Method for identifying activity type of stay node of dangerous goods transportation vehicle based on GPS data

Abstract

The invention relates to a method for identifying an activity type of a stay node of a dangerous goods transportation vehicle based on GPS data, comprising extracting the stay node. According to the mean longitude (shown in the description) and the mean latitude (shown in the description) of the stay node, clustering the stay node into an active hot area Hu; constructing the space-time characteristics according to the active hot area Hu, wherein the space-time characteristics comprise an average retention time avgTu, an average starting point containing rate avgFu and a mixed entropy index Entropyu; defining loading activity, unloading activity, returning activity and non-freight activity, and obtaining the actual value tendency of the space-time characteristics corresponding to the four activity types; acquiring the alternative vehicle activity types of the stay nodes according to the space-time characteristics and the defined four types of activity types by adopting an FCM clusteringmethod; setting an interest point category for each stay node, and judging the final vehicle activity type from the two alternative vehicle activity types.

Description

technical field [0001] The invention relates to the field of data processing, in particular to a method for identifying activity types at nodes of dangerous goods transport vehicles based on GPS track data. Background technique [0002] With the rapid growth of society's demand for dangerous goods, the road transport volume of dangerous goods has increased year by year in recent years, and the road transport accidents caused by this are also on the rise. The traffic authorities in many cities are facing insufficient and inadequate supervision of road transport of dangerous goods. And other issues. One of the reasons is that the competent authorities lack detailed data on the travel activities of vehicles transporting dangerous goods, which makes it difficult to understand the flow of goods in a timely manner and to determine the focus of supervision. [0003] In the past, the acquisition of vehicle travel activity information mostly relied on freight traffic surveys. This m...

AI Technical Summary

Problems solved by technology

[0012] 1) The technology used in this patent needs to use the actual labels of passenger travel activities to train the prediction model in advance, but it is difficult to collect labeled data in reality, and the practicability is not high

[0013] 2) This patent identifies the travel purpose of passengers. Since freight activities are very different from passenger activities, the method described cannot be directly used to identify the type of activity at the node of the dangerous goods transport vehicle;

[0017] This technology is limited to solving simple two-category problems of freight activities and non-freight activities. The proposed method has a low recognition accuracy for parking activities in the absence of auxiliary information, and cannot meet the needs of fine-grained supervision.

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