Walking is the most essential and human way to move through a city. When people feel safe doing so, streets come alive, communities connect, and cities become more sustainable and livable. Yet in many urban environments, perceived insecurity remains a major barrier that limits this potential.
In our project in Guadalajara, Mexico, we worked directly with local communities to better understand the disconnect between perceived and actual safety. Drawing from a comprehensive review of over 150 key performance indicators (KPIs)—ranging from environmental design to social dynamics and crime prevention strategies—we developed a context-sensitive, actionable framework of safety metrics.
We validated these metrics in the field through two weeks of intensive observation, community engagement, and data collection via group activities and mobile sensors. This multi-layered data was then cross-referenced with local insights, allowing us to calibrate the weight of each variable based on its relevance in context.
Building on this, we developed an agent-based simulation model (ABM) that enables real-time testing of urban interventions. The model allows us to visualize how specific design and policy decisions can influence both mobility and the perception of safety across a range of scenarios.
More than just a study, this work proposes a new methodology for urban transformation—one that places human experience at the core, and leverages data and technology to inform more humane urban planning. In the convergence of people, place, and digital tools lies the future of safe and walkable cities.