Safe Merging in Mixed Traffic with Confidence
Fuente:
arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866911792447356928 |
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| author | Bang, Heeseung Dave, Aditya Malikopoulos, Andreas A. |
| author_facet | Bang, Heeseung Dave, Aditya Malikopoulos, Andreas A. |
| contents | In this letter, we present an approach for learning human driving behavior, without relying on specific model structures or prior distributions, in a mixed-traffic environment where connected and automated vehicles (CAVs) coexist with human-driven vehicles (HDVs). We employ conformal prediction to obtain theoretical safety guarantees and use real-world traffic data to validate our approach. Then, we design a controller that ensures effective merging of CAVs with HDVs with safety guarantees. We provide numerical simulations to illustrate the efficacy of the control approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_05742 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Safe Merging in Mixed Traffic with Confidence Bang, Heeseung Dave, Aditya Malikopoulos, Andreas A. Systems and Control Robotics In this letter, we present an approach for learning human driving behavior, without relying on specific model structures or prior distributions, in a mixed-traffic environment where connected and automated vehicles (CAVs) coexist with human-driven vehicles (HDVs). We employ conformal prediction to obtain theoretical safety guarantees and use real-world traffic data to validate our approach. Then, we design a controller that ensures effective merging of CAVs with HDVs with safety guarantees. We provide numerical simulations to illustrate the efficacy of the control approach. |
| title | Safe Merging in Mixed Traffic with Confidence |
| topic | Systems and Control Robotics |
| url | https://arxiv.org/abs/2403.05742 |