Location of turning ratio and flow sensors for flow reconstruction in large traffic networks

Martin Rodriguez-Vega (1) , Carlos Canudas de Wit (1) , Hassen Fourati (1)

1 NECS-POST - Systèmes Commandés en Réseau

In this work we examine the problem of minimizing the number of sensors needed to completely recover the vehicular flow in a steady state traffic network. We consider two possible sensor technologies, one that allows the measurement of turning ratios at a given intersection, and other that directly measures the flow in a road. We formulate an optimization problem that finds the optimal location of both types of detectors, such that a minimum number of sensors is required. To solve this problem, we propose a method that relies on the structure of the underlying graph, which has a quasi-linear computational complexity, resulting in less computing time when compared to other works in the literature. This allows our method to be applied to large urban networks for which previous strategies may be too computationally heavy. We evaluate our results using dynamical traffic simulations in synthetic networks.

Mots clés: Flow estimation; Sensor location; Large traffic networks

Domaines: Automatique / Robotique

Martin Rodriguez-Vega, Carlos Canudas de Wit, Hassen Fourati. Location of turning ratio and flow sensors for flow reconstruction in large traffic networks. Transportation Research Part B: Methodological, 2019, 121, pp.21-40. ⟨10.1016/j.trb.2018.12.005⟩. ⟨hal-01958601⟩