Optimization-based queue length estimation on arterial networks using a macroscopic traffic model enforcing vehicles bounded acceleration

Abstract : In this paper, we consider a macroscopic hydrodynamic traffic model able to reproduce the bound-edness of the vehicles acceleration. It is based on a modified Lighthill-Whitham-Richards (LWR) model recast as a Hamilton-Jacobi Partial Differential Equation for which there exists explicit solution methods. We developed an optimization-based framework which is able to be extended to large scale networks in order to estimate queue lengths on arterial road networks, taking into account data from classical density or flow sensors and mobile sensors. We validated our results on real data extracted from the NGSIM Lankershim Boulevard dataset, comparing the estimation result from LWR model with and without the bounded acceleration constraint. Comparing to previous method without considering bounded acceleration, our method improves the queue lengths estimation precision under most cases. The MATLAB toolbox encompassing the queue estimation for the LWR model and for the modified LWR model with bounded acceleration, can be freely downloaded at https://utexas.box.com/s/ipm7fgucobsgu7nszxea49sx80i3p1nx.
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https://hal.inria.fr/hal-02175497
Contributeur : Guillaume Costeseque <>
Soumis le : jeudi 31 octobre 2019 - 10:39:39
Dernière modification le : vendredi 1 novembre 2019 - 01:20:49

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Kun Qian, Guillaume Costeseque, Edward Canepa, Christian Claudel. Optimization-based queue length estimation on arterial networks using a macroscopic traffic model enforcing vehicles bounded acceleration. 2019. ⟨hal-02175497v2⟩

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