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Traffic flow statistical method facing to urban traffic signal timing plan

A traffic signal and statistical method technology, applied in the field of intelligent transportation, can solve problems such as inability to handle complex scenes, limited video angles, slow calculation speed, etc., and achieve significant economic benefits, good precision and low cost.

Inactive Publication Date: 2019-04-05
CHANGAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems of limited video angle, slow calculation speed and inability to handle complex scenes in the prior art, the present invention provides a traffic flow statistics method for urban traffic signal timing, which includes the following steps:

Method used

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  • Traffic flow statistical method facing to urban traffic signal timing plan
  • Traffic flow statistical method facing to urban traffic signal timing plan
  • Traffic flow statistical method facing to urban traffic signal timing plan

Examples

Experimental program
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Embodiment

[0098] Such as Figure 8 For the creation and simulation of actual scene traffic flow models through Synchro. The traffic flow value of each lane at the intersection is realized by manual counting, and the saturated traffic flow, road channelization scheme, and traffic flow in different directions at each intersection are input into the system according to the road conditions in the actual traffic scene, such as Figure 9 shown.

[0099] The hourly traffic flow of each phase lane at the intersection is applied to the design of the intersection signal light timing scheme combined with the actual situation of the lane intersection. The signal is calculated by the Webster method which has a significant effect in the field of signal timing. When using the Webster method, the signal correlation of each phase must be known. parameter. Since right-turning vehicles are not controlled by signal lights and the traditional counting method cannot clearly distinguish the traffic flow in ...

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PUM

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Abstract

The invention belongs to the intelligent transportation field, and specifically relates to the traffic flow statistical method facing to an urban traffic signal timing plan. The method comprises the steps of detecting and tracking a traffic object in a video by using an image processing technology, acquiring the track information of the traffic object, extracting a start-destination coordinate ofeach track to cluster by analyzing and processing the track information and the video scene information, acquiring the subarea information of the scene, and at last, acquiring the detailed traffic flow information. The statistical method provided by the invention has better precision and data richness, provides richer traffic parameter information, can be used for the early warning of the accident, the jam prevention and the automatic route planning, and still has better effect specifically aiming at the complex situation of the heavy traffic flow scene. At the same time, the signal timing plan is performed by acquiring the traffic flow information of the cross road during different time periods, so as to bring obvious economic benefic and improve the traffic passing efficiency.

Description

technical field [0001] The invention belongs to the field of intelligent transportation, and in particular relates to a traffic flow statistical method oriented to urban traffic signal timing. Background technique [0002] Estimating the number of vehicles in traffic video sequences is an important task in intelligent transportation systems that can provide reliable information for traffic management and control. In traditional intelligent transportation systems, vehicle counting is done by special sensors such as magnetic rings, microwave or ultrasonic detectors. However, these sensors have some limitations, such as the data collected is too simple and the installation cost is high. With the development of image processing technology, compared with traditional sensor methods, video-based vehicle counting methods have begun to be paid attention to and valued. [0003] Vehicle counting methods using machine vision include: detection, tracking, and trajectory processing. Th...

Claims

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Application Information

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IPC IPC(8): G08G1/01G06K9/00G06K9/62
CPCG08G1/0145G06V20/52G06F18/23G06F18/2413
Inventor 宋焕生戴喆贾金明张朝阳侯景严云旭李润青王璇武非凡梁浩翔孙士杰刘莅辰唐心瑶
Owner CHANGAN UNIV
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