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Projects / Programmes source: ARIS

Development of models for intelligent management of road transports

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Research activity

Code Science Field Subfield
5.04.04  Social sciences  Administrative and organisational sciences  Logistics 

Code Science Field
S189  Social sciences  Organizational science 

Code Science Field
5.06  Social Sciences  Political science 
Keywords
logistics, services over the road infrastructure, GIS, GPS, smart networks, big data, big networks, cloud computing, algorithms
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (16)
no. Code Name and surname Research area Role Period No. of publications
1.  19284  PhD Marko Boben  Computer intensive methods and applications  Researcher  2013 - 2016  84 
2.  33477  PhD Jernej Bodlaj  Computer intensive methods and applications  Researcher  2013 - 2014  14 
3.  33987  PhD Monika Cerinšek  Computer intensive methods and applications  Researcher  2013 - 2016  21 
4.  24421  PhD Boris Horvat  Computer intensive methods and applications  Head  2013 - 2016  143 
5.  20269  PhD Iztok Kavkler  Mathematics  Researcher  2013 - 2016  59 
6.  34750  PhD Gašper Košmrlj  Mathematics  Researcher  2013 - 2016  19 
7.  34751  PhD Boštjan Kovač  Mathematics  Researcher  2013 - 2016  10 
8.  25662  PhD Rebeka Kovačič Lukman  Chemical engineering  Researcher  2014  190 
9.  26450  PhD Primož Lukšič  Computer intensive methods and applications  Researcher  2013 - 2016  96 
10.  32924  Damijan Omerza  Interdisciplinary research  Researcher  2013 - 2015  7 
11.  21658  PhD Alen Orbanić  Computer intensive methods and applications  Researcher  2013 - 2015  141 
12.  01941  PhD Tomaž Pisanski  Mathematics  Researcher  2013 - 2016  866 
13.  24270  PhD Jure Pražnikar  Computer science and informatics  Researcher  2014 - 2016  39 
14.  21555  PhD Marjan Šterk  Computer science and informatics  Researcher  2013 - 2016  69 
15.  22354  PhD Jernej Tonejc  Mathematics  Researcher  2014  13 
16.  04547  PhD Tatjana Zrimec  Computer science and informatics  Researcher  2015 - 2016  81 
Organisations (3)
no. Code Research organisation City Registration number No. of publications
1.  1669  University of Primorska, Andrej Marušič Insitute  Koper  1810014007  10,776 
2.  2012  XLAB software development and consulting Ltd.  Ljubljana  1639714  322 
3.  2975  ABELIUM d.o.o., research and development  Ljubljana  3557952  455 
Abstract
In the applied research project we want to investigate the theory, technology, standards, architecture and possibilities for the implementation of modern logistics information platform in the cloud with the support of modern information, sensor and communication technologies and standards. Through the development of selected logistical problems we want to build a prototype of a modern, secure, reliable, flexible and scalable-platform solution in cloud, which will be the basis for the development of new services in the smart logistics networks using logistic infrastructure as a service - LiaaS. We will focus on two key target problem set:   (1) segmentation of users and parts of the transport network according to different criteria for determining the needs of target groups in different contexts; (2) optimization of networks according to different constraints and prior the knowledge about what is happening on the network in a similar context.   To address these topics we will need to develop models of appropriate indicators for monitoring the traffic flow of specific groups, and also to identify, adapt and develop appropriate prediction methods, knowledge about networks of large datasets and build management tools for dealing with geolocation data. Data will be combined with other public databases. We will deal with issues of processing large volumes of ordered data, including anonymity, security and enrichment of databases. We will identify several use cases and for them investigate and implement optimization algorithms to visualize and analyze large amounts of data, which will be included in modules for the LiaaS platform. We will explore the fields of logistics, cloud computing, mathematical modeling, the development of optimization algorithms, machine learning, data analysis and visualization, location-based services and mobile technologies.   Identified enriched logistics services will allow use on smart mobile devices and OBU terminals. Identified specific examples are: - The municipal road maintenance: tracking, routing, route optimization, exceptional situations, upgrading the database system; - Municipal services responsible for waste packaging management: automation of the collection of waste carts optimization, decision support of methods of collecting waste; - Charging for road use and for environmental impact: Toll without contact, safe and reliable logistics infrastructure for user fees charging (entrance to the city, insurance) and environmental impact (CO2 footprint); - Public Services - planning the modernization of infrastructure and maintenance works , fluidity, automatic recording of incidents – e.g. driving the wrong way, an accident in the tunnels, congestion; - Insurance - new models of insurance based on correctly estimated risk of accident, based on information about where you drive; - Optimization services for use of empty space in the vehicles (increase in utilization); - Support to the citizens - the announcement of the location of defects on the roads.   The project involved an interdisciplinary team of researchers and domain experts: University of Primorska, Andrej Marusic Institute: logistics, technology, environment and sustainable development, algorithms, knowledge transfers to industry, Abelium R&D: applied mathematics and theor. computing, prediction, large-scale networks, 2D GIS, mobile technology, Xlab: geoinformatics, HPC, 3D GIS, cloud services, Nokia Siemens Networks: special hardware, sensor system, international logistics platform, examples of good practice from abroad, T-2: hardware and network infrastructure for SaaS solutions, development of business models, access to users.
Significance for science
This project provided direct scientific effects (PhDs of involved researchers, scientific articles, conference presentations, organization of international scientific conferences), direct applicative effects (transfer of research knowledge into practice, transfer of industry needs to the academics, employment of researchers from academia in the industry, helping Slovenian start-up companies to develop key competences, application of knowledge on logistics problems, establishing links with venture capital funds) and exceptional social effects (recognition of Slovenia and project partners, participation in EU projects, international awards for innovations, transfer of good practices from IBM and Microsoft, applications to H2020 calls, successful application to H2020 SME - phase 2 call, partnerships with excellent research partners from abroad). New discoveries Scientific research was directed primarily to the fields of machine learning, network analysis, graph theory and algorithm development in logistics. Scientific articles were published in scientific journals, also in the group A1, with a few contributions from the middle of 2016 still in publication. In the field of large networks two young researchers involved in the project received their PhDs; Monika Cerinšek (Analysis of Two-mode networks and the multiplication of networks) and Jernej Bodlaj (hierarchical displays of large networks). Dr. Cerinšek is continuing her research of to data analysis in the field of management and organizational sciences, where she successfully applied for a postdoctoral project "Large network of business systems analysis." In 2015 another mathematician, who collaborated on the project, received his PhD. Knowledge transfer Network analysis in the context of new platform models is becoming increasingly important as a tool for measuring the network effects of business interactions and enabling positive feedback loops. To this end, we have developed a library for interactive visualization of networks online. Competencies of large datasets and data analysis, developed on the project, ware included in the international application of the project "Da.Re. - Data Science Pathways to Re-Imagine Education " by the partners Abelium and the University of Primorska, and was approved in July 2016 to be financed by the ERASMUS+ programme. Application of results Some researchers on the project (following the example of the best universities in the world) decided to transfer the applied research into practice and in the next three years upgrade the knowledge of existing or create new start-up companies. Furthermore, Dr. Bodlaj focused on the development of GIS tools and is already employed in the economy.
Significance for the country
During the project we have worked with several Slovenian companies, especially start-ups. We joined forces with GoOpti, which has become an additional co-financier of the project and is one of the most representative start-up companies in Slovenia, already expanding its operations abroad. GoOpti and researchers on the project received several awards for innovation of business models and technology as well as awards in the field of cloud computing. Project cofinancers Abelium and GoOpti have been successful with the application to the SMEs - Phase 2 call of the Horizon 2020 Programme, with support for the project provided by the companies IBM and Microsoft. The consortium convinced the European agency for small and medium-sized enterprises with the internationalization strategy and its innovative business model of a digital market of passenger services, based on integrated and substantially upgraded research results of this project. Project members also participated in the core teams of two consortia that succeeded with the strategical development and innovation partnership (SRIP) proposals (Smart cities and communities, Mobility). In the context of research and development activities, we have strengthened the cooperation in the field of high technology with international IT giants, such as Microsoft, IBM and Cisco. On the basis of the project’s activities, we have established new contacts and got invited to participate in several international consortia (H2020, Erasmus+, Interreg Adrion). In the next few years we are planning to use the competencies for the development of intelligent platform-based business models, gained in the project, to create internationally successful business models and validate them on the market. Project members have also become active members of the Commission for the circular economy and economy of scale. At the end of the project (July 2016), we visited the European Commission (Cabinet of the Commissioner for Transport, MSc. Violeta Bulc), presented our activities and talked about various European initiatives in the field of digital logistics markets and smart city initiatives. In July 2016, we participated in the international conference "MIT Platform Strategy Summit 2016", organized by MIT (Cambridge, MA, USA), where we met with the most prominent researchers in the field of platform business models. In May 2016 we met with the US corporation Uber and started conversations about research collaboration, which we continued within the framework of our visit to the US, organized by the Government of Slovenia in September 2016.
Most important scientific results Annual report 2013, 2014, 2015, final report
Most important socioeconomically and culturally relevant results Annual report 2013, 2014, 2015, final report
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