CN107103755A - A kind of road traffic alert Forecasting Methodology - Google Patents
A kind of road traffic alert Forecasting Methodology Download PDFInfo
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- CN107103755A CN107103755A CN201710329234.4A CN201710329234A CN107103755A CN 107103755 A CN107103755 A CN 107103755A CN 201710329234 A CN201710329234 A CN 201710329234A CN 107103755 A CN107103755 A CN 107103755A
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- early warning
- value
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- alert
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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
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
-
- 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
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
-
- 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
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
-
- 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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention belongs to road traffic application field, and in particular to a kind of road traffic alert Forecasting Methodology.This method comprises the following steps：Gather traffic indicators feature in real time by supply equipment；Site of road where the every group of traffic indicators feature currently got and its supply equipment is corresponded；The real-time traffic index feature value currently obtained and several historical traffic index feature values are constituted into one group of characteristic vector；Go out to describe the early warning value of the site of road traffic behavior according to characteristic vector fusion calculation；Adaptive threshold is chosen；Early warning value W (t) and threshold value T is contrasted, if W (t)>T then early warning, otherwise not early warning.The calculating process of the present invention is concise, and objectivity is strong, the decision of timely, the accurate look-ahead of energy and identification responding and not responding.
Description
Technical field
The invention belongs to road traffic application field, and in particular to a kind of road traffic alert Forecasting Methodology.
Background technology
With scientific and technological progress and economic development, city vehicle is also rapidly increasing, and urban transportation supply can not be met increasingly
The transport need of growth, the traffic jam issue of urban road is increasingly severe.Arterial street is the artery of urban transportation, to city
City arterial highway traffic congestion state carries out timely, accurate look-ahead and identification, reduces the negative effect that traffic congestion is brought.
The content of the invention
The purpose of the present invention is to be needed based on modern urban road traffic there is provided a kind of road traffic alert Forecasting Methodology,
To reach traffic alert real-time early warning.
To achieve the above object, the present invention is adopted the following technical scheme that：
A kind of road traffic alert Forecasting Methodology, this method comprises the following steps：
Step A：Gather traffic indicators feature in real time by supply equipment, obtain vehicle flowrate, speed and time in current region
Occupation rate；
Step B：Site of road where the every group of traffic indicators feature currently got and its supply equipment is corresponded；
Step C：Construction feature vector, by the real-time traffic index feature value currently obtained and several historical traffic index feature values
Constitute one group of characteristic vector：
V(t) = [ F(t) S(t) O(t) ]
V(t-1) = [F(t-1) S(t-1) O(t-1) ]
……
V(t-n) = [F(t-n) S(t-n) O(t-n) ]
F (t) represents that current time vehicle flowrate, S (t) represent that current time speed, O (t) represent current time time occupancy, V
(t-n) feature V value before representing n minutes, n value is adjusted according to application scenarios；
Step D：Go out to describe the early warning value of the site of road traffic behavior according to characteristic vector fusion calculation：
Changing features moment matrix：
Calculate early warning value：
, wherein w1, w2, w3 be characterized value regulation coefficient；
Step E：By history early warning value and alert Data Matching, the early warning value array A [m] of record matching alert, m represents alert
Number, array A [m] record alert moment corresponding early warning value, traversal A [m] finds threshold value T；
Step F：Early warning value W (t) and threshold value T is contrasted, if W (t)>T then early warning, otherwise not early warning.
Further, the early warning value in the step E in A [m] is more than threshold value T number more than m*80%.
The beneficial effects of the present invention are：The calculating process of the present invention is concise, and objectivity is strong, can in time, accurately
Look-ahead and the decision of identification responding and not responding, reduce the negative effect that traffic congestion is brought, and cause unnecessary
Police strength allows expense.
Brief description of the drawings
Fig. 1 is a kind of flow chart of road traffic alert Forecasting Methodology of the invention.
Embodiment
In order to facilitate the understanding of the purposes, features and advantages of the present invention, below in conjunction with accompanying drawing and tool
Body embodiment, is described further to the present invention：
As shown in figure 1, the present invention comprising the step of be：
Step A：By placing supply equipment in urban traffic area, for gathering traffic indicators feature in real time；The supply
Equipment can be electronic police, geomagnetism detecting device, traffic video detection equipment Traficon and rf detector RFID；It is described
Traffic indicators feature includes vehicle flowrate, speed and time occupancy.
Step B：A pair of site of road 1 by the every group of traffic indicators feature currently got and where its supply equipment
Should.
Step C：Construction feature vector, the real-time traffic index feature value currently obtained and several historical traffic indexs is special
Value indicative constitutes one group of characteristic vector：
V(t) = [ F(t) S(t) O(t) ]
V(t-1) = [F(t-1) S(t-1) O(t-1) ]
……
V(t-n) = [F(t-n) S(t-n) O(t-n) ]
F (t) represents that current time vehicle flowrate, S (t) represent that current time speed, O (t) represent current time time occupancy, V
(t-n) represent that n is exemplified by 3 in n minutes preceding feature V value, the present embodiment；
Step D：Go out to describe the early warning value of the site of road traffic behavior according to characteristic vector fusion calculation：
Changing features moment matrix：
Calculate early warning value：
Step E：By history early warning value and alert Data Matching, the early warning value array A [m] of record matching alert, m represents alert
Number, array A [m] record alert moment corresponding early warning value, traversal A [m] finds threshold value T so that the early warning value in A [m] is more than
Threshold value T number is more than m*80%.
Step F：Early warning value W (t) and threshold value T is contrasted, if W (t)>T then early warning, otherwise not early warning.
The invention provides a kind of road traffic alert Forecasting Methodology, this method is applied to the road crowded period, assists
Traffic police quickly handles traffic accident, and whether by the way that early warning value W (t) and threshold value T is contrasted, determining the degree of crowding of the road needs
Want responding, it is to avoid because accident occur quickly to handle and accident is not enough to reach congestion status and traffic police is but caused by responding
The problem of police strength wasting of resources.
Finally it should be noted that：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；For
For those skilled in the art, it can still modify to the technical scheme described in previous embodiment,
Or equivalent substitution is carried out to which part or all technical characteristic；And these modifications or replacement, do not make relevant art
The essence of scheme departs from protection scope of the present invention.
Claims (2)
1. a kind of road traffic alert Forecasting Methodology, it is characterised in that：This method comprises the following steps：
Step A：Gather traffic indicators feature in real time by supply equipment, obtain vehicle flowrate, speed and time in current region
Occupation rate；
Step B：Site of road where the every group of traffic indicators feature currently got and its supply equipment is corresponded；
Step C：Construction feature vector, by the real-time traffic index feature value currently obtained and several historical traffic index feature values
Constitute one group of characteristic vector：
V(t) = [ F(t) S(t) O(t) ]
V(t-1) = [F(t-1) S(t-1) O(t-1) ]
……
V(t-n) = [F(t-n) S(t-n) O(t-n) ]
F (t) represents that current time vehicle flowrate, S (t) represent that current time speed, O (t) represent current time time occupancy, V
(t-n) feature V value before representing n minutes, n value is adjusted according to application scenarios；
Step D：Go out to describe the early warning value of the site of road traffic behavior according to characteristic vector fusion calculation：
Changing features moment matrix：
Calculate early warning value：
, wherein w1, w2, w3 be characterized value regulation coefficient；
Step E：By history early warning value and alert Data Matching, the early warning value array A [m] of record matching alert, m represents alert
Number, array A [m] record alert moment corresponding early warning value, traversal A [m] finds threshold value T；
Step F：Early warning value W (t) and threshold value T is contrasted, if W (t)>T then early warning, otherwise not early warning.
2. road traffic alert Forecasting Methodology as claimed in claim 1, it is characterised in that：It is pre- in A [m] in the step E
Alert number of the value more than threshold value T is more than m*80%.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710329234.4A CN107103755B (en) | 2017-05-11 | 2017-05-11 | Road traffic warning situation prediction method |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710329234.4A CN107103755B (en) | 2017-05-11 | 2017-05-11 | Road traffic warning situation prediction method |
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| Publication Number | Publication Date |
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| CN107103755A true CN107103755A (en) | 2017-08-29 |
| CN107103755B CN107103755B (en) | 2019-12-20 |
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| CN201710329234.4A Active CN107103755B (en) | 2017-05-11 | 2017-05-11 | Road traffic warning situation prediction method |
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|---|---|---|---|---|
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-
2017
- 2017-05-11 CN CN201710329234.4A patent/CN107103755B/en active Active
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|---|---|---|---|---|
| WO2004027356A3 (en) * | 2002-09-17 | 2005-05-12 | Inductive Signature Tech Inc | Vehicle speed estimation using inductive vehicle detection systems |
| US9076332B2 (en) * | 2006-10-19 | 2015-07-07 | Makor Issues And Rights Ltd. | Multi-objective optimization for real time traffic light control and navigation systems for urban saturated networks |
| CN101188064A (en) * | 2007-12-20 | 2008-05-28 | 北京交通大学 | 3D integrated freeway traffic event automatic detection method |
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| CN101587644A (en) * | 2009-06-02 | 2009-11-25 | 同济大学 | Automatic detection method for traffic accident on urban expressway based on non-continuous sliding sequence |
| CN101807345A (en) * | 2010-03-26 | 2010-08-18 | 重庆大学 | Traffic jam judging method based on video detection technology |
| CN104769655A (en) * | 2012-11-08 | 2015-07-08 | 丰田自动车株式会社 | Driving assistance device and driving assistance method |
| CN104992557A (en) * | 2015-05-13 | 2015-10-21 | 浙江银江研究院有限公司 | Method for predicting grades of urban traffic conditions |
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