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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.19582 |
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| _version_ | 1866915054575681536 |
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| author | Ghori, Salman Adil, Ania Feron, Eric |
| author_facet | Ghori, Salman Adil, Ania Feron, Eric |
| contents | Intersections pose critical challenges in traffic management, where maintaining operational constraints and ensuring safety are essential for efficient flow. This paper investigates the effect of intervention timing in management strategies on maintaining operational constraints at intersections while ensuring safe separation distance, avoiding collisions, and minimizing delay. We introduce control regions, represented as circles around the intersection, which refers to the timing of interventions by a centralized control system when agents approach the intersection. We use a mixed-integer linear programming (MILP) approach to optimize the system's performance. To analyze the effectiveness of early and late control measures, a simulation study is conducted, focusing on the safe, efficient, and robust management of agent movement within the control regions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_19582 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Early Versus Late Traffic Management For Autonomous Agents Ghori, Salman Adil, Ania Feron, Eric Systems and Control Intersections pose critical challenges in traffic management, where maintaining operational constraints and ensuring safety are essential for efficient flow. This paper investigates the effect of intervention timing in management strategies on maintaining operational constraints at intersections while ensuring safe separation distance, avoiding collisions, and minimizing delay. We introduce control regions, represented as circles around the intersection, which refers to the timing of interventions by a centralized control system when agents approach the intersection. We use a mixed-integer linear programming (MILP) approach to optimize the system's performance. To analyze the effectiveness of early and late control measures, a simulation study is conducted, focusing on the safe, efficient, and robust management of agent movement within the control regions. |
| title | Early Versus Late Traffic Management For Autonomous Agents |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2411.19582 |