ulnast

ULNAST, short for Urban Logistics Network Analysis and Simulation Tool, is an open-source software framework for modeling, analyzing, and simulating urban logistics networks. It supports planning for last-mile delivery, multi-modal transport, and hub-and-spoke systems. The framework emphasizes interoperability, modularity, and scalability, enabling users to integrate data from geographic information systems, transport networks, and demand models, and to run agent-based simulations of fleets, facilities, and pedestrians.

ULNAST was initiated in 2019 by researchers from the Institute of Urban Studies and industry partners to address the need for standardized data formats and reusable simulation components. The first public release appeared in 2021, introducing a core engine, a plugin architecture, and basic data adapters. Subsequent versions added a browser-based dashboard, calibration tools, and a Python API for experiments and integration with external tools.

Architecture and features. The core engine executes time-stepped simulations with discrete-event components. A plugin system allows custom agents, including drivers, dispatch centers, and warehouses. Supported data formats include CSV, GeoJSON, and OpenStreetMap-derived networks; a scenario editor; and visualization dashboards. The framework includes modules for calibration, sensitivity analysis, and optimization.

Applications. City planners use ULNAST to evaluate traffic impacts of policy changes, optimize last-mile deliveries, and assess disruption scenarios. Researchers employ it for experiments on network design, demand forecasting, and resilience. The project emphasizes reproducibility and sharing of scenarios and results.

Governance and license. ULNAST is released under an open-source license and maintained by a global community of contributors. Development is coordinated through a public repository with a core team and an advisory board.

See also. Urban logistics, agent-based modeling, geographic information systems.