Overview
This project advances an integrated, impairment-aware urban design decision framework that quantifies how street design interventions reshape urban permeability, road-user conflict, and access to opportunities at the street-segment scale. Using Liverpool as a case study, it combines an Agent-Based Model with a policy-centred 2.5D interactive geovisualisation tool, in collaboration with Liverpool City Region Combined Authority.
About this opportunity
Making street space more inclusive to prioritise people with impaired mobility (e.g., wheelchair users, individuals with walking aids, older adults, etc) is a societal commitment to equitable movement, participation, and dignity in everyday life. While step-free access, tactile guidance, and crossing priority are necessary measures, cities are also in need of credible decision-making tools that can indicate how such design choices impact the wider urban system by reshaping flows, road-user interactions, and access to essential activities for everyone
The aim of this work is to advance an integrated, impairment-aware urban design decision framework that quantifies the impact of street design interventions in terms of urban permeability, conflict in road-user interactions, and access to opportunities at the street-segment scale, and communicates them in a suitable form for policymakers, local authorities (i.e., our Partner – Liverpool City Region Combined Authority), and community stakeholders.
The project integrates two complementary layers: First, an Agent-Based Model (ABM) will be developed to measure how redesigning street space for people with impairments alters pedestrian and vehicular movement. Second, a policy-centred 2.5D interactive geovisualisation tool will be implemented to communicate how these spatial changes may take shape, making ABM results legible and actionable for stakeholders. The candidate will work with the Partner and potentially consult organisations lobbying for disabled rights.
This project builds on work currently being undertaken by the Supervisory Team and a PhD student on street-level accessibility for individuals with impaired mobility, which leverages street view imagery for obstacles and impediments detection.