Cooperative multi-vehicle localization using split covariance intersection filter

Abstract : Vehicle localization (ground vehicles) is an important task for intelligent vehicle systems and vehicle cooperation may bring benefits for this task. A new cooperative multi-vehicle localization method using split covariance intersection filter is proposed in this paper. In the proposed method, each vehicle maintains an estimate of a decomposed group state and this estimate is shared with neighboring vehicles; the estimate of the decomposed group state is updated with both the sensor data of the ego-vehicle and the estimates sent from other vehicles; the covariance intersection filter which yields consistent estimates even facing unknown degree of inter-estimate correlation has been used for data fusion. A comparative study based simulations demonstrate the effectiveness and the advantage of the proposed cooperative localization method.
Type de document :
Communication dans un congrès
IV 2012 - IEEE Intelligent Vehicles Symposium, Jun 2012, Alcala de Henares, Spain. pp.211 - 216, 2012, 〈10.1109/IVS.2012.6232155〉
Liste complète des métadonnées

https://hal.inria.fr/hal-00763811
Contributeur : Hao Li <>
Soumis le : mardi 11 décembre 2012 - 15:21:51
Dernière modification le : mardi 22 mars 2016 - 01:26:38

Identifiants

Collections

Citation

Hao Li, Fawzi Nashashibi. Cooperative multi-vehicle localization using split covariance intersection filter. IV 2012 - IEEE Intelligent Vehicles Symposium, Jun 2012, Alcala de Henares, Spain. pp.211 - 216, 2012, 〈10.1109/IVS.2012.6232155〉. 〈hal-00763811〉

Partager

Métriques

Consultations de la notice

306