CN102024323A - Method for extracting vehicle queue length based on floating vehicle data - Google Patents
Method for extracting vehicle queue length based on floating vehicle data Download PDFInfo
- Publication number
- CN102024323A CN102024323A CN 200910092506 CN200910092506A CN102024323A CN 102024323 A CN102024323 A CN 102024323A CN 200910092506 CN200910092506 CN 200910092506 CN 200910092506 A CN200910092506 A CN 200910092506A CN 102024323 A CN102024323 A CN 102024323A
- Authority
- CN
- China
- Prior art keywords
- floating car
- halt
- crossing
- floating
- highway section
- 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.)
- Granted
Links
Images
Abstract
The present invention relates to a method for extracting vehicle queue length based on floating vehicle data, which comprises the following steps: step 1, establishing a stop point floating vehicle record subdatabase; step 2, calculating the projection distance of the stop point floating vehicle; step 3, filtering the road where the stop point floating vehicle stays with the maximum allowable value of the projection distance; step 4, secondarily determining the road where the stop point floating vehicle stays in a check-back manner; step 5, calculating the distance from each stop point floating vehicle to the crossing; step 6, sorting the queuing position of the stop point floating vehicle; step 7, setting a reference length threshold value; step 8, carrying out a primary statisticsfor the number of the stop point floating vehicles; step 9, obtaining the maximum sum; step 10, carrying out a secondary statistics for the stop point floating vehicle; step 11, determining the queue length. The method can estimate the queue length of the vehicles in the crossing on the road by employing the floating vehicle data, thereby avoiding the shortage in the prior art which use video detecting devices and on-site actual measurement data.
Description
Technical field
The invention belongs to intelligent transportation road real-time information processing technology field, particularly a kind of method of utilizing floating car data to obtain transport information.Specifically, be a kind of method of utilizing floating car data to extract the queue length of crossing, highway section.
Background technology
Floating Car also claims the GPS probe vehicles, is one of the advanced technology means of section traffic information of obtaining that adopted in the international in recent years intelligent transportation system (ITS), has the advantages that to use convenience, economy, wide coverage.
Floating Car is by vehicle GPS (Global Position System, GPS) equipment is installed, and the vehicle that freely travels on actual highway section constitutes, and present most of Floating Car is that the taxi that GPS equipment is housed by normal operation constitutes.Floating Car returns data by radio communication to the backstage according to certain cycle, and data comprise vehicle GPS device numbering, vehicle GPS position coordinates, instantaneous velocity, position angle (travel direction angle), passback time etc.
The background computer processing enter gathers floating car data, through specific model and algorithm process, the transport information that generates the real-time highway section of reflection situation is as road-section average speed, journey time, congestion status etc., for vehicle supervision department with the public provides dynamically, traffic control accurately, induction information.
In intelligent traffic control system, the vehicle queue length of each crossing, highway section is one of traffic parameter of most critical in the road network, can provide very important information for traffic signals control and management.The method of detection crossing vehicle queue length commonly used has two kinds at present:
First kind is the vehicle queue length that video detection technology is measured the crossing, i.e. the video sequence of the vehicle queue that obtains by fixing camera, and comprehensive utilization vehicle detection and motion detection are calculated vehicle queue length.It need be at crossing installation and measuring equipment, and the video flow detection queue length is subjected to the influence of factors such as weather, illumination, camera shake easily in addition.
Second kind is by setting up the queue length and the relational model of signal lamp timing, vehicle arrival rate and the volume of traffic based on statistics, a large amount of measured datas of its needs, and the model transplantability is poor.
In the prior art, also do not utilize floating car data to detect the method for crossing vehicle queue.This is to extract and determination methods in default of effectively utilizing floating car data to carry out crossing queuing vehicle point.
In the data that Floating Car is passed back, can be divided into two big classes, one class is the transfer point floating car data, just Floating Car is in transport condition, instantaneous velocity is not the gps data of passback in 0 o'clock, another kind of is the halt floating car data, and just Floating Car is in halted state, and instantaneous velocity is the gps data of passback in 0 o'clock.
Deposit all floating vehicle data record that comprise transfer point, halt in the Floating Car information database at the background computer center of vehicle supervision department, wherein all transfer point floating car datas have been finished the coupling in highway section by the map-matching method of routine.
Conventional map-matching method is to carry out map match by the method for projector distance and vehicle heading and highway section direction vector difference weighting, judges the highway section of vehicle '.This method need use the position angle of vehicle heading as major parameter, when the instantaneous velocity of Floating Car is not 0, the GPS position angle of its passback is accurately, can carry out map match with the method for routine, when the instantaneous velocity of Floating Car is 0, the GPS position angle of its passback is inaccurate, can not carry out map match with the method for routine.
If want with the floating car data length calculation of ranking, can only use the halt floating car data, and can not use the transfer point floating car data, because be in halted state during vehicle queue, halt floating car data and vehicle queue state have certain getting in touch near the crossing, also are related with the highway section, how to utilize these contacts, judge highway section, halt Floating Car place, and to estimate queue length be the problem to be solved in the present invention.
Summary of the invention
The objective of the invention is to propose a kind of method based on floating car data extraction vehicle queue length, the floating car data that passes through was waited in ordinary queue before this method at first extracted the crossing, highway section by the highway section matching technique; Then the Floating Car halt is added up apart from the position distribution variation of crossing, estimated queue length.This method need not installation and measuring equipment and manually carries out a large amount of field measurements, can save lot of manpower and material resources.
For achieving the above object, the present invention is by the following technical solutions:
A kind of method based on floating car data extraction vehicle queue length may further comprise the steps:
From the Floating Car information total data storehouse of background computer processing enter, take out halt Floating Car record, every halt floating vehicle data record comprises GPS device numbering and passback time, GPS position coordinates, instantaneous velocity, position angle, each bar record is arranged by the time sequencing of passback, left in the halt Floating Car recording sub-data storehouse;
The projector distance of step 2, calculating halt Floating Car:
The projector distance of each halt Floating Car of data computation in the halt Floating Car recording sub-data storehouse that obtains with step 1, projector distance be the GPS position coordinates of each halt Floating Car to the air line distance between the highway section, leave in the Floating Car projector distance subdata base calculating good projector distance;
Projector distance and maximum permissible value in the Floating Car projector distance subdata base that step 2 is obtained compare, get the halt Floating Car record of all projector distances, leave it in Floating Car projector distance and satisfy in the subdata base that imposes a condition less than maximum permissible value;
The GPS device numbering that transfer point Floating Car in the subdata base is mated in original transfer point Floating Car highway section in the GPS device numbering that the Floating Car projector distance that step 3 is obtained satisfies halt Floating Car in the subdata base that imposes a condition and the Floating Car information total data storehouse compares, can in the coupling subdata base of transfer point Floating Car highway section, find identical transfer point Floating Car GPS device numbering if be recorded in the GPS device numbering of the halt Floating Car in the satisfied subdata base that imposes a condition of Floating Car projector distance, then the match is successful, just judge that this halt Floating Car belongs to this highway section, all halt floating car datas that the match is successful are put into halt Floating Car secondary highway section coupling subdata base;
From the Floating Car secondary highway section coupling subdata base that step 4 obtains, take out each halt Floating Car GPS position coordinates, according to the distance between beeline and dot formula, calculate the air line distance of each halt Floating Car to the crossing, highway section, with the distance that obtains after calculating leave in Floating Car to the crossing apart from the subdata base;
The Floating Car that step 5 is obtained writes down by arranging to crossing distance order from small to large apart from each bar Floating Car in the subdata base to the crossing, and the Floating Car record that will sort good then is placed on Floating Car in the queue subdata base of crossing;
Set a reference length threshold values, this reference length threshold values is to judge recommended value by the best that the relation between the queuing traffic density distributes in more a plurality of actual measurement queue length data and the Floating Car unit length obtains;
Interval with the reference length threshold values in the step 7 for once measuring, the quantity of the Floating Car of the Floating Car that step 6 is obtained in the queue subdata base of crossing is added up, counting the quantity that each once measures the Floating Car in the interval, is zero up to continuous two quantity of once measuring Floating Car in the interval occurring; Statistics is put into statistics table of queuing vehicle;
Find out Floating Car quantity maximum that step 8 obtains and time big two once tolerance is interval, to these two Floating Car quantity of once measuring in the interval carry out addition ask maximum and;
Twice with the reference length threshold values in the step 7 is interval as secondary tolerance, once to measure interval size is the interval, the quantity of the Floating Car of the Floating Car that step 6 is obtained in the queue subdata base of crossing is added up, count the quantity of the Floating Car in each secondary tolerance interval successively, statistics is put into queuing vehicle secondary statistics table;
Floating car data is made up of transfer point data and halt data two parts, quite a few is arranged again in the halt data is that vehicle produces when waiting in line signal lamp in the crossing, these halts concentrate near the crossing, highway section, and the position is the ascending arrangement of distance along the highway section far from the crossing.Arrangement has certain rules to the halt that causes owing to the waiting signal lamp in the interval, has stronger correlativity with vehicle queue length actual in the unit interval section, be the data form of expression of queuing vehicle, so let us can utilize these halt data computation vehicle queue lengths.
This method at first matches the halt floating car data on the highway section, extracts queuing vehicle point; Be starting point then with the crossing, according to crossing distance near to series arrangement far away.The Density Distribution of the interior vehicle point of lining up of unit length on the segmentation statistics highway section is set Rule of judgment and is determined queuing tail of the queue position, derives the maximum queue length of section interior crossing sometime.The present invention has avoided using in the conventional method deficiency of video detecting device and field measurement data, saves human and material resources and time.
The highway section coupling is carried out at twice, when mating for the first time, belongs to the halt in highway section with the deviation range preliminary judgement, filtration abends a little, secondary when coupling, the transfer point that the match is successful on halt and the same highway section is compared, adopt back the mode of looking into to verify the halt data.
The queue length principle of calculating is: the Density Distribution to queuing vehicle in the time period is added up, and sets best decision threshold condition, calculates the queue length of vehicle.
The present invention utilizes floating car data to carry out crossing queuing vehicle point and extracts and judgement, can estimate the length of crossing vehicle queue.This method does not need the outside to build equipment and facility, utilizes floating car data can easily finish estimation to all crossing vehicle queue lengths in the road network fast.
Description of drawings
Fig. 1 is a theory diagram of the present invention.
Fig. 2 is to be the distribution situation synoptic diagram of Floating Car in 20 minutes in a crossing.
Fig. 3 is halt Floating Car recording sub-data storehouse.
Fig. 4 is a Floating Car projector distance subdata base.
Fig. 5 is that the Floating Car projector distance satisfies the database that bears fruit that imposes a condition.
Fig. 6 is a transfer point Floating Car highway section coupling subdata base.
Fig. 7 is a Floating Car secondary highway section coupling subdata base.
Fig. 8 be Floating Car to the crossing apart from subdata base.
Fig. 9 is that Floating Car is to crossing queue subdata base.
Figure 10 is statistics table of queuing vehicle.
Figure 11 is a queuing vehicle secondary statistics table.
Figure 12 is statistical distribution curve map of queuing vehicle.
Embodiment
The present invention is a kind of method based on floating car data extraction vehicle queue length, comprises 11 steps, and flow process as shown in Figure 1.Each step of this method all is by computer runs programs, and data are handled realization, has practical value.Describe its principle below in detail:
Please refer to Fig. 2, Fig. 2 represents near the crossing, a highway section distribution situation of Floating Car in 20 minutes, and this crossing is made up of highway section 1, highway section 2, highway section 3, and the black ringlet is represented the halt of Floating Car.
In the present embodiment, have 43 Floating Car halts.The GPS device numbering of the Floating Car of these halt correspondences is respectively: 5097,6694,3313,2469,2006,4752,9284,7262,7826,5861,7710,8112,3571,9828,7716,5384,4115,3319,1915,7351,1960,3483,4901,7364,7878,6816,7649,1248,4323,1207,4323,1248,7383,8426,5856,7066,6847,2132,4253,2840,2093,528,5395.
Each step of following process in detail:
From the Floating Car information total data storehouse of background computer processing enter, take out halt Floating Car record, every halt floating vehicle data record comprises GPS device numbering and passback time, GPS position coordinates (GPS latitude and longitude coordinates), instantaneous velocity, position angle, each bar record is arranged by the time sequencing of passback, left in " halt Floating Car recording sub-data storehouse " as shown in Figure 3.
Please refer to Fig. 3, as can be seen from Figure 3: 43 halt Floating Car among Fig. 2 have returned data, these records are stored in the Floating Car information total data storehouse of background computer processing enter, and every halt floating vehicle data record comprises GPS device numbering, GPS position coordinates (GPS longitude and latitude), instantaneous velocity, position angle and passback time.
Wherein the GPS device numbering is that 1248 Floating Car has returned two secondary data: the passback time is respectively { 9:49:42} and { 9:51:19}.
Wherein the GPS device numbering is that 4323 Floating Car has also returned two secondary data: the passback time is respectively { 9:51:05} and { 9:51:16}.
Remaining halt Floating Car has all only returned a secondary data.
What deserves to be mentioned is: in Floating Car information total data storehouse, also deposit the record of transfer point Floating Car, because its deflection is non-vanishing, so gone up by conventional map-matching method and highway section coupling.
The record of these transfer point Floating Car all leaves in " transfer point Floating Car highway section coupling subdata base " as shown in Figure 6.The transfer point floating car data comprises vehicle GPS (GPS) device numbering, vehicle GPS position coordinates, instantaneous velocity, position angle, passback time, highway section, place etc.
Conventional map-matching method is to carry out map match by the method for projector distance and vehicle heading and highway section direction vector difference weighting, judges the highway section of vehicle '.
The projector distance of step 2, calculating halt Floating Car:
The projector distance of each halt Floating Car of data computation in " the halt Floating Car recording sub-data storehouse " that obtains with step 1, projector distance be the GPS position coordinates (longitude and latitude coordinate) of each halt Floating Car to the highway section 1 air line distance, leave in " Floating Car projector distance subdata base " shown in Figure 4 calculating good projector distance;
Because the starting point and the terminal point coordinate in highway section 1 are known, halt Floating Car GPS position coordinates also is known, according to the distance between beeline and dot formula, just can calculate the halt Floating Car to the highway section 1 projector distance.Please refer to Fig. 2, Fig. 4, is example with the Floating Car that is numbered 7649{9:49:13}: 9:49:13} this constantly, its GPS position coordinates is to the distance R in highway section 1
1=7 meters.
Projector distance and maximum permissible value in " the Floating Car projector distance subdata base " that step 2 is obtained compare, get the halt Floating Car record of all projector distances, it is left in " the Floating Car projector distance satisfies the subdata base that imposes a condition " less than maximum permissible value.
In the present embodiment, the maximum permissible value of projector distance is 20 meters, and as can be seen from Figure 4, the GPS device numbering is 2006,4752,9284,7262 a halt Floating Car record because greater than 20 meters, and deleted.There is not deleted halt Floating Car record to put into " the Floating Car projector distance satisfies the database that bears fruit that imposes a condition " as shown in Figure 5 all the other.
As can be seen from Figure 2, the GPS device numbering is that 2006,4752,9284,7262 halt Floating Car is actually and is in highway section 2.
The effect that step 3 is set is the floating car data deletion that possible be on other highway section.
In " Floating Car projector distance satisfy impose a condition subdata base " (as shown in Figure 5) that step 3 is obtained in the GPS device numbering of halt Floating Car and the Floating Car information total data storehouse GPS device numbering of original " transfer point Floating Car highway section coupling subdata base " (as shown in Figure 6) middle transfer point Floating Car compare, can in " transfer point Floating Car highway section coupling subdata base ", find identical transfer point Floating Car GPS device numbering if be recorded in the GPS device numbering of the halt Floating Car in " the Floating Car projector distance satisfies the subdata base that imposes a condition ", then the match is successful, this illustrates that this halt Floating Car belongs to highway section 1, because before this, this Floating Car is in mobile status just on highway section 1.
All are looked into the halt floating car data that the match is successful through returning, put into " Floating Car secondary highway section coupling subdata base " as shown in Figure 7.
That is to say, transfer point Floating Car record among halt Floating Car record and Fig. 6 among Fig. 5 is compared, if can in Fig. 6, find out with Fig. 5 in identical GPS device numbering, illustrate that these halt Floating Car belong to highway section 1, because before this, this Floating Car is in mobile status just on highway section 1.
By relatively, the GPS device numbering is that 6694,9828,4323,8426 halt Floating Car record does not find device numbering separately in Fig. 6, thus do not belong to highway section 1, and deleted.
From " Floating Car secondary highway section coupling subdata base " that step 4 obtains, take out each halt Floating Car GPS position coordinates (GPS longitude and latitude), according to the distance between beeline and dot formula, calculate the air line distance of each halt Floating Car, the distance that obtains after calculating is left in shown in Figure 8 " Floating Car to the crossing apart from subdata base " to the crossing, highway section.
Because the terminal point coordinate in highway section 1 is known, be that the position, crossing in highway section 1 and highway section 3 is known among Fig. 2, halt Floating Car GPS position coordinates also is known, according to the distance between beeline and dot formula, just can calculate the projector distance of halt Floating Car 1 terminal point to the highway section, this distance is exactly the air line distance of halt Floating Car to the crossing, highway section
Please refer to Fig. 2 and Fig. 8, is that 7649 Floating Car is an example with the GPS device numbering: 9:49:13} this constantly, its GPS position coordinates is to the air line distance L of crossing (highway section 3)
1=112 meters.
Each bar Floating Car record in " Floating Car to the crossing apart from subdata base " (as shown in Figure 8) that obtains in the step 5 is arranged by distance crossing distance order from small to large, and the good Floating Car that will sort then writes down and is placed in " Floating Car is to crossing queue subdata base " as shown in Figure 9.
Set a reference length threshold values, this reference length threshold values is to judge recommended value by the best that the relation between the queuing traffic density distributes in more a plurality of actual measurement queue length data and the Floating Car unit length obtains; In the present embodiment, the reference length threshold values is got 10 meters.
Interval with 10 meters of the reference length threshold values in the step 7 for once measuring, quantity to the Floating Car in " Floating Car is to crossing queue subdata base " shown in Figure 9 is added up, counting the quantity that each once measures the Floating Car in the interval, is zero up to continuous two quantity of once measuring Floating Car in the interval occurring.Promptly add up the traffic density in 10 meters apart from every interval, crossing, the result of traffic density statistics puts into " statistics table of queuing vehicle " as shown in figure 10.First vehicle number of once measuring interval (0-10 rice) is 0 among the figure, this is not from intersection because of vehicle queue, and actual be that preceding crossing stop line is sentenced and guaranteed the other direction vehicle pass-through in the crossing, there is certain distance this position far from the crossing, so intersection does not have vehicle between the stop line during vehicle queue.
Also can represent vehicle queue density with distribution plan, distribution plan as shown in figure 12, with distance crossing distance is horizontal ordinate, vehicle number is an ordinate, with 10 meters is that incremental change is added up the vehicle number in per 10 meters, can obtain distribution curve shown in Figure 12, we notice traffic density distribute along with vehicle queue near tail of the queue, the density of vehicle is reducing gradually, up to approaching 0 in the unit length.Therefore the present invention takes the method judgement queue length that the unit length density degree is judged.
Find out Floating Car quantity maximum in " statistics table of queuing vehicle " that step 8 obtains and time big two once tolerance is interval, to these two Floating Car quantity of once measuring in the interval carry out addition ask maximum and.
As can be seen from Figure 10, once the interval interior maximum vehicle number of tolerance is 5, and inferior big vehicle number is 4, and both sums are 5+4=9.
That is to say: interval as secondary tolerance with 20 meters, with 10 meters sizes serves as at interval the quantity of " Floating Car is to crossing queue subdata base " Floating Car in (as shown in Figure 9) to be added up, count the quantity of the Floating Car in each 20 meters successively, statistics is put into " queuing vehicle secondary statistics table " as shown in figure 11.
The maximum and 9 that obtains with step 9, each data with secondary shown in Figure 11 tolerance in interval relatively, vehicle number is 1 in the 80-100 rice, maximum and 9 1/4 greater than 1, can determine maximum queue length thus between 80-100 rice, promptly 90 meters is maximum queue length.
Claims (1)
1. one kind is extracted the method for vehicle queue length based on floating car data, may further comprise the steps:
Step 1, set up halt Floating Car recording sub-data storehouse:
From the Floating Car information total data storehouse of background computer processing enter, take out halt Floating Car record, every halt floating vehicle data record comprises GPS device numbering and passback time, GPS position coordinates, instantaneous velocity, position angle, each bar record is arranged by the time sequencing of passback, left in the halt Floating Car recording sub-data storehouse;
The projector distance of step 2, calculating halt Floating Car:
The projector distance of each halt Floating Car of data computation in the halt Floating Car recording sub-data storehouse that obtains with step 1, projector distance be the GPS position coordinates of each halt Floating Car to the air line distance between the highway section, leave in the Floating Car projector distance subdata base calculating good projector distance;
Step 3, usefulness projector distance maximum permissible value filter highway section, halt Floating Car place:
Projector distance and maximum permissible value in the Floating Car projector distance subdata base that step 2 is obtained compare, get the halt Floating Car record of all projector distances, leave it in Floating Car projector distance and satisfy in the subdata base that imposes a condition less than maximum permissible value;
Step 4, judge highway section, halt Floating Car place by returning the mode secondary look into:
The GPS device numbering that transfer point Floating Car in the subdata base is mated in original transfer point Floating Car highway section in the GPS device numbering that the Floating Car projector distance that step 3 is obtained satisfies halt Floating Car in the subdata base that imposes a condition and the Floating Car information total data storehouse compares, can in the coupling subdata base of transfer point Floating Car highway section, find identical transfer point Floating Car GPS device numbering if be recorded in the GPS device numbering of the halt Floating Car in the satisfied subdata base that imposes a condition of Floating Car projector distance, then the match is successful, just judge that this halt Floating Car belongs to this highway section, all halt floating car datas that the match is successful are put into halt Floating Car secondary highway section coupling subdata base;
Step 5, calculate the distance of each halt Floating Car to the crossing:
From the Floating Car secondary highway section coupling subdata base that step 4 obtains, take out each halt Floating Car GPS position coordinates, according to the distance between beeline and dot formula, calculate the air line distance of each halt Floating Car to the crossing, highway section, with the distance that obtains after calculating leave in Floating Car to the crossing apart from the subdata base;
Step 6, sorted in the queuing position of halt Floating Car:
The Floating Car that step 5 is obtained writes down by arranging to crossing distance order from small to large apart from each bar Floating Car in the subdata base to the crossing, and the Floating Car record that will sort good then is placed on Floating Car in the queue subdata base of crossing;
Step 7, setting reference length threshold values:
Set a reference length threshold values, this reference length threshold values is to judge recommended value by the best that the relation between the queuing traffic density distributes in more a plurality of actual measurement queue length data and the Floating Car unit length obtains;
Step 8, the quantity of halt Floating Car is once added up:
Interval with the reference length threshold values in the step 7 for once measuring, the quantity of the Floating Car of the Floating Car that step 6 is obtained in the queue subdata base of crossing is added up, counting the quantity that each once measures the Floating Car in the interval, is zero up to continuous two quantity of once measuring Floating Car in the interval occurring; Statistics is put into statistics table of queuing vehicle;
Step 9, ask maximum and:
Find out Floating Car quantity maximum that step 8 obtains and time big two once tolerance is interval, to these two Floating Car quantity of once measuring in the interval carry out addition ask maximum and;
Step 10, the quantity of halt Floating Car is carried out secondary statistics:
Twice with the reference length threshold values in the step 7 is interval as secondary tolerance, once to measure interval size is the interval, the quantity of the Floating Car of the Floating Car that step 6 is obtained in the queue subdata base of crossing is added up, count the quantity of the Floating Car in each secondary tolerance interval successively, statistics is put into queuing vehicle secondary statistics table;
Step 11, determine queue length: the interval Floating Car quantity of each secondary tolerance in the queuing vehicle secondary statistics table that obtains with obtain maximum of step 9 with step 10 relatively, up to occur for the first time secondary tolerance interval in Floating Car quantity less than maximum and 1/4, the intermediate value of then getting this secondary tolerance interval is the queue length value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200910092506 CN102024323B (en) | 2009-09-16 | 2009-09-16 | Method for extracting vehicle queue length based on floating vehicle data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200910092506 CN102024323B (en) | 2009-09-16 | 2009-09-16 | Method for extracting vehicle queue length based on floating vehicle data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102024323A true CN102024323A (en) | 2011-04-20 |
| CN102024323B CN102024323B (en) | 2012-12-26 |
Family
ID=43865575
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 200910092506 Active CN102024323B (en) | 2009-09-16 | 2009-09-16 | Method for extracting vehicle queue length based on floating vehicle data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102024323B (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102324186A (en) * | 2011-09-13 | 2012-01-18 | 大连海事大学 | Method for calculating time for vehicle to pass through signal lamp intersection |
| CN102855760A (en) * | 2012-09-27 | 2013-01-02 | 中山大学 | On-line queuing length detection method based on floating vehicle data |
| CN106056908A (en) * | 2016-06-28 | 2016-10-26 | 联想(北京)有限公司 | Information processing method and server |
| CN106097730A (en) * | 2016-08-10 | 2016-11-09 | 青岛海信网络科技股份有限公司 | The method of estimation of a kind of section vehicle queue length, Apparatus and system |
| CN106448136A (en) * | 2016-05-26 | 2017-02-22 | 中国铝业股份有限公司 | Mine car transportation counting method |
| CN107305739A (en) * | 2016-04-22 | 2017-10-31 | 沃尔沃汽车公司 | Apparatus and method for providing the adaptation to queue length for traffic lights assistance application |
| CN108922193A (en) * | 2018-08-03 | 2018-11-30 | 北京航空航天大学 | A kind of intersection signal phase estimate method based on Floating Car track data |
| CN109243177A (en) * | 2018-10-11 | 2019-01-18 | 招商局重庆交通科研设计院有限公司 | Road traffic wide area abductive approach |
| CN109785645A (en) * | 2019-03-04 | 2019-05-21 | 南京信息职业技术学院 | A kind of algorithm adjusting traffic lights duration according to vehicle flowrate dynamic |
| CN110782690A (en) * | 2019-09-23 | 2020-02-11 | 重庆交通大学 | Estimation method for secondary stopping rate of road signalized intersection |
| CN111091714A (en) * | 2020-01-10 | 2020-05-01 | 长沙理工大学 | Traffic light signal control scheme based on vehicle-road cooperation |
| CN111131384A (en) * | 2019-11-18 | 2020-05-08 | 腾讯科技（深圳）有限公司 | Position sorting method and device |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0669034B1 (en) * | 1992-11-10 | 1997-01-15 | Siemens Aktiengesellschaft | Process for detecting and eliminating the shadow of moving objects in a sequence of digital images |
| CN101270997B (en) * | 2007-03-21 | 2010-07-28 | 北京交通发展研究中心 | Floating car dynamic real-time traffic information processing method based on GPS data |
-
2009
- 2009-09-16 CN CN 200910092506 patent/CN102024323B/en active Active
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102324186B (en) * | 2011-09-13 | 2013-05-22 | 大连海事大学 | Method for calculating time for vehicle to pass through signal lamp intersection |
| CN102324186A (en) * | 2011-09-13 | 2012-01-18 | 大连海事大学 | Method for calculating time for vehicle to pass through signal lamp intersection |
| CN102855760A (en) * | 2012-09-27 | 2013-01-02 | 中山大学 | On-line queuing length detection method based on floating vehicle data |
| CN102855760B (en) * | 2012-09-27 | 2014-08-20 | 中山大学 | On-line queuing length detection method based on floating vehicle data |
| US11055995B2 (en) | 2016-04-22 | 2021-07-06 | Volvo Car Corporation | Arrangement and method for providing adaptation to queue length for traffic light assist-applications |
| CN107305739A (en) * | 2016-04-22 | 2017-10-31 | 沃尔沃汽车公司 | Apparatus and method for providing the adaptation to queue length for traffic lights assistance application |
| CN106448136A (en) * | 2016-05-26 | 2017-02-22 | 中国铝业股份有限公司 | Mine car transportation counting method |
| CN106056908A (en) * | 2016-06-28 | 2016-10-26 | 联想(北京)有限公司 | Information processing method and server |
| CN106097730A (en) * | 2016-08-10 | 2016-11-09 | 青岛海信网络科技股份有限公司 | The method of estimation of a kind of section vehicle queue length, Apparatus and system |
| CN108922193A (en) * | 2018-08-03 | 2018-11-30 | 北京航空航天大学 | A kind of intersection signal phase estimate method based on Floating Car track data |
| CN108922193B (en) * | 2018-08-03 | 2019-06-04 | 北京航空航天大学 | A kind of intersection signal phase estimate method based on Floating Car track data |
| CN109243177A (en) * | 2018-10-11 | 2019-01-18 | 招商局重庆交通科研设计院有限公司 | Road traffic wide area abductive approach |
| CN109785645A (en) * | 2019-03-04 | 2019-05-21 | 南京信息职业技术学院 | A kind of algorithm adjusting traffic lights duration according to vehicle flowrate dynamic |
| CN110782690A (en) * | 2019-09-23 | 2020-02-11 | 重庆交通大学 | Estimation method for secondary stopping rate of road signalized intersection |
| CN111131384A (en) * | 2019-11-18 | 2020-05-08 | 腾讯科技（深圳）有限公司 | Position sorting method and device |
| CN111091714A (en) * | 2020-01-10 | 2020-05-01 | 长沙理工大学 | Traffic light signal control scheme based on vehicle-road cooperation |
| CN111091714B (en) * | 2020-01-10 | 2021-06-22 | 长沙理工大学 | Traffic light signal control method based on vehicle-road cooperation |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102024323B (en) | 2012-12-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102024323B (en) | Method for extracting vehicle queue length based on floating vehicle data | |
| CN109272756B (en) | Method for estimating queuing length of signal control intersection | |
| CN103985250B (en) | The holographic road traffic state vision inspection apparatus of lightweight | |
| CN102855760B (en) | On-line queuing length detection method based on floating vehicle data | |
| CN103886756B (en) | Based on the freeway network method for detecting operation state of OBU | |
| Fang et al. | FTPG: A fine-grained traffic prediction method with graph attention network using big trace data | |
| CN103456172B (en) | A kind of traffic parameter measuring method based on video | |
| WO2018122803A1 (en) | Smart road traffic anomaly detection method | |
| CN102968900B (en) | Method for processing RFID (Radio Frequency Identification) traffic data | |
| CN105206057B (en) | Detection method and system based on Floating Car resident trip hot spot region | |
| CN110176139A (en) | A kind of congestion in road identification method for visualizing based on DBSCAN+ | |
| CN103794061B (en) | The method that road merges travel speed is calculated based on multiple location data | |
| CN105825669A (en) | System and method for identifying urban expressway traffic bottlenecks | |
| CN102521973A (en) | Road matching method for mobile phone switching positioning | |
| CN101777259A (en) | Method for acquiring mean delay of urban road junction | |
| CN105513362B (en) | A kind of bus platform adjacent area bus running state evaluation verification method | |
| Xing et al. | Traffic volume estimation in multimodal urban networks using cell phone location data | |
| CN109147323A (en) | A kind of vehicle GPS data processing method for highway passenger and freight transportation indicator-specific statistics | |
| CN101131796A (en) | Road traffic parameter checking device and method thereof | |
| CN103050014A (en) | Traffic speed detection system and detection method | |
| CN109121094A (en) | The pretreatment of pseudo-code signaling data and Trip chain recognition methods | |
| CN100446015C (en) | Method and system in use for menstruating traffic movement on ground road network | |
| CN110070720A (en) | Improve the calculation method of intersection road occupying construction section capacity model-fitting degree | |
| CN110610118A (en) | Traffic parameter acquisition method and device | |
| CN105046952A (en) | Sparse road traffic incident air ground combination detection method |
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 |