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Reducing Uneven Crowd Distribution in the Stockholm Metro System Using Data Driven Design

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Reducing Uneven Crowd Distribution in the Stockholm Metro System Using Data Driven Design DEGREE PROJECT IN DESIGN AND PRODUCT REALISATION, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2019 Reducing uneven crowd distribution in the Stockholm metro system using data driven design CHRISTOFFER INGEVALDSSON MARCUS LARSSON KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT Reducing uneven crowd distribution in the Stockholm metro system using data driven design Christoffer Ingevaldsson Marcus Larsson Master of Science Thesis TRITA-ITM-EX 2019:477 KTH Industrial Engineering and Management Machine Design SE-100 44 STOCKHOLM Abstract Master of Science Thesis TRITA-ITM-EX 2019:477 Reducing uneven crowd distribution in the Stockholm metro system using data driven design Christoffer Ingevaldsson Marcus Larsson Approved Examiner Supervisor 2019-06-24 Claes Tisell Liridona Sopjani Commissioner Contact person Tyréns AB Jan Eklund The purpose of this project was to develop several information system concepts with the goal of reducing uneven crowd distribution in the Stockholm subway system, using a data driven, user centred, and iterative design approach. These systems were designed to be implemented on-site in the subway. The project also sought to evaluate the efficacy of different types of information systems. The project was initiated with a background study, involving a study of available literature from previously conducted studies, as well as a state-of-the-art analysis of systems currently available on the market. The background study was followed by an analysis of train load data in order to find patterns in traveller behaviour, as well as stations of particular interest for user studies. Initial user studies were conducted through contextual and in-depth interviews, an online survey, and passive observations on- site in the subway. Findings from the load data and user study analyses were then utilised in the concept development phase, during which several concepts were created. Concepts were evaluated in an iterative manner, using continuous user feedback to drive development. In total, nine different concepts were developed and tested at some stage. Ultimately, one concept was chosen for field tests with a prototype implemented at Tekniska Högskolan subway station, which further drove development while also generating objective data through the load measuring systems built into the train. The test involved delivering real-time crowding information to travellers using a system of signs, and RGB-LED modules mounted in the ceiling of the platform. The findings generated throughout the project were condensed as a set of design considerations to be used when designing information systems for use in the subway. Such considerations include factors such as information detail and abstraction, information placement, and visual design principles. The field tests indicated that the delivery of real-time crowding information is highly valued by travellers and has the potential to both increase user satisfaction and reduce uneven crowd distribution. Sammanfattning Examensarbete TRITA-ITM-EX 2019:477 Reducering av snedbeläggning i Stockholms tunnelbanesystem genom datadriven design Christoffer Ingevaldsson Marcus Larsson Godkänt Examinator Handledare 2019-06-24 Claes Tisell Liridona Sopjani Uppdragsgivare Kontaktperson Tyréns AB Jan Eklund Syftet med detta projekt var att utveckla ett antal informationssystem med målet att minska snedbeläggning i Stockholms tunnelbanesystem, genom att använda en datadriven, användarcentrerad, och iterativ designprocess. Systemen utvecklades för att implementeras på plats i tunnelbanan. Projektet avsåg också att utvärdera effekten av olika typer av informationssystem. Projektet inleddes med en bakgrundsstudie, vilken involverade litteratur från tidigare genomförda studier, samt en state-of-the-art-analys av system som för närvarande finns på marknaden. Bakgrundsstudien följdes av en analys av lastdata från tunnelbanevagnarna, med målet att hitta mönster i resenärernas beteende samt lämpliga stationer för användarstudier. Användarstudierna bestod av kontextuella intervjuer, djupintervjuer, en onlineenkät, samt passiva observationer på plats i tunnelbanan. Datan från dessa studier analyserades sedan för att hitta gemensamma beteenden och åsikter, samt korrelationer mellan dessa. Insikterna från lastdataanalysen och användarstudieanalysen användes sedan i konceptutvecklingsfasen, där flera koncept utvecklades. Koncepten utvärderades iterativt med kontinuerlig återkoppling från användare. Totalt sett nio koncept utvecklades och testades. Slutligen valdes ett koncept att implementeras som en prototyp i fältstudier vid Tekniska Högskolans tunnelbanestation, vilket ledde till vidareutveckling samt objektiv data from lastmätningssystemen i tågen. Testet involverade att skicka realtidsdata om trängsel på tåget genom ett system av skyltar, samt RGB-LED-moduler monterade i perrongens tak. Insikterna som genererades under projektet samlades som ett antal designprinciper som bör följas när ett informationssystem för tunnelbanan ska designas. Dessa principer täcker faktorer som detaljrikedom och abstraktion, positionering, och grafisk design. Fältstudierna indikerade att realtidsinformation om trängselnivåer värderas högt av resenärer och att det har potentialen att både öka kundnöjdheten och minska snedbeläggning. Acknowledgements Firstly, we would like to thank our supervisor Liridona Sopjani for being an inspiration and for guiding us throughout this project. Furthermore, we would like to thank Jan Eklund and Tyréns for accommodating us and providing industry contact. We would also like to thank John Carlander, Jan Magnusson, and Johan Karlqvist at MTR, as well as Henrik Brusewitz at SL, for being instrumental in allowing us to conduct field tests. We would also like to thank Björn Thuresson and the VIC Studio at KTH for lending us prototyping equipment. Finally, we would like to thank the more than 1100 Stockholmers who participated in our studies. Table of contents 1 Introduction .......................................................................................................................................... 1 2 Background research and state of the art. ............................................................................................ 3 2.1 Systems in Stockholm public transport ......................................................................................... 3 2.2 Systems in other cities .................................................................................................................. 4 2.3 Conceptual systems ....................................................................................................................... 5 2.4 Software interfaces ........................................................................................................................ 7 3 Design Approach ................................................................................................................................. 8 3.1 Data driven design ........................................................................................................................ 8 3.2 Iterative design .............................................................................................................................. 8 3.3 Nudging......................................................................................................................................... 8 4 Methodology ...................................................................................................................................... 10 4.1 Load data analysis method .......................................................................................................... 10 4.2 User research methods ................................................................................................................ 10 4.3 Field tests and prototyping .......................................................................................................... 12 5 User research results .......................................................................................................................... 13 5.1 Load data analysis results ........................................................................................................... 13 5.2 Contextual interview insights...................................................................................................... 17 5.3 In-depth interviews ..................................................................................................................... 19 5.4 Survey insights ............................................................................................................................ 20 5.5 Observation insights .................................................................................................................... 22 6 Initial ideation .................................................................................................................................... 24 6.1 App for showing crowding levels on the train ............................................................................ 24 6.2 Concepts for showing crowding information on-site .................................................................. 25 6.3 Static directions using floor decals ............................................................................................. 26 6.4 Implied denial of entry for doors with high crowding levels ...................................................... 26 6.5
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