A Dynamic Programming Approach for Road Traffic Estimation
<|reference_start|>A Dynamic Programming Approach for Road Traffic Estimation: 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.<|reference_end|>
@article{laurini2024a,
    title={A Dynamic Programming Approach for Road Traffic Estimation},
    author={Mattia Laurini, Irene Saccani, Stefano Ardizzoni, Luca Consolini,
  Marco Locatelli},
    journal={arXiv preprint arXiv:2403.18561},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.18561},
    primaryClass={eess.SY cs.SY}
}