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Traffic mode clustering model training method, mode recognition method and storage medium

A traffic mode and model training technology, applied in the field of intelligent transportation, can solve problems such as lack of clear information on travel modes and difficulty in inferring users, and achieve the effects of alleviating label data requirements, good clustering performance, and saving application costs

Pending Publication Date: 2020-12-18
SOUTH UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA
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Problems solved by technology

However, it is very difficult to infer the user's travel mode only based on GPS trajectory data, because the GPS sensor can only record the spatio-temporal characteristics of the user's movement, and there is no clear information about the travel mode used.

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  • Traffic mode clustering model training method, mode recognition method and storage medium
  • Traffic mode clustering model training method, mode recognition method and storage medium
  • Traffic mode clustering model training method, mode recognition method and storage medium

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Embodiment Construction

[0026] The idea and technical effects of the present application will be clearly and completely described below in conjunction with the embodiments, so as to fully understand the purpose, features and effects of the present application. Apparently, the described embodiments are only some of the embodiments of the present application, not all of them. Based on the embodiments of the present application, other embodiments obtained by those skilled in the art without creative efforts belong to The protection scope of this application.

[0027] It should be noted that although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than in the flowchart. The terms "first", "second" and the like in the specification and claims and the above drawings are used to distinguish similar objects, and not necessarily used to describe a specific sequence or sequence.

[0028] The methods disclosed in the embodiments of th...

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Abstract

The invention discloses a traffic mode clustering model training method, a mode recognition method and a storage medium, and relates to the technical field of intelligent traffic. The method providedby the embodiment of the invention comprises the following steps: adding a clustering layer to an embedded layer of a convolutional auto-encoder network to obtain a composite clustering model; and training the label-free traffic track data by adopting a composite clustering model to obtain a traffic mode clustering model. According to the method, data mining and algorithm design are carried out onthe label-free data, so that the label data requirement can be effectively relieved, and the application cost is saved; by adding the clustering layer to the embedded layer of the convolutional auto-encoder network, better clustering performance can be obtained; and the traffic mode clustering model is obtained by training the composite clustering model through the label-free traffic trajectory data, and the traffic mode can be recognized under the label-free unsupervised learning condition.

Description

technical field [0001] The embodiments of the present application relate to the technical field of intelligent transportation, and in particular to a traffic mode clustering model training method, a pattern recognition method and a storage medium. Background technique [0002] Traffic pattern recognition is a task of inferring the travel mode of users from their travel data. Traffic pattern recognition location-based services can provide users with accurate and personalized information based on their real-time location and travel information. [0003] A Global Positioning System (GPS) sensor is a sensor that can capture a tuple with a timestamp and a latitude and longitude. They are deployed on most smartphones and cars, have a strong correlation with user behavior, and cover a wider path than traditional positioning sensors. However, it is very difficult to infer the user's travel mode only based on GPS trajectory data, because the GPS sensor can only record the spatio-te...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/02G06N3/08
CPCG06N3/088G06N3/02G06F18/23G06F18/214
Inventor 余剑峤马科斯·克里斯托斯宋晓壮
Owner SOUTH UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA
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