The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Dec. 10, 2013
Filed:
Nov. 09, 2010
Tao Wu, Beijing, CN;
Shaoya Wang, Beijing, CN;
Junjian He, Beijing, CN;
Weisong HU, Beijing, CN;
Jia Rao, Beijing, CN;
Xiaowei Liu, Beijing, CN;
Tao Wu, Beijing, CN;
Shaoya Wang, Beijing, CN;
Junjian He, Beijing, CN;
Weisong Hu, Beijing, CN;
Jia Rao, Beijing, CN;
Xiaowei Liu, Beijing, CN;
NEC (China) Co., Ltd., Beijing, CN;
Abstract
A system and method for traffic prediction based on space-time relation are disclosed. The system comprises a section spatial influence determining section for determining, for each of a plurality of sections to be predicted, spatial influences on the section by its neighboring sections; a traffic prediction model establishment section for establishing, for each of the plurality of sections to be predicted, a traffic prediction model by using the determined spatial influences and historical traffic data of the plurality of sections; and a traffic prediction section for predicting traffic of each of the plurality of sections to be predicted for a future time period by using real-time traffic data and the traffic prediction model. An apparatus and method for determining spatial influences among sections, as well as an apparatus and method for traffic prediction, are also disclosed. With the present invention, a spatial influence of a section can be used as a spatial operator and a time sequence model can be incorporated, such that the influences on a current section by its neighboring section for a plurality of spatial orders can be taken into account. In this way, the traffic condition in a spatial scope can be measured more practically, so as to improve accuracy of prediction.