rescuePY: Simulation-Based Rescue Response Impact Assessment
DOI:
https://doi.org/10.52825/scp.v5i.1029Keywords:
Simulation, Emergency Service, Mobility ChangesAbstract
Mobility in metropolitan regions is changing. The distribution of space in cities, the design of transport modes, and the organization of mobility are being re-thought. However, no matter the changes and innovations on the way to a more sustainable future, essential constants must be upheld: In the event of minor, regionally limited emergencies, medical assistance must reach those in need quickly. When dealing with large-scale emergencies, the ability to evacuate the area promptly must be ensured. The impact analysis of mobility innovations on emergency services within urban areas so far has been based purely on empirical observations using existing data. Currently, it is only possible to analyze what-if considerations in a limited way. Nevertheless, due to the increasingly rapid changes in mobility, a comprehensive and interlinked analysis will be necessary. This is the key contribution of rescuePY: rescuePY is a simulation suite based on the mesoscopic and microscopic simulation environment hybridPY. It allows holistic and microscopic transport modeling of rescue infrastructure to quantify the impact of the mobility transition towards higher sustainability on the performance of rescue services.
The main features of this software are:
- Rescue system assessment for strategic, long-term planning
- Mobility-influence studies for operative, mid-term planning
- Activity-based urban evacuation modeling
The capabilities of rescuePY are demonstrated by two applications: a simulation- based, mesoscopic system analysis of emergency services in Munich compared to real-world data and microscopic modeling of emergency vehicles (EMVs) in different road architectures. Ongoing developments aim to improve the evaluation methodology for the aggregated impact analysis of mobility innovations on rescue response services.
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Copyright (c) 2024 Fabian Schuhmann, Maximilian Sievers, Stefan Schrott, Ivan Kapovich, Lijie Feng, Markus Lienkamp
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
Accepted 2024-04-03
Published 2024-07-17
