| 1. |
- Cats, Oded, 1983-, et al.
(författare)
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Unravelling Mobility Patterns using Longitudinal Smart Card Data : Final report for Trafik och Region 2019SLL-KTH research project
- 2021
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- BackgroundThis project followed-up on a project called FairAccess which was granted in Trafik och Region 2018.In FairAccess, we processed Access card data and performed a sequence of inferences to derive timedependent origin-destination matrices for the entire Region Stockholm system. Tap-in records werematched with corresponding inferred tap-out locations and time stamps for about 80% of all records.Moreover, we implemented an algorithm to generate a journey database based on our transferinference method. We used the outputs of this process to evaluate the impacts of the fare schemechange (i.e. from zone-based to flat fare) on different user profiles. Access card products and zonalattributes were used for analysing policy impacts on different market segments.The “Unravelling Mobility Patterns using Longitudinal Smart Card Data” project was granted on May27, 2020 and the contract was signed on July 17, 2020. In this project, we capitalise on the capabilitiesof the inferences performed in previous work to conduct a series of market segmentation andadvanced data analytics to empirically analysis demand patterns for public transport in the StockholmCounty. The growing travel demand in Stockholm County is accompanied by an increased diversity ofsub-centres within the region as well as in individual travel patterns. It is thus increasingly importantto understand how demand patterns evolve over time, what the key market segments are and howdifferent users are affected by changes in service provision. The latter is studied in the contact of theopening of the Citybanan project.As stated in the SLL Research and Innovation Plan, the development of transport solutions for theStockholm region requires new knowledge regarding travellers’ needs and preferences, and theimpacts for different types of travellers.
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| 2. |
- Kolkowski, Lukas, et al.
(författare)
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Measuring activity-based social segregation using public transport smart card data
- 2022
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Konferensbidrag (refereegranskat)abstract
- While social segregation is often assessed using static data concerning residential areas, the extentto which people with diverse background travel to the same destinations may offer an additional perspective on the extent of urban segregation. This study further contributes to the measurement of activity-based social segregation between multiple groups using public transport smart card data. In particular, social segregation is measured using the ordinal information theory index to measure the income group mix at public transport journey destination zones. The method isapplied to the public transport smart card data of Stockholm County, Sweden. Applying the index on 2017-2020 smart card data sets for a selected week, shows significant differences between income groups’ segregation along the radial public transport corridors. The overall slight decrease in income segregation over the years can be linked to declining segregation in the city center as a travel destination and its public transport hubs. Increasing zonal segregation is observed in suburban and rural zones with commuter train stations. This method helps to quantify social segregation, enriching the analysis of urban segregation and can aid in evaluating policies based on the dynamics of social life.
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| 3. |
- Kolkowski, Lukas, et al.
(författare)
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Measuring activity-based social segregation using public transport smart card data
- 2023
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Ingår i: Journal of Transport Geography. - : Elsevier BV. - 0966-6923 .- 1873-1236. ; 110
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Tidskriftsartikel (refereegranskat)abstract
- While social segregation is often assessed using static data concerning residential areas, the extent to which people with diverse background travel to the same destinations may offer an additional perspective on the extent of urban segregation. This study further contributes to the measurement of activity-based social segregation between multiple groups using public transport smart card data. In particular, social segregation is quantified using the ordinal information theory index to measure the income group mix at public transport journey destination zones. The method is applied to the public transport smart card data of Stockholm County, Sweden. Applying the index on 2017-2020 data sets for a selected week, shows significant differences between income groups' segregation along the radial public transport corridors following the opening of a major rail project in the summer of 2017. The overall slight decrease in segregation over the years can be linked to declining segregation in the city center as a travel destination and its public transport hubs. Increasing zonal segregation is observed in suburban and rural zones with commuter train stations. This method helps to quantify social segregation, enriching the analysis of urban segregation and can aid in evaluating policies based on the dynamics of social life.
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