Taxi passenger-carrying trajectory clustering algorithm Tr-OPTICS

A trajectory clustering and taxi technology, which is applied in computing, computer components, instruments, etc., can solve the problems that the calculation efficiency of trajectory data clustering algorithm needs to be improved, and the trajectory clustering results have a greater impact

Inactive Publication Date: 2017-11-24
NANJING UNIV OF INFORMATION SCI & TECH
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AI Technical Summary

Problems solved by technology

[0003] Although the research on trajectory clustering has achieved certain results, there is still room for improvement in the division of specific sub-trajectories. Different sub-trajectory division methods have a greater impact on the results of trajectory clustering, and for trajectory data clustering algorithms. Computational efficiency still needs to be improved

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  • Taxi passenger-carrying trajectory clustering algorithm Tr-OPTICS
  • Taxi passenger-carrying trajectory clustering algorithm Tr-OPTICS
  • Taxi passenger-carrying trajectory clustering algorithm Tr-OPTICS

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Embodiment Construction

[0068] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0069] Enumerate concrete example below, carry out detailed description to passenger locus clustering algorithm Tr-OPTICS of the present invention:

[0070] In order to test the performance of the improved algorithm of the present invention, the experimental environment is set as Intel(R) Core(TM) i5-2410CPU@2.30GHz processor, memory 4.00GB, 850EVO 120GB solid state hard drive, and operating system is Windows10 64 bits. The experimental data is the GPS data set of more than 8,000 taxis in Nanjing on September 12, 2010, including vehicle ID, latitude and longitude, passenger loading time, direction, speed and other information. After data preprocessing, unreasonable data is eliminated, and the main urban area is selected as the research scope. According to the passenger status information in the data, the taxi passenger trajectory is extracted, ...

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Abstract

The invention discloses a taxi passenger-carrying trajectory clustering algorithm Tr-OPTICS. A research object of the algorithm is passenger-carrying trajectories; reachable distance of trajectories, concepts of core trajectories and search neighborhood scopes of the core trajectories are redefined. For passenger-carrying trajectories of large data volumes, an adjacency list is used for replacing a spatial index in the algorithm, and therefore calculation complexity of the algorithm can be lowered. Algorithm execution efficiency and accuracy of clustering results can be improved via the Tr-OPTICS algorithm put forward in the invention. Stability can be maintained despite different sample sizes, and a frequent pattern of passenger-carrying sub-trajectories can be effectively found based on clustering results via the algorithm disclosed in the invention.

Description

technical field [0001] The invention relates to a clustering algorithm for taxi passenger trajectories, specifically referring to a Tr-OPTICS (Trajectory Ordering Points to Identify the Clustering Structure) algorithm suitable for mass trajectory space clustering based on the characteristics of taxi trajectory data. Background technique [0002] With the rapid development of technologies such as GPS positioning, satellite navigation, and wireless communication, positioning equipment such as GPS for civilian use continues to be popularized and widely used. These GPS positioning devices and various applications based on location information services (LBS) generate a large amount of spatiotemporal trajectory data from moving objects. The continuous maturity of spatio-temporal data mining technology and geographic information technology also makes it possible to study the trajectory data of a large number of moving objects. These moving object trajectory data can be divided int...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q50/30G01S19/42
CPCG06Q50/30G01S19/42G06F18/2321
Inventor 毕硕本周浩杨树亮凌德泉那泽
Owner NANJING UNIV OF INFORMATION SCI & TECH
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