CN106023591A - Urban trunk line green wave control evaluation method and device - Google Patents
Urban trunk line green wave control evaluation method and device Download PDFInfo
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- CN106023591A CN106023591A CN201610444828.5A CN201610444828A CN106023591A CN 106023591 A CN106023591 A CN 106023591A CN 201610444828 A CN201610444828 A CN 201610444828A CN 106023591 A CN106023591 A CN 106023591A
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- 238000011156 evaluation Methods 0.000 title claims abstract description 11
- 238000012360 testing method Methods 0.000 claims abstract description 56
- 238000000034 method Methods 0.000 claims abstract description 17
- 230000010365 information processing Effects 0.000 claims abstract description 14
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- DMBHHRLKUKUOEG-UHFFFAOYSA-N diphenylamine Chemical compound C=1C=CC=CC=1NC1=CC=CC=C1 DMBHHRLKUKUOEG-UHFFFAOYSA-N 0.000 claims description 9
- 206010000060 Abdominal distension Diseases 0.000 claims description 5
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- 230000007115 recruitment Effects 0.000 claims description 5
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Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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Abstract
The invention discloses a green wave control evaluation method and device for urban trunk lines. The invention obtains the evaluation parameters through the vehicle-mounted module arranged on the test vehicle, and quickly evaluates the control effect of the green wave band according to the travel time of the test route, the parking times of the test vehicle and the saturation of the intersection by utilizing an evaluation algorithm in the information processing and calculating module of the handheld device. By adopting the method, the green wave control effect of various types of trunk lines can be rapidly evaluated, the feedback of the control effect can be timely obtained, and an evaluation report can be generated, so that the purposes of optimizing the control scheme, relieving urban traffic jam and guaranteeing the driving safety can be achieved.
Description
Technical field
The invention belongs to technical field of intelligent traffic, be specifically related to a kind of traffic signalization assessment technology, do for city
Drawing lines road provides green ripple to control the method and device of operational effect assessment.
Background technology
At present, arterial road, as the important component part of urban road network, carries main vehicle pass-through task.
Along with continuing to increase of automobile pollution, arterial road becomes the severely afflicated area that traffic congestion occurs.Therefore the intelligence of arterial road
Traffic signal control strategy becomes one of important means alleviating traffic congestion.For urban trunk road in various researchs and invention
The traffic control on road has carried out exploring widely, wherein controls most widely used and best results with the green ripple of main line.But, owing to calculating
The problems such as the accuracy of method and high efficiency, cause most green ripple to control effect uneven；Comment simultaneously as lack control effect
The feedback of valency, also causes control program cannot upgrade and adapt to the feature of traffic flow change in time.Therefore, control effect is obtained in time
Fruit feedback, has extremely important meaning to optimization control scheme, alleviation urban traffic blocking, guarantee driving safety.
Summary of the invention
Controlling present in recruitment evaluation not enough for the green ripple of current arterial road, the present invention combines car by assessment algorithm
Carry to put and control effect is carried out rapid evaluation, contribute to traffic control department and grasp control program effect in time, and carry out necessary tune
Whole.Specifically adopt the following technical scheme that
The green ripple of urban trunk controls appraisal procedure, comprises the steps:
Step 1: obtain tested main line green wave band width and the saturation of crossing, sets test car speed, sets testing time；
Step 2: using the vehicle module being arranged on test vehicle to obtain assessment parameter, described assessment parameter includes measurement circuit
Hourage, test vehicle stop frequency；
Step 3: green wave band controls recruitment evaluation, uses the information processing in handheld device and computing module according to measurement circuit trip
Row time, test vehicle stop frequency, intersection saturation degree control effect to green wave band and are estimated, and the calculating of evaluating is such as
Shown in following formula:
In formula,Represent evaluating；tmRepresent test vehicle theSecondary test hourage by main line；SmRepresent test
VehicleSecondary test is by stop frequency during main line；W represents total testing time；WithRepresent weight coefficient；xm(i)
Represent theDuring secondary test, the saturation of i-th crossing on main line；Represent the quantity of crossing；
Step 4: generate assessment report, when 0<P<during K, then judges that crossing does not blocks up, if during P>K, it is determined that crossing blocks up；Its
In, K is that the crossing set blocks up threshold value.
Preferably, also include wheelpath and the speed obtaining test vehicle, if the wheelpath of test vehicle and speed
Not at green wave band alleviating distention in middle-JIAO, being then modified assessment parameter, modification method is to reacquire assessment parameter until the driving of vehicle
Track and speed are in green wave band alleviating distention in middle-JIAO.
The application green ripple of urban trunk controls the device of appraisal procedure, including the information processing in handheld device and calculating mould
Block, the vehicle module being arranged on test vehicle, wireless communication module；Information processing and computing module are based on Android/IOS
Operating system, including evaluating acquisition module and GIS module；Vehicle module includes GPS/ Big Dipper module and video module；Nothing
The network transmission technologies such as line communication module energy the most compatible TCP/IP, Wifi, 3G/4G.
Preferably, vehicle module utilizes the vehicle coordinate information, OK of the GPS/ Big Dipper module record test vehicle comprised
Sailing track, speed, timestamp etc., calculate Vehicle Speed and hourage with this, video module is used for calculating stop frequency
With coupling vehicle running path.
Preferably, information processing and the computing module data to collecting carry out pretreatment, by evaluating acquisition module
The data gathered filter, and remove illegal, invalid data, according to standard, effective, legal data are formatted place
Reason, and the data after processing are stored.
Preferably, information processing and computing module, by GIS module marks vehicle driving trace, accept video module simultaneously
Real-time video, by video modification speed, driving path.
Preferably, assessment result is wirelessly sent to traffic control center or pushes away by information processing and computing module
Deliver to traffic control department and formulate position.
3, the present invention has a most useful technique effect:
(1) function is advanced, convenient and practical, Instant City arterial road filtering can control recruitment evaluation；
(2) utilizing vehicle GPS/Big Dipper, video module can revise test vehicle driving trace, it is ensured that assessment result more accurately and
Reliably.
Accompanying drawing explanation
Fig. 1 is that the green ripple of urban trunk of the present invention controls apparatus for evaluating schematic diagram.
Fig. 2 is that the green ripple of urban trunk of the present invention controls appraisal procedure flow chart.
Detailed description of the invention
1 GPS/ Big Dipper data reception module (is arranged on test vehicle interior)；
2 video modules (are arranged on test outside vehicle)；
3 wireless transport modules (are arranged on test outside vehicle)
4 GIS modules (are arranged on the handheld device of Android/IOS operating system)
5 video modules (are arranged on the handheld device of Android/IOS operating system)
6 handheld devices being provided with Android/IOS operating system
In FIG, GPS/ Big Dipper module obtains the position coordinate data of test vehicle, vehicle speed data, timestamp number in real time
According to etc., video module (employing IP Camera can be by wireless network transmissions video stream data) obtains the driving of test in real time and regards
Frequently, it is sent to information processing and computing module by wireless (Wifi, 3G/4G etc.) mode.Information processing in handheld device and
The computing module data to collecting carry out pretreatment, mainly will once test the data and stop frequency hourage of collection
Data filter, and remove illegal, invalid data, and according to standard, effective, legal data are formatted process, and right
Data after process store.GPS/ Big Dipper module coordinate data GIS module in the handheld device carries out path matching,
And in this module real-time reception video stream data.Then, recruitment evaluation algorithm is controlled to currently by built-in main line filtering
Control effect to be estimated, and generate assessment report；Finally, by wireless (Wifi, 3G/4G etc.) mode, assessment result is sent
To traffic control center or be pushed to traffic control department formulate position.
In fig. 2, the green ripple of urban trunk controls appraisal procedure, it is necessary first to obtains during the green ripple of tested main line controls and designs
Green wave band width, i.e. Vehicle Speed is interval, and sets the travel speed of test vehicle according to this (in principle at this speed interval
The vehicle of interior traveling can be not parking normal through green swash road), and obtain the saturation of crossing；Secondly, real for main line
Border situation, sets testing time, the number of times that i.e. test vehicle comes and goes；Again, test vehicle proceeds by test, and period passes through
GPS/ Big Dipper module and video module obtain assessment parameter (include the hourage of measurement circuit, the stop frequency of test vehicle,
The wheelpath of test vehicle and speed), judgement schematics is as follows:
In formula,Represent evaluating；tmRepresent test vehicle theSecondary test hourage by main line；SmRepresent test
VehicleSecondary test is by stop frequency during main line；W represents total testing time；WithRepresent weight coefficient；xm(i)
Represent theDuring secondary test, the saturation of i-th crossing on main line；Represent the quantity of crossing.
If speed and the driving trace of testing vehicle in test process fail to reach to set requirement, i.e. speed, track not
At green wave band alleviating distention in middle-JIAO, then need to re-start test；Finally utilize assessment algorithm to calculate assessment parameter P, and generate assessment report.
Claims (7)
1. the green ripple of urban trunk controls appraisal procedure, it is characterised in that comprise the steps:
Step 1: obtain tested main line green wave band width and the saturation of crossing, sets test car speed, sets testing time；
Step 2: using the vehicle module being arranged on test vehicle to obtain assessment parameter, described assessment parameter includes measurement circuit
Hourage, test vehicle stop frequency；
Step 3: green wave band controls recruitment evaluation, uses the information processing in handheld device and computing module according to measurement circuit trip
Row time, test vehicle stop frequency, intersection saturation degree control effect to green wave band and are estimated, and the calculating of evaluating is such as
Shown in following formula:
In formula,Represent evaluating；tmRepresent test vehicle theSecondary test hourage by main line；SmRepresent test
VehicleSecondary test is by stop frequency during main line；W represents total testing time；WithRepresent weight coefficient；xm(i)
Represent theDuring secondary test, the saturation of i-th crossing on main line；Represent the quantity of crossing；
Step 4: generate assessment report, when 0<P<during K, then judges that crossing does not blocks up, if during P>K, it is determined that crossing blocks up；Its
In, K is that the crossing set blocks up threshold value.
2. the green ripple of urban trunk as claimed in claim 1 controls appraisal procedure, it is characterised in that also include obtaining test vehicle
Wheelpath and speed, if the test wheelpath of vehicle and speed is not at green wave band alleviating distention in middle-JIAO, then assessment parameter is repaiied
Just, modification method is to reacquire assessment parameter until the wheelpath of vehicle and speed are in green wave band alleviating distention in middle-JIAO.
3. the device of an application urban trunk as claimed in claim 1 or 2 green ripple control appraisal procedure, it is characterised in that: bag
Include the information processing in handheld device and computing module, the vehicle module being arranged on test vehicle, wireless communication module；Information
Process and computing module is based on Android/IOS operating system, including evaluating acquisition module and GIS module；Vehicle module
Including GPS/ Big Dipper module and video module；The network transmission such as wireless communication module energy the most compatible TCP/IP, Wifi, 3G/4G
Technology.
Device the most according to claim 3, it is characterised in that: vehicle module utilizes the GPS/ Big Dipper module record comprised
Test the vehicle coordinate information of vehicle, driving trace, speed, timestamp etc., calculate Vehicle Speed and hourage with this,
Video module is used for calculating stop frequency and coupling vehicle running path.
5. according to the device described in claim 3-4, it is characterised in that: the data collected are entered by information processing with computing module
The data of evaluating acquisition module collection are filtered, remove illegal, invalid data by row pretreatment, by effective, legal
Data format process according to standard, and the data after processing are stored.
6. according to the device described in claim 3-5, it is characterised in that: information processing and computing module are by GIS module marks
Vehicle driving trace, accepts the real-time video of video module simultaneously, by video modification speed, driving path.
7. according to the device described in claim 3-6, it is characterised in that: information processing and computing module wirelessly will be commented
Estimate result be sent to traffic control center or be pushed to traffic control department formulation position.
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| CN201610444828.5A CN106023591B (en) | 2016-06-20 | 2016-06-20 | Urban trunk line green wave control evaluation method and device |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106297333A (en) * | 2016-10-28 | 2017-01-04 | 东南大学 | A kind of main line green ripple appraisal procedure of car record of making a slip of the tongue based on intersection |
| CN106558222A (en) * | 2016-12-07 | 2017-04-05 | 北京工业大学 | A kind of system and computational methods of green ripple recruitment evaluation index based on mobile phone A PP |
| CN108010356A (en) * | 2016-10-31 | 2018-05-08 | 中国电信股份有限公司 | For coordinating method, vehicle traveling conditioning unit and its vehicle of vehicle traveling |
| CN109493602A (en) * | 2018-11-27 | 2019-03-19 | 公安部交通管理科学研究所 | A kind of evaluation method, the device and system of Urban arterial road coordinate control benefit |
| CN110874940A (en) * | 2018-08-30 | 2020-03-10 | 广州汽车集团股份有限公司 | Green wave vehicle speed guiding method and system |
| CN111462476A (en) * | 2019-01-22 | 2020-07-28 | 上海宝康电子控制工程有限公司 | Method for realizing green wave effect inspection and prediction based on neural network algorithm under TensorFlow framework |
| CN112767680A (en) * | 2020-11-30 | 2021-05-07 | 北方工业大学 | Green wave traffic evaluation method based on trajectory data |
| CN113380029A (en) * | 2021-06-03 | 2021-09-10 | 阿波罗智联(北京)科技有限公司 | Data verification method, device, equipment and storage medium |
| CN113447278A (en) * | 2021-06-24 | 2021-09-28 | 国汽(北京)智能网联汽车研究院有限公司 | Green wave vehicle speed guiding function test method, system and equipment |
| CN115035717A (en) * | 2022-06-01 | 2022-09-09 | 南京理工大学 | Main line green wave traffic evaluation method based on checkpoint data |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101980318A (en) * | 2010-10-27 | 2011-02-23 | 公安部交通管理科学研究所 | Multi-control target compound optimization method for traffic signals |
| CN102165501A (en) * | 2008-09-30 | 2011-08-24 | 西门子公司 | Method for optimizing the traffic control at a traffic signal-controlled intersection in a road traffic network |
| WO2014019461A1 (en) * | 2012-08-02 | 2014-02-06 | 中兴通讯股份有限公司 | Arterial traffic light optimization and control method and device |
| CN104751652A (en) * | 2015-04-14 | 2015-07-01 | 江苏物联网研究发展中心 | Algorithm for optimizing green waves on basis of genetic algorithms |
-
2016
- 2016-06-20 CN CN201610444828.5A patent/CN106023591B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102165501A (en) * | 2008-09-30 | 2011-08-24 | 西门子公司 | Method for optimizing the traffic control at a traffic signal-controlled intersection in a road traffic network |
| CN101980318A (en) * | 2010-10-27 | 2011-02-23 | 公安部交通管理科学研究所 | Multi-control target compound optimization method for traffic signals |
| WO2014019461A1 (en) * | 2012-08-02 | 2014-02-06 | 中兴通讯股份有限公司 | Arterial traffic light optimization and control method and device |
| CN104751652A (en) * | 2015-04-14 | 2015-07-01 | 江苏物联网研究发展中心 | Algorithm for optimizing green waves on basis of genetic algorithms |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106297333A (en) * | 2016-10-28 | 2017-01-04 | 东南大学 | A kind of main line green ripple appraisal procedure of car record of making a slip of the tongue based on intersection |
| CN108010356A (en) * | 2016-10-31 | 2018-05-08 | 中国电信股份有限公司 | For coordinating method, vehicle traveling conditioning unit and its vehicle of vehicle traveling |
| CN106558222A (en) * | 2016-12-07 | 2017-04-05 | 北京工业大学 | A kind of system and computational methods of green ripple recruitment evaluation index based on mobile phone A PP |
| CN110874940A (en) * | 2018-08-30 | 2020-03-10 | 广州汽车集团股份有限公司 | Green wave vehicle speed guiding method and system |
| CN109493602A (en) * | 2018-11-27 | 2019-03-19 | 公安部交通管理科学研究所 | A kind of evaluation method, the device and system of Urban arterial road coordinate control benefit |
| CN111462476A (en) * | 2019-01-22 | 2020-07-28 | 上海宝康电子控制工程有限公司 | Method for realizing green wave effect inspection and prediction based on neural network algorithm under TensorFlow framework |
| CN112767680A (en) * | 2020-11-30 | 2021-05-07 | 北方工业大学 | Green wave traffic evaluation method based on trajectory data |
| CN112767680B (en) * | 2020-11-30 | 2022-03-29 | 北方工业大学 | Green wave traffic evaluation method based on trajectory data |
| CN113380029A (en) * | 2021-06-03 | 2021-09-10 | 阿波罗智联(北京)科技有限公司 | Data verification method, device, equipment and storage medium |
| CN113380029B (en) * | 2021-06-03 | 2023-02-03 | 阿波罗智联(北京)科技有限公司 | Data verification method, device, equipment and storage medium |
| CN113447278A (en) * | 2021-06-24 | 2021-09-28 | 国汽(北京)智能网联汽车研究院有限公司 | Green wave vehicle speed guiding function test method, system and equipment |
| CN115035717A (en) * | 2022-06-01 | 2022-09-09 | 南京理工大学 | Main line green wave traffic evaluation method based on checkpoint data |
| CN115035717B (en) * | 2022-06-01 | 2023-09-26 | 南京理工大学 | Main line green wave traffic evaluation method based on bayonet data |
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Effective date of registration: 20210330 Address after: 100144 room 708, 7 / F, No.17 Shidai Huayuan South Road, Shijingshan District, Beijing Patentee after: Beijing Yunhai Zhitong Technology Development Co.,Ltd. Address before: 100144 Beijing City, Shijingshan District Jin Yuan Zhuang Road No. 5 Patentee before: North China University of Technology |