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CN109035783B - Virtual road network missing road section automatic identification method based on bus GPS track - Google Patents

Virtual road network missing road section automatic identification method based on bus GPS track Download PDF

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CN109035783B
CN109035783B CN201811081356.7A CN201811081356A CN109035783B CN 109035783 B CN109035783 B CN 109035783B CN 201811081356 A CN201811081356 A CN 201811081356A CN 109035783 B CN109035783 B CN 109035783B
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CN109035783A (en
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王炜
刘岩
郑永涛
李欣然
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Southeast University
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
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    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • 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
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    • H—ELECTRICITY
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    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/029—Location-based management or tracking services
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
    • H04W4/42—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for mass transport vehicles, e.g. buses, trains or aircraft

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Abstract

本发明公开了一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，首先在城市虚拟交通平台载入公交GPS轨迹点与路网，然后对每个GPS轨迹点以距离l为半径画圆，将该圆形区域包围的所有路网拓扑点构成候选点集R，若R集非空，则判断其中任意两点之间的连接关系，选取具有连接关系的拓扑点对，构成检测点周边路段集D，并计算该GPS点到D中各路段的距离，选取其中最小的距离与最大容许偏差比较，判断该GPS点是否在该路段上，若在则排除该检测点并按照类似的方法进行下一GPS点的判断，若不在则不断迭代l的取值，重复上述过程直至l达到极限值，所有未被排除的检测点对应的路段即为缺失路段。本发明可以节省人工识别的时间，提高路网识别精度。

Figure 201811081356

The invention discloses an automatic identification method for missing sections of a virtual road network based on the GPS track of public transport. Firstly, the GPS track points and the road network of the bus are loaded on the urban virtual traffic platform, and then a circle is drawn for each GPS track point with the distance l as the radius. , all the topological points of the road network surrounded by the circular area form a candidate point set R, if the R set is not empty, then judge the connection relationship between any two points, and select the topological point pair with the connection relationship to form the surrounding of the detection point Road segment set D, and calculate the distance from the GPS point to each road segment in D, select the smallest distance and compare it with the maximum allowable deviation to determine whether the GPS point is on this road segment, if so, exclude the detection point and follow a similar method The next GPS point is judged, if not, the value of l is continuously iterated, and the above process is repeated until l reaches the limit value, and the sections corresponding to all the detected points that are not excluded are the missing sections. The invention can save the time of manual identification and improve the identification accuracy of the road network.

Figure 201811081356

Description

Virtual road network missing road section automatic identification method based on bus GPS track
Technical Field
The invention relates to an automatic identification method for a missing road section, in particular to an automatic identification method for a virtual road network missing road section based on a bus GPS track.
Background
The rapid development of the information technology provides the possibility of electronization for the analysis of urban traffic problems, the big data technology provides real-time road traffic data information, and the construction of an urban virtual traffic system platform based on big data is an effective method for analyzing the urban traffic problems at present. The urban virtual traffic system platform can centralize multi-source traffic data in one system, reproduce complex traffic phenomena on the virtual platform, and an analyst can perform various operations according to different research targets to solve problems in time.
The urban traffic problem analysis can not be carried out without constructing an urban road network, the urban road network is used as a framework and a foundation of an urban traffic system, and the integrity of road network basic data provides guarantee for the reliability of subsequent traffic analysis. However, there are certain obstacles to the current further research into urban traffic problems. On one hand, due to the hysteresis and timeliness of information updating, the urban road network electronic map often has the problem of local deletion. On the other hand, some traffic analysis processes have high requirements on road network accuracy, the existing road network accuracy is difficult to guarantee, the problem of the existing traffic analysis processes is solved mainly by manual observation, relevant materials of government departments are obtained through early-stage traffic investigation, missing roads are perfected and supplemented, and the method not only consumes a large amount of manpower, material resources and financial resources, but also depends on personal judgment of workers, so that the analysis result is poor.
Research shows that the GPS track point data of the ground public transport line has the advantages of being timely in updating and relatively high in position precision, and therefore possibility is provided for matching urban road data through the GPS track point data of the public transport line, and therefore missing road sections are identified.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the practical problems and the defects of the prior art, the invention provides a method for automatically identifying the missing road sections of the virtual network.
The technical scheme is as follows: in order to achieve the purpose of the invention, the technical scheme adopted by the invention is as follows: a virtual road network missing road section automatic identification method based on a GPS track comprises the following steps:
(1) recording GPS data recorded at intervals of a certain time by buses as bus GPS track points, wherein the time interval is usually 30s, loading the bus GPS track points and a road network into a city virtual traffic system platform, and displaying a city road network and a city bus line and analyzing the city traffic demand by the platform;
(2) starting from the bus, along the driving direction, the bus will be on the routeThe measured GPS track points are sequentially recorded as a detection point b1,b2,…,bnThus forming a detection point set B, wherein n is the number of times of last detection on the bus line;
(3) for all detection points B in detection point set B i1, n, from b1Starting with b1Drawing a circle by taking the custom distance l as a radius as a circle center, and taking all road network topological points surrounded by the circular area as candidate points so as to form a candidate point set R, wherein l can be set according to actual needs and is usually 100 m;
(4) if no candidate point exists in the step (3), entering a step (8), otherwise, entering a step (5);
(5) based on a comprehensive traffic network topology connection table in an urban virtual traffic system platform, with each road section as a unit, sequentially storing candidate points contained in the road section, including road network nodes and inflection points, judging whether any two candidate points in a candidate point set R are adjacent, if so, judging that a connection relation exists, otherwise, traversing all candidate points in the R, selecting topological point pairs with the connection relation, and forming a detection point b1A set of peripheral road segments D;
(6) separately calculating the detection points b1The distance D to each segment in the set D is given by the following formula:
Figure BDA0001802042290000021
Figure BDA0001802042290000022
wherein r is a calculation index, M, N is two endpoints of a certain road segment in the set D, and P is b1A vertical point to the MN; selecting the smallest distance dminThe maximum allowable deviation d is used as the judgment index0Comparison, d0Can be set according to actual needs, and can be 15m in general, if dmin＜d0Then, it indicates the detection point b1On the road section, it is moved out of the detection point set B(ii) a If d ismin＞d0Then, it indicates the detection point b1Roads do not exist around the detection point set B, and the detection point set B is reserved with the roads;
(7) if the detection point b is detected in the step (6)1If the detection point set B is moved out, the step (9) is carried out, otherwise, the step (8) is carried out;
(8) adding a fixed radius increment iteration value delta l to l, recording the value as l again, and judging whether l exceeds a given upper limit llimitIf not, repeating the step (3) and the step (4); if a given upper limit l is exceededlimitThen B is reserved in the detection point set B1Wherein Δ l and llimitCan be set according to actual needs, and the delta l is usually 100m and llimitTypically 1000 m;
(9) in sequence with b2,b3,…,bnRepeating the steps (3) to (8) by taking the GPS track points as the circle center until all the GPS track points on the bus line are traversed;
(10) and outputting the remaining detection points in the B, and judging the road sections corresponding to the detection points as missing road sections, wherein the missing road sections comprise:
(a) road middle section missing: the first situation is that a certain section of road between two road nodes is missing in the advancing direction of the road, and the situation mainly occurs in a block with dense branch networks or a newly built development area, and the reason for the situation is mainly new road building; the second condition is that in the advancing direction of the road, the road has local lane change and the lane after lane change is lost, which mainly appears on the road along the subway and is a temporary measure for facilitating the subway construction;
(b) end segment missing of road: the terminal point or the starting point of the bus line can be arranged on a branch road with a relatively far position, and some branch roads are omitted in the road network data because of being communicated with only one road;
(c) the intersection right-turn special lane is absent: this is often the case at large intersections, and the additional right-turn lanes are not updated in the road network in time due to the intersection reconstruction and the like.
Has the advantages that: compared with the prior art, the invention has the following advantages: the traditional process of manually identifying the virtual road network missing road sections is replaced by computer automatic identification, so that the labor, material resources and financial resources are saved, the defect of experience in manual identification is overcome, and the accuracy of road network identification is improved.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2(a), (b), and (c) are schematic diagrams showing three positional relationships between the detection point and the link.
Detailed Description
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
As shown in fig. 1, the method for automatically identifying a virtual road network missing road section based on a bus GPS track according to the present invention comprises the steps of:
(1) and recording GPS data recorded by buses at intervals of 30s as bus GPS track points, and loading the bus GPS track points and the road network into the urban virtual traffic system platform.
The present embodiment selects 41 bus routes GPS track points and urban road network data in wuhan city as experimental data, the bus route name and the number of GPS track points of each route, i.e., the number of detection points, as shown in table 1 below.
TABLE 1
Figure BDA0001802042290000041
(2) Taking the bus number 201 as an example, 324 GPS track points measured on the line along the driving direction from the start of the bus are sequentially marked as b1,b2,…,b324And forming a detection point set B.
(3) For all detection points B in detection point set B i1.., 324 from b1Starting with b1And drawing a circle with the distance of 100m as a radius as a circle center, and regarding all road network topological points surrounded by the circular area as candidate points to form a candidate point set R.
(4) If no candidate point exists in the step (3), entering a step (8), otherwise, entering a step (5);
(5) for the candidate point set R, judging the connection relation between any two candidate points, traversing all the candidate points in the R, selecting a topological point pair with the connection relation, and forming a detection point b1A set of peripheral road segments D;
the basis for judging the connection relation between any two candidate points is as follows: and a comprehensive traffic network topology connection table in the urban virtual traffic system platform. The table takes each road section as a unit, and sequentially stores topological points contained in the road section, including road network nodes and inflection points, wherein a connection relation exists between two adjacent topological points, and two non-adjacent topological points do not have a connection relation. Detection point b1The comprehensive traffic network topology connection table of the peripheral road segment set D is shown in Table 2.
TABLE 2
Figure BDA0001802042290000051
It can be seen that 6 road topology points with serial numbers of 0-5 exist in D, and 20 road sections are formed.
(6) Separately calculating the detection points b1Selecting the distance D to each road section in the set D, wherein the minimum distance DminIs compared with the maximum allowable deviation d0Comparison, if dmin＜d0Then, it indicates the detection point b1On the road section, removing the road section from the detection point set B; if d ismin＞d0Then, it indicates the detection point b1Roads do not exist around the detection point set B, and the detection point set B is reserved with the roads;
calculating the detection point b1The method for the distance to each road section in the set D comprises the following steps: to detect point b1And section MN in set D as an example: b1The vertical point to the MN is denoted as point P, b1The position relation with the MN is divided into three cases:
(a)b1is within the line segment MN, as shown in fig. 2 (a);
(b)b1is outside the point N of the line segment MN, as shown in fig. 2 (b);
(c)b1is projected outside of point M of line segment MN, e.g.FIG. 2(c) shows.
In consideration of the directivity of the road section MN, a calculation index r is introduced as shown in the following formula:
Figure BDA0001802042290000061
then b is1The distance d to the segment MN is:
Figure BDA0001802042290000062
in the present embodiment, the maximum allowable deviation d0Taking 15m as the minimum distance d found by calculationmin15.8m, point b is indicated1The periphery has no road and is retained in the detection point set B.
(7) If the detection point b is detected in the step (6)1If the detection point set B is moved out, the step (9) is carried out, otherwise, the step (8) is carried out;
(8) selecting an area radius of 100m for the initial candidate point, increasing the radius of 100m each time, repeating iteration, judging whether the radius size after iteration exceeds a given radius upper limit of 1000m, and if not, repeating the step (3) and the step (4); if the given upper limit is exceeded, B is reserved in the detection point set B1。
In this embodiment, when the radius is 300m, the candidate point exists in R, and the process proceeds to step (5).
(9) In sequence with b2,b3,…,b324Repeating the steps (3) to (8) by taking the GPS track points as the circle center until all the GPS track points on the bus line are traversed;
(10) and outputting the remaining detection points in the B, and judging the road sections corresponding to the detection points as missing road sections, wherein the missing road sections comprise:
(a) road middle section missing: the first situation is that a certain section of road between two road nodes is missing in the advancing direction of the road, and the situation mainly occurs in a block with dense branch networks or a newly built development area, and the reason for the situation is mainly new road building; the second condition is that in the advancing direction of the road, the road has local lane change and the lane after lane change is lost, which mainly appears on the road along the subway and is a temporary measure for facilitating the subway construction;
(b) end segment missing of road: the terminal point or the starting point of the bus line can be arranged on a branch road with a relatively far position, and some branch roads are omitted in the road network data because of being communicated with only one road;
(c) the intersection right-turn special lane is absent: this is often the case at large intersections, and the additional right-turn lanes are not updated in the road network in time due to the intersection reconstruction and the like.
In this embodiment, the remaining detection points B are 8, respectively1,b63,b67,b106,b177,b191,b245,b307And the road sections corresponding to the detection points are missing road sections, and the missing type of the road sections is further found to be newly-built road missing by comparing the map.
The method for identifying the missing road sections of the other lines is similar to the method for identifying the missing road sections of the other lines, wherein the method is only one bus line and adjacent roads.

Claims (8)

1.一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于，包括以下步骤：1. a virtual road network missing road section automatic identification method based on public transport GPS track, is characterized in that, comprises the following steps: (1)将公交GPS轨迹点与路网载入城市虚拟交通系统平台；(1) Load the bus GPS track points and road network into the urban virtual traffic system platform; (2)自公交始发起，沿行驶方向，将线路上测得的GPS轨迹点依次记为检测点b1,b2,…,bn，从而构成检测点集B，其中n为该公交线上最后一次检测时的次数；(2) From the start of the bus, along the driving direction, the GPS track points measured on the line are recorded as detection points b 1 , b 2 , ..., b n in turn, so as to form a detection point set B, where n is the bus The number of times of the last detection on the line; (3)对于检测点集B中的所有检测点bi，i＝1,...,n，从b1开始，以b1为圆心、以自定义距离l为半径画圆，将该圆形区域包围的所有路网拓扑点视为候选点，从而构成候选点集R；(3) For all the detection points b i in the detection point set B, i=1,...,n, starting from b 1 , draw a circle with b 1 as the center and a custom distance l as the radius, and the circle All road network topology points surrounded by the shape area are regarded as candidate points, thus forming a candidate point set R; (4)若步骤(3)中无候选点，则进入步骤(8)，否则进入步骤(5)；(4) If there is no candidate point in step (3), then enter step (8), otherwise enter step (5); (5)对于候选点集R，判断其中任意两候选点之间的连接关系，遍历R中所有候选点，选取具有连接关系的拓扑点对，构成检测点b1周边路段集D；(5) For the candidate point set R, determine the connection relationship between any two candidate points, traverse all the candidate points in R, select the topological point pair with the connection relationship, and form the detection point b 1 surrounding road section set D; (6)分别计算检测点b1到集合D中各路段的距离d，选取其中最小的距离dmin，将其与最大容许偏差d0比较，若dmin＜d0，则表明检测点b1在该路段上，并将其从检测点集B中移出；若dmin＞d0，则表明检测点b1周边不存在道路，并将其保留在检测点集B中；其中，距离d的计算公式为：(6) Calculate the distance d from the detection point b 1 to each road section in the set D respectively, select the smallest distance d min among them, and compare it with the maximum allowable deviation d 0 , if d min <d 0 , it indicates that the detection point b 1 On this road segment, it is removed from the detection point set B; if d min >d 0 , it means that there is no road around the detection point b 1 , and it is retained in the detection point set B; The calculation formula is:
Figure FDA0002891050640000011
Figure FDA0002891050640000011
Figure FDA0002891050640000012
Figure FDA0002891050640000012
 其中，r为计算指标，M、N为集合D中某路段的两个端点，P为b1到MN的垂点；Among them, r is the calculation index, M and N are the two endpoints of a certain road section in the set D, and P is the vertical point from b 1 to MN; (7)若步骤(6)中检测点b1已从检测点集B移出，则进入步骤(9)，否则进入步骤(8)；(7) If the detection point b 1 has been removed from the detection point set B in step (6), then enter step (9), otherwise enter step (8); (8)给l增加一个定长Δl，并重新记为l，判断l是否超过给定上限llimit，若没有，则重复步骤(3)和步骤(4)；若超过给定上限llimit，则在检测点集B中保留b1；(8) Add a fixed length Δl to l, and record it as l again to judge whether l exceeds the given upper limit l limit , if not, repeat steps (3) and (4); if it exceeds the given upper limit l limit , Then keep b 1 in the detection point set B; (9)依次以b2,b3,…,bn为圆心，重复步骤(3)至步骤(8)，直至遍历公交线路上的所有GPS轨迹点；(9) Taking b 2 , b 3 ,..., b n as the center of the circle in turn, repeat steps (3) to (8) until all GPS track points on the bus route are traversed; (10)输出B中剩余检测点，则可判定这些检测点对应的路段为缺失路段。(10) Output the remaining detection points in B, then it can be determined that the road sections corresponding to these detection points are missing road sections. 2.根据权利要求1所述的一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于：步骤(1)中所述的公交GPS轨迹点为公交车每间隔一定时间所记录下来的GPS数据。2. a kind of automatic identification method of virtual road network missing road section based on bus GPS track according to claim 1, it is characterized in that: bus GPS track point described in step (1) is that bus is recorded every certain time interval down the GPS data. 3.根据权利要求1所述的一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于：步骤(1)中所述的城市虚拟交通系统平台是一种可以显示城市道路网络、城市公交线路以及分析城市交通需求的宏观分析软件。3. a kind of automatic identification method of virtual road network missing road section based on bus GPS track according to claim 1, is characterized in that: the urban virtual traffic system platform described in step (1) is a kind of can display urban road network , urban bus routes and macro analysis software for analyzing urban traffic demand. 4.根据权利要求1所述的一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于：步骤(5)中判断任意两候选点之间连接关系的依据为：城市虚拟交通系统平台中的综合交通网络拓扑连接表；该表以每一条路段为单位，按顺序存储该路段所包含拓扑点，包括路网节点和拐点，而相邻的两个拓扑点之间存在连接关系，不相邻的两个拓扑点之间不具有连接关系。4. a kind of automatic identification method of virtual road network missing road section based on public transport GPS track according to claim 1, it is characterized in that: in step (5), the basis for judging the connection relationship between any two candidate points is: urban virtual traffic The comprehensive traffic network topology connection table in the system platform; the table takes each road segment as a unit, and stores the topological points contained in the road segment in order, including road network nodes and inflection points, and there is a connection relationship between two adjacent topological points. , there is no connection between two non-adjacent topological points. 5.根据权利要求1所述的一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于：步骤(6)中的最大容许偏差d0是判断检测点是否在路段上的指标。5. a kind of automatic identification method based on the virtual road network missing road section of public transport GPS track according to claim 1, is characterized in that: the maximum allowable deviation d in step (6 ) is the index that judges whether the detection point is on the road section . 6.根据权利要求1所述的一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于：步骤(6)中所述的定长Δl为每次以检测点为圆心，l为半径画圆时半径增加的迭代值。6. a kind of virtual road network missing road section automatic identification method based on public transport GPS track according to claim 1, is characterized in that: the fixed length Δ1 described in step (6) is to take detection point as center of circle every time, l The iteration value by which the radius increases when drawing a circle for the radius. 7.根据权利要求1所述的一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于：步骤(8)中所述的给定上限llimit为每次以检测点为圆心，l为半径画圆时半径的最大值。7. a kind of virtual road network missing road section automatic identification method based on public transport GPS track according to claim 1, is characterized in that: the given upper limit 1 limit described in the step (8) is that every time the detection point is the center of the circle , l is the maximum radius when drawing a circle. 8.根据权利要求1所述的一种基于公交GPS轨迹的虚拟路网缺失路段自动识别方法，其特征在于：步骤(10)中所述的缺失路段包括：8. The method for automatically identifying missing sections of a virtual road network based on a GPS track of public transport according to claim 1, wherein the missing sections described in step (10) comprise: (1)道路中间路段缺失：可分为两种情况，第一种情况是在道路前进方向，位于两个道路节点之间的某段道路缺失；第二种情况是在道路前进方向，道路出现局部改线，改线后的道路缺失；(1) The middle section of the road is missing: it can be divided into two cases. The first case is that a certain section of road between two road nodes is missing in the direction of the road; the second case is that the road appears in the direction of the road. Local re-routing, the road after re-routing is missing; (2)道路的末端路段缺失：公交线路的终点或起点可能设置在位置相对偏远的支路上，一些支路由于仅与一条道路连通而在路网数据中被遗漏；(2) The end section of the road is missing: the end point or starting point of the bus line may be set on a relatively remote branch road, and some branch roads are missed in the road network data because they are only connected to one road; (3)交叉口右转专用道缺失：由于交叉口改造等原因，增设的右转专用道没有及时在路网中更新。(3) Lack of dedicated right-turn lanes at intersections: Due to intersection reconstruction and other reasons, the additional right-turn lanes have not been updated in the road network in time.
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