Density and flow reconstruction in urban traffic networks using heterogeneous data sources

Andres Ladino 1 Carlos Canudas de Wit 1 Alain Kibangou 1 Hassen Fourati 1 Martin Rodriguez-Vega 1
1 NECS - Networked Controlled Systems
Inria Grenoble - Rhône-Alpes, GIPSA-DA - Département Automatique
Abstract : — In this paper, we consider the problem of joint reconstruction of flow and density in a urban traffic network using heterogeneous sources of information. The traffic network is modeled within the framework of macroscopic traffic models, where we adopt Lighthill-Whitham-Richards model (LWR) conservation equation characterized by a piecewise linear fundamental diagram. The estimation problem considers two key principles. First, the error minimization between the measured and reconstructed flows and densities, and second the equilibrium state of the network which establishes flow propagation within the network. Both principles are integrated together with the traffic model constraints established by the supply/demand paradigm. Finally the problem is casted as a constrained quadratic optimization with equality constraints in order to shrink the feasible region of estimated variables. Some simulation scenarios based on synthetic data for a manhattan grid network are provided in order to validate the performance of the proposed algorithm.
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Communication dans un congrès
16th European Control Conference (ECC 2018), Jun 2018, Limassol, Cyprus. pp.1-6
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Andres Ladino, Carlos Canudas de Wit, Alain Kibangou, Hassen Fourati, Martin Rodriguez-Vega. Density and flow reconstruction in urban traffic networks using heterogeneous data sources. 16th European Control Conference (ECC 2018), Jun 2018, Limassol, Cyprus. pp.1-6. 〈hal-01731356〉

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