Road traffic flow prediction method based on cell phone data

A technology of road traffic and forecasting method, which is applied in the field of traffic management, can solve the problems of huge capital and manpower investment and poor operability, and achieve the effect of solving traffic congestion, reducing capital and manpower investment, and predicting traffic flow in a timely and efficient manner

Inactive Publication Date: 2013-01-09
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Installing dense detection equipment on the road is definitely the most effective method, but the investment in capital and manpower is huge, and obviously its operability is poor

Method used

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Embodiment Construction

[0012] In cities with a high penetration rate of mobile phones, using a large amount of receipt data to predict traffic flow is one of the important ways to solve the problem of predicting traffic flow. The invention utilizes mobile phone data to predict and monitor road traffic flow.

[0013] The traffic flow prediction method of the present invention is divided into two stages, the first step is the observation stage, and the second step is the real-time prediction stage.

[0014] The present invention first divides the time that needs to be predicted in a day into various time periods, for example, from 6:00 am to 10:00 pm, divided into 16 time periods according to the number of hours. In the observation stage, the number of mobile phones on a certain road is collected and counted according to each time period, and the existing road traffic flow detection equipment is used to detect the traffic flow in each time period. According to the number of mobile phones in each time...

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Abstract

The invention belongs to the technical field of traffic management, and relates to a road traffic flow prediction method based on cell phone data. The method comprises the following steps of: dividing the time when the traffic flow is needed to be predicted and monitored during the day into different periods of time; in an observation phase, for each observed day, obtaining the cell phone data ofeach period of time through monitoring cell phone switching quantity among different base stations arranged at the same road section, and monitoring and counting road traffic flow data of each periodof time; calculating a related coefficient between the cell phone data and the road traffic flow data; in a prediction phase, monitoring the cell phone data of each period of time in real time; and predicting the traffic flow data in the current period of time according to the cell phone data monitored in real time and the related coefficient. The road traffic flow prediction method based on the cell phone data can reduce cost and labor power invested in road detection devices, and provides an effective way for implementing intelligent urban traffic and solving problems of traffic jams.

Description

technical field [0001] The invention belongs to the technical field of traffic management and relates to a traffic flow prediction method. Background technique [0002] At present, with the rapid development of society and economy, traffic congestion has become a serious problem restricting social development. At the same time, when public emergencies occur, traffic congestion will seriously affect the response speed of emergency personnel to accidents, causing many unnecessary economic losses. Therefore, being able to predict traffic flow in a timely and efficient manner through effective means is an effective means to solve traffic congestion. Installing dense detection equipment on the road is definitely the most effective method, but its capital and manpower investment is very huge, and its operability is obviously poor. Contents of the invention [0003] The purpose of the present invention is to overcome the above-mentioned deficiencies of the prior art and provide...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G08G1/065
Inventor 李乐王文俊
Owner TIANJIN UNIV
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