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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.
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Contributor : Hao Li Connect in order to contact the contributor
Submitted on : Tuesday, December 11, 2012 - 3:21:51 PM
Last modification on : Thursday, February 3, 2022 - 11:17:52 AM




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, ⟨10.1109/IVS.2012.6232155⟩. ⟨hal-00763811⟩



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