CN109920245A - Traffic state judging method based on GPS Floating Car information - Google Patents
Traffic state judging method based on GPS Floating Car information Download PDFInfo
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Abstract
The present invention relates to a kind of traffic state judging method based on GPS Floating Car information, the processes such as the matching of pretreatment, map including data, Floating Car speed calculate, wherein map match is the core process of this method.Using the traffic state judging method based on GPS Floating Car information in the invention, matching accuracy rate of the GPS Floating Car on map can be made higher, the average speed accuracy of calculating is also high.This method preferably compensates for electricity alert bayonet, the not covered section of video capture device simultaneously, and by the alert bayonet of fusion electricity, video, Floating Car three data, can preferably indicate urban highway traffic situation, people is facilitated to go on a journey, cost is also lower, has wider application range.
Description
Technical Field
The invention relates to the technical field of urban traffic, in particular to the technical field of information acquisition, and specifically relates to a traffic state discrimination method based on GPS floating car information.
Background
The floating car technology is a road information acquisition mode, can provide real-time urban road condition information, is one of advanced technical means for acquiring road section traffic information adopted in an international intelligent traffic system in recent years, and has the characteristics of convenience in application, economy and wide coverage; the floating car is composed of a vehicle which is provided with a vehicle-mounted GPS (global positioning system) device and runs on an actual road section; the floating car GPS positioning system transmits the data of the longitude and latitude, the instantaneous speed, the driving direction angle, the time, the equipment number and the like of the floating car to a background database according to a certain period through a certain communication method. The background computer processing center collects floating car data, and generates traffic information capable of reflecting real-time road section conditions through specific algorithm models and technical processing, so that the traffic condition of roads can be monitored in all weather. The core algorithm of the floating car algorithm is map matching, the map matching problem is effectively solved, the floating car technology is realized, all-weather monitoring on road conditions on a road network is realized by adopting corresponding technical measures through a certain communication means, and the map matching refers to associating the current vehicle running track collected by the floating car loaded with the GPS terminal device in the running process with road information in an electronic map through a specific model and algorithm, and finally outputting the specific position of the vehicle on the road. In the map matching method in the prior art, map matching is performed by a method of weighting a difference value between a projection distance, a vehicle driving direction and a road section vector direction, and a road section on which a vehicle drives is judged. When the vehicle running speed is low, the running direction angle transmitted by the vehicle is inaccurate, so that the vehicle cannot be applied, and the existing matching method does not separately process the running direction angle; also when the electronic map is a two-way link for matching (not matching the center line of a road), and the map is not a vector diagram (i.e., the direction of the link is not known), the prior art map matching does not describe a method of screening for a two-way link.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a traffic state discrimination method based on GPS floating car information, which can discriminate bidirectional road sections.
In order to achieve the above object, the traffic state determination method based on the GPS floating car information of the present invention is as follows:
the traffic state distinguishing method based on the GPS floating car information is mainly characterized by comprising the following steps of:
(1) collecting a current GPS point of the GPS floating car;
(2) judging whether the current GPS point is in the range of the GPS database, if so, continuing the step (3), otherwise, returning to the step (1);
(3) acquiring n candidate road sections within a reasonable range, wherein n is any positive integer;
(4) calculating a matching weight value of each candidate road section;
(5) judging whether the difference value of the maximum matching weight value and the matching weight values of other remaining candidate road sections is larger than a first threshold value, if so, deleting the candidate road section with the maximum matching weight value and returning to the step (5), otherwise, continuing the step (6);
(6) selecting two candidate road sections with the maximum matching weight value and screening to obtain a final candidate road section;
(7) calculating the average speed of the GPS floating car and acquiring the road speed of any candidate road section;
(8) and judging the traffic state of any candidate road section.
In the step (4) of the traffic state discrimination method based on the GPS floating car information,
when the instantaneous speed of the GPS floating car is smaller than a second threshold value, the matching weight value is calculated by the following formula:
when the instantaneous speed of the GPS floating car is greater than a second threshold value, the matching weight value is calculated by the following formula:
wherein,is the matching weight value of the ith candidate link,is a normalized value of the vertical distance of the current GPS point from the ith candidate segment, is a normalized value of an included angle between the running direction of the GPS floating car and the direction of the ith candidate road section,kθis the weight coefficient, k, of the direction of traveldIs a weight coefficient, k, of the vertical distance of the current GPS point from the ith candidate road sectionθ+kdI is any positive integer and i is ≦ n.
In the matching weight value formula of the traffic state discrimination method based on the GPS floating car information,
and is
Wherein d isiIs the vertical distance, Delta, of the current GPS point from the ith candidate road segmentGPSIs the average error of the current GPS point,
θiand the included angle between the running direction of the GPS floating car and the ith candidate road section direction is determined.
Theta of traffic state discrimination method based on GPS floating car informationiCalculated by the following formula:
θi＝abs(θ2-θg)×π/180
wherein, theta2Is the direction angle, theta, of the ith candidate linkgThe direction angle of the GPS floating car.
In step (6) of the traffic state discrimination method based on the GPS floating car information, the two candidate road sections with the maximum matching weight values are a road section A and a road section B respectively, and the matching point of the road section A is (X)A，YA) The matching point of the road section B is (X)B，YB)，Said XA，XBRespectively, the abscissa of the road section A and the road section B, the YA，YBAnd the final candidate road sections are determined according to the coordinate size of the matching points of the road section A and the road section B and the angle of the running direction of the GPS floating car.
The final candidate road section of the traffic state judging method based on the GPS floating car information is specifically as follows:
when X is presentA＞XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＞XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section A;
when X is presentA＜XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is a road section A;
when X is presentA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section B;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is a road section A;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section B;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between 135 degrees and 225 degrees, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBAnd when the angle of the running direction of the GPS floating car is between (135 degrees and 225 degrees), the final candidate road section is the road section B.
When the running direction of the GPS floating car of the traffic state discrimination method based on the GPS floating car information is in the due north direction, the angle of the running direction of the GPS floating car is 0 degree.
In step (7) of the traffic state discrimination method based on the GPS floating car information, the step of acquiring the road speed of any candidate road section comprises the following steps:
(7.1) calculating the average speed of any one candidate road section at the first cycle threshold;
(7.2) judging whether the average speed which is greater than the third threshold value or less than the fourth threshold value exists, if so, rejecting the average speed and continuing the step (7.3), otherwise, directly carrying out the step (7.3);
and (7.3) averaging the remaining average speeds to obtain the speed of the road section.
By adopting the traffic state discrimination method based on the GPS floating car information, the matching accuracy of the GPS floating car on the map can be higher, and the accuracy of the calculated average speed is also high. Meanwhile, the method better makes up the road sections which cannot be covered by the electric police bayonet and the video acquisition equipment, and can better represent the urban road traffic condition by fusing the data of the electric police bayonet, the video and the floating car, thereby being convenient for people to go out, having lower cost and wider application range.
Drawings
Fig. 1 is a schematic flow chart of a map matching process in the traffic state determination method based on the GPS floating car information according to the present invention.
Fig. 2 is a schematic flow chart of a first stage process of calculating an average speed in the traffic state discrimination method based on the GPS floating car information.
Fig. 3 is a schematic flow chart of a second stage process of calculating an average speed in the traffic state determination method based on the GPS floating car information according to the present invention.
Fig. 4 is a schematic diagram of calculating an average speed in the traffic state determination method based on the GPS floating car information according to the present invention.
Fig. 5 is a schematic diagram of processing abnormal points in the traffic state determination method based on the GPS floating car information according to the present invention.
Fig. 6 is a schematic diagram of a path within a reasonable range for searching a GPS point in the traffic state determination method based on the GPS floating car information.
Fig. 7 is a schematic diagram of calculating a road section direction in the traffic state determination method based on the GPS floating car information according to the present invention.
Fig. 8 is a schematic diagram illustrating the discrimination of a bidirectional road section in the traffic state discrimination method based on the GPS floating car information according to the present invention.
Fig. 9 is another schematic diagram for discriminating a bidirectional road section in the traffic state discrimination method based on the GPS floating car information according to the present invention.
Fig. 10 is a schematic flow chart of the traffic state determination method based on the GPS floating car information according to the present invention.
Detailed Description
In order to more clearly describe the technical contents of the present invention, the following further description is given in conjunction with specific embodiments.
The traffic state distinguishing method based on the GPS floating car information is mainly characterized by comprising the following steps of:
(1) collecting a current GPS point of the GPS floating car;
(2) judging whether the current GPS point is in the range of the GPS database, if so, continuing the step (3), otherwise, returning to the step (1);
(3) acquiring n candidate road sections within a reasonable range, wherein n is any positive integer;
(4) calculating a matching weight value of each candidate road section;
(5) judging whether the difference value of the maximum matching weight value and the matching weight values of other remaining candidate road sections is larger than a first threshold value, if so, deleting the candidate road section with the maximum matching weight value and returning to the step (5), otherwise, continuing the step (6);
(6) selecting two candidate road sections with the maximum matching weight value and screening to obtain a final candidate road section;
(7) calculating the average speed of the GPS floating car and acquiring the road speed of any candidate road section;
(8) and judging the traffic state of any candidate road section.
Fig. 1 is a schematic flow chart showing a map matching process in the method for determining a traffic state based on GPS floating car information according to the present invention. The steps (1) to (6) are specific map matching processes.
In the step (4) of the traffic state discrimination method based on the GPS floating car information,
when the instantaneous speed of the GPS floating car is smaller than a second threshold value, the matching weight value is obtained by calculating according to the following formula 1:
when the instantaneous speed of the GPS floating car is greater than a second threshold value, the matching weight value is calculated by the following formula 2:
wherein,is the matching weight value of the ith candidate link,is a normalized value of the vertical distance of the current GPS point from the ith candidate segment, is a normalized value of an included angle between the running direction of the GPS floating car and the direction of the ith candidate road section,kθis a stand forThe weight coefficient of the driving direction, kdIs a weight coefficient, k, of the vertical distance of the current GPS point from the ith candidate road sectionθ+kdI is any positive integer and i is ≦ n.
In a matching weight value formula of the traffic state discrimination method based on the GPS floating car information, wherein,
in equations 3 and 4, diIs the vertical distance, Delta, of the current GPS point from the ith candidate road segmentGPSIs the average error of the current GPS point,
θiand the included angle between the running direction of the GPS floating car and the ith candidate road section direction is determined.
Theta of traffic state discrimination method based on GPS floating car informationiCalculated by the following formula:
θi＝abs(θ2-θg) X pi/180 (formula 5);
wherein, theta2Is the direction angle, theta, of the ith candidate linkgThe direction angle of the GPS floating car.
In step (6) of the traffic state discrimination method based on the GPS floating car information, the two candidate road sections with the maximum matching weight values are a road section A and a road section B respectively, and the matching point of the road section A is (X)A，YA) The matching point of the road section B is (X)B，YB) Said XA，XBRespectively, the abscissa of the road section A and the road section B, the YA，YBRespectively, the longitudinal coordinates of the road section A and the road section B, according to the road section A and the roadAnd determining the final candidate road section according to the coordinate size of the matching point of the section B and the angle of the driving direction of the GPS floating car.
The final candidate road section of the traffic state judging method based on the GPS floating car information is specifically as follows:
when X is presentA＞XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＞XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section A;
when X is presentA＜XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is a road section A;
when X is presentA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section B;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is a road section A;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section B;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between 135 degrees and 225 degrees, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBAnd when the angle of the running direction of the GPS floating car is between (135 degrees and 225 degrees), the final candidate road section is the road section B.
When the running direction of the GPS floating car of the traffic state discrimination method based on the GPS floating car information is in the due north direction, the angle of the running direction of the GPS floating car is 0 degree.
In step (7) of the traffic state discrimination method based on the GPS floating car information, the step of acquiring the road speed of any candidate road section comprises the following steps:
(7.1) calculating the average speed of any one candidate road section at the first cycle threshold;
(7.2) judging whether the average speed which is greater than the third threshold value or less than the fourth threshold value exists, if so, rejecting the average speed and continuing the step (7.3), otherwise, directly carrying out the step (7.3);
and (7.3) averaging the remaining average speeds to obtain the speed of the road section.
Please refer to fig. 2 and fig. 3, which are schematic flow charts of a first stage process and a second stage process of calculating an average speed in the method for determining a traffic state based on GPS floating car information according to the present invention. In the process of calculating the average speed of the GPS floating car, firstly obtaining a matched GPS point, and recording the ID (linkid) of a matched road, the ID (Carid) of the car, the position (Pos) of a matched road section, the time ti of the GPS positioning and the distance d (i-1, i) from the previous matched point; d (i-1, i) can be directly obtained by arcgis; secondly, judging whether a previous matching point and a current matching point are on the same road section and whether the driving directions are the same, if so, taking the calculation time as t (i-1, i) ═ ti-t (i-1), if the previous matching point and the current matching point are not on the same road section or the previous matching point and the current matching point are on the same road section but the driving directions are different (namely, the floating car turns around to drive on the original road), searching a path through Arcgis to obtain the distance between adjacent matching points, and calculating the driving time t (i-1, i) ═ ti-t (i-1) of the adjacent matching points; the average velocity V (i-1, i) of the neighboring matching points is then calculated:
if V (i-1, i) is greater than or equal to the instantaneous speed V transmitted by the floating car at the momentssThen the average speed at that moment is taken as V (i-1, i), otherwise the average speed is calculated by equation 7:
the time corresponding to the speed is the time when the vehicle passes through the downstream intersection. When the ID of the road section matched by the current taxi is different from the matching of the previous time, the calculated speed is matched on the two road sections and is used as a sample of the two road sections.
In practical application, the detailed calculation method of the speed of the GPS floating vehicle is as follows:
fig. 4 is a schematic diagram of calculating an average speed in the method for determining a traffic state based on GPS floating car information according to the present invention. After the GPS points of the floating cars are matched on the road section, the average speed V (i-1, i) of the FCD is calculated according to the positions of the matching points, and the matching points of the taxi GPS on the road are assumed to be 1,2,3,4 and 5 on the graph 4. a, b and c are intersections of the intersection.
The average speed is calculated as follows:
(1) if the matching point of the taxi crosses a road section such as 1,3 matching points, there is no matching point on the road section ab, the driving distance is L13 (the driving distance can be obtained through Arcgis service), because the route passed by the vehicle can not be recorded on gis service, the speed on the road section ab can not be calculated, the speed of the road section ab is taken as the speed of the road section on which the matching point falls, for example, the matching points 1 and 3 fall on the road section 1a and the road section bc respectively, the speed calculated by the road sections 1 and 3 through the matching points (the calculation way is shown in formula 8 and formula 9) represents the speed of the road sections 1a and bc, and the time corresponding to the speed is the time from the GPS point to the matching point 3 (namely, the calculated speed represents the speed of the two road sections when the two adjacent matching points IDs of the road sections are different)
(2) If the matching point of the taxi does not cross the road section, for example, the 2,5 matching points are all on the road section ab, and the IDs of the two adjacent matching points are the same, the calculated speed represents the speed of the road section, and the time corresponding to the speed is the time of the latest matching point, which is specifically calculated by formula 10:
(3) please refer to fig. 5, which is a schematic diagram illustrating abnormal points processed in the method for determining a traffic state based on GPS floating car information according to the present invention. On the road section ab, if the first GPS point is matched on the road section ab, the second GPS point is matched on the road section cd, and the third GPS point is matched on the road section ab, the second GPS point is matched incorrectly, the second GPS point is discarded during calculation, and the speed is calculated by using the first GPS point and the third GPS point. Only when a plurality of GPS points fall on the same road section, whether a matching point is wrong or not can be judged, and if the first GPS point and the third GPS point are not on the same road section, whether the second GPS point is matched wrongly or not can not be judged.
In practical applications, the road speed is calculated as follows:
acquiring data of all floating cars T minutes before the current time of a certain road section, removing data with the speed less than a certain reasonable trained numerical value, setting a maximum threshold value V0 according to the driving condition of the vehicles on the road section, removing data samples with the speed more than V0 if the data samples with the speed of T minutes are more than V0, then averaging the rest data, fusing the average speed of the time and the previous speed as the speed of the road section at the time if the sample data with the speed of T minutes are less than the certain reasonable trained numerical value, or directly averaging the data as the speed of the road section at the time.
Please refer to fig. 6, which is a schematic diagram of a route for searching a reasonable range of GPS points in the traffic state determination method based on GPS floating car information according to the present invention, and the specific method is as follows:
all paths within a reasonable range around the floating car are searched by taking the GPS point position of the floating car as the center, and the path is shown in figure 1. All paths in a reasonable range of the GPS point location can be automatically found on the Arcgis service, and because each section of path is composed of broken lines, the coordinates of all inflection points on the path can be obtained while all paths are obtained. Assuming that the coordinates of the inflection point are RPi (xi, yi) and the coordinates of the GPS point are P (x0, y0), taking fig. 6 as an example, the distance from the GPS point (P point) to the section CE is calculated;
wherein, GPSi (x)0,y0) The distance calculation formula of the points to the C (x1, y1) and E (x2, y2) lines is as follows:
in practical application, the vertical distances from the GPS point to all paths meeting the conditions are searched in a loop, and the specific calculation method is as follows:
the longitude and latitude of each inflection point A, B, C, E, F, G in fig. 6 can be known through the GIS service, wherein a point P represents a positioning point of a GPS, and the vertical distance from the point P to each broken line can be calculated according to the triangle theorem; however, when the perpendicular line from point P to the polyline is outside the polyline, the present application takes the distance from point P to the starting point or the ending point, for example, in Δ PAB, the distance from point P to point AB is the length of PB; taking PF as the distance from middle P to FG; before calculating the foot drop, firstly, whether a perpendicular line from a point P to a broken line is within the broken line is calculated, and taking Δ PCE in fig. 6 as an example, a judgment formula is as follows:
when t is less than or equal to 0, the droop of P on CE is on the extension line of EC, and the distance is taken as the length of PC:
when t is more than or equal to 1, the P is hung on the CE on the extension line of the CE, and the distance is equal to the length of PE:
when t is more than 0 and less than 1, the vertical leg of P on CE is on CE, and the coordinate of vertical leg is D (X)d,Yd) The calculation formula is as follows:
and (4) pulling the GPS matching point to the matched road section through the coordinate of the drop foot (the matching point of the point P on the road section CE is the point D or the point C, E).
In practical application, please refer to fig. 7, which is a schematic diagram of calculating a road direction in the method for determining a traffic state based on GPS floating car information according to the present invention: assuming that the coordinates of two inflection points of a road segment are 1(x1, y1) and 2(x2, y2), respectively, the coordinates are calculated to be 1(x1, y1) and 2(x2, y2), respectively
The included angle theta between the GPS floating car and the due north direction can be obtained2Comprises the following steps:
or
θ 2 is 270 ° - θ 1 (formula 19);
wherein theta is2Take a value close to the vehicle heading angle.
In practical application, the calculated road section weights are sequenced to determine the matched road sections, and the method comprises the following steps:
and calculating the difference value between the road section with the maximum weight and other road sections meeting the conditions, and if the difference value is greater than a certain proportion obtained by training of the maximum weight, excluding the road section and not taking the road section as a matching object.
Through the calculation, the candidate matching road section of the GPS and the matching point (foot) on the road section can be obtained, wherein the weight value of each road section is arranged from large to small, and the maximum weight value on each road section is assigned to the road section.
In practical application, the road section with the maximum weight (generally, two driving directions of one road section) is selected for screening the directions of the two-way road sections, and the screening method comprises the following steps:
when map matching is carried out, the used map layers are bidirectional road sections, and the center line of the road is only used for searching the distance between adjacent matching points. Because the two-way road sections are two-way road sections of one road and the two-way road sections have different IDs, which direction the floating cars are matched to on one road needs to be discriminated, and the detailed discrimination method is as follows:
in practical application, please refer to fig. 8 and fig. 9, which are two schematic diagrams respectively illustrating the method for discriminating a bidirectional road section according to the present invention based on the GPS floating car information:
assuming that a and B are bidirectional road sections of a road, based on coordinates of matching points of longitude and latitude of a GPS of a floating car on different road sections, for example, the GPS original data is (X0, Y0), and the matching points on different road sections are (X1, Y1), (X2, Y2).. once. (Xn, Yn), selecting two road sections with the largest matching weight and the second largest matching weight, assuming that the GPS matching maximum and the second largest weight road sections of an original floating car are road section a and road section B (a and B are two directions of a road section), how to determine which road section to match, the matching logic is as follows:
when X is presentA＞XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＞XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section A;
when X is presentA＜XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is a road section A;
when X is presentA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section B;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is a road section A;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section B;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between 135 degrees and 225 degrees, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBAnd the angle of the running direction of the GPS floating car is (135 DEG, 225 DEG)And in time, the final candidate road section is the road section B.
And finally, obtaining the final road section matched with the GPS point, the matched coordinate on the road section and the time.
In practical application, please refer to fig. 10, which is a schematic flow chart of the method for determining a traffic state based on GPS floating car information according to the present invention, the method includes the processes of data preprocessing, map matching, floating car speed calculation, etc., wherein the map matching is a core process of the method.
By adopting the traffic state discrimination method based on the GPS floating car information, the matching accuracy of the GPS floating car on the map can be higher, and the accuracy of the calculated average speed is also high. Meanwhile, the method better makes up the road sections which cannot be covered by the electric police access and the video acquisition equipment, can better represent the urban road traffic condition by fusing the data of the electric police access, the video and the floating car, can better plan the driving road section to facilitate the travel of people, and has lower cost and wider application range.
In this specification, the invention has been described with reference to specific embodiments thereof. It will, however, be evident that various modifications and changes may be made thereto without departing from the broader spirit and scope of the invention. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.
Claims (8)
1. A traffic state discrimination method based on GPS floating car information is characterized by comprising the following steps:
(1) collecting a current GPS point of the GPS floating car;
(2) judging whether the current GPS point is in the range of the GPS database, if so, continuing the step (3), otherwise, returning to the step (1);
(3) acquiring n candidate road sections within a reasonable range, wherein n is any positive integer;
(4) calculating a matching weight value of each candidate road section;
(5) judging whether the difference value of the maximum matching weight value and the matching weight values of other remaining candidate road sections is larger than a first threshold value, if so, deleting the candidate road section with the maximum matching weight value and returning to the step (5), otherwise, continuing the step (6);
(6) selecting two candidate road sections with the maximum matching weight value and screening to obtain a final candidate road section;
(7) calculating the average speed of the GPS floating car and acquiring the road speed of any candidate road section;
(8) and judging the traffic state of any candidate road section.
2. The method for discriminating the traffic state based on the GPS floating car information as claimed in claim 1, wherein in the step (4),
when the instantaneous speed of the GPS floating car is smaller than a second threshold value, the matching weight value is calculated by the following formula:
when the instantaneous speed of the GPS floating car is greater than a second threshold value, the matching weight value is calculated by the following formula:
wherein,is the matching weight value of the ith candidate link,is a normalized value of the vertical distance of the current GPS point from the ith candidate segment, is a normalized value of an included angle between the running direction of the GPS floating car and the direction of the ith candidate road section,kθis the weight coefficient, k, of the direction of traveldIs a weight coefficient, k, of the vertical distance of the current GPS point from the ith candidate road sectionθ+kdI is any positive integer and i is ≦ n.
3. The method for judging the traffic state based on the GPS floating car information as claimed in claim 2, wherein in the matching weight value formula,
and is
Wherein d isiIs the vertical distance, Delta, of the current GPS point from the ith candidate road segmentGPSIs the average error of the current GPS point, θiAnd the included angle between the running direction of the GPS floating car and the ith candidate road section direction is determined.
4. The method of claim 3, wherein θ is a value obtained by subtracting the GPS floating car information from the GPS floating car informationiCalculated by the following formula:
θi＝abs(θ2-θg)×π/180
wherein, theta2Is the direction angle, theta, of the ith candidate linkgThe direction angle of the GPS floating car.
5. According to claimThe method for determining a traffic state based on the GPS floating car information according to claim 1, wherein in the step (6), the two candidate road segments having the largest matching weight values are the road segment a and the road segment B, respectively, and the matching point of the road segment a is (X)A，YA) The matching point of the road section B is (X)B，YB) Said XA，XBRespectively, the abscissa of the road section A and the road section B, the YA，YBAnd the final candidate road sections are determined according to the coordinate size of the matching points of the road section A and the road section B and the angle of the running direction of the GPS floating car.
6. The method for judging the traffic state based on the GPS floating car information as claimed in claim 5, wherein the final candidate road section is specifically:
when X is presentA＞XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＞XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section A;
when X is presentA＜XBAnd the angle of the running direction of the GPS floating car is [90 degrees ], 270 degrees]In the meantime, the final candidate road section is a road section A;
when X is presentA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 90 degrees) ∪ (270 degrees and 360 degrees), the final candidate road section is a road section B;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is a road section A;
when X is presentA＝XB，YA＞YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [225 degrees ], 315 degrees DEG]In the meantime, the final candidate road section is the road section B;
when X is presentA＝XB，YA＜YBAnd the angle of the running direction of the GPS floating car is [45 degrees ], 135 degrees]In the meantime, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section B;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between 135 degrees and 225 degrees, the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBWhen the angle of the running direction of the GPS floating car is between (0 degrees and 45 degrees) ∪ (315 degrees and 360 degrees), the final candidate road section is a road section A;
when Y isA＝YB，XA＜XBAnd when the angle of the running direction of the GPS floating car is between (135 degrees and 225 degrees), the final candidate road section is the road section B.
7. The method for determining a traffic state based on GPS floating car information according to claim 6, wherein when the travel direction of the GPS floating car is in the due north direction, the angle of the travel direction of the GPS floating car is 0 °.
8. The method for determining the traffic state based on the GPS floating car information according to claim 1, wherein in the step (7), the step of obtaining the link speed of any candidate link comprises the steps of:
(7.1) calculating the average speed of any one candidate road section at the first cycle threshold;
(7.2) judging whether the average speed which is greater than the third threshold value or less than the fourth threshold value exists, if so, rejecting the average speed and continuing the step (7.3), otherwise, directly carrying out the step (7.3);
and (7.3) averaging the remaining average speeds to obtain the speed of the road section.
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