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Bus punctuality prediction method based on GPS data

A technology of GPS data and prediction method, which is applied in the direction of traffic flow detection, road vehicle traffic control system, traffic control system, etc., can solve the problems of ineffective use of data, time-consuming, low cost, etc. The effect of data processing costs

Inactive Publication Date: 2017-01-11
BEIHANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the research on bus punctuality mainly focuses on the reliability of travel time and the punctuality of the whole bus, and there are few detailed studies on the operation of buses between stations.
Moreover, when analyzing the bus travel time, in the past, manual field surveys were often used to obtain data, which was time-consuming, laborious and inaccurate
As my country's GPS technology is more widely used, a large amount of data collected in real time has not been effectively utilized

Method used

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  • Bus punctuality prediction method based on GPS data
  • Bus punctuality prediction method based on GPS data
  • Bus punctuality prediction method based on GPS data

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Embodiment 1

[0056] In order to further illustrate this specific implementation manner, this embodiment is provided. In this embodiment, in order to facilitate the parameter understanding and algorithm realization of the present invention, specific basic data in the five steps are described in detail.

[0057] The basic data (departure data) and actual operation data (bus GPS data) are provided by XX Company in XX City. The basic data is the basis and important reference for reliability judgment. The bus departure data includes route identification, train number identification, start time, end Information such as time, planned time to arrive at each station, start status, end status, and distance from the first stop. Actual operating data is the main body and core data of punctual forecasting. Bus GPS data includes information such as route identification, train number identification, station identification, time, latitude and longitude, speed, azimuth, uplink and downlink identification, ...

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Abstract

The invention discloses a bus punctuality prediction method based on GPS data, and belongs to the field of public transport information processing. The method comprises the steps: the collection and processing of bus GPS data and departure data, the determining of a bus punctuality value, the extraction of bus punctuality influence factors and the prediction of bus punctuality. The method employs an SVM (support vector machine) algorithm. The method combines the bus GPS data, extracts the track information and departure information of a plurality of buses, is convenient and quick, and reduces the data processing cost. Moreover, the method employs the SVM algorithm for the two-class prediction of the punctual conditions of a downstream stop, and enables passengers to know the bus operation conditions better to reasonably adjust the travel time. Meanwhile, the method enables a bus operation department to be able to timely adjust the departure interval of buses, and improves the bus service level.

Description

technical field [0001] The invention relates to the technical field of public transportation information processing, in particular to a method for predicting public transportation punctuality based on GPS data. Background technique [0002] The urban public transportation system is a complex system of dynamic interaction among people, vehicles, roads, information and rules. It is the lifeline of the city and carries the daily operation of the city. Therefore, a stable and efficient road transportation system is very important to the city. Smooth and reliable urban traffic operation is not only the basis for travelers to achieve their travel goals, but also the goal of urban traffic managers. However, when the urban traffic system is in operation, it is often disturbed by random factors such as bad weather, traffic time, and traffic accidents, which increases the uncertainty of travelers in the travel process, reduces the traffic capacity of road facilities, and makes the pur...

Claims

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Application Information

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IPC IPC(8): G08G1/01G08G1/123
CPCG08G1/0125G08G1/123
Inventor 于海洋陈栋伟马晓磊吴志海
Owner BEIHANG UNIV
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