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Smart-phone track chain-cluster identification method considering sequential DBSCAN

A technology of smart phones and identification methods, which is applied in the traffic control system of road vehicles, special data processing applications, instruments, etc. It can solve the error of identification results, cannot take into account the characteristics of time continuity or difference, and cannot perfectly support behavior trajectory data, etc. problem, to achieve the effect of improving accuracy

Active Publication Date: 2015-12-30
SOUTHEAST UNIV
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AI Technical Summary

Problems solved by technology

However, since these recognition algorithms do not break away from the dependence on spatial features in essence, they cannot take into account the continuous or difference characteristics of time, and cannot perfectly support behavior trajectory data with time series information, and there are inevitably certain errors in the recognition results.

Method used

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  • Smart-phone track chain-cluster identification method considering sequential DBSCAN
  • Smart-phone track chain-cluster identification method considering sequential DBSCAN
  • Smart-phone track chain-cluster identification method considering sequential DBSCAN

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Embodiment Construction

[0046] In the following, the method of the present invention will be further described in detail in combination with the embodiment of a person's travel trajectory data on weekdays and the accompanying drawings.

[0047] 1. Data format description

[0048] In step 1, the behavior trajectory data of the respondents is obtained through the self-developed "Travel Pattern Collection Software for Smartphones TransGPSCollectorV1.0". The data attributes include: user number, date and time, latitude, longitude, mode, direction, accuracy, Eight items of data such as speed, the specific data form is shown in Table 1.

[0049] Table 1 Example of initial data of behavior trajectory

[0050]

[0051] In order to ensure that the behavior trajectory data can match the map base map, in the data preprocessing stage, the longitude and latitude coordinates of the trajectory should be converted into Mercator plane coordinates. The specific Mercator projection calculation formula is as follows...

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Abstract

The invention discloses a smart-phone track chain-cluster identification method considering sequential DBSCAN. The method comprises that data collection and preprocessing are carried out; the sequential angle offset of behavior track points is calculated; the sequential distance offset of the behavior track points is calculated; chains and non-chains are identified and gathered according to rules; and whether a non-chain segment belongs to a point cluster is determined by using DBSCAN, and outputs an analysis result. The logical process of the behavior track identified by the human eyes is integrated with the DBSCAN by providing the two indexes, namely the sequential angle offset and the sequential distance offset, the disadvantage that a traditional algorithm cannot identify sequential features is overcome, and the accuracy of behavior track chain-cluster identification is improved.

Description

technical field [0001] The invention belongs to the field of travel behavior data collection and analysis in traffic planning, and relates to a smart phone track chain cluster identification method considering time series DBSCAN. Background technique [0002] Travel behavior refers to the displacement process that takes a certain amount of time from the departure point to the destination through a certain path by using a certain mode of transportation in order to accomplish a certain purpose. Through the investigation of travel behavior, the travel characteristics of residents can be grasped, the current situation of traffic demand and supply in the region can be understood, and basic data can be provided for traffic demand forecasting and transportation planning. [0003] Compared with traditional methods (such as face-to-face interviews, computer-aided telephone surveys, CATI, etc.), travel behavior surveys based on smartphones do not require additional installation and ma...

Claims

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Application Information

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IPC IPC(8): G08G1/00G06F17/30
Inventor 季彦婕高良鹏王炜周洋
Owner SOUTHEAST UNIV
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