CN205247622U - Vehicle length monitoring system that lines up - Google Patents
Vehicle length monitoring system that lines up Download PDFInfo
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- CN205247622U CN205247622U CN201521090573.4U CN201521090573U CN205247622U CN 205247622 U CN205247622 U CN 205247622U CN 201521090573 U CN201521090573 U CN 201521090573U CN 205247622 U CN205247622 U CN 205247622U
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- vehicle
- ground magnetic
- earth magnetism
- data
- queue length
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Abstract
The utility model provides a vehicle length monitoring system that lines up, including consecutive ground magnetic cell, data acquisition unit, data communication unit and data processing unit, the ground magnetic cell contains a plurality of ground magnetic unit, and the ground magnetic unit uses charge station's floodgate machine be the initial point, lines up one section distance at wait each interval of orientation along the vehicle and buries underground on arriving corresponding runway, the ground magnetic cell includes first ground magnetic unit, second ground magnetic unit, third ground magnetic unit and fourth ground magnetic unit, the floodgate machine department in the charge station is buried underground to first ground magnetic unit, second ground magnetic unit is buried underground from 50 meters in the charge station floodgate machine, third ground magnetic unit is buried underground from 125 meters in the charge station floodgate machine, fourth ground magnetic unit is buried underground from 200 meters in the charge station floodgate machine, through inbuilt 4 organizing earth magnetism collection vehicle through geomagnetic speed and holding time in advance, and with these for the data data processing element analysis calculate and to reach the vehicle length of lining up, thereby important reference frame is provided for the traffic management and control.
Description
Technical field
The utility model relates to road traffic control field, is specifically related to a kind of vehicle queue length monitoring system.
Background technology
Along with the sustainable growth of socioeconomic high speed development, population and the raising gradually of living standards of the people, China's vehicle guaranteeding organic quantity is all speed increases that do not have just in the past also, huge vehicles number can't bear the heavy load urban road and means of transportation thereof, and the even large-area traffic congestion in part occurs often. During high speed crossing is the place that vehicle pass-through is comparatively concentrated, especially festivals or holidays, tend to produce jam, this has caused very large puzzlement to people's trip and road traffic control.
Traffic flow detection technique mainly detects road traffic, speed of a motor vehicle detection, pedestrian density at present, transfers to traffic signals central platform, to control and decision-making. Queue length is as the important evaluation index of road passage capability, and the main video image processing mode that adopts detects at present, and adaptive capacity to environment is poor. The utility model judges vehicle queue length by monitoring high speed crossing vehicle by monitoring point speed and holding time, thereby provides important reference frame for traffic control.
Utility model content
The purpose of this utility model aims to provide a kind of monitoring system that can effectively monitor high speed crossing vehicle queue length.
A kind of vehicle queue length monitoring system of the present utility model, comprises successively connected ground magnetic cell, data acquisition unit, data communication units and data processing unit; Described ground magnetic cell comprises multiple earth magnetism groups, and earth magnetism group, taking charge station's gate as starting point, is respectively spaced a distance and is embedded on corresponding runway along vehicle queue wait direction; Described ground magnetic cell comprises the first earth magnetism group, the second earth magnetism group, the 3rd earth magnetism group and the 4th earth magnetism group, described the first earth magnetism group is embedded in gate place of charge station, the second earth magnetism group is embedded in from 50 meters of of charge station's gate, the 3rd earth magnetism group is embedded in from 125 meters of of charge station's gate, and the 4th earth magnetism group is embedded in from 200 meters of of charge station's gate.
Described data acquisition unit gathers on each earth magnetism vehicle Negotiation speed and vehicle holding time data and transfers to data processing unit by data communication units, data processing unit, by the analytical calculation to each ground magnetic vehicle Negotiation speed and vehicle holding time data in nearest a period of time, draws the queue length that vehicle queue is waited for.
Preferably, described data processing unit calculates the data analysis in nearest 5 minutes, draws the queue length that vehicle queue is waited for.
The utility model has the following advantages with respect to prior art:
1, a kind of vehicle queue length monitoring system of the present utility model is simple in structure, pass through speed and the holding time of earth magnetism by 4 groups of earth magnetism collection vehicle burying underground in advance, and these data are drawn to vehicle queue length with data processing unit analytical calculation, thereby provide important reference frame for traffic control.
2, the theoretical method of a kind of vehicle queue length monitoring system of the present utility model institute foundation has passed through actual inspection, queues up effective product is provided for monitor vehicle in road traffic.
Brief description of the drawings
Fig. 1 is the structural representation of utility model.
Detailed description of the invention
Below in conjunction with accompanying drawing, a kind of vehicle queue length monitoring system of the present utility model is described in further detail.
As shown in Figure 1, a kind of vehicle queue length monitoring system of the present utility model, comprises successively connected ground magnetic cell 1, data acquisition unit 2, data communication units 3 and data processing unit 4; Ground magnetic cell 1 comprises multiple earth magnetism groups, earth magnetism group is taking charge station's gate as starting point, respectively be spaced a distance and bury underground on corresponding runway along vehicle queue wait direction, ground magnetic cell 1 comprises the first earth magnetism group 5, the second earth magnetism group 6, the 3rd earth magnetism group 7 and the 4th earth magnetism group 8, the first earth magnetism group 5 is embedded in gate place of charge station, the second earth magnetism group 6 is embedded in from 50 meters of of charge station's gate, the 3rd earth magnetism group 7 is embedded in from 125 meters of of charge station's gate, and the 4th earth magnetism group 8 is embedded in from 200 meters of of charge station's gate.
Data acquisition unit 2 gathers on each earth magnetism vehicle Negotiation speed and vehicle holding time data and transfers to data processing unit 4 by data communication units 3.
Data processing unit 4 is by the analytical calculation to each ground magnetic vehicle Negotiation speed and vehicle holding time data in nearest a period of time, draw the queue length that vehicle queue is waited for, further, data processing unit 4 is that the data analysis in nearest 5 minutes is calculated, and draws the queue length that vehicle queue is waited for.
In practice, after geomagnetic data is analyzed, find that real data exists environment to have noise, abnormal data, thereby proposed the thinking of dealing with problems from the direction of noise reduction; Analyzing the laying situation of terminal device data and bonding apparatus, geomagnetic data is being analyzed and in conjunction with the professional knowledge aspect traffic, find that average speed in the unit interval can reflect the blocking up of road, unimpeded feature, again can be to leaking car, change and the situation such as data exception has good noise reduction, fault-tolerance; Determining after thinking, first analyze Rule Summary from speed history graphs, the computational methods of Negotiation speed derivation queue length are found, and use video verification result method validation result, guarantee the correctness of derivation, finally determine queue length algorithm, utilize the method for data analysis to derive the strong correlation relation that exists between average holding time of earth magnetism and average speed simultaneously, by historical data is analyzed, obtain average holding time and queue length computational methods.
Expressway entrance and exit is embedded with respectively 4 road earth magnetism, lays respectively at gate position (section 1), apart from 50 meters of of gate cross section place (section 2), and 125 meters of (section 3), 200 meters of (section 4).
The master data that can collect by earth magnetism terminal has car to pass through quantity, speed, holding time, length of wagon etc.
Vehicle can produce noise data because of various situations in the process of moving, as:
1, vehicle converts road when through earth magnetism, causes producing many data, causes vehicle to occur exceptional value by data such as quantity, speed, holding times;
2, vehicle travels between two road, causes a car to produce two data, or causes earth magnetism not collect data;
3, there is the situation in branch road in gateway, causes not necessarily passing through section 2 through the vehicle of earth magnetism section 4 or section 3.
Due in data, exist part noise data, undetected, examine data more, in the time calculating, need to choose and have strong correlation relation with queue length (jam situation), there are again good fault-tolerance data and calculate; Here chosen average occupancy speed in average speed and the timing statistics in unit interval as calculating; Because the average holding time has strong correlation relation with speed, algorithm has also been taken into account the method for calculating queue length by the average holding time.
Functional relation between speed and queue length:
There is the relation of strong negative correlation according to the jam situation of speed and earth magnetism section, utilize the queue length between jam situation and the section of speed derivation section.
Computation rule:
Utilize speed to derive the jam situation of each section, be divided into and block up with unimpeded, obtain by the average speed setting threshold in the unit interval, two threshold values: 1, the threshold value of blocking up (f0) (think that section blocks up when average speed during lower than this threshold value, the queue length between this section and a upper section is 50); 2, unimpeded threshold value (f1) (when average speed is during higher than this threshold value, task section is unimpeded, and the queue length between this section and a upper section is 0); When speed is in the time that the threshold value of blocking up is followed between unimpeded threshold value, the account form of queue length is: section spacing is from d*(v-f0)/(f1-f0).
If section 2 is unimpeded, the queue length that utilizes the average speed speedometer in 2 unit interval of section to calculate between section 1 and section 2 is gateway queue length.
If section 2 blocks up, judge that whether section 3 is for blocking up, if section 3 is unimpeded, utilize the average speed in 3 unit interval of section to calculate the queue length between section 2 and section 3, the result obtaining adds 50 meters and is gateway queue length.
If section 3 blocks up, judge that whether section 4 is for blocking up, if section 4 blocks up, queue length is more than 200 meters, if section 4 is unimpeded, utilize the average speed in 4 unit interval of section to calculate the queue length between section 4 and section 3, the result obtaining adds 125 meters and is gateway queue length.
The setting of scalar in computation rule (threshold value):
Analyze thinking: in the time blocking up, last car of translational speed Main Basis of vehicle moves rear vacated distance, this distance has the short feature of distance, therefore, while blocking up, the translational speed of vehicle has the feature of cluster, by can obtain the block up fuzzy value of threshold value of each gateway section to the analysis of the each section average speed of historical data low-value, by the adjustment to this value, can obtain the queue length of realistic rule; In like manner, when unimpeded, also can in a similar fashion historical data analysis be obtained and be adjusted.
The relation of average holding time of earth magnetism section and speed:
By magnetic data is practically added up, computing, form chart to data analysis, obtain affecting the average speed of traffic congestion degree, the average holding time the relationship of the two of vehicle, then by the analysis of average holding time historical data is obtained to the computation rule between average holding time and queue length.
Statistical analysis explanation
1, average speed
Statistical method
A, according to time sequencing, all data are rearranged.
B, the speed that filters out are higher than 120 data.
The average speed of C, statistics 2015-08-02 Long hilllock charge station each section in 5 minutes, in average speed=every 5min by car speed summation/pass through vehicle number.
D, using the time as X-axis, each track average speed is drawn two-dimentional broken line graph as Y-axis, and the average speed relation of each section is analyzed.
Analytical method
The average speed of section 2,3,4 all existed the average speed in special time period to have the feature of low speed, cluster in three days, and the scope of cluster is in 15km/h left and right, this with section above-mentioned while blocking up the speed of a motor vehicle to have the feature of cluster consistent, and the temporal characteristics of these data also meets our Heuristics, therefore can use the block up threshold value of 15km/h as section. In 1-71 moment, section 2,3,4 should be unimpeded state experience, can be using average speed during this period of time as the unimpeded threshold value of section. The unimpeded threshold value that can obtain section 2,3,4 is about respectively 30km/h, 32km/h, 35km/h.
Analysis result
Result meets the gateway charge station feature of blocking up, confirmed simultaneously section block up, when unimpeded, the average speed of each section has the feature of cluster, we can utilize this feature to carry out the reckoning of speed and queue length, and the setting of scalar in prediction equation.
2, the average holding time
Statistical method
A, according to time sequencing, all data are rearranged.
B, average vehicle flow and the vehicle average holding time of statistics in 5 minutes.
Vehicle flowrate summation in vehicle flowrate=every 5min.
Average holding time=vehicle holding time summation/the vehicle flowrate of vehicle (in 5min).
C, two column datas entirety are extracted and carried out independent list, and from small to large new table is arranged according to average speed.
D, taking average speed as X-axis, the average holding time of vehicle is that Y-axis is drawn two-dimentional broken line graph, and the relationship of the two is analyzed.
Analytical method
A, for whole day 24h, 5min is very little data break, and the information of vehicles data in every 5min are done on average, can either keep data characteristics, again can equilibrium criterion error, be conducive to find the related law between different pieces of information by two-dimentional broken line graph.
Vehicle holding time=vehicle occupies the time in track
The mean value of car speed in average speed=unit interval
B, according to road traffic practical operation situation, the vehicle holding time is longer, block up more serious, but the faster road of the speed of a motor vehicle is more unimpeded, the two all can be used to characterize the track degree of blocking up. The two is placed in same reference axis, can obtain being both the rule existing between the factor that affects traffic congestion degree.
Analysis result
The general trend of A, two-dimentional broken line graph middle polyline: along with the growth of the speed of a motor vehicle, the vehicle holding time declines. In the time that the speed of a motor vehicle increases, vehicle congestion degree reduces, and the vehicle holding time reduces, and conforms to actual traffic situation, and the average holding time of average speed and vehicle has strong negative correlation between the two.
B, in actual traffic running, rule of thumb, in the time that wagon flow speed declines, queue length increase, in the time of wagon flow speed rising, queue length reduce, there is negative correlation in the two.
C, average speed and vehicle holding time are strong negative correlation, average speed and vehicle queue length are negative correlation, known by recurrence relation: vehicle holding time and being proportionate property of vehicle queue length,, facing to the rising of vehicle holding time, fleet's queue length is risen.
3, according to average holding time derivation queue length
Statistical method
From aforementioned, can derive queue length by speed, because the average holding time is with the relation that has strong negative correlation between speed, so by the analysis to the average holding time, it is feasible finding and using the algorithm of average holding time derivation queue length, and specific analytical method is as follows:
A, according to time sequencing, all data are rearranged.
B, the vehicle average holding time of statistics in 5 minutes.
Average holding time=vehicle holding time summation/the vehicle flowrate of vehicle (in 5min).
C, two column datas entirety are extracted and carried out independent list, and from small to large new table is arranged according to time sequencing.
D, using the time as X-axis, the average holding time of vehicle is that Y-axis is drawn two-dimentional broken line graph, and the relationship of the two is analyzed.
Result verification
Afternoon on August 6th, 2015, the video of Long hilllock charge station between having taken at 14:20 to 16, video packets has contained the situation of blocking up for twice and occurring, actual queue length has all arrived 200 meters, with queue length on same day curve map relatively after, the time can both well be mated actual conditions with queue length result.
A kind of vehicle queue length monitoring system of the present utility model, reach the requirement of monitor vehicle queue length, and for abnormal, fail to report data and have good fault-tolerance, can reduce to a certain extent earth magnetism and bury cost, construction requirement and later maintenance requirement underground, can ensure stability and the accuracy of queue length data.
The foregoing is only preferred embodiment of the present utility model; not in order to limit the utility model; all any amendments of doing within spirit of the present utility model and principle, be equal to and replace and improvement etc., within all should being included in protection domain of the present utility model.
Claims (5)
1. a vehicle queue length monitoring system, is characterized in that, comprises successively connected ground magnetic cell (1), data acquisition unit (2), data communication units (3) and data processing unit (4); Described ground magnetic cell (1) comprises multiple earth magnetism groups, and described earth magnetism group, taking charge station's gate as starting point, is respectively spaced a distance and buries underground on corresponding runway along vehicle queue wait direction.
2. a kind of vehicle queue length monitoring system as claimed in claim 1, it is characterized in that, described ground magnetic cell (1) comprises the first earth magnetism group (5), the second earth magnetism group (6), the 3rd earth magnetism group (7) and the 4th earth magnetism group (8), described the first earth magnetism group (5) is embedded in gate place of charge station, the second earth magnetism group (6) is embedded in from 50 meters of of charge station's gate, the 3rd earth magnetism group (7) is embedded in from 125 meters of of charge station's gate, and the 4th earth magnetism group (8) is embedded in from 200 meters of of charge station's gate.
3. a kind of vehicle queue length monitoring system as claimed in claim 2, it is characterized in that, described data acquisition unit (2) gathers on each earth magnetism vehicle Negotiation speed and vehicle holding time data and transfers to data processing unit (4) by data communication units (3).
4. a kind of vehicle queue length monitoring system as claimed in claim 3, it is characterized in that, described data processing unit (4), by the analytical calculation to each ground magnetic vehicle Negotiation speed and vehicle holding time data in nearest a period of time, draws the queue length that vehicle queue is waited for.
5. a kind of vehicle queue length monitoring system as claimed in claim 4, is characterized in that, described data processing unit (4) is that the data analysis in nearest 5 minutes is calculated, and draws the queue length that vehicle queue is waited for.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201521090573.4U CN205247622U (en) | 2015-12-24 | 2015-12-24 | Vehicle length monitoring system that lines up |
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| CN201521090573.4U CN205247622U (en) | 2015-12-24 | 2015-12-24 | Vehicle length monitoring system that lines up |
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| CN205247622U true CN205247622U (en) | 2016-05-18 |
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| CN201521090573.4U Expired - Fee Related CN205247622U (en) | 2015-12-24 | 2015-12-24 | Vehicle length monitoring system that lines up |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106355898A (en) * | 2016-11-04 | 2017-01-25 | 南京理工大学 | Method and device for speed measurement based on geomagnetic sensing |
| CN107784835A (en) * | 2016-08-30 | 2018-03-09 | 蓝色信号株式会社 | Traffic behavior model prediction system and its Forecasting Methodology based on traffic data analyzing |
-
2015
- 2015-12-24 CN CN201521090573.4U patent/CN205247622U/en not_active Expired - Fee Related
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107784835A (en) * | 2016-08-30 | 2018-03-09 | 蓝色信号株式会社 | Traffic behavior model prediction system and its Forecasting Methodology based on traffic data analyzing |
| CN107784835B (en) * | 2016-08-30 | 2021-06-25 | 蓝色信号株式会社 | Traffic state mode prediction system based on traffic data analysis and prediction method thereof |
| CN106355898A (en) * | 2016-11-04 | 2017-01-25 | 南京理工大学 | Method and device for speed measurement based on geomagnetic sensing |
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| Date | Code | Title | Description |
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| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20160518 Termination date: 20171224 |
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| CF01 | Termination of patent right due to non-payment of annual fee |