Public transport in the 15-minute city

Abstract

The 15-minute city is a powerful planning concept to counter car-dependence by promoting active mobility to amenities and fostering inclusive urban environments. However, this policy has challenges in amenity-poor urban peripheries. Public transport remains underexplored in this discourse despite its role in distant access. Here, we propose a framework that incorporates public transport into the 15-minute city model using openly available data. By comparing Helsinki, Madrid, and Budapest, we demonstrate that multimodal mobility substantially increases access to amenities and enhances socio-spatial integration within a 15-minute reach. Although urban periphery benefit significantly from radial or high-speed public transport lines in their social mixing potential, such lines alone do not improve their access to amenities. These findings underscore the need to optimize polycentric public transport networks that can improve inclusive urban accessibility and complement active mobility in polycentric cities.

Figures (11)

• Figure 1: Creation of the accessibility network, using public transport time-table data.a) Public transport stops are clustered into mobility hubs. The figure example is "Fővám tér" in Budapest that represents a collection of bus, tram, metro and trolley bus stops. b) Considering all lines and their time tables, we create a multilayer network between mobility hubs weighted by travel times and identify the fastest public transport access assuming 3-minute transit between lines. Here, we consider trips between Fővám tér (A) and Astoria (C). c) We depict the area of 15-minutes walk from the mobility hub on the street network and identify the maximum spread of multimodal access that combines 10 minutes of public transport travel --using the fastest rides-- that can be reached with 5 minutes walk.
• Figure 2: Ellipticity of multimodal access $E_p$.a) Multimodality can extend access evenly (creating a round shape as the blue area) and non-evenly (creating an elliptic, leaf shape such as the orange area). High $E_p$ values define access corridors in urban peripheries in b) Budapest, c) Helsinki, and d) Madrid.
• Figure 3: Amenity access in multimodal 15-minute cities.a) We quantify the diversity of amenities that can be reached within a 15-minute walk to a multimodal radius. b) Multimodal reach increases amenity access. c) Regression coefficients, broken down to high- and low-status neighborhoods, highlight the role of multimodal mobility and elliptic transportation in increasing amenity access. Coefficients of ellipticity decreases in urban periphery in d) Helsinki, e) Madrid, and f) Budapest.
• Figure 4: Social mixing potential in multimodal 15-minute cities.a) We quantify the diversity of socio-economic status that can be reached within a 15-minute walk to a multimodal radius. b) Multimodal reach only slightly increases the mixing potential of socio-economic groups. c) Regression coefficients highlight that multimodal mobility and elliptic transportation increases social mixing potentials differently in high- and low-status neighborhoods. Coefficients of ellipticity increases in urban periphery for residential measures in d) Helsinki, e) Madrid, and f) Budapest, but not for experienced mixing in Budapest in g).
• Figure S1: Bayesian optimization result for public transport stop clustering in Helsinki.