Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914768114155520 |
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| author | Ameli, Mostafa Mcquade, Sean Lee, Jonathan W. Bunting, Matthew Nice, Matthew Wang, Han Barbour, William Weightman, Ryan Denaro, Chris Delorenzo, Ryan Hornstein, Sharon Davis, Jon F. Timsit, Dan Wagner, Riley Xu, Rita Mahmood, Malaika Mahmood, Mikail Monache, Maria Laura Delle Seibold, Benjamin Work, Daniel B. Sprinkle, Jonathan Piccoli, Benedetto Bayen, Alexandre M. |
| author_facet | Ameli, Mostafa Mcquade, Sean Lee, Jonathan W. Bunting, Matthew Nice, Matthew Wang, Han Barbour, William Weightman, Ryan Denaro, Chris Delorenzo, Ryan Hornstein, Sharon Davis, Jon F. Timsit, Dan Wagner, Riley Xu, Rita Mahmood, Malaika Mahmood, Mikail Monache, Maria Laura Delle Seibold, Benjamin Work, Daniel B. Sprinkle, Jonathan Piccoli, Benedetto Bayen, Alexandre M. |
| contents | Previous controlled experiments on single-lane ring roads have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts the question of how these findings can be generalized to field operational, high-density traffic conditions. To address this question, the Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) Consortium conducted MegaVanderTest (MVT), a live traffic control experiment involving 100 vehicles near Nashville, TN, USA. This article is a tutorial for developing analytical and simulation-based tools essential for designing and executing a live traffic control experiment like the MVT. It presents an overview of the proposed roadmap and various procedures used in designing, monitoring, and conducting the MVT, which is the largest mobile traffic control experiment at the time. The design process is aimed at evaluating the impact of the CIRCLES AVs on surrounding traffic. The article discusses the agent-based traffic simulation framework created for this evaluation. A novel methodological framework is introduced to calibrate this microsimulation, aiming to accurately capture traffic dynamics and assess the impact of adding 100 vehicles to existing traffic. The calibration model's effectiveness is verified using data from a six-mile section of Nashville's I-24 highway. The results indicate that the proposed model establishes an effective feedback loop between the optimizer and the simulator, thereby calibrating flow and speed with different spatiotemporal characteristics to minimize the error between simulated and real-world data. Finally, We simulate AVs in multiple scenarios to assess their effect on traffic congestion. This evaluation validates the AV routes, thereby contributing to the execution of a safe and successful live traffic control experiment via AVs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_15533 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date Ameli, Mostafa Mcquade, Sean Lee, Jonathan W. Bunting, Matthew Nice, Matthew Wang, Han Barbour, William Weightman, Ryan Denaro, Chris Delorenzo, Ryan Hornstein, Sharon Davis, Jon F. Timsit, Dan Wagner, Riley Xu, Rita Mahmood, Malaika Mahmood, Mikail Monache, Maria Laura Delle Seibold, Benjamin Work, Daniel B. Sprinkle, Jonathan Piccoli, Benedetto Bayen, Alexandre M. Systems and Control Previous controlled experiments on single-lane ring roads have shown that a single partially autonomous vehicle (AV) can effectively mitigate traffic waves. This naturally prompts the question of how these findings can be generalized to field operational, high-density traffic conditions. To address this question, the Congestion Impacts Reduction via CAV-in-the-loop Lagrangian Energy Smoothing (CIRCLES) Consortium conducted MegaVanderTest (MVT), a live traffic control experiment involving 100 vehicles near Nashville, TN, USA. This article is a tutorial for developing analytical and simulation-based tools essential for designing and executing a live traffic control experiment like the MVT. It presents an overview of the proposed roadmap and various procedures used in designing, monitoring, and conducting the MVT, which is the largest mobile traffic control experiment at the time. The design process is aimed at evaluating the impact of the CIRCLES AVs on surrounding traffic. The article discusses the agent-based traffic simulation framework created for this evaluation. A novel methodological framework is introduced to calibrate this microsimulation, aiming to accurately capture traffic dynamics and assess the impact of adding 100 vehicles to existing traffic. The calibration model's effectiveness is verified using data from a six-mile section of Nashville's I-24 highway. The results indicate that the proposed model establishes an effective feedback loop between the optimizer and the simulator, thereby calibrating flow and speed with different spatiotemporal characteristics to minimize the error between simulated and real-world data. Finally, We simulate AVs in multiple scenarios to assess their effect on traffic congestion. This evaluation validates the AV routes, thereby contributing to the execution of a safe and successful live traffic control experiment via AVs. |
| title | Designing, simulating, and performing the 100-AV field test for the CIRCLES consortium: Methodology and Implementation of the Largest mobile traffic control experiment to date |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2404.15533 |