CN104021670A - Method for extracting vehicle queue state information in urban road network based on high-resolution remote-sensing image - Google Patents
Method for extracting vehicle queue state information in urban road network based on high-resolution remote-sensing image Download PDFInfo
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Abstract
Vehicle queue state information is one of basic parameters for urban road traffic analysis. The invention provides a method for extracting vehicle queue state information in an urban road network based on a high-resolution remote-sensing image. The extraction method in the invention comprises the following steps: 1) obtaining planar road and planar vehicle information data in the high-resolution remote-sensing image; 2) extracting center line and edge lines of a planar road and carrying out cutting according to a certain length threshold to form road searching blocks; 3) calculating road vehicle occupation ratio of each road searching block; 4) taking a certain vehicle occupation ratio as a threshold value under the condition of a congestion queue, and screening out the road searching blocks, of which the road vehicle occupation ratio is larger or equal to the threshold value, at this moment, the total length of the plurality of road searching blocks being the length of the congestion vehicle queue in this road section. Specific position is determined by matching the central position of the road searching blocks with an electronic map or combining GPS data.
Description
Technical field
The invention belongs to macro-traffic condition discrimination technical field, be specifically related to traffic remote sensing application and intelligent transport technology.
Background technology
In recent years, Urbanization in China is accelerated, and traffic jam issue is day by day serious.And even grasp how comprehensively, fast that whole urban road network traffic blocks up and traffic bottlenecks distribution node, understand traffic congestion state predicted congestion range of scatter, for vehicle supervision department carries out traffic dispersion and road network Scientific Construction provides scientific data foundation.Vehicle platoon (information comprises position and length) is the important behaviour form that city blocks up, and is one of basic parameter carrying out urban highway traffic analysis.Yet, current traffic above-ground information data obtaining means (video, coil, microwave, radar) mostly is point source microcosmic traffic information, data acquisition intermediate conveyor link is too much, storage physical space is large, data are preserved and difficult treatment, and macroscopical visualization is low, and data cover face is limited, equipment operation maintenance cost is expensive, cannot meet city and even the group of cities road network intelligent transportation demand data of traffic state analysis and macro-plan on a large scale.Along with the continuous lifting of satellite technology and remote sensing image image quality, national high score satellite " No. 3, resource " heaven in 2012, high-resolution remote sensing image enters " popular epoch ".The road vehicle queue differentiation that high score remote sensing data application is carried out under traffic congestion in intelligent transportation field becomes an important and popular research topic.
Patent documents 1(201010220935.2), announce a kind of crossroad camera video image and carried out the detection of car two length, this invention can only be obtained a crossing finite length vehicle platoon situation, cannot obtain from macroscopic view the vehicle platoon information of whole road network.
Patent documents 2(200910092506.9), announced a kind of floating car data and extracted vehicle queue length, but because Floating Car is counted quantitative limitation, also the vehicle platoon information in the whole city road network of Obtaining Accurate comprehensively.
Patent documents 3(201210044347.7), announce a kind of data of Data mining device and carried out the extraction of vehicle platoon, belong to point source monitoring, the I&M of its detecting device all has certain damage to road, and limited by cost factor, cannot obtain obtaining of vehicle platoon information in whole city road network.
Above method all belongs to traffic above-ground acquisition of information means, Shortcomings, and do not belong to same information source with the inventive method.
Technical paper documents 1(Jens Leitloff, Stefan Hinz & UweStilla, etal. Detection of Vehicle Queues in QuickBird Imagery of City[J] Areas PhotogrammetrieFernerkundungGeoinformation, 4/2006,315-325), proposed a kind of by building vehicle platoon feature knowledge storehouse in high score remote sensing image, the information such as applied morphology, gray scale, directly from remote sensing image, extract the method for vehicle platoon information, be also different from method of the present invention.
Summary of the invention
The object of the invention is to overcome the deficiency of vehicle platoon method of discrimination in prior art, has proposed the slide block threshold search method based on high-resolution remote sensing image, extracts vehicle platoon information.
The inventive method comprises the following steps:
(1), application image processes related algorithm, based on remote sensing image, extracts planar road and planar vehicle vector information;
(2), extract planar road axis and sideline, formation search piece road;
A, obtain planar road, find the head and the tail point of planar road: as shown in Figure 1, first obtain the point set P={P that forms planar road boundary
1, P
2... P
m, P
m+1..., P
m+n, comprise altogether the individual point of m+n (n>=m>=2), by point set in the direction of the clock combination of two become vectorial P={P
1, P
2... P
m, P
m+1..., P
m+n, comprise altogether the individual point of m+n (n>=m>=2), by point set, combination of two one-tenth is vectorial in the direction of the clock
be total to m+n vector.Calculate successively its cosine value, as a q:
When q=1, calculate
with
the cosine value of two vectors;
When 1<q<m+n, calculate and take the vector that a q is starting point
with after a q, any put the vector that q-1 is terminal
cosine value, calculate
wherein θ is vector
and vector
angle;
When q=m+n, calculate
with
cosine.
Wherein the minimum corresponding point of cosine value, is road head and the tail point (because the line segment at the two ends, place, gateway on planar road is approximate parallel in image).
B, road axis: as shown in Figure 2, suppose that road puts from beginning to end as a P
1and P
m.Planar road is interrupted at head and the tail point place and form two highway sideline point sets, A={P
1, P
2... P
mand B={P
m+1, P
m+2..., P
m+n.At a P
1place adopts clockwise direction combination point set A, connects successively P
1, P
2... P
mform highway sideline X; Point P
m+1place adopts combination point set B, i.e. P counterclockwise
m+n, P
m+n-1..., P
m+1, P
mform highway sideline Y.Get and form that highway sideline point is concentrated comprises the less concentrated initial point of point of a number, be assumed to be a P
1, difference calculation level P
1with a P
m+n, some P
1with a P
m+n-1middle point coordinate, the like, the mid point that calculates two highway sideline point sets forms point set C={C
1, C
2..., C
n-1, C
n, comprise altogether n point, point set C is in turn connected into line and is center line of road;
C, division road search piece: the center line of road that point set C is formed interrupts by certain length L, and L chooses, and during according to the common urban road congestion of reality, queue minimum length is chosen.Form center line fixed length point set D={D
1, D
2..., D
i-1, D
i, being total to i point, the part of last not enough L is no longer classified; The ratio of definition highway sideline length and center line of road length is scale factor Ф, and two sideline highway sidelines are interrupted by L * Ф respectively, forms respectively two sideline point set X={X
1, X
2..., X
i-1, X
i, Y={Y
1, Y
2..., Y
i-1, Y
i, now adjacent 2 in point set D, X, Y are connected, form and take center line as marginal the right and left road search piece;
D, repetition a, b, c, carry out road search piece to all planar roads in city road network and divide.
(3), calculate vehicle occupation rate in each road search piece.
Road vehicle area ratio/occupancy ratio is defined as: the vehicle area summation in road accounts for the percentage of certain search piece section area.
As represented with zed, can calculate by the mathematic(al) mode of (1) formula:
In formula, Z represents the road vehicle area occupancy in certain search piece road, S
carrepresent the single unit vehicle area in this search road piece, ∑ S
carrepresent the summation of vehicle area in this search piece road, S
roadrepresent the area on certain search piece road.
(4) threshold method detects road queuing message; The path area occupancy of setting under congestion status is threshold value z, if the path area occupancy of described road search piece is more than or equal to threshold value z's, be judged to be the road search piece that comprises the vehicle platoon that blocks up, the total length of now some jam roads search pieces, being is the length of vehicle platoon of blocking up on this section.The position at certain vehicle platoon place on this section is thought in the vehicle platoon that blocks up search Kuai center, in conjunction with electronic chart or GPS, can obtain the area road title at this queue place.
The present invention adopts high score remote sensing image to realize the detection of vehicle platoon, has that broad perspectives is good, visualization is high, surveyed area area is large.Testing result can be traffic administration and planning department science decision provides data supporting accurately.Apply method of the present invention, on year-on-year basis with documents in vehicle congestion queue extracting method, there is computational accuracy.Meanwhile, due to the present invention, adopt iterative search method, build iterative formula and can realize cycle calculations, in computer hardware constantly upgrading and CPU calculation times constantly under lifting, the shorter and shorter advantage of computing velocity is more and more obvious.
Accompanying drawing explanation
Fig. 1 is the planar highway sideline schematic diagram extracting according to remote sensing images, wherein gathers P={P
1, P
2... P
m, P
m+1..., P
m+nto obtain the point set that forms planar highway sideline;
Fig. 2 is the schematic diagram of planar road extraction center line of road, wherein gathers C={C
1, C
2..., C
n-1, C
nit is the point set that forms center line of road;
Fig. 3 forms road search piece schematic diagram, set X={X
1, X
2..., X
i-1, Xi}, Y={Y
1, Y
2..., Y
i-1, Y
i, D={D
1, D
2..., D
i-1, D
iit is both sides road search piece sideline point set;
Fig. 4 differentiates the method flow diagram of vehicle platoon based on high score remote sensing image.
Embodiment
In order to be illustrated more clearly in the technical scheme of the embodiment of the present invention, the invention will be further described by reference to the accompanying drawings:
The outstanding method step of the present invention is as shown in Figure 4:
(1), application image processes related algorithm, based on remote sensing image, extracts planar road and planar vehicle vector information;
(2), extract planar road axis and sideline, formation search piece road;
A, obtain planar road, find the head and the tail point of planar road: as shown in Figure 1, first obtain the point set P={P that forms planar road boundary
1, P
2... P
m, P
m+1..., P
m+n, comprise altogether the individual point of m+n (n>=m>=2), by point set, combination of two one-tenth is vectorial in the direction of the clock
be total to m+n vector.Calculate successively its cosine value, as a q:
When q=1, calculate
with
the cosine value of two vectors;
When 1<q<m+n, calculate and take the vector that a q is starting point
with after a q, any put the vector that q-1 is terminal
cosine value, calculate
wherein θ is vector
and vector
angle;
When q=m+n, calculate
with
cosine.
Wherein the minimum corresponding point of cosine value, is road head and the tail point (because the line segment at the two ends, place, gateway on planar road is approximate parallel in image);
B, road axis: as shown in Figure 2, suppose that road puts from beginning to end as a P
1and P
m.Planar road is interrupted at head and the tail point place and form two highway sideline point sets, A={P
1, P
2... P
mand B={P
m+1, P
m+2..., P
m+n.At a P
1place adopts clockwise direction combination point set A, i.e. P
1, P
2... P
mfor being in turn connected into line segment, form highway sideline X; Point P
m+1place adopts combination point set B, i.e. P counterclockwise
m+n, P
m+n-1..., P
m+1, P
mform highway sideline Y.Get and form that highway sideline point is concentrated comprises the less concentrated initial point of point of a number, be assumed to be a P
1, difference calculation level P
1with a P
m+n, some P
1with a P
m+n-1middle point coordinate, the like, the mid point that calculates two highway sideline point sets forms point set C={C
1, C
2..., C
n-1, C
n, comprise altogether n point, point set C is in turn connected into line and is center line of road;
C, divide road search piece: the center line of road that point set C is formed by distance L=20 meter (rule of thumb and factual survey, choose the shortest queue length L=20 rice, because the general vehicle commander of Chinese car is 5 meters, big bus and public transport are generally at 10 meters, get that modal 3 cars block up or two length that big bus is queued up) interrupt, form center line fixed length point set D={D
1, D
2..., D
i-1, D
i, be total to i point, as pentagram sign in Fig. 3, in last center line of road, the part of curtailment d is no longer classified.The ratio of definition highway sideline length and center line of road length is scale factor Ф, and due to X, Y length difference, therefore two corresponding sideline scale factors are also different, specifically size, is as the criterion with result of calculation.Two sideline highway sidelines are interrupted by L * Ф respectively, form respectively two sideline point set X={X
1, X
2..., X
i-1, X
i, Y={Y
1, Y
2..., Y
i-1, Y
i, now adjacent 2 in point set D, X, Y are connected, form and take center line as marginal the right and left road search piece; As Fig. 3 intermediate cam shape sign, all comprise i point.The point set of formation is in turn connected into line segment, in point set D, X, Y, gets successively respectively 2 combinations, symbiosis becomes 2i-2 section search piece road;
D, repetition a, b, c, until all planar roads all form search piece road;
(3), calculate vehicle occupation rate in each road search piece.
Road vehicle occupation rate is defined as: the vehicle area summation in road accounts for the percentage of certain search piece section area.As represented with zed, can calculate by the mathematic(al) mode of (1) formula:
In formula, Z represents the road vehicle area occupancy in certain search piece road, S
carrepresent the single unit vehicle area in this search road piece, ∑ S
carrepresent the summation of vehicle area in this search piece road, S
roadrepresent the area on certain search piece road.
(4), threshold method detects road queuing message; The path area occupancy of setting under certain quene state is that threshold value z is that 70%(considers spaces of vehicles, article one, road can not all be taken by car head and the tail gapless), be greater than threshold value z's, be judged to be the vehicle platoon search piece that blocks up under this degree, the total length of now some jam roads search pieces, being is the length of vehicle platoon of blocking up on this section.The position at certain vehicle platoon place on this section is thought in the vehicle platoon that blocks up search Kuai center, in conjunction with electronic chart or GPS, can obtain the area road title at this queue place.
Claims (4)
1. one kind is utilized high score remote sensing image to extract the block up method of vehicle platoon information of city road network, it is characterized in that: choosing planar road and the planar vehicle vector data in high-resolution remote sensing image, extracted is input parameter, and then calculate vehicle platoon length, in conjunction with electronic chart or gps data, can obtain vehicle platoon position, at least comprise following steps:
Step 1: extract planar road and planar information of vehicles data in city road network from high score resolution remote sense image;
Step 2: extract planar road axis and sideline, and block by the length threshold of setting, form road search piece;
Step 3: the road vehicle occupation rate of calculating described road search piece;
Step 4: the road vehicle occupation rate of usining under the condition of blocking up is as threshold value, the road vehicle occupation rate calculating in step 3 and described threshold values are made comparisons, filter out the road search piece that is more than or equal to this threshold value, the total length of now some roads search pieces, being is the length of vehicle platoon of blocking up on this section;
Step 5: the center of road being searched for to piece combines with electronic map match or in conjunction with gps data, the vehicle platoon positional information of blocking up in acquisition city road network.
2. a kind of high score remote sensing image that utilizes as claimed in claim 1 extracts the block up method of vehicle platoon information of city road network, it is characterized in that: center line and the sideline of from city road network, extracting planar road, the search of road described in obtaining step two piece, at least comprises following steps:
Step 1: the head and the tail point that obtains planar road: first obtain the point set P={P that forms planar road boundary
1, P
2... P
m, P
m+1..., P
m+n, comprise altogether m+n(n>=m>=2) individual point, by point set, combination of two one-tenth is vectorial in the direction of the clock
,
...,
,
m+n vector, calculates its cosine value successively altogether; Wherein the minimum corresponding point of cosine value, is road head and the tail point;
Step 2: obtain road axis: suppose that road puts from beginning to end as a P
1and P
m, planar road is interrupted at head and the tail point place and forms two highway sideline point sets, A={P
1, P
2... P
mand B={P
m+1, P
m+2..., P
m+n; At a P
1place adopts clockwise direction combination point set A, connects successively P
1, P
2... P
mform highway sideline X; Point P
m+1place adopts combination point set B, i.e. P counterclockwise
m+n, P
m+n-1..., P
m+1, P
mform highway sideline Y; Get and form that highway sideline point is concentrated comprises the less concentrated initial point of point of a number, be assumed to be a P
1, difference calculation level P
1with a P
m+n, some P
1with a P
m+n-1middle point coordinate, the like, the mid point that calculates two highway sideline point sets forms point set C={C
1, C
2..., C
n-1, C
n, comprise altogether n point, each point in point set C is in turn connected into line, be center line of road;
Step 3: obtain road search piece: the center line of road that point set C is formed interrupts by certain length L, and L chooses, and during according to the common urban road congestion of reality, queue minimum length is chosen, form center line fixed length point set D={D
1, D
2..., D
i-1, D
i, being total to i point, the part of last not enough L is no longer classified; The ratio of definition highway sideline length and center line of road length is scale factor Ф, and two sideline highway sidelines are interrupted by L * Ф respectively, forms respectively two sideline point set X={X
1, X
2..., X
i-1, X
i, Y={Y
1, Y
2..., Y
i-1, Y
i, now adjacent 2 in point set D, X, Y are connected, form and take center line as marginal the right and left road search piece;
Step 4: repeating step one to three, carries out road search piece to all planar roads in city road network and divides.
3. a kind of high score remote sensing image that utilizes as claimed in claim 1 extracts the block up method of vehicle platoon information of city road network, it is characterized in that: calculating the mathematic(al) mode that described road vehicle area ratio/occupancy ratio adopts is:
Wherein, Z represents the road vehicle area occupancy in road search piece,
represent the area of the single unit vehicle in road search piece,
represent the summation of vehicle area in road search piece,
represent the area of road search piece.
4. a kind of high score remote sensing image that utilizes as claimed in claim 1 extracts the block up method of vehicle platoon information of city road network, it is characterized in that: the path area occupancy of setting under congestion status is threshold value z, the path area occupancy of described road search piece is more than or equal to threshold value z's, be judged to be the road search piece that comprises the vehicle platoon that blocks up, the total length of now some jam roads search pieces, being is the length of vehicle platoon of blocking up on this section.
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| CN105157710B (en) * | 2015-06-06 | 2016-09-07 | 烟台惠通网络技术有限公司 | Section congestion level detecting system based on remote sensing communication |
| CN106373397A (en) * | 2016-09-28 | 2017-02-01 | 哈尔滨工业大学 | Fuzzy neural network-based remote sensing image road traffic situation analysis method |
| CN107945720A (en) * | 2018-01-08 | 2018-04-20 | 赵福 | Based on satellite remote sensing date road traffic display screen |
| CN108288014A (en) * | 2017-01-09 | 2018-07-17 | 北京四维图新科技股份有限公司 | Intelligent road extracting method and device, extraction model construction method and hybrid navigation system |
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| CN109241938A (en) * | 2018-09-27 | 2019-01-18 | 深圳金三立视频科技股份有限公司 | Congestion in road detection method and terminal |
| CN111047856A (en) * | 2019-04-09 | 2020-04-21 | 泰州市赛得机电设备有限公司 | Multi-channel congestion index acquisition platform |
| CN113129595A (en) * | 2021-04-23 | 2021-07-16 | 济南金宇公路产业发展有限公司 | Traffic signal control method, equipment and medium for road intersection |
| CN113570858A (en) * | 2021-07-22 | 2021-10-29 | 吉林大学 | System and method for assisting vehicle to identify traffic jam condition by unmanned aerial vehicle |
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| CN106373397A (en) * | 2016-09-28 | 2017-02-01 | 哈尔滨工业大学 | Fuzzy neural network-based remote sensing image road traffic situation analysis method |
| CN106373397B (en) * | 2016-09-28 | 2018-10-02 | 哈尔滨工业大学 | Remote sensing images road situation analysis method based on fuzzy neural network |
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| CN109241938A (en) * | 2018-09-27 | 2019-01-18 | 深圳金三立视频科技股份有限公司 | Congestion in road detection method and terminal |
| CN111047856A (en) * | 2019-04-09 | 2020-04-21 | 泰州市赛得机电设备有限公司 | Multi-channel congestion index acquisition platform |
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