Difference between revisions of "AY1516 T2 Team CommuteThere Methodology"
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| − | === | + | ===1. Distribution Analysis on Multimode Commuters=== |
| − | + | In order to analyse multimode commuters, we will join the MRT and Bus dataset together using card number attribute, time attribute and date attribute. | |
| − | === | + | ====Analyse Transfer Interval==== |
| − | + | According to Transit Link (Transit Link Pte Ltd, 2016), a transfer can be from: | |
| + | the MRT/LRT to a bus service, | ||
| + | a bus service to another bus service, or | ||
| + | a bus service to the MRT/LRT | ||
| − | + | Transfer interval refers to the amount of time taken for the students to transfer from one mode of transportation to another mode of transportation.This is calculated using the difference between Bus entry time and MRT exit time (for MRT→Bus) and MRT entry time and Bus exit time(for Bus →MRT) | |
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Revision as of 15:36, 15 April 2016
Contents
Analyse Commuter Patterns
This analysis aims to identify commuter patterns of each demographic groups - students, adults and elderly - as each group has differing interests and preferences in the places to frequent at. Data used for this methodology involves the ez-link and points of interests (POI) data. Given that the places that each demographic groups frequent at varies due to differing interests and preferences, to include points of interests (POI) in this analysis will be helpful to understand which places attract various groups of people at various periods of the week. With that, our team conclude that POI should be places that serve the primary needs of the people.
Analysing commuter patterns is further segregated to two sub-methods:
1. Identifying common destination points
An initial analysis will be conducted to find out the common destinations that commuters travel to given that each demographic groups will have different needs and hence different places they frequent to. A heatmap of the common points will be visualized using QGIS. Areas with a darker intensity of colour would show the areas where many commuters alight at.
2. Identifying travel patterns
Travel patterns are categorized into four different segments: Island wide, inter town, intra town and most frequently travelled trips, where commuters may travel just within Tampines planning area, or within the east region, or island wide. To do so, we will use QGIS to map out.
Analysis of commuter patterns is split into 4 segments:
| Segments | Description |
|---|---|
| Island wide | Overall commuting activity for each demographic groups as a whole, regardless of place of origin. This will provide an overview of the commuters’ travelling pattern in Singapore. |
| Inter town | Travelling patterns of the commuters whose trips originate from Tampines planning area and end in the East region i.e Bedok,Paya Lebar, Changi, Pasir Ris |
| Intra town | Travelling patterns of the commuters whose trips originate and end in Tampines planning area i.e Tampines, Simei |
| Most frequent travelled trips | Commuters who made the same trip for at least four times in a week can be categorised as such. The data for each demographic groups are analysed based on weekdays which has most of the activities reflected on |
Analyse Multimodal Transportation Patterns
1. Distribution Analysis on Multimode Commuters
In order to analyse multimode commuters, we will join the MRT and Bus dataset together using card number attribute, time attribute and date attribute.
Analyse Transfer Interval
According to Transit Link (Transit Link Pte Ltd, 2016), a transfer can be from: the MRT/LRT to a bus service, a bus service to another bus service, or a bus service to the MRT/LRT
Transfer interval refers to the amount of time taken for the students to transfer from one mode of transportation to another mode of transportation.This is calculated using the difference between Bus entry time and MRT exit time (for MRT→Bus) and MRT entry time and Bus exit time(for Bus →MRT)
