigger speed (TS). The TS is usually set to a constant, normally proportional to the speed limit on the particular segment of road. Decisions concerning the TS largely depend on the local traffic authorities. The primary objective of this article is to help authorities determine the TS that gives an optimal effect on the Mean and Standard Deviation of speed. The data were systematically collected using radar technology whilst varying the TS. The results show that when the applied TS was set near the speed limit, the standard deviation was high. However, the Standard Deviation decreased substantially when the threshold was set to the 85th percentile. This decrease occurred without a significant increase in the mean speed. It is concluded that the optimal threshold speed should approximate the 85th percentile, though VASs should ideally be individually calibrated to the traffic conditions at each site.

  • 16.
    Kostela, Johan
    et al.
    Dalarnas forskningsråd.
    Bjerre, Bo
    Trafikverket.
    Primary prevention of drink driving by the large-scale use of alcolocks in commercial vehicles2008In: Accident Analysis and Prevention, ISSN 0001-4575, E-ISSN 1879-2057, Vol. 40, no 4, p. 1294-1299Article in journal (Refereed)
    Abstract [en]

    Alcolocks are commercial breath test devices that prevent a motor vehicle from starting when a driver's blood alcohol concentration (BAC) is elevated. This report is an evaluation of the experiences and BAC data from the first use of alcolocks in commercial vehicles as a primary prevention strategy. In most applications, the alcolock is imposed only after an impaired driving conviction. This study, implemented in Sweden, estimates drink driving on a large scale in a variety of commercial vehicles.

    Officials from 118 companies were interviewed representing 3689 alcolock-equipped vehicles used by 9614 professional drivers, an 80% compliance rate. In a contrast group of 230 transport businesses without alcolocks the interview compliance rate was 57%. Survey results probed motivation for and experience with alcolocks. Analysis of BAC test patterns showed alcohol consumption among employees through prevalence estimates of drink-driving attempts at the rate of BAC ≥ the legal limit 0.020%.

    Before alcolock installation, 64% of the employers suspected alcohol problems among their employees and their motive for installing alcolocks (cost averaged 1700 €/vehicle) was to improve the transport quality. Several companies had technical problems with the alcolocks; but 98% recommended that other companies install alcolocks.

    Among 600, heavy vehicles, 0.19% of all starts were prevented by elevated BAC; most during weekends and mornings. Daytime Saturday and Sunday mornings 0.72% of the drivers had elevated BAC.

    Conclusions

    The prevalence of drink driving among professional drivers is probably similar to that among drivers in general. Alcolocks would improve the safety margin and reduce public risk. Provided that the entire fleet of trucks, buses, and taxis in Sweden had installed alcolocks that would correspond to about half a million drink driving trips being prevented every year.

  • 17.
    Landré, Martin
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Using GIS to measure regional enlargement and strengthening in Sweden2014In: Journal of Intelligent Transportation and Urban Planning, ISSN 2373-0757, Vol. 2, no 1, p. 41-50Article in journal (Refereed)
    Abstract [en]

    The aim of this paper is to determine the size of regional enlargement and strengthening in Sweden over a period of eight years and the relationship with economic growth by analyzing changes in commuting patterns in that period using geographical information system (GIS) techniques. For this analysis, commuting regions have been delimited using the classic concept of commuting field for one-way flows from homes to employment centres functioning as central places. The delimitation procedure is supported by a geo-processing model that automates the process of building such fields. The analysis results show that substantial regional enlargement and strengthening occurred around major employment centres between 2000 and 2008. More than 40% of municipalities could enlarge their commuting field, while for more than 80% of municipalities in these fields their orientation to the core of such a field increased. A significant strong, positive correlation exists between economic growth and regional strengthening, expressed by an increased orientation to the core municipality of a commuting field of commuters living in surrounding municipalities and decreased internal commuting in the core municipality. Municipalities with enlarged commuting fields have on average more employment growth than municipalities whose fields have not changed. There is no indication that regional enlargement of an employment centre is influenced by growing numbers of employed residents in surrounding municipalities.

  • 18.
    Macuchova, Zuzana
    et al.
    Dalarna University, School of Culture and Society, Human Geography.
    Brandt, Daniel
    Dalarna University, School of Culture and Society, Human Geography.
    Public transport provision and social sustainability in Sweden2024In: Geografiska Annaler. Series B, Human Geography, ISSN 0435-3684, E-ISSN 1468-0467Article in journal (Refereed)
    Abstract [en]

    The provision of public transport is important for a sustainable society and is vital for many groups. Children, older people, and people from carless households are examples of such groups: they rely on public transport and risk social exclusion without it. The aim of this study is to identify areas in Sweden where an improved public transport system might enhance social sustainability. To this end, an index of public transport needs at a sub-municipality level was calculated along with an index of public transport provision using data from public transport authorities in Sweden. The results indicate that areas with a mismatch between the provision of and estimated demand for public transport are relatively heterogenous. High gaps exist both in rural and peripheral regions of Sweden as well as the suburbs of urban regions. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

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  • 19.
    Nerhagen, Lena
    VTI, Statens väg- och transportforskningsinstitut.
    Dieselization in Sweden: blessing or curse?2018Report (Other academic)
    Abstract [en]

    In this paper we discuss, based on research on the external cost of air pollution, if diesel as a fuel in the transport sector should be encouraged or discouraged in Swedish environmental policy. There are two main reasons for posing this question. The first is the international context where the use of diesel is generally considered to be a bad, due to its negative health effects. The second is the Swedish context with an ambitious vision for a fossil free vehicle fleet in 2030 where the use of diesel produced from forestry residues could be part of the solution. In recent years the use of diesel cars has been encouraged by various policy measures, for example a subsidy based on assessments of emissions for CO2 per kilometer. Is this a policy that should be continued or abandoned? In this paper we focus on the health impacts and our conclusion is that dieselization is more a blessing than a curse. The reason is that Sweden is a sparsely populated country and therefore the health costs of emissions from road transport are low by international standards.

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  • 20.
    Nerhagen, Lena
    Statens väg- och transportforskningsinstitut, Transportekonomi, TEK.
    Externa kostnader för luftföroreningar: kunskapsläget avseende påverkan på ekosystemet i Sverige, betydelsen av var utsläppen sker samt kostnader för utsläpp från svensk sjöfart2016Report (Other academic)
    Abstract [en]

    This report presents the basis and calculations for the subproject air pollution carried out within the framework of VTI’s second government commission on traffic economic costs (Samkost2). In this study, we have estimated marginal external costs of air pollution with the method developed and used in the EU for this purpose, the so-called “Impact Pathway Approach”, focusing on the importance and the impact on the ecosystem and emissions from shipping.

    In the earlier study of air pollution in Samkost was concluded that a largely unexplored question was how much the transport sector contributes to secondary pollution and the impact these have on population exposure and impact on the ecosystem. It was found that this is an important issue because it is these pollutants that are the focus of the EU’s air quality policy. To carry out impact assessments of the proposals at EU level in this field, and to compare the results of different studies, it is important to clarify the pollution that has been the basis for the analysis.

    For this reason, the focus of Samkost2 on air pollution became how to perform calculations for the secondary pollutants. There was also a desire to gain more knowledge about the marginal costs of emissions from Swedish shipping, and on how impacts on ecosystems can be included in these calculations. To carry out these calculations required information in the form of dispersion modelling. Therefore, SMHI was commissioned to provide data on emissions at sea and their dispersion. Due to time constraints, since this VTI’s commission had a deadline and dispersion modelling involves complex calculation that requires time, the calculations got adapted to the restrictions of the commission. Only emissions from Swedish shipping and not from the other modes were included. To get some information about geographical differences in the impact of emissions that occur in different places separate calculations for three different areas was conducted; Skagerrak and Kattegat, the Baltic Sea south of Åland and the Baltic Sea north of the Åland Islands. Specific effects, i.e. exposure, were only modelled for the population and not for different types of ecosystems.

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  • 21.
    Nerhagen, Lena
    et al.
    Dalarna University, School of Culture and Society, Economics.
    Brandt, Daniel
    Dalarna University, School of Culture and Society, Human Geography.
    Mortazavi, Reza
    Dalarna University, School of Culture and Society, Economics.
    Use of public transport as a means to reach national climate objectives - On the importance of accounting for spatial differences and costs, Transport Policy2023In: Transport Policy, ISSN 0967-070X, E-ISSN 1879-310X, Vol. 131, p. 56-65Article in journal (Refereed)
    Abstract [en]

    Sweden has since the end of the 1990s, when the environmental objective system was adopted, had the ambitionof being an environmental frontrunner. In line with this, in 2009 the Parliament adopted the goal of achieving afossil free vehicle fleet in 2030. Replacing private car use with public transport is expected to contribute to thisgoal. In 2008, a co-operation between actors in the public transport sector was launched with support from theGovernment with the aim to double its use. Sweden however is a country with important geographical differ-ences. Much of the country is sparsely populated, especially in the north. From previous research it is well knownthat usage of public transport is dependent on population density and accessibility to employment and schools.Understanding how spatial differences influence the cost of public transport provision is therefore crucial whendiscussing if public transport is a cost-efficient way to achieve national goals for the transport sector. In thispaper, Swedish county level panel data, including variables that provide information on geographical differencesbetween the counties, have been used to estimate average marginal costs of boardings. Results show that theseare much lower in the three counties with the largest urbanized areas. In the other counties there is a variationwhich illustrates that there are a number of factors that influence the average marginal costs. In relation to policy, we find that the doubling ambition established in 2008 has not been achieved.

  • 22.
    Nerhagen, Lena
    et al.
    VTI, Statens väg- och transportforskningsinstitut.
    Forsstedt, Sara
    The Swedish Transport Agency.
    Edvardsson, Karin
    The Swedish Transport Agency.
    The precautionary principle and regulatory impact assessment: on the need for initial screening of hazards in regulatory work with examples from transport2018Report (Other academic)
    Abstract [en]

    To achieve effective regulation, the OECD and the European Commission recommend the use of regulatory impact assessment (RIA). The full RIA process has however not been implemented in Sweden. There is for example a lack of established practices at the national level for the analysis of risk in regulatory work. Instead, soft law in the form of management by objective systems is guiding transport and environmental policy. These systems were introduced in the end of the 1990s following the international discussion on the precautionary principle. According to findings in other countries, policy making based on the precautionary principle may result in unexpected and unwanted consequences and therefore, based on a literature review and an assessment of current practices in transport regulation in Sweden, we suggest the use of an initial screening of hazards in regulatory work. We also apply the proposed method to four transport related case studies to illustrate how an initial assessment can provide the basis for an informed discussion on what hazards to counteract with regulation and on what grounds.

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  • 23.
    Olsmats, Carl
    Dalarna University, School of Information and Engineering, Industrial Engineering and Management.
    Expert panel discussion participant2022Conference paper (Other (popular science, discussion, etc.))
  • 24.
    Olsmats, Carl
    Dalarna University, School of Technology and Business Studies, Industrial Engineering and Management.
    From supply chain to supply loop management in the circular economy2018Conference paper (Other (popular science, discussion, etc.))
  • 25.
    Olsmats, Carl
    Dalarna University, School of Technology and Business Studies, Industrial Engineering and Management.
    Förpackningar för ökad lönsamhet: ett Supply Chain Management-perspektiv på förpackningar2018In: Supply Chain Effect: För beslutsfattare i Supply Chain, ISSN 2000-8457, Vol. 4, p. 22-26Article in journal (Other (popular science, discussion, etc.))
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  • 26.
    Olsmats, Carl
    Dalarna University, School of Technology and Business Studies, Industrial Engineering and Management.
    Speaker and expert panel member2020Conference paper (Other (popular science, discussion, etc.))
  • 27.
    Olsmats, Carl
    Dalarna University, School of Technology and Business Studies, Industrial Engineering and Management.
    The role of packaging in a supply chain management context2019Conference paper (Other (popular science, discussion, etc.))
  • 28.
    Omer, Mohamed Ali
    Dalarna University, School of Information and Engineering.
    Människors upplevelser av (o) trygghet på Busstorget i Kista – en viktig kollektiv trafikknutpunkt: En fallstudie av Kista centrum2023Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The purpose of this study was to investigate individuals' experiences of safety at Kista bus station. The study aimed to provide answers to the research questions of whether individuals perceive safety at Kista bus station and on the way to and from the bus station, if there is a difference in perceived safety between men and women, and during daytime and nighttime, and how well the results from the observation analysis aligned with the results from the survey.

    In this study, I chose to use a case study design which involved studying a specific location and focusing on the specific place of Kista bus station. A combination of various methods such as survey, observation analysis, and literature review were used in this work to facilitate the study of the location. This combination provided a deeper understanding of the functions and conditions of the location, as such a type of combination of methods helps to study the research questions from different perspectives. Thus, these methods used in this study contributed to validate the results. The conclusion of this study was that Kista bus station is relatively safe currently, but some areas around the station are perceived as unsafe.

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  • 29.
    Paidi, Vijay
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Developing decision support systems for last mile transportation problems2019Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Last mile transportation is the most problematic phase of transportation needing additional research and effort. Longer waits or search times, lack of navigational directions and real-time information are some of the common problems associated with last mile transportation. Inefficient last mile transportation has an impact on the environment, fuel consumption, user satisfaction and business opportunities. Last mile problems exist in several transportation domains, such as: the landing of airplanes, docking of ships, parking of vehicles, attended home deliveries, etc. While there are dedicated inter-connected decision support systems available for ships and aircraft, similar systems are not widely utilized in parking or attended handover domains. Therefore, the scope of this thesis covers last mile transportation problems in parking and attended handover domains. One problem area for parking and attended handovers is due to lack of real-time information to the driver or consumer. The second problem area is dynamic scheduling where the handover vehicle must traverse additional distance to multiple handover locations due to lack of optimized routes. Similarly, during parking, lack of navigational directions to an empty parking space can lead to increased fuel consumption and CO2 emissions. Therefore, aim of this thesis is to design and develop decision support systems for last mile transportation problems by holistically addressing real time customer communication and dynamic scheduling problem areas. The problem areas discussed in this thesis consists of persistent issues even though they were widely discussed in the literature. In order to investigate the problem areas, microdata analysis approach was implemented in the thesis. The phases involved in Microdata analysis are: data collection, data processing, data storage, data analysis and decision-making. Other similar research domains, such as: computer science or statistics also involve phases such as data collection, processing, storage and analysis. These research domains also work in the fields of decision support systems or knowledge creation. However, knowledge creation or decision support systems is not a mandatory phase in these research domains, unlike Microdata analysis. Three papers are presented in this thesis, with two papers focusing on parking domains, while the third paper focuses on attended handover domains.

    The first paper identifies available smart parking tools, applications and discusses their uses and drawbacks in relation to open parking lots. The usage of cameras in identifying parking occupancy was recognized as one of the suitable tools in this paper. The second paper uses a thermal camera to collect the parking lot data, while deep learning methodologies were used to identify parking occupancy detection. Multiple deep learning networks were evaluated for identifying parking spaces and one method was considered suitable for acquiring real time parking occupancy. The acquired parking occupancy information can be communicated to the user to address real-time customer communication problems. However, the decision support system (DSS) to communicate parking occupancy information still needs to be developed. The third paper focuses on the attended handovers domain where a decision support system was reported which addresses real-time customer communication and dynamic scheduling problems holistically. Based on a survey, customers accepted the use of mobile devices for enabling a real-time information flow for improving customer satisfaction. A pilot test on vehicle routing was performed where the decision support system reduced the vehicle routing distance compared to the route taken by the driver. The three papers work in developing decision support systems for addressing major last mile transportation problems in parking and attended handover domains, thus improving customer satisfaction, and business opportunities, and reducing fuel costs, and pollution.

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  • 30.
    Paidi, Vijay
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Parking support model for open parking lots2022Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Parking is a common process performed by vehicle drivers when they arrive at their destination. It is considered to be the last mile transportation problem of personal vehicles. Some of the common problems observed by drivers are additional cruising, congestion, pollution, and driver frustration. This thesis is focused on open parking lots that provide free parking spaces. Since parking spaces are provided free, open parking lots are in high demand leading to additional cruising and pollution. One of the primary reasons for these problems is the lack of information on parking availability. Such information can be provided using a parking support model, or a smart parking system. As open parking lots do not provide any direct return on investments, no parking support models were available on the market. Therefore, this thesis aims to develop a parking support model suitable for open parking lots which can facilitate in providing real-time and short-term forecast of parking availability. This thesis also examines the magnitude of additional cruising and CO2 emissions observed in an open parking lot. A thermal camera was utilized for collecting data on open parking lots as it is not susceptible to varying illumination and environmental conditions. Since there were no pre-trained algorithms for enabling object detection using thermal camera images, a dataset was created with varying environmental and illumination conditions. This dataset was utilized by deep learning algorithms to facilitate multi-object, real-time detection. The developed parking support model facilitates in providing a real-time and short-term forecast of parking availability. Despite the use of low volume of data, the methods utilized in this thesis facilitated providing better detection and forecasting results. Algorithms, such as ResNet18 and Yolo, facilitated in providing real-time, multi-object detection with high accuracy. Similarly, a short-term forecast of parking availability was provided for the open parking lot using methods such as the Ensemble-based method, LSTM and SARIMAX. Ensemble-based method and LSTM provided better test prediction results with lower errors compared to SARIMAX. A new CO2 emissions model was proposed to estimate the magnitude of emissions observed at an open parking lot. The mean CO2 emissions of additional cruising is 2.7 times more than optimal cruising. Despite the individual CO2 emissions of vehicles being lower, aggregating CO2 emissions from multiple vehicles leads to higher pollution. This problem can be reduced by utilizing the parking support model.

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  • 31.
    Paidi, Vijay
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Short-term prediction of parking availability in an open parking lot2022In: Journal of Intelligent Systems, ISSN 0334-1860, E-ISSN 2191-026X, Vol. 31, no 1, p. 541-554Article in journal (Refereed)
    Abstract [en]

    The parking of cars is a globally recognized problem, especially at locations where there is a high demand for empty parking spaces. Drivers tend to cruise additional distances while searching for empty parking spaces during peak hours leading to problems, such as pollution, congestion, and driver frustration. Providing short-term predictions of parking availability would facilitate the driver in making informed decisions and planning their arrival to be able to choose parking locations with higher availability. Therefore, the aim of this study is to provide short-term predictions of available parking spaces with a low volume of data. The open parking lot provides parking spaces free of charge and one such parking lot, located beside a shopping center, was selected for this study. Parking availability data for 21 days were collected where 19 days were used for training, while multiple periods of the remaining 2 days were used to test and evaluate the prediction methods. The test dataset consists of data from a weekday and a weekend. Based on the reviewed literature, three prediction methods suitable for short-term prediction were selected, namely, long short-term memory (LSTM), seasonal autoregressive integrated moving average with exogenous variables (SARIMAX), and the Ensemble-based method. The LSTM method is a deep learning-based method, while SARIMAX is a regression-based method, and the Ensemble method is based on decision trees and random forest to provide predictions. The performance of the three prediction methods with a low volume of data and the use of visitor trends data as an exogenous variable was evaluated. Based on the test prediction results, the LSTM and Ensemble-based methods provided better short-term predictions at multiple times on a weekday, while the Ensemble-based method provided better predictions over the weekend. However, the use of visitor trend data did not facilitate improving the predictions of SARIMAX and the Ensemble-based method, while it improved the LSTM prediction for the weekend. © 2022 Vijay Paidi, published by De Gruyter.

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  • 32.
    Paidi, Vijay
    Dalarna University, School of Information and Engineering.
    Short-term prediction of parking availability in an open parking lotManuscript (preprint) (Other academic)
    Abstract [en]

    The parking of cars is a globally recognized problem, especially at locations where there is a high demand for empty parking spaces. Drivers tend to cruise additional distances while searching for empty parking spaces during peak hours leading to problems such as pollution, congestion, and driver frustration. Providing short-term predictions of parking availability would facilitate the driver in making informed decisions and planning their arrival to be able to choose parking locations with higher availability. Therefore, the aim of this study is to provide short-term predictions of available parking spaces with a low volume of data. The open parking lot provides parking spaces free of charge and one such parking lot, located beside a shopping center, was selected for this study. Parking availability data for 21 days was collected where 19 days were used for training, while multiple periods of the remaining 2 days were used to test and evaluate the prediction methods. The test dataset consists of data from a weekday and a weekend. Based on the reviewed literature, three prediction methods suitable for short-term prediction were selected, namely, Long-short term memory (LSTM), Seasonal autoregressive integrated moving average with exogenous variables (SARIMAX), and the Ensemble-based method. TheLSTM method is a deep learning-based method, while SARIMAX is a regression-based method, and the Ensemble method is based on decision trees and random forest to provide predictions. The performance of the three prediction methods with low volume of data and the use of visitor trends data as an exogenous variable was evaluated. Based on the test prediction results, the LSTM and Ensemble-based methods provided better short-term predictions at multiple times on a weekday, while the Ensemble-based method provided better predictions over the weekend. However, the use of visitor trend data did not facilitate improving the predictions of SARIMAX and the Ensemble-based method, while it improved the LSTM prediction for the weekend.

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  • 33.
    Paidi, Vijay
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Fleyeh, Hasan
    Dalarna University, School of Information and Engineering, Computer Engineering.
    Nyberg, Roger G.
    Dalarna University, School of Information and Engineering, Informatics.
    CO2 Emissions Induced by Vehicles Cruising for Empty Parking Spaces in an Open Parking Lot2022In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 7, article id 3742Article in journal (Refereed)
    Abstract [en]

    Parking lots are places of high air pollution as numerous vehicles cruise to find vacant parking places. Open parking lots receive high vehicle traffic, and when limited empty spaces are available it leads to problems, such as congestion, pollution, and driver frustration. Due to lack of return on investment, open parking lots are little studied, and there is a research gap in understanding the magnitude of CO2 emissions and cruising observed at open parking lots. Thus, this paper aims to estimate CO2 emissions and cruising distances observed at an open parking lot. A thermal camera was utilized to collect videos during peak and non-peak hours. The resulting videos were utilized to collect cruising trajectories of drivers searching for empty parking spaces. These trajectories were analyzed to identify optimal and non-optimal cruising, time to park, and walking distances of drivers. A new CO2 model was proposed to estimate emissions in smaller geographical regions, such as open parking lots. The majority of drivers tend to choose parking spaces near a shopping center, and they prefer to cruise non-optimal distances to find an empty parking space near the shopping center. The observed mean non-optimal cruising distance is 2.7 times higher than the mean optimal cruising distance. Excess CO2 emissions and non-optimal cruising were mainly observed during visitor peak hours when there were limited or no empty parking spaces. During visitor peak hours, several vehicles could not find an empty parking space in the region of interest, which also leads to excess cruising.

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  • 34.
    Paidi, Vijay
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Nyberg, Roger G.
    Dalarna University, School of Technology and Business Studies, Information Systems.
    A holistic decision support system for last mile handovers2019In: Article in journal (Other academic)
    Abstract [en]

    The last mile handover is assumed to be the most problematic part in the delivery process and the costs can go upto 50% of the total logistic cost. Real time consumer communication and dynamic scheduling are the major problem areas associated with effective attended last mile handovers. Therefore, aim of this paper is to report the design and development of a holistic decision support system’s functionalities which simultaneously addresses real time consumer communication and dynamic scheduling. A decision support system was designed and developed based on workshops, expert group interviews and its functionalities were proposed with the use cases. A survey was conducted with consumers of a retailer where majority of the consumers accepted the use of mobile communication devices to enable real time communication and alternate handover location which improves customer satisfaction and facilitates to avoid missed handovers. A pilot test was performed where routing distance was reduced with the use of optimized handover routes. However the improvement is subjected to the experience of driver and real time traffic conditions. We conclude that a holistic decision support system with multi-party communication among the stakeholders facilitates in reducing operational costs for logistic companies and improving customer satisfaction and business opportunities.

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  • 35.
    Paidi, Vijay
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Nyberg, Roger G.
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Dynamic Scheduling and Communication System to Manage Last Mile Handovers2020In: Logistics, ISSN 2305-6290, Vol. 4, no 2, article id 0013Article in journal (Refereed)
    Abstract [en]

    Last mile handover is the most problematic phase in the delivery process, while real-time communication and dynamic scheduling are major problem areas associated with attended last mile handovers. These problem areas need to be addressed holistically to facilitate efficient last mile handovers. The aim of this paper is to report the design and functionalities of a decision-support system which holistically addresses these problem areas. The functionalities of decision-support system which addresses dynamic scheduling and real-time communication problem areas are discussed using case studies. We conclude that a holistic decision-support system with multiparty communication among the stakeholders facilitates improving customer satisfaction, business opportunities and reducing operational costs for logistics companies.

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  • 36.
    Ranhagen, Ulf
    Chalmers University of Technology, Gothenburg.
    Transport and Sustainable Urban Development: A comparative project in collaboration between Cape Town, Kisumu and Gothenburg2021Report (Other academic)
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  • 37.
    Ranhagen, Ulf
    Dalarna University, School of Information and Engineering, Construction. Sweco.
    Transport Hubs connect the City: A Story from Gothenburg in Chapter 2 Space and Place2021In: Realising Just Cities / [ed] Leonie Joubert with the Mistra Urban Futures Realising Just Cities Team, African Centre for Cities and Mistra Urban Futures , 2021, p. 33-33Chapter in book (Other academic)
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  • 38.
    Ranhagen, Ulf
    et al.
    Chalmers University of Technology, Gothenburg.
    Gustafsson, Anna
    The Urban Station Community: Towards A Resource-Efficient Transport System. Final Report For The Years 2017-20192020Report (Other academic)
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  • 39.
    Sadeghian, Paria
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    A Multi-Dimensional Approach to Human Mobility and Transportation Mode Detection Using GPS Data2024Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    GPS tracking data is an essential resource for analyzing human travel patterns and evaluating the effects on transportation systems. The primary challenge, however, is to accurately identify the modes of transportation within unlabeled GPS data. These approaches range from simple rule-based systems to advanced machine-learning techniques. This dissertation aims to bridge this gap by examining the critical features and techniques of these methods and proposing a novel approach for detecting transportation modes in GPS tracking data. To achieve this goal, a comprehensive understanding of individual journeys is crucial. Thus, this research adopts a microdata analytic approach, encompassing data collection, processing, analysis, and decision-making stages. Doing so contributes to advancing human mobility research and transportation mode detection. 

    Paper I undertook a systematic review of transport mode detection methodologies to fill the research gap, emphasizing the predominance of supervised learning algorithms and highlighting the need for further research to address the limitations of small datasets. Paper II introduced a stepwise methodology, integrating unsupervised learning, GIS, and supervised algorithms to detect transport modes while minimizing reliance on labelled data. The Random Forest algorithm emerged as a precise but time-intensive solution. Paper III showcased a novel approach to transport mode detection using deep learning models, outperforming traditional machine learning methods. This paper signals the potential of deep learning in the field and demonstrates the importance of raw GPS data in enhancing accuracy. Paper V addressed the challenge of predicting human mobility patterns under the Hidden Markov Model (HMM) framework, highlighting the applicability of HMMs to understanding and predicting complex mobility behaviour. This paper emphasized the need for GPS tracking data in developing advanced mobility models. Paper IV ventured into hybrid methodology by combining K-means clustering with the ANP-PSO algorithm to enhance transportation mode classification. This pioneering approach improved classification accuracy while reducing dependence on labelled datasets. 

    Collectively, these papers underscore the opportunities and limitations in human mobility research, offering insights into future directions for mitigating data quality issues and improving the accuracy of transportation mode detection. These innovative methodologies have practical implications for transportation planning, resource allocation, and intelligent transportation system development, ultimately shaping the future of transportation research and decision-making. Standardized data collection, processing, and labelling methods are crucial and need attention in future research. Future research can focus on developing such benchmarks and validation protocols to enhance the reliability and comparability of results.

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  • 40.
    Sadeghian, Paria
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Enhanced Clustering Approach for Transportation Mode Classification using GPS Data and Particle Swarm OptimizationManuscript (preprint) (Other academic)
    Abstract [en]

    The widespread adoption of Global Positioning Systems (GPS) in transportation has significantly contributed to the understanding of human behaviour, enabling the extraction of crucial travel information. However, the exploration of transportation modes using GPS data remains an under-researched domain due to its intricate analytical demands. While various methods, ranging from rule-based approaches to advanced machine learning algorithms, have been employed to identify transportation modes from GPS data, most have been tested on limited labelled datasets. This study introduces an innovative clustering method that combines multi-criteria decision-making, network analysis, and the meta-heuristic algorithm of particle swarm optimization to effectively cluster transportation modes. Pioneering a hybrid approach, the study utilizes elements from the Analytic Network Process (ANP) super matrix in conjunction with transportation modes as variables, harnessing the particle swarm optimization (PSO) algorithm with a fully unlabelled dataset. The compelling findings underscore the model's effectiveness, achieving an impressive accuracy rate exceeding 88% in transportation mode clustering.

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  • 41.
    Sadeghian, Paria
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Human mobility behavior: Transport mode detection by GPS data2021Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    GPS tracking data are widely used to understand human travel behavior and to evaluate the impact of travel. A major advantage with the usage of GPS tracking devices for collecting data is that it enables the researcher to collect large amounts of highly accurate and detailed human mobility data. However, unlabeled GPS tracking data does not easily lend itself to detecting transportation mode and this has given rise to a range of methods and algorithms for this purpose. The algorithms used vary in design and functionality, from defining specific rules to advanced machine learning algorithms. There is however no previous comprehensive review of these algorithms and this thesis aims to identify their essential features and methods and to develop and demonstrate a method for the detection of transport mode in GPS tracking data. To do this, it is necessary to have a detailed description of the particular journey undertaken by an individual. Therefore, as part of the investigation, a microdata analytic approach is applied to the problem areas, including the stages of data collection, data processing, analyzing the data, and decision making.

    In order to fill the research gap, Paper I consists of a systematic literature review of the methods and essential features used for detecting the transport mode in unlabeled GPS tracking data. Selected empirical studies were categorized into rule-based methods, statistical methods, and machine learning methods. The evaluation shows that machine learning algorithms are the most common. In the evaluation, I compared the methods previously used, extracted features, types of dataset, and model accuracy of transport mode detection. The results show that there is no standard method used in transport mode detection. In the light of these results, I propose in Paper II a stepwise methodology to detect five transport modes taking advantage of the unlabeled GPS data by first using an unsupervised algorithm to detect the five transport modes. A GIS multi-criteria process was applied to label part of the dataset. The performance of the five supervised algorithms was evaluated by applying them to different portions of the labeled dataset. The results show that stepwise methodology can achieve high accuracy in detecting the transport mode by labeling only 10% of the data from the entire dataset. 

    For the future, one interesting area to explore would be the application of the stepwise methodology to a balanced and larger dataset. A semi-supervised deep-learning approach is suggested for development in transport mode detection, since this method can detect transport modes with only small amounts of labeled data. Thus, the stepwise methodology can be improved upon for further studies. 

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  • 42.
    Sadeghian, Paria
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Golshan, Arman
    Dalarna Univ, Sch Technol & Business Studies, SE-79188 Falun, Sweden..
    Zhao, Xiaoyun
    Dalarna University, School of Information and Engineering, Microdata Analysis. Dalarna Univ, Sch Technol & Business Studies, SE-79188 Falun, Sweden..
    Håkansson, Johan
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    A deep semi-supervised machine learning algorithm for detecting transportation modes based on GPS tracking data2024In: Transportation, ISSN 0049-4488, E-ISSN 1572-9435Article in journal (Refereed)
    Abstract [en]

    Transportation research has benefited from GPS tracking devices since a higher volume of data can be acquired. Trip information such as travel speed, time, and most visited locations can be easily extracted from raw GPS tracking data. However, transportation modes cannot be extracted directly and require more complex analytical processes. Common approaches for detecting travel modes heavily depend on manual labelling of trajectories with accurate trip information, which is inefficient in many aspects. This paper proposes a method of semi-supervised machine learning by using minimal labelled data. The method can accept GPS trajectory with adjustable length and extract latent information with long short-term memory (LSTM) Autoencoder. The method adopts a deep neural network architecture with three hidden layers to map the latent information to detect transportation mode. The proposed method is assessed by applying it to the case study where an accuracy of 93.94% can be achieved, which significantly outperforms similar studies.

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  • 43.
    Sadeghian, Paria
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Han, Mengjie
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhao, Xiaoyun
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Testing feasibility of using a hidden Markov model on predicting human mobility based on GPS tracking data2024In: Transportmetrica B: Transport Dynamics, ISSN 2168-0566, Vol. 12, no 1, article id 2336037Article in journal (Refereed)
    Abstract [en]

    Human mobility behaviour is far from random and can be predictable. Predicting human mobility behaviour has the potential to improve location selection for facilities, transportation services, urban planning, and can be beneficial in providing more efficient sustainable urban development strategies. However, it is difficult to model urban mobility patterns since incentives for mobility is complex, and influenced by several factors, such as dynamic population, weather conditions. Thus, this paper proposes a prediction-oriented algorithm under the framework of a Hidden Markov Model to predict next-location and time-of-arrival of human mobility. A comprehensive evaluation of these two schemes for the representation of latent and observable variables is discussed. In conclusion, the paper provides a valuable contribution to the field of mobility behaviour prediction by proposing a novel algorithm. The evaluation shows that the proposed algorithm is stable and consistent in predicting the next location of users based on their past trajectories. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

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  • 44.
    Sadeghian, Paria
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhao, Xiaoyun
    Dalarna University, School of Information and Engineering, Microdata Analysis. KTH Royal Institute of Technology, Stockholm.
    Review and evaluation of methods in transport mode detection based on GPS tracking data2021In: Journal of Traffic and Transportation Engineering (English Edition), ISSN 2095-7564, Vol. 8, no 4, p. 467-482Article in journal (Refereed)
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  • 45.
    Sadeghian, Paria
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Håkansson, Johan
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhao, Xiaoyun
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Review in transport mode detection based on GPS data2021In: Journal of Traffic and Transportation Engineering (English Edition), ISSN 2095-7564Article in journal (Refereed)
  • 46.
    Sadeghian, Paria
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Zhao, Xiaoyun
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Golshan, A.
    Håkansson, Johan
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    A stepwise methodology for transport mode detection in GPS tracking data2022In: Travel Behaviour & Society, ISSN 2214-367X, E-ISSN 2214-3688, Vol. 26, p. 159-167Article in journal (Refereed)
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  • 47.
    Saleh, Roxan
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis. Swedish Transport Administration,Borlänge.
    Fleyeh, Hasan
    Dalarna University, School of Information and Engineering, Computer Engineering.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Hintze, Arend
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Assessing the color status and daylight chromaticity of road signs through machine learning approaches2023In: IATSS Research, ISSN 0386-1112, Vol. 47, no 3, p. 305-317Article in journal (Refereed)
    Abstract [en]

    The color of road signs is a critical aspect of road safety, as it helps drivers quickly and accurately identify and respond to these signs. Properly colored road signs improve visibility during the day and make it easier for drivers to make informed decisions while driving. In order to ensure the safety and efficiency of road traffic, it is essential to maintain the appropriate color level of road signs. The objective of this study was to analyze the color status and daylight chromaticity of in-use road signs using supervised machine learning models, and to explore the correlation between road sign's age and daylight chromaticity. Three algorithms were employed: Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN). The data used in this study was collected from road signs that were in-use on roads in Sweden. The study employed classification models to assess the color status (accepted or rejected) of the road signs based on minimum acceptable color levels according to standards, and regression models to predict the daylight chromaticity values. The correlation between road sign's age and daylight chromaticity was explored through regression analysis. Daylight chromaticity describes the color quality of road signs in daylight, that is expressed in terms of X and Y chromaticity coordinates. The study revealed a linear relationship between the road sign's age and daylight chromaticity for blue, green, red, and white sheeting, but not for yellow. The lifespan of red signs was estimated to be around 12 years, much shorter than the estimated lifespans of yellow, green, blue, and white sheeting, which are 35, 42, 45, and 75 years, respectively. The supervised machine learning models successfully assessed the color status of the road signs and predicted the daylight chromaticity values using the three algorithms. The results of this study showed that the ANN classification and ANN regression models achieved high accuracy of 81% and R2 of 97%, respectively. The RF and SVM models also performed well, with accuracy values of 74% and 79% and R2 ranging from 59% to 92%. The findings demonstrate the potential of machine learning to effectively predict the status and daylight chromaticity of road signs and their impact on road safety in the Swedish context. © 2023 International Association of Traffic and Safety Sciences

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  • 48.
    Salin, Hannes
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Lundgren, M.
    A Gap Analysis of the Adoption Maturity of Certificateless Cryptography in Cooperative Intelligent Transportation Systems2023In: Journal of Cybersecurity and Privacy, ISSN 2624-800X, Vol. 3, no 3, p. 591-609Article in journal (Refereed)
    Abstract [en]

    Cooperative Intelligent Transport Systems (C-ITSs) are an important development for society. C-ITSs enhance road safety, improve traffic efficiency, and promote sustainable transportation through interconnected and intelligent communication between vehicles, infrastructure, and traffic-management systems. Many real-world implementations still consider traditional Public Key Infrastructures (PKI) as the underlying trust model and security control. However, there are challenges with the PKI-based security control from a scalability and revocation perspective. Lately, certificateless cryptography has gained research attention, also in conjunction with C-ITSs, making it a new type of security control to be considered. In this study, we use certificateless cryptography as a candidate to investigate factors affecting decisions (not) to adopt new types of security controls, and study its current gaps, key challenges and possible enablers which can influence the industry. We provide a qualitative study with industry specialists in C-ITSs, combined with a literature analysis of the current state of research in certificateless cryptographic in C-ITS. It was found that only 53% of the current certificateless cryptography literature for C-ITSs in 2022–2023 provide laboratory testing of the protocols, and 0% have testing in real-world settings. However, the trend of research output in the field has been increasing linearly since 2016 with more than eight times as many articles in 2022 compared to 2016. Based on our analysis, using a five-phased Innovation-Decision Model, we found that key reasons affecting adoption are: availability of proof-of-concepts, knowledge beyond current best practices, and a strong buy-in from both stakeholders and standardization bodies. © 2023 by the authors.

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  • 49.
    Sharma, Janpriy
    et al.
    Univ Trento, Povo, Italy.
    Singh, Shweta
    Univ Texas Austin, USA.
    Tyagi, Mohit
    Punjab Engn Coll, India.
    Powar, Satvasheel
    Dalarna University, School of Information and Engineering, Energy Technology. Indian Inst Technol, India.
    Avenues of decarbonisation in the dynamics of processed food supply chains: Towards responsible production consumption2024In: Heliyon, E-ISSN 2405-8440, Vol. 10, no 5, article id e26456Article in journal (Refereed)
    Abstract [en]

    Nowadays, the demand for processed food items is surging. To fulfil the enhanced demand, a significant impact is laid on the environment, which enhances the carbon footprint being generated. Hence, to overcome this, the avenues of decarbonisation need to be explored. The presented work is aimed at promoting the decarbonisation of the existing practices within the processed food supply chains. It finds strong compliance with the sustainable development goal (SDG-12), focusing on responsible production-consumption mechanisms. For the same, key enactors of decarbonisation are identified and mapped with the practices at various stages of food supply chains, i.e. upstream, downstream, and other allied practices. Based upon these enactors, a relational, hierarchical framework is developed to provide a comprehensive perspective on complex intricacies. This framework is analysed with an innovative approach which comprises the fundamentals of Interval-Valued Intuitionistic Hesitant Fuzzy Set with the Entropy measures. It results in the outranking of the enactors relative to its importance in the decarbonisation of processed food supply chains. Furthermore, the empirical findings are validated by the sensitivity analysis to felicitate robust decision-making. The outcomes of the presented work provide a roadmap and stepped approach to achieve the decarbonisation goals and make productionconsumption mechanisms sustainable. It finds implications in the development of the framework, policy formulation, and decisional attributes for the decarbonisation of food supply chains. It focuses on the adoption of strategies that align with global efforts to mitigate climate change and promote a sustainable future.

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  • 50.
    Tayfur, Mesud
    Dalarna University, School of Information and Engineering.
    Den upplevda tryggheten i två bostadsområden2023Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Sweden is badly affected by insecurity and crime has been repeatedly presented by both right-wing populist parties and the left parties in the government. In Sweden, insecurity is a continuing growing problem and is found everywhere in the country.

    The purpose of this study is to compare how security is experienced between two residential areas in Borlänge. One residential area has been listed as a risk area by the police operational department with major socio-economic challenges and the other as having good socio-economic conditions. It will also be compared how the structure differs.The study's approach is a quantitative survey with 60 respondents. The data was processed in SPSS and Excel.

    The results of the survey show that regardless of the media and the surrounding image, it does not automatically mean that the perceived security is low. That different residential areas have different elements for what is considered safe and unsafe. The structures can be separated but still have a high level of perceived security.

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