Microscopic door-to-door simulation studies of urban superblocks — street grids closed to through motor traffic to favour walking, cycling and public transport — currently hold every person's activity locations (home, work, other destinations) fixed, so their reported benefits are short- to medium-term estimates. The source study (Nguyen et al. 2024, Bologna, 49 superblocks) found a car-to-bus shift, reduced traffic volumes and emissions, and no increase on surrounding roads, but explicitly flags the unmodeled long-term effect: people whose origins or destinations lie within or between superblocks may relocate as accessibility and livability change, feeding back into travel demand. The open problem is to make activity locations endogenous in superblock evaluation — coupling residential/workplace relocation (land-use feedback) and dynamic activity scheduling with door-to-door multi-modal microsimulation — and to determine whether the fixed-location conclusions persist, weaken, or reverse as the spatial distribution of activities adapts. No published framework yet couples land-use feedback and dynamic activity scheduling with door-to-door microscopic simulation for superblock evaluation, and reviews continue to list relocation, gentrification and exposure displacement among the unanswered evaluation concerns.

Background

A superblock (Catalan superilla) is an urban-design scheme, implemented first in Barcelona, in which a group of city blocks — typically a 3x3 grid of roughly 400 m side — is closed to through motor traffic and inner on-street parking, so that interior streets are reserved for pedestrians, cycling and local access while motorized traffic and buses are routed along the perimeter roads. Evaluations before 2024 relied mostly on aggregate four-step transport models, which are too coarse to capture how a superblock changes the full door-to-door travel time of an individual — the total time of a trip from origin to destination, including walking to a stop or centralized car park, waiting, riding, and the final walk. Nguyen et al. (2024) filled this gap with a large-scale, activity-based microscopic simulation: an agent-based model in which each synthetic person executes a daily plan of activities and trips, modes are chosen by a maximum-utility model Us,i=αs−βTs,iU_{s,i} = \alpha_s - \beta T_{s,i} (utility of plan ss for person ii, with mode-specific constant αs\alpha_s, value of time β\beta, and simulated door-to-door plan time Ts,iT_{s,i}), and traffic flow is resolved on the individual vehicle level. Applied to Bologna, where 49 feasible superblocks were identified by a multiple-criteria analysis, the study reported that car drivers' walking time rose by 83.73% and their total travel time by 23.66%, bus waiting time fell by 32.07%, car trips fell by about 5% citywide with a matching rise in bus trips, absolute traffic volumes and traffic-related emissions fell, and — surprisingly — traffic on the roads surrounding the superblocks did not increase (it fell slightly, by 6.09%). However, the mode-choice model assumes each person keeps the same activity locations and socio-economic attributes across scenarios, with only travel times varying, so all of these results are short- and medium-term: the simulation answers how people re-choose modes and routes after the intervention, not how the city itself changes. This matters because superblocks plausibly alter residential and workplace attractiveness — a feedback that the empirical green-gentrification literature on Barcelona (documented, e.g., in the 2024 review by Nieuwenhuijsen et al.) says is real: pedestrianization and greening raise an area's attractiveness and property values, which can attract new residents and displace existing ones. Modeling such feedback is the classic domain of land-use–transport interaction (LUTI) models, in which travel conditions and location choices (where households live, where firms and services sit) mutually influence each other over years; dynamic activity scheduling denotes the extension of activity-based demand models in which a person's daily activity program — which activities are performed, where, when and in what order — is itself re-planned rather than held fixed. No existing framework couples these long-horizon mechanisms with door-to-door microscopic traffic simulation for superblock evaluation; the source study states the activity-location (relocation) part of this gap as its central limitation: it 'still has limitations in modeling the long-term effects of the superblocks, such as changes in the activity locations of the people who have either their origin or/and destination located within and between the superblocks'.

Problem Statement

Extend superblock impact evaluation to the long term by making activity locations endogenous. Concretely: starting from a validated microscopic, activity-based door-to-door simulation of a specified city-scale superblock program (as instantiated for Bologna's 49 superblocks by Nguyen et al. 2024), integrate (i) land-use feedback — residential, workplace and other activity-location choice that responds to the accessibility, livability and attractiveness changes the superblocks induce — and (ii) dynamic activity scheduling, in which daily activity programs are re-planned rather than fixed, and use the coupled framework to assess how superblock implementation reshapes the spatial distribution of activities over time and what this implies for modal shares, network traffic performance, and traffic-related emissions. The governing question, which defines the completion boundary: do the short-/medium-term conclusions obtained under fixed activity locations — the car-to-bus shift, the significant reductions in traffic volumes and emissions, and the absence of traffic increase on the roads surrounding the superblocks — persist, weaken, or reverse once households and firms are allowed to relocate within, into, or away from superblock areas? Addressing this question requires the coupled framework (relocation and scheduling components, calibrated and validated), the long-run equilibrium or dynamic-path results for the stated scenario, and the comparison against the fixed-location baseline.

References

  1. Ngoc An Nguyen, Joerg Schweizer, Federico Rupi, Sofia Palese, Leonardo Posati (2024), 'Superblock Design and Evaluation by a Microscopic Door-to-Door Simulation Approach', ISPRS International Journal of Geo-Information 13(3):77, doi:10.3390/ijgi13030077, https://doi.org/10.3390/ijgi13030077
  2. Georgios Banias, Ariadni-Konstantina Bourouti, Georgios Palantzas, Dimitrios Nalmpantis (2025), 'Superblocks in Thessaloniki: Residents Perceptions', in Climate Crisis and Resilient Transportation Systems, Lecture Notes in Intelligent Transportation and Infrastructure, Springer, doi:10.1007/978-3-031-82714-3_28, https://doi.org/10.1007/978-3-031-82714-3_28
  3. Benyamin Heidary, Joerg Schweizer, Ngoc An Nguyen, Federico Rupi, Cristian Poliziani (2025), 'An Efficient Parallelization of Microscopic Traffic Simulation', Applied Sciences 15(13):6960, doi:10.3390/app15136960, https://doi.org/10.3390/app15136960
  4. Mark Nieuwenhuijsen, Audrey de Nazelle, Marta Cirach Pradas, Carolyn Daher, Angel M. Dzhambov, Cynthia Echave, Stefan Gössling, Tamara Iungman, Haneen Khreis, Nicolina Kirby, Sasha Khomenko, Ulrich Leth, Florian Lorenz, Vlatka Matkovic, Johannes Müller, Laia Palència, Evelise Pereira Barboza, Katherine Pérez, Lambed Tatah, Jernej Tiran, Cathryn Tonne, Natalie Mueller (2024), 'The Superblock model: A review of an innovative urban model for sustainability, liveability, health and well-being', Environmental Research 251:118550, doi:10.1016/j.envres.2024.118550, https://doi.org/10.1016/j.envres.2024.118550
  5. Sven Eggimann (2025), 'Deprioritising cars beyond rerouting: Future research directions of the Barcelona Superblock', Cities 157:105609, doi:10.1016/j.cities.2024.105609, https://doi.org/10.1016/j.cities.2024.105609
  6. Lucinda Cash-Gibson, Alexandra Bretones Diaz, Oriol Marquet Sardà, Joan Benach (2024), 'How do superblock interventions influence health? A scoping review', Cities 153:105262, doi:10.1016/j.cities.2024.105262, https://doi.org/10.1016/j.cities.2024.105262
  7. Lucinda Cash-Gibson, Ferran Muntané Isart (2026), 'Superblock interventions: the need for policy design and realist evaluations to unpack complexity', Cities & Health, doi:10.1080/23748834.2025.2610864, https://doi.org/10.1080/23748834.2025.2610864
  8. Sven Eggimann (2022), 'The potential of implementing superblocks for multifunctional street use in cities', Nature Sustainability 5:406-414, doi:10.1038/s41893-022-00855-2, https://doi.org/10.1038/s41893-022-00855-2
  9. Sven Eggimann (2022), 'Expanding urban green space with superblocks', Land Use Policy 117:106111, doi:10.1016/j.landusepol.2022.106111, https://doi.org/10.1016/j.landusepol.2022.106111
  10. Samra Sarwar, Sergi Saurí, Muhammad Tabish Bilal, Genís Majoral (2023), 'Analysis of superblocks during the transition phase from traditional vehicles to fully automated vehicle environment: A case study of Barcelona City', Transportation Engineering 13:100203, doi:10.1016/j.treng.2023.100203, https://doi.org/10.1016/j.treng.2023.100203