US 12,254,763 B2
Information fusion method and system
Zeshu Shen, Shenzhen (CN); and Nengwu Xiang, Shenzhen (CN)
Assigned to Shenzhen Yinwang Intelligent Technologies Co., Ltd., Shenzhen (CN)
Filed by Shenzhen Yinwang Intelligent Technologies Co., Ltd., Shenzhen (CN)
Filed on Apr. 26, 2022, as Appl. No. 17/729,834.
Application 17/729,834 is a continuation of application No. PCT/CN2020/101542, filed on Jul. 13, 2020.
Claims priority of application No. 201911026822.6 (CN), filed on Oct. 26, 2019; and application No. 202010196398.6 (CN), filed on Mar. 19, 2020.
Prior Publication US 2022/0252420 A1, Aug. 11, 2022
Int. Cl. G06V 10/25 (2022.01); G01C 21/00 (2006.01); G01C 21/36 (2006.01); G06V 10/74 (2022.01); G06V 10/80 (2022.01); G06V 10/94 (2022.01); G06V 20/56 (2022.01); G08G 1/01 (2006.01); G08G 1/0967 (2006.01)
CPC G08G 1/0112 (2013.01) [G01C 21/3667 (2013.01); G01C 21/387 (2020.08); G06V 10/25 (2022.01); G06V 10/74 (2022.01); G06V 10/80 (2022.01); G06V 10/95 (2022.01); G06V 20/56 (2022.01); G08G 1/0967 (2013.01); G06V 2201/07 (2022.01)] 16 Claims
OG exemplary drawing
 
1. An information fusion method, wherein the method is applied to an intelligent vehicle and comprises:
obtaining a plurality of sensing information sets, wherein each sensing information set of the plurality of sensing information sets comprises information about at least one target and different sensing information sets come from sensing systems of different device types, wherein the different device types generating the plurality of different sensing information sets include a vehicle communicating with the intelligent vehicle, a roadside device communicating with the intelligent vehicle, and the intelligent vehicle; and
based on at least two sensing information sets in the plurality of sensing information sets comprising information about a first target, fusing the information about the first target in the at least two sensing information sets to obtain fused information about the first target,
wherein the fusing the information about the first target in the at least two sensing information sets to obtain fused information about the first target comprises:
obtaining confidence of the information about the first target in each sensing information set of the plurality of sensing information sets; and
fusing the information about the first target in the at least two sensing information sets based on the confidence of the information about the first target in each sensing information set of the plurality of sensing information sets to obtain the fused information about the first target;
wherein the confidence of the information about the first target in each sensing information set of the plurality of sensing information sets is confidence of a corresponding sensing information set, and the method further comprises:
calculating a matching degree between information about a target in each sensing information set of the plurality of sensing information sets at a previous moment and fused information about a target corresponding to a sensing information set at the previous moment, wherein calculating a matching degree includes one of obtaining an intersection set between information about the target in a sensing information set of each device type and the information about the target in the fused sensing information set obtained at the previous moment, or calculating an average value of comprehensive distances between information about the same target in a sensing information set of each device type and the fused sensing information set obtained at the previous moment; and
determining confidence of each sensing information set of the plurality of sensing information sets at a current moment based on the matching degree.