Computing Earth mover's distances on a road map with applications to one-way vehicle sharing

Treleaven, Kyle

doi:10.1109/acc.2014.6859297

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2018

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“…Unfortunately, preliminary investigations [23] have shown that both these approaches are highly ill-conditioned and then computationally infeasible. Let us finally mention the semi-discrete approach proposed by Treleaven and Frazzoli [30], which is well-conditioned but in practice it is still too expensive from the computationally point of view, especially on large networks. It is therefore necessary to find an alternative method to compute the Wasserstein distance.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of the LWR model for traffic forecast on large networks using Wasserstein distance

Briani

Cristiani

Iacomini

2018

Communications in Mathematical Sciences

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In this paper we investigate the sensitivity of the LWR model on network to its parameters and to the network itself. The quantification of sensitivity is obtained by measuring the Wasserstein distance between two LWR solutions corresponding to different inputs. To this end, we propose a numerical method to approximate the Wasserstein distance between two density distributions defined on a network. We found a large sensitivity to the traffic distribution at junctions, the network size, and the network topology.

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Section: Introductionmentioning

confidence: 99%