Coping with Randomness in Highly Complex Sys-tems Using the Example of Quantum-Inspired Traffic Flow Optimization
Developing new solutions to complicated large-scale problems typically requires large-scale numerical simulation. Therefore, traffic simulations often run against randomized simulations instead of real-world traffic situations. This paper demonstrates a method to calculate the statistical significa...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
TIB Open Publishing
2023-06-01
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| Series: | SUMO Conference Proceedings |
| Subjects: | |
| Online Access: | https://www.tib-op.org/ojs/index.php/scp/article/view/216 |
| Summary: | Developing new solutions to complicated large-scale problems typically requires large-scale numerical simulation. Therefore, traffic simulations often run against randomized simulations instead of real-world traffic situations. This paper demonstrates a method to calculate the statistical significance of numerical simulations and optimizations in the presence of numerous random variables in complex systems using one-sided paired t-tests. While the paper covers a specific Fujitsu traffic-optimization project which uses SUMO for simulating the traffic situation, the method can be applied to many similar projects where a complete investigation of the solution space is not feasible due to the size of the solution space.
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| ISSN: | 2750-4425 |