Decentralized Near-to-Near Approach for Vehicle Platooning based on Memorization and Heuristic Search

Jano Yazbeck 1 Alexis Scheuer 1 François Charpillet 1
1 MAIA - Autonomous intelligent machine
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : This paper deals with vehicle platooning, where a convoy aims at following closely and safely its leader's path without collision nor lateral deviation. In this paper, we propose a platooning algorithm based on a near-to-near decentralized approach. Each vehicle estimates and memorizes on-line the path of its predecessor as a set of points. After choosing a suitable position to aim for, the follower estimates on-line the predecessor's path curvature around the selected target. Then, based on a heuristic search, it computes an angular velocity using the estimated curvature. The optimization criteria used in this work allows the robot to follow its predecessor's path without oscillation while reducing the lateral and angular errors.
Type de document :
Communication dans un congrès
International Conference on Robotics and Automation ICRA, May 2014, Hong-Kong, China. 2014
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https://hal.inria.fr/hal-00936056
Contributeur : Jano Yazbeck <>
Soumis le : lundi 10 mars 2014 - 15:19:04
Dernière modification le : jeudi 11 janvier 2018 - 06:25:23

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  • HAL Id : hal-00936056, version 1

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Jano Yazbeck, Alexis Scheuer, François Charpillet. Decentralized Near-to-Near Approach for Vehicle Platooning based on Memorization and Heuristic Search. International Conference on Robotics and Automation ICRA, May 2014, Hong-Kong, China. 2014. 〈hal-00936056〉

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