Master's Degree Programme in Transport and Urban Planning Programplan

The Master's Degree Program in Smart Mobility and Urban Analytics (SMUA) is a full-time course of study over two years with 120 ECTS that is given in English. The program represents a continuation and specialization in relation to the bachelor's degree program in Civil Engineering, under the technical planning course option. This program offers a practical and profession-oriented specialization, extending a bachelor’s in civil engineering in the study field of integrated urban and transport planning, geographical planning, technology or landscape architecture.

In line with expectations from the industry, the program is planned to be cross disciplinary from the start, with a unique focus also on IT, digital tools and skills commonly used and highly needed in the industry, especially tools and skills related to urban and transport analytics and planning, geographical information systems (GIS) and data science.

Society and authorities place increasing demands on environmentally friendly, innovative and sustainable design of mobility and urban solutions. Climate change in the form of increased temperatures, more precipitation and extreme weather exposes constructions, infrastructure and networks to greater and less predictable stressors. Industry and researchers highlight the need of candidates with expertise at master's degree level (engineers) in the fields of smart mobility and urban analytics who have knowledge in environmental issues relating to this field as well as updated skills on new technology.

This study program offers a combination of expert and interdisciplinary knowledge where the students will achieve a high level of proficiency in sustainable urban development as well as achieving strong digital skills and knowledge. Interdisciplinary studies involve the combination of two or more academic disciplines into one activity. The interdisciplinary nature of this program has two major aspects according to the academic professionals developing this program at the faculty. The first related to the knowledge developed in urban planning and design, urban transport and mobility, as well as ethics and sustainability in this field. The second being digital competence, new technologies and tools, like simulation tools AIMSUN or SUMO, or data analysis software Python, R or Weka, or geographical information systems such as ArcGIS or QGIS.

Specialization areas in this master program will be:

Space Syntax (20 ECTS) which will provide in-depth knowledge of how complex architectural and urban systems work, and how spaces can be planned, designed and manufactured to create a better society bringing together the fields of architecture and urbanism. Space Syntax is a theoretical and analytical framework, as well as a modeling tool to design and analyze the human-built environment. Students will investigate spatial morphology and its social implications by a practical, hands-on program of lectures, workshops and a project.

Urban Mobility (20 ECTS) which will provide in-depth knowledge in land use and transportation planning for smart and sustainable cities that meet the needs of all residents. Students will learn how to experiment and test hypotheses and think strategically about multi-modal transport systems, the movement of people and goods, and intelligent transport systems in urban areas. Students will grow their expertise joining a session of lectures, workshops and through work on projects.

The goal with this program is to educate and train candidates who are qualified to address the challenges of both professional life and scholarly enquiry within their specialization as well as being a productive member of interdisciplinary teams.

Graduates from this program will:

• understand the role of their specialization in organizations and society
• possess deep technical skills from their own specialization that can be applied in a variety of real-life scenarios
• understand how their specialization is part of a wider fabric of skills necessary to solve tomorrow's challenges
• have a professional and ethical attitude towards their role in the workplace
• display creative thinking in real-life situations, leaning both on theoretical knowledge and on pragmatism
• plan and execute their work in a structured and independent manner, be it as professionals or as researchers in their field
• have expertise that is in high demand in both the private and public sector. The most relevant employers are advisory engineering firms, municipalities or other public agencies, private companies within transport and urban planning industry and research institutes
• qualify students for further studies at the doctoral degree level.

More specifically, the graduates will:

• Be able to identify needs in the smart society. This particularly means that the students are trained to plan for mobilities and accessibility to/from services, jobs and amenities that are more fluent in times when tele-commuting and online consumption has increased.
• Be aware of and sensitive to, and responsive when planning and suggesting policy measures to handle vulnerabilities. Pandemics, 100-year-storms, and similar have proven to be more than fiction. Planning for a resilient society includes planning for alternative transport solutions, and prioritization of lines, roads, and services in case of emergency.
• Be able to integrate sustainability in plans, execution, evaluation and circularity of societal development.
• Be equipped with tools and methods for planning and implementing integrative urban landscapes. With specific focus on planning for equal opportunities in urban areas where new technologies for participation in and communication with citizens may be used to different extent due to language barriers, age, trust, etc

After completing the education, the student will be especially suitable for:

• Employments in urban, regional and transport planning departments in municipalities and public organizations
• Jobs in firms and agencies developing stakeholder strategies, meta-data description and tech-mediation between smart-city developers and users
• Consultancy firms developing strategies for smart city developments
• Creation and analysis of geo-coded data, including statistical analyses
• Research and evaluation work

Students who complete the master's degree program will be awarded the degree of Master of Science (MSc) in Smart Mobility and Urban Analytics.

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The master’s degree program is aimed at candidates with at least a three-year bachelor’s degree in civil engineering, preferably in integrated urban and transport planning, who want a solid professional and academic supplement to their education in smart mobility and urban analytics.

The program is also open for candidates holding a bachelor’s degree in planning related subjects who have good knowledge of urban and spatial planning or transportation engineering, IT, geography, architecture or landscape architecture. It is recommended to have programming skills.

Please refer to the Regulations relating to Admission to Studies at OsloMet, https://lovdata.no/dokument/SF/forskrift/2015-12-15-1681, which is our basis for these admission requirements.

Admission to the master’s degree program requires a bachelor’s degree with a grade point average of C or better according to the ECTS grading scale in the following disciplines

• In civil engineering,
• In other disciplines covering urban and/or transport planning, spatial planning, transportation engineering, human and physical geography, architecture or landscape architecture, urban analytics, and urban economics.

All applicants must have taken at least:

• 20 ECTS in mathematics and/ or statistics and/or spatial analysis

Proof of your English proficiency https://www.oslomet.no/en/study/admission/english-proficiencyrequirements-masters

It is recommended to have programming skills.

Applicant groups and ranking

In line with Section 15 Quotas, paragraph 3 of the Regulations concerning Admission to Higher Education regarding master’s degree programs taught in English, this master program will reserve a minimum of 30% of the places to Norwegian applicants. https://student.oslomet.no/en/regulations-admission-studies-oslomet

On completion of the master’s degree program in Smart Mobility and Urban Analytics, candidates are expected to have the following learning outcome defined in terms of knowledge, skills and general competence:

Knowledge:

The candidate has advanced knowledge

• of theory and tools for modelling and design across the areas of smart city transportation, logistics and urban areas
• of methods and regulations used in the design and policy of urban areas and urban mobility
• to evaluate climate and environmental effects on urban areas and mobility infrastructures and apply this knowledge in solving new urban and mobility challenges
• to analyze issues related to mobility and urbanization based on the historical and current development of the discipline and take into account new technology and society’s need for more sustainable design of mobility and urban environment

Skills:The candidate is able to

• analyze space in terms of built environment, transportation, topography and climate sensitivity based on relevant data
• use relevant computer software and information and communication technology (ICT) tools in the analysis, optimization, prediction, design and visualization of mobility and urban structures
• carry out an independent, delimited research or development project under supervision and in accordance with applicable research ethical standards
• utilize earlier research and information for own innovation and development
• work independently and in cross-disciplinary teams to solve complex, practical and theoretical problems related to city transportation, logistics and urban planning

General competence:

The candidate is able to:

• identify reliable data sources, find relevant data and ensure its quality
• analyze academic, research and professional issues and make ethically sound recommendations of smart mobility and urban solutions, including their impact on humans and the environment
• apply his/her knowledge and skills to analyze and design solutions on cross-disciplinary and complex issues
• communicate the results of independent and project work, both in writing and orally, to authorities, professionals and general public
• contribute to development and innovation within smart city transportation, logistics and urban planning

The program is a full-time program over two years that consists of a lecture-based component with a scope of 90 credits and an independent project, the master’s thesis, with a scope of 30 credits. The master’s degree program will prepare students to meet society’s need for up-todate, forward-looking expertise in sustainable and smart urban analytics and transport planning. In this master program, the students will achieve knowledge in both the fields of smart mobility and urban analytics.

The courses are organized in a systematic way. The transport courses provided in the first semester will provide students strategic and technological knowledge of the state-of-the-art transport system and the challenges it is facing. Moreover, basic research skills will also be provided to help students to handle more methodological courses in the second semester. During the second semester, the widely applied analytic and modeling method will be provided to students with the focus on human activity and needs. Their knowledge will be expanded from the transport system to the whole city. Students will have in-depth skills and concepts of urban analytics and regional science. In the second year, students will select their expertise and conduct a master thesis based on everything they learned in the first year.

Smart mobility concerns the evolution of transportation networks and transport planning strategies. The study program focuses on providing the students with more detailed knowledge of the history, trends, problems, and opportunities in land use and transportation. The program incorporates substantive knowledge in transport demand and travel behavior, land use and transportation policy and planning, street design and urban space, and implications for a sustainable urban future. The study program also aims to provide updated skills on new technology in this field as well as knowledge in innovations in equitable and sustainable urban mobility.

Urban analytics is analyzing and understanding the evolution and challenges of urban development, as well as urban and land use planning. The study program focuses on providing the students with solid, theoretical knowledge and applied skills in urban systems, management of urban design and human factors in sustainable cities. Climate change and increased focus on resource use and environmental impacts thereby entail a greater focus on the choice of urban design. The study program focuses on providing the students with more detailed knowledge of town-friendly planning and green policy. The study program also aims to provide updated skills on new technology in this field as well as knowledge in innovative and sustainable urban planning.

In the third semester, students have the option to specialize in either smart mobility or in urban analytics. Students who choose to specialize in smart mobility will take the Urban Mobility elective, and students who choose to specialize in urban analytics will take the Space Syntax elective. The specialization courses give students necessary knowledge in these areas, and experience applying the skills and methods learned in the first and second semester to specific problems in smart mobility or urban analytics. After completing the specialized elective, students will then complete a master’s thesis in the fourth semester. The master’s thesis will then give the students further practice in applying their knowledge and skills to relevant issues through more comprehensive project work.

The study program focuses on teaching students how to use advanced computer programs and simulation tools to solve complex problems relating to sustainable urban and transportation problems, so the development of digital skills is an important integrated part of all the courses. This also helps make the program cross-disciplinary, including elements of computer science, analytic disciplines (like modeling, simulation), artificial intelligence, machine learning etc., because that is what the industry needs today

The study program also aims to qualify candidates with the competence to participate in research work in the field. The two courses Research Methods and Research Ethics (5 ECTS) and Advanced Research Methods (5 ECTS) underpins the master’s thesis and provides an introduction to qualitative and quantitative research methods, ethics, and academic writing and dissemination of results

The master’s thesis is an independent, supervised research or development project in the core areas and represents further specialisation in either smart mobility or urban analytics.

The structure of the programe:

The master’s degree program consists of eight compulsory courses, two elective courses in addition to a master’s thesis. The course portfolio is composed so that the compulsory courses ensure academic and professional breadth, at the same time as the students are given an opportunity for in-depth study and specialisation through elective courses and the master’s thesis.

Specialization in the field of smart mobility consists of the following courses (80 credits):

• Transport Policy and Transport (10 ECTS)
• Traffic Engineering and Intelligent Transport Systems (10 ECTS)
• Transport Modelling and Analytics (10 ECTS)
• Urban Mobility (20 ECTS)
• Master’s Thesis, with specialization in smart mobility (30 ECTS)

Specialization in the field of urban analytics consists of the following courses (80 credits):

• Inclusive Sustainable Smart Cities (10 ECTS)
• Geographical Information Systems (10 ECTS)
• Urban Analytics and Visualization (10 ECTS)
• Space Syntax (20 ECTS)
• Master’s Thesis, with specialization in urban analytics (30 ECTS)

The choice of specialization for the third semester (smart mobility or urban analytics) is made at the end of the second semester. The whole fourth semester is dedicated to the master’s thesis. It is natural that the master’s thesis builds on the project work that forms part of the specialization topic in the third semester. The topic of the thesis can either be linked to a client’s issue or to relevant research projects in the department.

In order for students to be able to present the master’s thesis, all courses from the first year of the study program must be passed.

Students are encouraged to contact relevant enterprises in the region for the purpose of gaining practical training and experience in the fields through a summer job or similar, and to establish cooperation on project assignments.

The work and teaching methods in the program includes group work, cross disciplinary projects, lectures, exercise sessions including digital labs, presentations, field work and discussions. The students will be involved in peer feedback which will be part of the learning process. The scheduled study activities shall be motivating and inspiring for the students and induce nonorganized academic work. The work methods are intended to stimulate cooperation, individual activity, reflection and fresh thinking. Contact with business and industry through external lecturers and projects in addition to ordinary tuition is intended to give the students a relevant and motivational approach throughout the study program.

To work as an expert researcher in urban or mobility design and planning requires a high level of expertise in the use of advanced computer programs and simulation tools (ICT tools) for problem-solving. Computer exercises and tasks that require the use of advanced ICT tools are therefore one of the main work methods used in the study program.

Research and teaching are also integrated throughout the study program. The teaching is to be constantly updated to encompass new knowledge, and research articles are part of the syllabus. Furthermore, the students will participate in research-related discussions and be included in ongoing research and development through projects that are part of the study program.

Project-based learning relating to urban and mobility design and planning tasks is used to give the students practice in work on complex issues. The study program will prepare the students for work methods used in the industry, through group work and project assignments in cooperation with partner companies in the industry. The projects are intended to develop the students’ ability to formulate and analyze research questions using scientific methods. Projects are normally carried out in groups, and the students will also thereby develop their ability to listen to others, exchange knowledge and discuss solutions in cooperation with others. Project work shall culminate in reports written on the basis of a template for scholarly articles/reports.

The master's thesis shall take the form of independent, supervised research or development work in one of the key subject areas of the study program.

The master's thesis must follow at least one scientific approach, and the result must contain elements of new knowledge or new methods. Each student or group of students will be assigned an internal supervisor who will ensure that the project complies with research ethics principles and help students to formulate the research question and ensure quality in the collection and analysis of data. The master's thesis shall be a written report based on research principles and methods.

Planen er utarbeidet ved OsloMet - storbyuniversitetet etter forskrift om rammeplan for ingeniørutdanningen, fastsatt av Kunnskapsdepartementet 18. mai 2018.

Nasjonalt kvalifikasjonsrammeverk for høyere utdanning, fastsatt av Kunnskapsdepartementet 20. mars 2009, gir oversikt over det totale læringsutbytte definert i kunnskap, ferdigheter og generell kompetanse som kandidaten forventes å ha etter fullført utdanning. Læringsutbyttebeskrivelsene i planen er utarbeidet i henhold til rammeplan og kvalifikasjonsrammeverket.

Studiet er en treåring rammeplanstyrt ingeniørutdanning. Kandidater som har fullført i henhold til programplanen tildeles graden Bachelor i ingeniørfag – matematisk modellering og datavitenskap. Studiets profil er preget av samhandling mellom informatikk, matematikk, statistikk og fysikk. Utdanningen skal gi studentene kompetanse til å arbeide med ingeniørfaglige problemstillinger knyttet til realfaglige anvendelsesområder. Gjennom tre år med ingeniør-rettede emner vil studenten tilegne seg kunnskap som er essensiell for naturvitenskapelige problemstillinger i arbeidslivet. Studiet er tilpasset ingeniørfaglige premisser og er forskningsbasert; forskning og utviklingsarbeid danner grunnlag for en kontinuerlig utvikling av studiets innhold og struktur, som involverer både stipendiater og studenter.

Studentene følger samme emner første studieår, og så fordyper de seg i økende grad i andre og tredje studieår. I siste semester gjennomfører studentene en bacheloroppgave knyttet til arbeidslivsrettede problemstillinger.

Videre studier

Det finnes en rekke videreutdanningsmuligheter for kandidater med bachelor i ingeniørfag. En del fortsetter fram til en mastergrad i ved OsloMet, hvor Anvendt data- og informasjonsteknologi (ACIT) er mest relevant. Studiet er spesielt tilrettelagt for spesialiseringene «Anvendt kunstig intelligens», «Datavitenskap», «Matematisk modellering og kvanteteknologier» i ACIT-programmet. Spennende mastertilbud finnes også ved NTNU, UMB, UiO eller andre norske og utenlandske universiteter

Studiets målgruppe er søkere med realfaglig bakgrunn som ønsker høyere utdanning innen et ingeniørfaglig område. Søkere som ikke har realfaglig bakgrunn kan søke på universitetets forkurs for ingeniørfag eller tre-semesterordning for å kvalifisere seg videre til ingeniørutdanning. Se universitetets nettsider: www.oslomet.no

Dette studiet er en interdisiplinær utdanning som kobler sammen matematisk analyse, numerisk og diskret matematikk, fysikk, statistikk, og datadrevne metoder. Studenter som søker seg til studiet bør være motivert for å jobbe disse temaene og hvordan de kobles sammen for å løse komplekse ingeniørfaglige problemstillinger fra arbeidslivet. Dette er et ambisiøst program med stort innslag av matematikk i løpet av studiet, som vil forfine en matematisk tilnærming til problemløsning som kan anvendes både i og utenfor matematiske rammer

Generell studiekompetanse/realkompetanse og i tillegg matematikk R1+R2 og fysikk 1. Forkurs eller teknisk fagskole fra tidligere strukturer oppfyller kvalifikasjonskravene. Søkere med teknisk fagskole etter lov om fagskoler av 2003 må ta matematikk R1+R2 og fysikk 1.

Viser til forskrift om opptak til høyere utdanning: https://lovdata.no/dokument/LTI/forskrift/2007- 01-31-173

En kandidat med fullført og bestått kvalifikasjon 3-årig skal ha følgende totale læringsutbytte definert i kunnskap, ferdigheter og generell kompetanse.

Kunnskap

Kandidaten:

• har bred kunnskap som gir et helhetlig systemperspektiv på ingeniørfaget generelt, med fordypning i matematisk modellering og datavitenskap. Sentrale kunnskaper inkluderer matematisk problemløsning, forståelse for fysiske prinsipper, samt utvikling og bruk av realfaglig programvare.
• har grunnleggende kunnskaper i matematikk, naturvitenskap, relevante samfunns- og økonomifag og om hvordan disse kan benyttes i ingeniørfaglig problemløsning.
• har kunnskap om teknologiens historie, teknologiutvikling, ingeniørens rolle i samfunnet, relevante lovbestemmelser knyttet til bruk av matematisk modellering og datavitenskap og har kunnskaper om ulike konsekvenser ved bruk av teknologien.
• kjenner til forsknings- og utviklingsarbeid innenfor matematisk modellering og datavitenskap, samt relevante metoder og arbeidsmåter innenfor ingeniørfaget.
• kan oppdatere sin kunnskap innenfor fagfeltet, både gjennom informasjonsinnhenting og kontakt med fagmiljøer og praksis.

Ferdigheter

Kandidaten:

• kan anvende kunnskap og relevante resultater fra forsknings- og utviklingsarbeid for å løse teoretiske, tekniske og praktiske problemstillinger innenfor matematisk modellering og datavitenskap, samt begrunne sine valg
• har kunnskap om programvare og programmeringsspråk relevant for matematisk modellering og datavitenskap og har bred ingeniørfaglig digital kompetanse.
• kan bruke relevante programmeringsspråk til å løse naturvitenskapelige problemstillinger.
• kan arbeide i digitale laboratorier og behersker metoder og verktøy som grunnlag for reproduserbar, målrettet og innovativt arbeid.
• kan identifisere, planlegge og gjennomføre ingeniørfaglige prosjekter, arbeidsoppgaver, forsøk og eksperimenter både selvstendig og i team.
• kan finne, vurdere, bruke og henvise til informasjon og fagstoff og framstille dette slik at det belyser en problemstilling.
• kan bidra til nytenkning, innovasjon og entreprenørskap gjennom deltakelse i utvikling og realisering av bærekraftige og samfunnsnyttige produkter, systemer og løsninger.

Generell kompetanse

Kandidaten:

• har innsikt i miljømessige, helsemessige, samfunnsmessige og økonomiske konsekvenser av bruk av matematisk modellering og datavitenskap.
• kan sette resultater av matematisk modellering og datavitenskap i et etisk og livsløpsperspektiv.
• kan identifisere sikkerhets-, sårbarhets-, personverns- og datasikkerhetsaspekter i produkter og systemer som anvender IKT.
• kan formidle ingeniørfaglig kunnskap til ulike målgrupper både skriftlig og muntlig og kan bidra til å synliggjøre teknologiens betydning og konsekvenser.
• kan reflektere over egen faglig utøvelse, også i team og i en tverrfaglig sammenheng, og kan tilpasse denne til den aktuelle arbeidssituasjon.
• kan bidra til utvikling av god praksis gjennom å delta i faglige diskusjoner innenfor matematisk modellering og datavitenskap og dele sine kunnskaper og erfaringer med andre.
• har informasjonskompetanse; vet hvorfor man skal søke etter kvalitetssikrede kunnskapskilder, hvorfor man skal henvise til kilder og kjenner til hva som defineres som plagiat og fusk i studentarbeider.
• kan oppdatere sin kunnskap gjennom litteraturstudier, informasjonssøking, kontakt med fagmiljøer og brukergrupper og gjennom erfaring.