A device and method for judging traffic status based on bus GNSS spatio-temporal trajectory data

Abstract

The invention relates to a traffic state judgment device based on bus GNSS space-time trajectory data and a method thereof. The device comprises a client side and a server side. The server side comprises a GNSS data acquisition module and a bus station board position judgment module. The server side comprises a data preprocessing module and a traffic state mining module. According to the traffic state judgment device based on the bus GNSS space-time trajectory data, the traffic state can be effectively predicted, and people can be guided to select appropriate bus departure periods to go out in production and life so that traffic pressure can be effectively and reasonably reduced; besides, the device performs data acquisition based on buses and performs analysis according to different bus departure periods of the buses and finally performs summarization so that the traffic state of all periods and all dates can be obtained and data sources are more objective and more persuasive.

Description

Technical field: [0001] The invention relates to a device and method for judging traffic status based on bus GNSS spatio-temporal trajectory data, belonging to the technical field of data mining. Background technique: [0002] With the increase of urban population, the number of vehicles has also increased sharply, and the real-time traffic status has also changed more and more. The actual traffic status of each time period and road section in a day has become the information that residents are very concerned about when traveling. Traditional traffic data acquisition methods mainly include manual field surveying and satellite remote sensing technology, which requires repeated measurements by professionals and specialized equipment. The huge amount of traffic data poses a severe test to the survey work. Artificial field surveying and satellite remote sensing technology requires a lot of manpower and material resources, and the acquisition cycle is long and the data timeliness...

AI Technical Summary

Problems solved by technology

Traditional traffic data acquisition methods mainly include manual field surveying and satellite remote sensing technology, which requires repeated measurements by professionals and professional equipment. The huge amount of traffic data poses a severe test to the measurement work

Artificial field surveying and satellite remote sensing technology requires a lot of manpower and material resources, and the collection cycle is long and the data timeliness is poor; so that the traditional traffic data acquisition methods cannot accurately and real-time reflect the latest traffic status

It is a huge challenge to objectively and comprehensively obtain the traffic status information of each time period and each road section

Images