Study on effective wayfinding system at Mass Rapid Transport (MRT) station
More MRT stations will evolve into interchange stations in line with Land Transport Authority’s plan to double Singapore MRT network by 2030. Additional service line at a station increases the possible navigations paths, thereby increasing the complexity of the wayfinding system, which is subject of...
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sg-ntu-dr.10356-642002023-03-03T16:50:33Z Study on effective wayfinding system at Mass Rapid Transport (MRT) station Chee, Pei Nen Wong Yiik Diew School of Civil and Environmental Engineering Centre for Infrastructure Systems DRNTU::Engineering::Civil engineering More MRT stations will evolve into interchange stations in line with Land Transport Authority’s plan to double Singapore MRT network by 2030. Additional service line at a station increases the possible navigations paths, thereby increasing the complexity of the wayfinding system, which is subject of this study. This project aims to identify the key elements to be taken care in the process of upgrading a wayfinding system of a MRT station that experiences the transformation. Also, this project focuses on inside-out navigation and transfers between service lines. A systematic process that involves onsite observation, feedback collection from station staff and commuters, and data mining on social media website was used to study the effectiveness of the selected wayfinding systems and identify users’ expectations. A non-interchange station (Boon Lay Station), an interchange station serving two service lines (Buona Vista Station) and an interchange station serving three service lines (Dhoby Ghaut Station) were selected to study the relationship between the number of service lines at a MRT station and the number of complications concerning wayfinding. Also, an analysis model, Nodes Analysis Model (NAM) which enables better integration of new signage into an existing wayfinding system was developed based on reviews on two analysis models, Visibility Index and Bayesian Network Approach. The aim of Nodes Analysis Model is to identify the key locations of directional signs and the respective contents. Findings show that lack of integration between new signs and the existing signs is the key wayfinding issue at the Dhoby Ghaut Station. The identified problem has to be tackled timely as more stations will face similar problem with the expansion of MRT network. Re-assessment of existing wayfinding system is needed whenever there is addition of service line at a station. Nodes Analysis Model is designed to look for possible locations where new signs can be integrated with the existing signs. Lastly, there is a need for an easy and direct platform for commuters to give feedbacks on top of the existing channels provided by the public service providers and the relevant authorities so that users’ needs can be captured and translated into valuable improvements timely. Bachelor of Engineering (Civil) 2015-05-25T06:17:46Z 2015-05-25T06:17:46Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/64200 en Nanyang Technological University 60 p. application/pdf |
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DRNTU::Engineering::Civil engineering Chee, Pei Nen Study on effective wayfinding system at Mass Rapid Transport (MRT) station |
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More MRT stations will evolve into interchange stations in line with Land Transport Authority’s plan to double Singapore MRT network by 2030. Additional service line at a station increases the possible navigations paths, thereby increasing the complexity of the wayfinding system, which is subject of this study. This project aims to identify the key elements to be taken care in the process of upgrading a wayfinding system of a MRT station that experiences the transformation. Also, this project focuses on inside-out navigation and transfers between service lines. A systematic process that involves onsite observation, feedback collection from station staff and commuters, and data mining on social media website was used to study the effectiveness of the selected wayfinding systems and identify users’ expectations. A non-interchange station (Boon Lay Station), an interchange station serving two service lines (Buona Vista Station) and an interchange station serving three service lines (Dhoby Ghaut Station) were selected to study the relationship between the number of service lines at a MRT station and the number of complications concerning wayfinding. Also, an analysis model, Nodes Analysis Model (NAM) which enables better integration of new signage into an existing wayfinding system was developed based on reviews on two analysis models, Visibility Index and Bayesian Network Approach. The aim of Nodes Analysis Model is to identify the key locations of directional signs and the respective contents. Findings show that lack of integration between new signs and the existing signs is the key wayfinding issue at the Dhoby Ghaut Station. The identified problem has to be tackled timely as more stations will face similar problem with the expansion of MRT network. Re-assessment of existing wayfinding system is needed whenever there is addition of service line at a station. Nodes Analysis Model is designed to look for possible locations where new signs can be integrated with the existing signs. Lastly, there is a need for an easy and direct platform for commuters to give feedbacks on top of the existing channels provided by the public service providers and the relevant authorities so that users’ needs can be captured and translated into valuable improvements timely. |
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Wong Yiik Diew |
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Wong Yiik Diew Chee, Pei Nen |
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Final Year Project |
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Chee, Pei Nen |
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Chee, Pei Nen |
title |
Study on effective wayfinding system at Mass Rapid Transport (MRT) station |
title_short |
Study on effective wayfinding system at Mass Rapid Transport (MRT) station |
title_full |
Study on effective wayfinding system at Mass Rapid Transport (MRT) station |
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Study on effective wayfinding system at Mass Rapid Transport (MRT) station |
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Study on effective wayfinding system at Mass Rapid Transport (MRT) station |
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study on effective wayfinding system at mass rapid transport (mrt) station |
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2015 |
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http://hdl.handle.net/10356/64200 |
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1759854518210658304 |