From the city's point of view, understanding how and why response times to emergencies are distributed is important for creating efficient operational policies and programs. The model introduced in this document is based on the idea that patrolling efficiency comes from a combination of dynamic factors (traffic conditions, vehicle distribution, accessibility of the road network, and incident density, among others). Instead of focusing on these indicators independently, the presented model integrates real cartographic data to simulate patrol behaviour and the optimal routes they take across the city. Using advanced computational simulations helps make sense of these mobility flows, showing how coverage patterns and response times naturally emerge within the urban fabric.
 

The SPADE Police Routing Tool (SPADE-PRT) is an AI-powered, multi-agent simulation model designed to support evidence-based decision-making in urban public safety. Built on the SPADE and SimFleet frameworks, it models police patrols, emergency events, and road networks to create realistic Digital Twins of city operations. The model dynamically assigns patrol units to incidents based on proximity and routing constraints, generating interoperable GeoJSON outputs and operational performance metrics that can be integrated into GIS platforms and Local Digital Twin environments.

SPADE-PRT enables municipalities and law enforcement agencies to evaluate patrol strategies, identify operational bottlenecks, optimise emergency response times, and improve the allocation of public resources. Designed as an open-source, interoperable solution, it supports scalable simulations across different urban environments while promoting transparency, explainability, and alignment with European digital and AI standards.