Method for predicting path destination of moving object

A technology of moving objects and trajectories, applied in the computer field, can solve problems such as data sparseness, reduce the impact of prediction accuracy and optimize calculation time

Inactive Publication Date: 2015-03-11
XIDIAN NINGBO INFORMATION TECH INST
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Problems solved by technology

[0010] The technical problem to be solved by the present invention is to provide a new method for predicting the end point of the trajectory of the moving object in view of the above-mentioned existing methods, so as t

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  • Method for predicting path destination of moving object
  • Method for predicting path destination of moving object
  • Method for predicting path destination of moving object

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[0046] The present invention will be described in further detail below in conjunction with the embodiments of the drawings.

[0047] The present invention provides a method for predicting the end point of the trajectory of a moving object. The following takes Beijing taxi trajectory data set as an example for detailed description. The taxi trajectory data set comes from the Geolife project of Microsoft Research Asia: The project homepage website is: http: / / research.microsoft.com / en-us / projects / geolife / default.aspx This data set records the original GPS trajectory information of 182 taxis in Beijing from July 2007 to August 2012, represented by a series of locations represented by latitude and longitude. The entire data set contains a total of 17,621 trajectories, with a total length of 1,292951 kilometers.

[0048] In this example, the above-mentioned Beijing taxi trajectory data set is randomly divided into a training data set H and a test data set TH, where the ratio of the numb...

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Abstract

The invention discloses a method for predicting the path destination of a moving object, and mainly solves the problems of sparse data, a low hit rate and poor real-time performance during the prediction of the path destination in the prior art. The method includes the following steps: off-line calculating the history path data in a training data set to obtain a location set, a prior probability of each location, a single-step transition probability matrix and a comprehensive transition probability matrix; calculating the conditional probability and the posterior probability of each location being the destination based on the off-line calculated data; on-line predicting the destination of the path to be predicted based on the posterior probability. Compared with the existing path prediction method, the method provided by the invention has the advantages that a prediction can be performed even when the data in the training data set is sparse; the calculation process of the prediction is optimized, so that the impact of the non-aftereffect property of Markov chain on the prediction accuracy is reduced; the prediction accuracy is improved; the method can be used for pushing location-related targeted advertisements and deploying criminal arrest plans in advance.

Description

technical field [0001] The invention belongs to the field of computers, and relates to data mining and location prediction, in particular to a method for predicting the end point of the trajectory of a moving object, that is, by analyzing and mining the obtained historical trajectory data, the destination of the new trajectory is predicted The method can be used for location-related targeted advertisement push, early deployment of criminal arrest plan, etc. Background technique [0002] With the development of Internet of Things technology, various sensors are embedded in portable mobile terminals or fixedly installed on public facilities to participate in people's daily activities. Examples include GPS sensors in taxis and smartphones, among others. They can capture and record changes in people's daily life in real time. Analyze and mine the historical trajectory data collected by these sensors to build a destination prediction model, which is conducive to scientific deci...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06Q30/0251G06N7/01
Inventor 黄健斌孙鹤立徐礼治杨洲
Owner XIDIAN NINGBO INFORMATION TECH INST
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