CN102610098B - Method for setting road section traffic flow detector based on discrete model - Google Patents

Method for setting road section traffic flow detector based on discrete model Download PDF

Info

Publication number
CN102610098B
CN102610098B CN201210059784.6A CN201210059784A CN102610098B CN 102610098 B CN102610098 B CN 102610098B CN 201210059784 A CN201210059784 A CN 201210059784A CN 102610098 B CN102610098 B CN 102610098B
Authority
CN
China
Prior art keywords
section
road
traffic flow
speed
traffic
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Expired - Fee Related
Application number
CN201210059784.6A
Other languages
Chinese (zh)
Other versions
CN102610098A (en
Inventor
史忠科
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xian Feisida Automation Engineering Co Ltd
Original Assignee
Xian Feisida Automation Engineering Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xian Feisida Automation Engineering Co Ltd filed Critical Xian Feisida Automation Engineering Co Ltd
Priority to CN201210059784.6A priority Critical patent/CN102610098B/en
Publication of CN102610098A publication Critical patent/CN102610098A/en
Application granted granted Critical
Publication of CN102610098B publication Critical patent/CN102610098B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Traffic Control Systems (AREA)

Abstract

The invention provides a method for setting a road section traffic flow detector based on a discrete model in order to solve the problem that an existing traffic flow detector in manual layout cannot obtain needed traffic parameters by the aid of a small number of monitoring points. Road section condition observability discriminant is defined according to a macroscopic traffic flow discrete model, various traffic parameters including traffic flow, vehicle speed, traffic density, road occupancy rate and the like are detected in real time on a road by adjusting the setting scheme of the traffic flow detector, information is analyzed, judged and issued by a monitoring center, the basis of a control scheme is proposed, and integral running efficiency and management level are improved.

Description

A kind of road section traffic volume current sensor method to set up based on discrete model
Technical field
The present invention relates to road traffic current sensor method to set up, particularly a kind of road section traffic volume current sensor method to set up based on discrete model.
Background technology
Along with developing rapidly of highway transportation industry, highway administration department need to make regular check on road occupation situation, to damaged road surface is made to corresponding maintenance measure.The method of the artificial visual inspection of traditional use, paper notes record pavement behavior, is difficult to adapt to the requirement of high grade highway development; How in the situation that not affecting normal traffic transportation, to occurring on whole road section surface that damaged position makes detection and localization rapidly and accurately, become current urgent problem; In addition, the crossing of current many domestic city, Important Sections and expressway ramp mouth, responsive section (Frequent Accidents, bend many etc.) all set up fixed position checkout equipment.Can detect in real time traffic (as vehicle flowrate, the speed of a motor vehicle, density etc.) and accident generation information in fixed range; But, due to many-sided reason (being mainly funds reason), fixed test point can not be all set in each section; Like this, for the section that checkout equipment is not set, conventionally adopt following two kinds of modes to obtain relevant information: the one, to close on check point obtaining information, as basis, estimate this road section traffic volume situation, the 2nd, accident, congestion information circular telephone number are set, passive type is accepted the phone circular traffic that the human pilot of driving vehicle on this section is made, and namely in artificial mode, carrys out obtaining information; On the section that checkout equipment is not set, once there is sudden traffic hazard, in order to wait for that traffic police comes to process, need to retain the scene of the accident so that investigate and collect evidence and confirmation accident responsibility side, so just very easily cause blocking up of section.And traffic behavior perception is one of the basis of intelligent transportation system and gordian technique, accurately, obtain fast and reliably basic traffic data and comprehensive traffic information, for monitoring, management, maneuver traffic operation, improve transport services quality, guarantee traffic safety, alleviate traffic congestion significant.
Aspect transport information administration obtains, be mainly used in the management of the transportations such as toll on the road and bridge, long-distance transport or city bus both at home and abroad, can adopt administrative means acquisition unit separating vehicles and segment path information; But the most vehicles that travel in city, at present can be by the GPS information reporting of own vehicle to administrative authority, even in developed countries such as the U.S., because the human rights issues such as privacy also can not be executed in the recent period; On modern road, surveillance is a lot, but at least which monitor must detect in real time the various traffic parameters such as the magnitude of traffic flow, car speed, vehicle density and road occupancy on road, as Surveillance center, analyze, judge, release news and propose the basic foundation of control program, improve overall operation efficiency and management level; Traffic flow detecting device remains artificial layout at present.
Summary of the invention
In order to overcome the artificial layout of existing magnitude of traffic flow detecting device, can not obtain with a small amount of monitoring point the problem of required traffic parameter, the invention provides a kind of road section traffic volume current sensor method to set up based on discrete model, the method is according to Macro-traffic Flow discrete model definition section condition observability discriminant, by adjusting the plan of establishment of traffic flow detecting device, on road, detect in real time the magnitude of traffic flow, car speed, the various traffic parameters such as vehicle density and road occupancy, as Surveillance center, analyze, judgement, release news and propose the basic foundation of control program, improve overall operation efficiency and management level
The technical solution adopted for the present invention to solve the technical problems: a kind of road section traffic volume current sensor method to set up based on discrete model, is characterized in that comprising the following steps:
1, definition section condition observability discriminant is:
Figure 2012100597846100002DEST_PATH_IMAGE001
Wherein:
Figure 233502DEST_PATH_IMAGE002
for observing matrix,
Figure 2012100597846100002DEST_PATH_IMAGE003
for the sampling period,
Figure 2012100597846100002DEST_PATH_IMAGE005
for specifying highway section label,
Figure 993385DEST_PATH_IMAGE006
for the section sum of this appointment highway division,
Figure 2012100597846100002DEST_PATH_IMAGE007
be
Figure 710805DEST_PATH_IMAGE008
individual section exists
Figure 2012100597846100002DEST_PATH_IMAGE009
the average density in moment,
Figure 770596DEST_PATH_IMAGE010
be
Figure 2012100597846100002DEST_PATH_IMAGE011
individual section exists the average velocity in moment,
Figure 532064DEST_PATH_IMAGE012
for
Figure 736781DEST_PATH_IMAGE009
moment enters from ring road entrance
Figure 653790DEST_PATH_IMAGE011
the flow in individual section,
Figure 2012100597846100002DEST_PATH_IMAGE013
for
Figure 729193DEST_PATH_IMAGE009
moment flows out the from ramp exit
Figure 440666DEST_PATH_IMAGE011
the flow in individual section, be
Figure 338532DEST_PATH_IMAGE011
individual road section length,
Figure 2012100597846100002DEST_PATH_IMAGE015
for equivalent speed, ,
Figure 2012100597846100002DEST_PATH_IMAGE017
,
Figure 2012100597846100002DEST_PATH_IMAGE019
for free stream velocity,
Figure 606276DEST_PATH_IMAGE020
be
Figure 316743DEST_PATH_IMAGE011
there is the impact of information display board indication speed parity price speed in individual section,
Figure 2012100597846100002DEST_PATH_IMAGE021
for the maximum potential density in single track, for weight coefficient,
Figure 2012100597846100002DEST_PATH_IMAGE023
be reflection special parameter and adjustable correction factor, make the more realistic traffic of whole model;
2, select observing matrix , by twice observation, can express the estimated value of density, speed, if traffic flow detecting device is not installed in this section, the density in this section, speed must meet the substantially unimpeded condition of road for a long time:
Figure 882088DEST_PATH_IMAGE024
、
Figure 2012100597846100002DEST_PATH_IMAGE025
Wherein:
Figure 548693DEST_PATH_IMAGE026
,
Figure 2012100597846100002DEST_PATH_IMAGE027
for the given positive number that is less than 1, otherwise to install traffic flow detecting device additional.
The invention has the beneficial effects as follows: according to the criterion of system condition observability, traffic flow detecting device is set scientifically and rationally, on road, detect in real time the various traffic parameters such as the magnitude of traffic flow, car speed, vehicle density and road occupancy, for Surveillance center analyzes, judges, releases news and control program is selected to provide basic foundation.
Below in conjunction with embodiment, the present invention is elaborated.
Embodiment
, definition section condition observability discriminant is:
Figure 280370DEST_PATH_IMAGE001
Wherein:
Figure 247189DEST_PATH_IMAGE003
for the sampling period,
Figure 487677DEST_PATH_IMAGE011
for specifying highway section label,
Figure 156425DEST_PATH_IMAGE006
for the section sum of this appointment highway division, be
Figure 329097DEST_PATH_IMAGE011
individual section exists
Figure 740487DEST_PATH_IMAGE009
the average density in moment,
Figure 896531DEST_PATH_IMAGE010
be individual section exists the average velocity in moment,
Figure 27801DEST_PATH_IMAGE012
for
Figure 421873DEST_PATH_IMAGE009
moment enters from ring road entrance
Figure 115023DEST_PATH_IMAGE008
the flow in individual section, for
Figure 650751DEST_PATH_IMAGE009
moment flows out the from ramp exit
Figure 532119DEST_PATH_IMAGE011
the flow in individual section,
Figure 497801DEST_PATH_IMAGE014
be individual road section length,
Figure 56007DEST_PATH_IMAGE015
for equivalent speed,
Figure 80464DEST_PATH_IMAGE016
,
Figure 115416DEST_PATH_IMAGE017
, for free stream velocity,
Figure 964609DEST_PATH_IMAGE020
be
Figure 820570DEST_PATH_IMAGE011
there is the impact of information display board indication speed parity price speed in individual section,
Figure 659213DEST_PATH_IMAGE021
for the maximum potential density in single track,
Figure 18650DEST_PATH_IMAGE022
for weight coefficient,
Figure 542603DEST_PATH_IMAGE023
be reflection special parameter and adjustable correction factor, make the more realistic traffic of whole model;
If 2 get
Figure 620280DEST_PATH_IMAGE028
time,
Figure 2012100597846100002DEST_PATH_IMAGE029
Wherein:
Figure 449565DEST_PATH_IMAGE030
Speed and the density Estimation value that can observe by measuring speed this section, if traffic flow detecting device is not installed in this section, the density in this section, speed must meet the substantially unimpeded condition of road for a long time: for example:
Meet the substantially unimpeded condition of road:
Figure 2012100597846100002DEST_PATH_IMAGE031
、 ，
Otherwise install traffic flow detecting device additional.

Claims (1)

1. the road section traffic volume current sensor method to set up based on discrete model, is characterized in that comprising the following steps:
1) definition section condition observability discriminant is:
Wherein:
Figure 309474DEST_PATH_IMAGE002
for observing matrix,
Figure 2012100597846100001DEST_PATH_IMAGE003
for the sampling period, for specifying highway section label, for the section sum of this appointment highway division, be individual section exists
Figure 2012100597846100001DEST_PATH_IMAGE009
the average density in moment,
Figure 887457DEST_PATH_IMAGE010
be
Figure 495156DEST_PATH_IMAGE005
individual section exists
Figure 547426DEST_PATH_IMAGE009
the average velocity in moment,
Figure 2012100597846100001DEST_PATH_IMAGE011
for
Figure 455863DEST_PATH_IMAGE009
moment enters from ring road entrance
Figure 378820DEST_PATH_IMAGE005
the flow in individual section, for
Figure 946254DEST_PATH_IMAGE009
moment flows out the from ramp exit
Figure 468502DEST_PATH_IMAGE005
the flow in individual section, be
Figure 495233DEST_PATH_IMAGE005
individual road section length,
Figure 444734DEST_PATH_IMAGE014
for equivalent speed,
Figure 2012100597846100001DEST_PATH_IMAGE015
,
Figure 392967DEST_PATH_IMAGE016
,
Figure 718906DEST_PATH_IMAGE018
for free stream velocity,
Figure 2012100597846100001DEST_PATH_IMAGE019
be there is the impact of information display board indication speed parity price speed in individual section,
Figure 717617DEST_PATH_IMAGE020
for the maximum potential density in single track,
Figure 2012100597846100001DEST_PATH_IMAGE021
for weight coefficient,
Figure 169458DEST_PATH_IMAGE022
be reflection special parameter and adjustable correction factor, make the more realistic traffic of whole model;
2) select observing matrix
Figure 282776DEST_PATH_IMAGE002
, by the estimated value of twice observation expression density, speed, if traffic flow detecting device is not installed in this section, the density in this section, speed must meet the substantially unimpeded condition of road for a long time:
Figure 2012100597846100001DEST_PATH_IMAGE023
、
Wherein:
Figure 2012100597846100001DEST_PATH_IMAGE025
,
Figure 450769DEST_PATH_IMAGE026
for the given positive number that is less than 1, otherwise to install traffic flow detecting device additional;
Specific implementation is: get
Figure 2012100597846100001DEST_PATH_IMAGE027
time,
Wherein:
Figure 2012100597846100001DEST_PATH_IMAGE029
By measuring speed, observe speed and the density Estimation value in this section, if traffic flow detecting device is not installed in this section, the density in this section, speed must meet the substantially unimpeded condition of road for a long time:
Meeting the substantially unimpeded condition of road is:
Figure 762375DEST_PATH_IMAGE030
、
Figure 2012100597846100001DEST_PATH_IMAGE031
，
Otherwise install traffic flow detecting device additional.
CN201210059784.6A 2012-03-09 2012-03-09 Method for setting road section traffic flow detector based on discrete model Expired - Fee Related CN102610098B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201210059784.6A CN102610098B (en) 2012-03-09 2012-03-09 Method for setting road section traffic flow detector based on discrete model

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201210059784.6A CN102610098B (en) 2012-03-09 2012-03-09 Method for setting road section traffic flow detector based on discrete model

Publications (2)

Publication Number Publication Date
CN102610098A CN102610098A (en) 2012-07-25
CN102610098B true CN102610098B (en) 2014-05-07

Family

ID=46527432

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201210059784.6A Expired - Fee Related CN102610098B (en) 2012-03-09 2012-03-09 Method for setting road section traffic flow detector based on discrete model

Country Status (1)

Country Link
CN (1) CN102610098B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103198672A (en) * 2013-03-27 2013-07-10 大连海事大学 Method for laying urban road network traffic flow detectors
CN103489316B (en) * 2013-09-10 2016-05-18 同济大学 A kind of network traffic flow detector distribution method based on road network topology relation

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19729914A1 (en) * 1997-07-04 1999-01-07 Mannesmann Ag Process for the analysis of a traffic network, traffic analysis, traffic forecast as well as creation of a historical traffic database and traffic analysis and forecasting center
CN101025861A (en) * 2007-02-12 2007-08-29 吉林大学 Detector layout method for urban traffic signal control system
CN102169630A (en) * 2011-03-31 2011-08-31 上海电科智能系统股份有限公司 Quality control method of road continuous traffic flow data
CN102306450A (en) * 2011-08-30 2012-01-04 同济大学 Layout method for traffic detectors of sparse road network
CN102360526A (en) * 2011-09-28 2012-02-22 东南大学 Real-time monitoring method for road section state of high road

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE19729914A1 (en) * 1997-07-04 1999-01-07 Mannesmann Ag Process for the analysis of a traffic network, traffic analysis, traffic forecast as well as creation of a historical traffic database and traffic analysis and forecasting center
CN101025861A (en) * 2007-02-12 2007-08-29 吉林大学 Detector layout method for urban traffic signal control system
CN102169630A (en) * 2011-03-31 2011-08-31 上海电科智能系统股份有限公司 Quality control method of road continuous traffic flow data
CN102306450A (en) * 2011-08-30 2012-01-04 同济大学 Layout method for traffic detectors of sparse road network
CN102360526A (en) * 2011-09-28 2012-02-22 东南大学 Real-time monitoring method for road section state of high road

Also Published As

Publication number Publication date
CN102610098A (en) 2012-07-25

Similar Documents

Publication Publication Date Title
CN108806296B (en) Road traffic incident detection early warning method and detection early warning system based on vehicle-road cooperation
CN104408925B (en) Crossing evaluation of running status method based on display radar
Skabardonis et al. I-880 field experiment: Data-base development and incident delay estimation procedures
CN109285349B (en) Method for detecting highway traffic incident under cooperative vehicle and road environment and early warning system
CN107657813A (en) Freeway traffic law enforcement method of discrimination based on wheelpath
CN102592455B (en) Road traffic flow detector setting method based on discrete model
CN107331191A (en) Abnormal driving vehicle localization method, Cloud Server and system
CN102819954A (en) Traffic region dynamic map monitoring and predicating system
CN103578295A (en) Real-time estimating and preventing method for rear-end collision accident risk at tail of expressway queue
CN205158645U (en) Device is initiatively inductiond in highway's grade separation export
CN101882374A (en) System and method for analysis of comprehensive information on vehicle trip distribution
CN106781542A (en) A kind of vehicle queue length detecting system, method and apparatus
CN109191857A (en) A kind of wisdom traffic management system based on big data
CN106548630A (en) A kind of detection method and device of driving behavior
CN100481153C (en) Method for automatically inspecting highway traffic event based on offset minimum binary theory
CN106530714A (en) Secondary traffic accident time prediction method based on traffic flow data
CN109785627A (en) A kind of crossroad access flux monitoring system
CN104575049B (en) A kind of elevated ramp intellectual inducing method and device based on array radar
CN103198707B (en) A kind of vehicle regulate and control method based on traffic flow character dangerous under fine day situation
CN102360524B (en) Automatic detection and confirmation method of dangerous traffic flow characteristics of highway
CN202013659U (en) Intelligent safe traffic information platform based on embedded platform imaging processing and wireless communication
CN102610098B (en) Method for setting road section traffic flow detector based on discrete model
CN102610097B (en) Method for setting road section traffic flow detector based on improved discrete model
CN102610096B (en) Method for setting highway traffic flow detector based on improved discrete model based
CN206848501U (en) A kind of expressway weather monitoring system

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20140507