Taxi passenger refusing act detection method based on large-scale real-time track analysis

Abstract

The invention discloses a taxi passenger refusing act detection method based on large-scale real-time track analysis. The method comprises the steps that mesh dividing is performed on a city to be analyzed; the track record of each taxi to be detected is acquired, and statistics of the number of times of getting on or getting off of passengers of each mesh of each taxi to be detected is performed; the get-on passenger diversity index or the get-off passenger diversity index of each taxi to be detected is calculated according to statistics of the number of times of getting on or getting off of the passengers of each mesh of each taxi to be detected; and the get-on passenger diversity index or the get-off passenger diversity index of each taxi to be detected is compared with an existing passenger refusing act threshold one by one, and the passenger refusing act of the taxi to be detected is proved if the get-on passenger diversity index or the get-off passenger diversity index of each taxi to be detected is less than the threshold. According to the method, powerful technical support is provided for effective management of the taxi industry by starting from the two aspects of accurate positioning of the taxi passenger refusing act and macro estimation of the taxi passenger refusing act.

Description

technical field [0001] The invention relates to the application field of big data in the taxi industry, in particular to a method for detecting taxi refusal behavior based on large-scale real-time trajectory analysis. Background technique [0002] With the advent of the data age, big data has begun to show its strong potential for applications in various fields such as biology, medicine, society, and geography. The taxi industry bears a large burden of urban traffic and provides flexible travel in most urban areas. In recent years, in order to better supervise and manage taxis, with the help of modern information technology, a large amount of taxi trajectory data has been generated, collected and stored. At the same time, it provides rich opportunities for the research of big data. [0003] Many topics worthy of investigation and research in the taxi industry have been implemented, including taxi driver safety and health assessment, commuting mode selection, labor supply i...

AI Technical Summary

Problems solved by technology

However, there are still relatively few investigations and studies on the refusal of boarding, which has caused certain problems for the improvement of the service quality of taxi companies.

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