A Dynamic Programming Approach for Road Traffic Estimation
Fuente:
arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866915203886612480 |
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| author | Laurini, Mattia Saccani, Irene Ardizzoni, Stefano Consolini, Luca Locatelli, Marco |
| author_facet | Laurini, Mattia Saccani, Irene Ardizzoni, Stefano Consolini, Luca Locatelli, Marco |
| contents | We consider a road network represented by a directed graph. We assume to collect many measurements of traffic flows on all the network arcs, or on a subset of them. We assume that the users are divided into different groups. Each group follows a different path. The flows of all user groups are modeled as a set of independent Poisson processes. Our focus is estimating the paths followed by each user group, and the means of the associated Poisson processes. We present a possible solution based on a Dynamic Programming algorithm. The method relies on the knowledge of high order cumulants. We discuss the theoretical properties of the introduced method. Finally, we present some numerical tests on well-known benchmark networks, using synthetic data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_18561 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Dynamic Programming Approach for Road Traffic Estimation Laurini, Mattia Saccani, Irene Ardizzoni, Stefano Consolini, Luca Locatelli, Marco Systems and Control We consider a road network represented by a directed graph. We assume to collect many measurements of traffic flows on all the network arcs, or on a subset of them. We assume that the users are divided into different groups. Each group follows a different path. The flows of all user groups are modeled as a set of independent Poisson processes. Our focus is estimating the paths followed by each user group, and the means of the associated Poisson processes. We present a possible solution based on a Dynamic Programming algorithm. The method relies on the knowledge of high order cumulants. We discuss the theoretical properties of the introduced method. Finally, we present some numerical tests on well-known benchmark networks, using synthetic data. |
| title | A Dynamic Programming Approach for Road Traffic Estimation |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2403.18561 |