| 1. |
- Kolkowski, Lukas, et al.
(författare)
-
Measuring activity-based social segregation using public transport smart card data
- 2023
-
Ingår i: Journal of Transport Geography. - : Elsevier BV. - 0966-6923 .- 1873-1236. ; 110
-
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.
|
|
| 2. |
- Lin, Joanne Yuh-Jye, et al.
(författare)
-
The equity of public transport crowding exposure
- 2023
-
Ingår i: Journal of Transport Geography. - : Elsevier BV. - 0966-6923 .- 1873-1236. ; 110
-
Tidskriftsartikel (refereegranskat)abstract
- Public transport crowding exposure is known to cause discomfort, stress and dissatisfaction. However, the distribution and equity of crowding exposure across socioeconomic groups has been largely unexplored. This paper opens a new research topic connecting crowding exposure in public transport to travelers’ socioeconomic characteristics. We present a framework for assessing the equity of in-vehicle crowding exposure based on automatic data sources. Two metrics are considered for quantifying the travelers’ in-vehicle crowding exposure: (1) the excess perceived travel time and (2) the relative excess perceived travel time. The proposed methodology computes the two metrics based on travel diaries and in-vehicle loads inferred from automated fare collection data. We implement Lorenz curves, Gini and Suits coefficients to evaluate horizontal (across the population) and vertical equity (considering income as well as mobility ability and need). The vertical equity is further discussed using clusters of socioeconomic groups and results from spatial lag regression models to assess the distribution of crowding exposure across socioeconomic characteristics. The results for the Stockholm Region case study indicate that crowding exposure varies substantially across the service area, with the highest values found in the denser urban areas close to Stockholm City. We find that the distribution across socioeconomic groups is relatively even, but travelers from areas that are wealthier, higher educated, have higher share of rental housing or lower vehicle ownership areas tend to be exposed to more crowding. The paper provides tools to support public transport planners in decision-making, showing where to intervene to reduce crowding exposure efficiently to achieve urban equity and sustainability.
|
|
