VertiSim distinguishes itself from legacy aviation simulators by simultaneously modeling three critical flows: passenger, aircraft, and energy. This integrated approach reflects the unique operational characteristics of e-VTOL networks where flight durations, passenger waiting times, and aircraft charging times at vertiports are closely interrelated, necessitating a comprehensive understanding and detailed study of each flow for a holistic evaluation of system performance. VertiSim processes these interdependent flow into key metrics instrumental for effective network operation, such as aircraft utilization, average load factor, vertiport throughput, terminal area congestion, utilization of resources, energy consumption for each flight phase, repositioning flights, and passenger waiting times.
We adopted the building blocks approach to model the vertiport simulator. This approach allowed us to build comprehensive and flexible vertiport models that can be customized to meet different design and operational requirements. Our main building blocks are structural entities, flow entities, generator entities, and control entities. Structural entities form the static layout of the simulation environment with elements like queues and servers. Flow entities such as aircraft, passengers, passenger groups, and energy interact with and move within these structural entities. Generator entities produce flow entities based on their schedule, while control entities handle tasks such as assigning TLOF (Touch-down and Lift-Off area) for arrival and departure, allocating parking pads, determining service priorities, dispatching flights, initiating charging and routing.
VertiSim employs a graph-theoretic methodology to build structural entities based on the input vertiport layout. The simulation environment is conceptualized as a network of nodes and links,
The units of the timed inputs are seconds. These seconds are converted into miliseconds internally. This is the design choice.
Small circular shapes are parking pads and large circular shapes are FATO. The light red lines represent aircraft trajectories. Passenger trajectories are hidden.
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Triad Flow Modeling: A unique capability to simultaneously model passenger, aircraft, and energy flows, which is pivotal for understanding e-VTOL operations.
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Holistic Infrastructure Modeling: Comprehensive infrastructure representation, encompassing vertiports, air routes, and flight profiles.
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Advanced Charging & Discharging: Capture the nuances of energy dynamics through non-linear charging models, moving beyond the constraints of traditional linear models.
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Dynamic Optimization Engine: An offline optimization model that harmonizes flight and charging schedules, adapting to variable demand scenarios.
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Multi-Vertiport System: Specialized numerical analysis focusing on a two-vertiport system to optimize fleet utilization, resource management, and passenger experience.
- Aircraft Utilization
- Average Load Factor
- Vertiport Throughput
- Terminal Area Congestion
- Vertiport Resource Utilization
- Aircraft Energy Consumption
- Repositioning Flights
- Passenger Trip Times
- and more...
- Download all of the files.
- Open your terminal and cd to vertisim folder
- Create a virtual environment: If you are using conda write
conda create -n vertisim python=3.11
- After you create your environment activate your environment by writing
conda activate vertisim
to your terminal. - Install the requirements with
pip install -r requirements.txt
- Done!
For questions and collaborations, please email eminburak_onat@berkeley.edu. Thanks!
- Activate the vertisim environment (for conda users
conda activate vertisim
) - Create config.json file
- There are three ways of running vertisim.
(inside VertiSim folder):
a) Run a single configuration:python3 -m vertisim.runner --config vertisim/config.json
Currently, the below methods are not maintained and won't work.
b) Run many configuration serially:loop_runner.py
c) Run many configuration in parallel (CPU parallelization by multiprocessing):loop_runner_multiprocess.py
Please cite based on your application:
- Onat, E. B. (2024). Urban Air Mobility: Infrastructure and Operations (Doctoral dissertation, University of California, Berkeley).
- Onat, E. B., Bulusu, V., Chakrabarty, A., Hansen, M., Sengupta, R., & Sridhar, B. (2024). Evaluating evtol network performance and fleet dynamics through simulation-based analysis. In AIAA Scitech 2024 Forum (p. 0336).
- Onat, E. B., Cao, S., Rizwan, R., Jiang, X., Hansen, M., Sengupta, R., & Chakrabarty, A. (2024). A simulation-optimization framework for developing wind-resilient AAM networks. arXiv preprint arXiv:2405.11118.