Eco-Driving in Urban Traffic Networks using Traffic Signal Information

Giovanni de Nunzio 1, 2, * Carlos Canudas de Wit 1 Philippe Moulin 2 Domenico Di Domenico 2
* Corresponding author
1 NECS - Networked Controlled Systems
Inria Grenoble - Rhône-Alpes, GIPSA-DA - Département Automatique
Abstract : This work addresses the problem of finding energy-optimal velocity profiles for a vehicle in an urban traffic network. Assuming communication between infrastructure and vehicles (I2V) and a complete knowledge of the upcoming traffic lights timings, a preliminary velocity pruning algorithm is proposed in order to identify the feasible region a vehicle may travel along in compliance with city speed limits. Then, a graph discretizing approach is utilized for advanced selection, among the feasible ''green windows'', of the optimal ones in terms of energy consumption. Finally, a velocity trajectory is advised, which will be tracked by the driver-in-the-loop in order to pass through the signalized intersections without stopping. The proposed eco-driving assistance algorithm results are compared to the optimal solution provided by the Dynamic Programming, in order to prove not only the effectiveness but also its capability to be employed online due to its low computational load.
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Giovanni de Nunzio, Carlos Canudas de Wit, Philippe Moulin, Domenico Di Domenico. Eco-Driving in Urban Traffic Networks using Traffic Signal Information. 52nd IEEE Conference on Decision and Control (CDC 2013), Dec 2013, Florence, Italy. ⟨10.1109/CDC.2013.6759995⟩. ⟨hal-00909223⟩

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