Method for predicting arrival time of bus with missing data

Abstract

The invention discloses a method for predicting arrival time of a bus with missing data. According to the method, firstly, a density-based clustering method is designed to discover important geographic positions; according to the method, excavated geographic positions are used for representing the geographic structure of each route to form node information, and weighted side information with traffic importance is constructed according to the similarity of the geographic structures, so that a public traffic network diagram is formed. Then, a multi-head space-time diagram attention network prediction model is established to learn correlation between bus routes from the angles of space and time, a space attention module is a multi-head diagram attention module with masks, and a time attention module is constructed by an LSTM layer and a transformer layer. According to the method, the travel time of each path in the public transport network can be accurately and effectively learned and predicted, wherein the arrival time prediction accuracy of the bus route with few current travel records can be improved, and the predicted travel time can be provided for the bus route which does not have historical records and is in a design stage.

Description

technical field [0001] The invention relates to the field of bus arrival time prediction, in particular to a bus arrival time prediction method for missing data, which is used to provide accurate data for bus lines with uncertain departure times, problems with GPS equipment, etc. arrival time forecast. Background technique [0002] The bus network is very important to the rapid development of urban transportation. Due to the characteristics of economy and environmental protection, buses are still the main solution for urban travel. The main factors hindering passengers from choosing public transport are their long waiting time and uncertainty of journey time, so accurate prediction of bus arrival time is very important to solve this problem. It can also help reduce traffic congestion and be used in other comprehensive intelligent transportation applications, such as trip planning. [0003] Existing bus arrival or travel time prediction methods rely on a large amount of his...

AI Technical Summary

Problems solved by technology

[0008] In order to solve the problem of predicting the arrival time of buses with missing data, the present invention provides a method for predicting the arrival time of buses with missing data, which can accurately and effectively learn and predict each route in the public transportation network It can not only improve the accuracy of arrival time prediction for bus lines with few current travel records, but also provide estimated travel time for bus lines in the design stage without historical records

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