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  • 1.
    Aramrattana, Maytheewat
    et al.
    VTI, Sweden; Halmstad University, Sweden.
    Andersson, Anders
    VTI, Sweden.
    Burden, Håkan
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Reichenberg, Frida
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Mellegård, Niklas
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Testing Cooperative Intelligent Transport Systems in Driving Simulators2018Conference paper (Other academic)
    Abstract [en]

    Cooperative IntelligentTransport Systems include many actors in the transport system that are con-nected to each other via wireless communication in order to interact andcooperate. Majority of the actors in thesystems are vehicles, which can range from fully autonomous vehicles tomanually driven vehicles, equipped withwireless communication modules. Creating realistic scenarios for testing suchcomplex systems often need a com-bination of simulators. This paper presents a distributed simulation frameworkthat consists of a) a moving basedriving simulator; b) a real-time hardware-in-the-loop simulator; and c) anetwork simulator and traffic simulator. Wepresent our approach for connecting and co-simulating the mentioned simulators.As a first test of our simulationframework, a crossing scenario is simulated. Lastly, we discuss potentialbenefits and future work.

  • 2.
    Aramrattana, Maytheewat
    et al.
    VTI Swedish National Road and Transport Research Institute,Sweden.
    Andersson, Anders
    VTI Swedish National Road and Transport Research Institute,Sweden.
    Reichenberg, Frida
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Mellegård, Niklas
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Burden, Håkan
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Testing cooperative intelligent transport systems in distributed simulators2019In: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 65, p. 206-216Article in journal (Refereed)
    Abstract [en]

    Simulation is often used as a technique to test and evaluate systems, as it provides a cost-efficient and safe alternative for testing and evaluation. A combination of simulators can be used to create high-fidelity and realistic test scenarios, especially when the systems-under-test are complex. An example of such complex systems is Cooperative Intelligent Transport Systems (C-ITS), which include many actors that are connected to each other via wireless communication in order to interact and cooperate. The majority of the actors in the systems are vehicles equipped with wireless communication modules, which can range from fully autonomous vehicles to manually driven vehicles. In order to test and evaluate C-ITS, this paper presents a distributed simulation framework that consists of (a) a moving base driving simulator; (b) a real-time vehicle simulator; and (c) network and traffic simulators. We present our approach for connecting and co-simulating the simulators. We report on limitation and performance that this simulation framework can achieve. Lastly, we discuss potential benefits and feasibility of using the simulation framework for testing of C-ITS. 

  • 3.
    Burden, Håkan
    et al.
    RISE - Research Institutes of Sweden, ICT, Viktoria. University of Gothenburg, Sweden.
    Haraldson, Sandra
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Karlsson, Mathias
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Mellegård, Niklas
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Olsson, Eddie
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Accelerating Acquisition in an Open Innovation Ecosystem2019Conference paper (Refereed)
    Abstract [en]

    Maritime transports are to be regarded as a self-organized ecosystem (Kay et al., 1999) characterized by sub-optimization where historically each actor to has optimized its own operations, often giving rise to inefficiencies as a whole. In recent years however, digital transformation has challenged this by providing means for enhanced transparency in data sharing and situational awareness, enabling better coordination and improved efficiency on the whole (Lind et al. 2018a). Digital transformation drives the possibilities of creating new value by enabling higher degrees of connectivity between actors, digitally twin physical objects, drawing patterns of behaviour based on extensive sets of historical data, as well as harmonizing data sharing through standardized interfaces and communication protocols (e.g. Almirall and Casadesus-Masanell 2010; Gassman et al. 2010; Lakhani et al. 2006). To break existing patterns of behaviour and to avoid the creation of proprietary solutions that feed sub-optimization, there is a need for new inspiration and perspectives that capitalize on the opportunities that digital transformation provides. From an open innovation point of view, this means that innovators both having experience from the sector as well as from other sectors would come together, come up with, and provide new applications not previously possible or never thought about before. A core capability that the ecosystem needs to develop and ensure is data streams made accessible for those that can provide new applications aimed for the single actor and/or clusters of actors, within or outside the maritime sector (Lind et al. 2018).This has also been one of the objectives for Port Collaborative Decision Making (PortCDM), which is a concept that provides guidelines and standards for the data exchange within and between ports, between ships and ports, and between ports and hinterland operators (Lind et al 2018). Such data exchange is necessary if enhanced efficiency during port call operations is to be achieved but also facilitates open 

    innovation within the maritime sector. In order to realise that potential, a purposive transfer of knowledge between the established actors and potential new service providers has to be established (Chesbrough 2006). We therefore set out to explore How can open innovation intermediaries accelerate acquisition in an ecosystem through the management and throughput of knowledge transfer?We address the question through a longitudinal study by applying an action research approach involving actors from the local port and students from three bachelor programs. Before we describe the specifics of the research methodology, we outline our theoretical framework in terms of how knowledge transfer can be framed within an open innovation ecosystem. After the research methodology we detail the five iterations and then discuss the effect on knowledge transfer within the ecosystem. Finally, we conclude and give directions on future research.

  • 4.
    Holm, Henrik
    et al.
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Mellegård, Niklas
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Fast decoding of Automatic Identification Systems (AIS) data2018Conference paper (Other academic)
    Abstract [en]

    Decodinglarge AIS encoded data sets into clear text is time consuming. This paperdetails an approach on how to structure the innermost part of AIS decoding toincrease performance. The method is compared to existing Open Sourceimplementations, as well as to a straight forward example. The proposedapproach can increase decoding performance 20-30 times compared to these.

  • 5.
    Mellegård, Niklas
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Using weekly open defect reports as anindicator for software process efficiency : Theoretical framework and a longitudinal automotive industrial case study2017In: Proceedings of IWSM/Mensura'17, October 25–27, 2017, Gothenburg, Sweden (MENSURA’17), 2017, p. 170-175Conference paper (Refereed)
    Abstract [en]

    Well-defined, informative and cheap indicators are important inany software development organization that needs to evaluateaspects of its development processes and product quality. This isespecially true for large organizations and for organizationsdeveloping complex products; for example automotive safetyfunctions where mechanical, electronic and software systemsneed to interact. In this paper we describe defect backlog profilesas a well-defined, cheap and informative indicator. We definedefect backlog profiles in terms of ISO/IEC 15939, provide atheoretical framework for interpretation, and finally present anevaluation in which we applied the indicator in a longitudinalcase study at an automotive manufacturer. In the case study, wecompare the software integration defect backlog profile for theactive safety component released in 2010 to the profile for thefollowing generation of the same component released in 2015.The results are then linked to a number of process and productchanges that occurred between the two product generations. Weconclude that defect backlog profiles are cheap in terms of datacollection and analysis, and can provide valuable process andproduct quality information although with limitations.

  • 6.
    Mellegård, Niklas
    et al.
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Burden, Håkan
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Levin, Daniel
    Volvo Car Corporation, Sweden.
    Lind, Kenneth
    HiMinds Göteborg AB, Sweden.
    Magazinius, Ana
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Contrasting Big Bang with Continuous Integration Through Defect Reports2018In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194Article in journal (Refereed)
    Abstract [en]

    Continuous integration promises earlier defect detection, quality improvements and more customer value delivered faster. But what evidence is there? In this longitudinal case study we examined the development of software for the advanced safety and driver support component of a Swedish vehicle manufacturer in two consecutive projects, where the first was developed in a big bang fashion, typical to a traditional waterfall process, while the second project utilized continuous integration. By contrasting the two projects, we evaluated the introduction of continuous integration and supplement earlier claims based on interview studies with a quantitative analysis of defect reports.

  • 7.
    Mellegård, Niklas
    et al.
    RISE, Swedish ICT, Viktoria.
    Ferwerda, Adry
    Centric, Netherlands.
    Lind, Kenneth
    RISE, Swedish ICT, Viktoria.
    Heldal, Rogardt
    Chalmers University of Technology, Sweden; University of Gothenburg, Sweden.
    Chaudron, Michel R. V.
    Chalmers University of Technology, Sweden; University of Gothenburg, Sweden.
    Impact of Introducing Domain-Specific Modelling in Software Maintenance: An Industrial Case Study2016In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520, Vol. 42, no 3, p. 248-263, article id 7270333Article in journal (Refereed)
    Abstract [en]

    Domain-specific modelling (DSM) is a modern software development technology that aims at enhancing productivity. One of the claimed advantages of DSM is increased maintainability of software. However, current empirical evidence supporting this claim is lacking. In this paper, we contribute evidence from a case study conducted at a software development company. We study how the introduction of DSM affected the maintenance of a legacy system. We collected data about the maintenance phase of a system that was initially developed using manual programming, but which was gradually replaced by DSM development. We performed statistical analyses of the relation between the use of DSM and the time needed to resolve defects, the defect density, and the phase in which defects were detected. The results show that after introducing DSM the defect density is lower, that defects are found earlier, but resolving defects takes longer. Other observed benefits are that the number of developers and the number of person-hours needed for maintaining the system decreased, and the portability to new platforms increased. Our findings are useful for organizations that consider introducing DSM and would like to know which benefits can be realized in software maintenance.

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