CN110310476B - Road congestion degree evaluation method and device, computer equipment and storage medium - Google Patents
Road congestion degree evaluation method and device, computer equipment and storage medium Download PDFInfo
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- CN110310476B CN110310476B CN201910371277.8A CN201910371277A CN110310476B CN 110310476 B CN110310476 B CN 110310476B CN 201910371277 A CN201910371277 A CN 201910371277A CN 110310476 B CN110310476 B CN 110310476B
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- G08G1/00—Traffic control systems for road vehicles
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Abstract
The application belongs to the technical field of big data, and relates to a method and a device for evaluating road congestion degree, computer equipment and a storage medium. The method comprises the following steps: determining N selected road sections in a road network database, wherein N is a positive integer; obtaining the maximum traffic flow Bi (i-1, i-2, i-3 … … i-N) of each selected road section in a preset time period from a traffic flow database; acquiring the traffic flow Ai (i-1, i-2, i-3 … … i-N) of each selected road section in the evaluation time period from a traffic flow database; calculating a congestion index ei of each selected road section in the evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi; calculating the weight wi of contribution of each selected road section to the congestion conditions of all the selected road sections according to the obtained maximum traffic flow Bi; and calculating the congestion indexes E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi contributing to the congestion conditions of all the selected road sections. The method can accurately evaluate the congestion degree of the road.
Description
Technical Field
The application belongs to the technical field of big data, and relates to a method and a device for evaluating road congestion degree, computer equipment and a storage medium.
Background
The road gate refers to an electronic device distributed at a road gate for collecting vehicle information data. The electronic eye at the road junction is one of the road bayonets. The road gate adopts photoelectric technology, image processing technology, pattern recognition technology and the like to acquire information data such as images of each passing vehicle. And the information data of the vehicles collected by the road gate is stored in a traffic flow database. The number of vehicles passing through a road section per unit time can be acquired through the traffic database.
Under the existing technical conditions, the evaluation on the road congestion degree is limited to a limited road section, or only a less accurate evaluation can be carried out on the whole route between two places, and the method lacks sufficient guiding significance for traveling. In addition, under the existing technical conditions, the road congestion degree of the road network in a geographic area cannot be evaluated, which is not beneficial to knowing the traffic condition of the road network in a geographic area.
Disclosure of Invention
The embodiment of the application discloses a method, a device, equipment and a storage medium for evaluating road congestion degree, and aims to accurately evaluate the congestion degree of a road.
Some embodiments of the present application disclose a method for evaluating a degree of road congestion. The method for evaluating the road congestion degree comprises the following steps: determining N selected road sections in a road network database, wherein N is a positive integer; obtaining the maximum traffic flow Bi (i ═ 1, i ═ 2, i ═ 3 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·; acquiring the traffic flow Ai (i ═ 1, i ═ 2, i ═ 3 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·; calculating a congestion index ei of each selected road section in the evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi; calculating the weight wi of contribution of each selected road section to the congestion conditions of all the selected road sections according to the obtained maximum traffic flow Bi; and calculating the congestion indexes E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi contributing to the congestion conditions of all the selected road sections.
In some embodiments of the present application, the step of calculating the congestion index ei of each selected road segment in the evaluation period according to the acquired traffic flow Ai and the maximum traffic flow Bi includes: calculating the congestion index ei of each selected road segment in the evaluation time period according to the following formula:
in some embodiments of the present application, the step of calculating the weight wi of each selected road segment contributing to the congestion condition of all selected road segments according to the obtained maximum traffic flow Bi includes: calculating the weight wi that each selected road segment contributes to the congestion condition of all selected road segments according to the following formula:
in some embodiments of the present application, the step of calculating the congestion index E for all selected road segments in combination with the congestion index ei for each selected road segment and the weight wi of the contribution to congestion conditions for all selected road segments comprises: calculating the congestion index E for all selected road segments according to the following formula:
in some embodiments of the present application, the method for evaluating road congestion degree further includes obtaining a weight adjustment parameter ki.
In some embodiments of the present application, the step of calculating the congestion index E for all selected road segments in combination with the congestion index ei for each selected road segment and the weight wi of the contribution to congestion conditions for all selected road segments comprises: calculating the congestion index E for all selected road segments according to the following formula:
In some embodiments of the present application, the step of obtaining the weight adjustment parameter includes: establishing a mapping table of the number of lanes, the road width value, the road length value and the value of the weight adjustment parameter ki; acquiring the number of lanes, the road width value and the road length value of each selected road section; and acquiring the value of the corresponding weight adjustment parameter ki in the mapping table according to the number of the lanes, the road width value and the road length value of each selected road section.
In some embodiments of the present application, the greater the number of lanes, the greater the road width value, and the greater the road length value of the selected road segment, the greater the value of the weight adjustment parameter ki; k is more than 0i＜1。
An embodiment of the application discloses evaluation device of road congestion degree. The evaluation device for the road congestion degree comprises: the road section selection module is used for determining N selected road sections in a road network database, wherein N is a positive integer; the first traffic flow acquiring module is used for acquiring the maximum traffic flow Bi (i ═ 1, i ═ 2, i · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·; a second traffic acquiring module, configured to acquire traffic flow Ai (i ═ 1, i ═ 2, i · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·; the road section congestion index calculation module is used for calculating a congestion index ei of each selected road section in an evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi; the weight calculation module is used for calculating the weight wi of the contribution of each selected road section to the congestion conditions of all the selected road sections according to the acquired maximum traffic flow Bi; and the overall congestion index calculation module is used for calculating the congestion indexes E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi contributing to the congestion conditions of all the selected road sections.
In some embodiments of the present application, the link congestion index calculation module calculates the congestion index ei for each selected link over an evaluation period according to the following formula:
in some embodiments of the present application, the weight calculation module calculates the weight wi that each selected road segment contributes to the congestion condition of all selected road segments according to the following formula:
in some embodiments of the present application, the overall congestion index calculation module includes a first congestion index calculation unit configured to calculate congestion indexes E of all selected road segments according to the following formula:
in some embodiments of the present application, the apparatus for evaluating road congestion degree further includes a weight adjustment parameter module, configured to obtain a weight adjustment parameter ki.
In some embodiments of the present application, the overall congestion index calculation module includes a second congestion index calculation unit, which is configured to calculate the congestion index E of all selected road segments according to the following formula:
In some embodiments of the present application, the weight adjustment parameter module comprises: the mapping table unit is used for establishing a mapping table of the number of lanes, the road width value, the road length value and the value of the weight adjustment parameter ki; the road information acquisition unit is used for acquiring the number of lanes, the road width value and the road length value of each selected road section; and the weight adjustment parameter acquisition unit is used for acquiring the value of the corresponding weight adjustment parameter ki in the mapping table according to the number of lanes, the road width value and the road length value of each selected road section.
Some embodiments of the present application disclose a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the above methods for assessing road congestion level when executing the computer program.
Some embodiments of the present application disclose a computer-readable storage medium having a computer program stored thereon, which, when being executed by a processor, implements the steps of any one of the above-mentioned methods for assessing a degree of road congestion.
Compared with the prior art, the technical scheme disclosed by the application mainly has the following beneficial effects:
in the embodiment of the application, the method for evaluating road congestion degree can select partial road sections or all road sections of a road network in a geographic area to evaluate the road congestion degree, and is beneficial to the evaluation and expansion of the road congestion degree into a geographic area, so that the method for evaluating road congestion degree can help to know the traffic condition of the road network in a geographic area. In the embodiment of the application, the method for evaluating the road congestion degree calculates the congestion index ei of each selected road section in the evaluation time period, then calculates the weight wi of each selected road section contributing to the congestion conditions of all the selected road sections, and finally calculates the congestion index E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi of each selected road section contributing to the congestion conditions of all the selected road sections. Therefore, the method for evaluating the road congestion degree reflects the influence of each selected road section on the congestion degrees of all the selected road sections, and can accurately evaluate the congestion degree of the road.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
FIG. 1 is a schematic illustration of two directional road segments R1 and R2 in an embodiment of the present application;
fig. 2 is a schematic diagram illustrating a method for evaluating a road congestion degree according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram illustrating a step of obtaining a weight adjustment parameter ki according to an embodiment of the present application;
FIG. 4 is a schematic diagram of road networks in a geographic area according to an embodiment of the present application;
FIG. 5 is a schematic diagram of road networks in a geographic area according to another embodiment of the present application;
fig. 6 is an exemplary diagram of the device for evaluating road congestion degree according to an embodiment of the present application;
fig. 7 is a schematic diagram of the overall congestion index calculation module 60 according to an embodiment of the present application;
FIG. 8 is a diagram of a weight adjustment parameter module 70 according to another embodiment of the present application;
fig. 9 is a block diagram illustrating a basic structure of a computer device 100 according to an embodiment of the present application.
Description of reference numerals:
Detailed Description
To facilitate an understanding of the present application, the present application will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present application are shown in the drawings. This application may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
An embodiment of the application discloses a method for evaluating road congestion degree.
Referring to fig. 1 and 2, fig. 1 is a schematic diagram of two directional road segments R1 and R2 according to an embodiment of the present disclosure, and fig. 2 is a schematic diagram of the method for evaluating road congestion level according to an embodiment of the present disclosure.
As illustrated in fig. 1, in the embodiment of the present application, the road between the road mount f1 and the road mount f2 has no branch, forming a road unit. A road section R1 is arranged between the road bayonet f1 and the road bayonet f2, and the direction of the road section R1 is that the road bayonet f1 points to the road bayonet f 2. The road between the road gate f3 and the road gate f4 has no branch, forming another road unit. A road section R2 is arranged between the road bayonet f3 and the road bayonet f4, and the direction of the road section R2 is that the road bayonet f3 points to the road bayonet f 4. In the embodiments of the present application, all road segments within one geographic area are referred to as road network. Road bayonets are arranged at road openings of the road network and used for collecting information data such as images of each passing vehicle. And information data such as images and the like acquired by all road checkpoints form a road network database. Analyzing the road network database can obtain the traffic flow passing through a certain road section in a time period. In order to evaluate the degree of road congestion in a geographic area, a plurality of road segments in the geographic area need to be selected for evaluation, or all the road segments in the geographic area may be selected for evaluation.
As illustrated in fig. 2, the method for evaluating the degree of road congestion includes:
s1: determining N selected road segments in a road network database, wherein N is a positive integer, and the road segments refer to road units which do not contain branches and have directionality.
S2: and acquiring the maximum traffic flow Bi (i & lt1 & gt, i & lt2 & gt, i & lt3 & gtin & ltn & gt) of each selected road section in a preset time period from a traffic flow database.
Referring to table 1 below, for example, a selected road segment is obtained from the road network database from 1/month 1/2018 to 1/month 7/2018 in morning 7: and selecting the traffic flow with the maximum traffic flow value from the traffic flows of 00 to 9:00 as the maximum traffic flow.
| 2018-1-1 | 7:00～9:00 | 100100 |
| 2018-1-2 | 7:00～9:00 | 100020 |
| 2018-1-3 | 7:00～9:00 | 100010 |
| 2018-1-4 | 7:00～9:00 | 100030 |
| 2018-1-5 | 7:00～9:00 | 100050 |
| 2018-1-6 | 7:00～9:00 | 100200 (maximum traffic flow) |
| 2018-1-7 | 7:00～9:00 | 100090 |
Table 1
And the maximum traffic flow Bi of each selected road section in the preset time period constitutes a maximum traffic flow data set.
S3: and acquiring the traffic flow Ai (i-1, i-2, i-3. i. N) of each selected road section in the evaluation time period from a traffic flow database.
Referring to table 2 below, for example, a selected road segment is obtained from the road network database from 1/8/2018 to 1/14/2018 in the morning 7: all traffic flows from 00 to 9: 00.
| 2018-1-8 | 7:00～9:00 | 99100 |
| 2018-1-9 | 7:00～9:00 | 100045 |
| 2018-1-10 | 7:00～9:00 | 100013 |
| 2018-1-11 | 7:00～9:00 | 100510 |
| 2018-1-12 | 7:00～9:00 | 101230 |
| 2018-1-13 | 7:00～9:00 | 102143 |
| 2018-1-14 | 7:00～9:00 | 100253 |
Table 2
The traffic Ai of each selected section during the evaluation period constitutes a traffic data set during the evaluation period.
In an embodiment of the present application, the congestion index of the selected road segment is estimated mainly by using the maximum traffic data set and the traffic data set in the estimation time period in a congestion degree estimation model.
The congestion degree evaluation model is mainly used for realizing the following steps:
s4: and calculating the congestion index ei of each selected road section in the evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi.
In some embodiments of the present application, a ratio of the traffic flow Ai of each selected section in the evaluation period to the maximum traffic flow Bi of each selected section in the preset period is used as the congestion index ei.
The step of calculating the congestion index ei of each selected road section in the evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi comprises the following steps: calculating the congestion index ei of each selected road segment in the evaluation time period according to the following formula:
s5: and calculating the weight wi of contribution of each selected road section to the congestion conditions of all the selected road sections according to the acquired maximum traffic flow Bi.
In some embodiments of the present application, a ratio of the maximum traffic flow of each selected road segment in the preset time period to a sum of the maximum traffic flows of all the selected road segments in the preset time period is used as the weight wi.
The step of calculating the weight wi of each selected road section contributing to the congestion conditions of all the selected road sections according to the acquired maximum traffic flow Bi comprises the following steps: calculating the weight wi that each selected road segment contributes to the congestion condition of all selected road segments according to the following formula:
s6: and calculating the congestion indexes E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi contributing to the congestion conditions of all the selected road sections.
In some embodiments of the present application, the sum of the products of the congestion index ei and the weight wi for each selected road segment is taken as the congestion index E for all selected road segments.
The step of calculating the congestion index E for all selected road segments in combination with the congestion index ei for each selected road segment and the weight wi of the contribution to the congestion conditions for all selected road segments comprises: calculating the congestion index E for all selected road segments according to the following formula:
the duration of the evaluation time period is equal to the duration of the preset time period. And corresponding to the timing of the natural day, the timing starting point of the evaluation time period is the same as the timing starting point of the preset time period, and the timing end point of the evaluation time period is the same as the timing end point of the preset time period.
In the embodiment of the application, the method for evaluating road congestion degree can select partial road sections or all road sections of a road network in a geographic area to evaluate the road congestion degree, and is beneficial to the evaluation and expansion of the road congestion degree into a geographic area, so that the method for evaluating road congestion degree can help to know the traffic condition of the road network in a geographic area. In the embodiment of the application, the method for evaluating the road congestion degree calculates the congestion index ei of each selected road section in the evaluation time period, then calculates the weight wi of each selected road section contributing to the congestion conditions of all the selected road sections, and finally calculates the congestion index E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi of each selected road section contributing to the congestion conditions of all the selected road sections. Therefore, the method for evaluating the road congestion degree reflects the influence of each selected road section on the congestion degrees of all the selected road sections, and can accurately evaluate the congestion degree of the road.
In some embodiments of the present application, the step of calculating the congestion index E for all selected road segments in combination with the congestion index ei for each selected road segment and the weight wi of the contribution to congestion conditions for all selected road segments may also calculate the congestion index E for all selected road segments in the remaining manner. For example, the sum of the congestion index ei of each selected road segment multiplied by the weight wi and the weight adjustment parameter ki is used as the congestion index E of all selected road segments; and calculating the congestion index E of all selected road segments according to the following formula:
referring to fig. 3, a schematic diagram of a step of obtaining the weight adjustment parameter ki in an embodiment of the present application is shown.
In some embodiments of the present application, the method for evaluating road congestion degree further includes obtaining a weight adjustment parameter, including:
s71: and establishing a mapping table of the number of lanes, the road width value, the road length value and the value of the weight adjustment parameter ki.
A set of said number of lanes, said road width value and said road length value is mapped to a value of one of said weight adjustment parameters ki.
S72: and acquiring the number of lanes, the road width value and the road length value of each selected road section.
S73: and acquiring the value of the corresponding weight adjustment parameter ki in the mapping table according to the number of the lanes, the road width value and the road length value of each selected road section.
In some embodiments of the present application, the greater the number of lanes, the greater the road width value, and the greater the road length value of the selected road segment, the greater the value of the weight adjustment parameter ki;
0＜ki＜1。
it should be noted that, when the congestion indexes E of all the selected road segments are calculated according to the above two methods at the same time, the congestion indexes E of all the selected road segments may be selected and applied in an alternative manner. Are generally selected when all selected road segments are less correlated with one another (e.g., reverse traffic, farther apart, etc.)
The congestion index E for all selected road segments is calculated. Mutual association of selected road sectionsTo a greater extent (e.g. uniform direction of traffic, connections between road sections, etc.)
The congestion index E for all selected road segments is calculated.
The method for evaluating the degree of road congestion will be further described below by way of example.
Fig. 4 is a schematic diagram of a road network in a geographic area according to an embodiment of the present application.
As illustrated in fig. 4, this embodiment is mainly used to explain the road network composed of several road segments with inconsistent traffic directions, and the method for evaluating road congestion level in this application is applied to the road network.
A branch circuit is not arranged between the road bayonet h1 and the road bayonet h2 and serves as a road section P1; a branch circuit is not arranged between the road bayonet h3 and the road bayonet h4 and serves as a road section P2; a branch circuit is not arranged between the road bayonet h5 and the road bayonet h6 and serves as a road section P3; there is no branch between the road bayonet h7 and the road bayonet h8 as a road segment P4. The passing direction of the road section P1 is consistent with that of the road section P3, and the passing direction of the road section P2 and the road section P4 is opposite to that of the road section P1 and the road section P3.
Acquiring the maximum traffic flow B1 of the road section P1 in a preset time period from a traffic flow database; acquiring the maximum traffic flow B2 of the road section P2 in a preset time period from a traffic flow database; acquiring the maximum traffic flow B3 of the road section P3 in a preset time period from a traffic flow database; and acquiring the maximum traffic flow B4 of the road section P4 in a preset time period from a traffic flow database.
Acquiring the traffic flow A1 of the road segment P1 in an evaluation time period from a traffic flow database; acquiring the traffic flow A2 of the road segment P2 in an evaluation time period from a traffic flow database; acquiring the traffic flow A3 of the road segment P3 in an evaluation time period from a traffic flow database; and acquiring the traffic flow A4 of the road section P4 in the evaluation time period from a traffic flow database.
Calculating a congestion index e1 of the road segment P1 in an evaluation time period，
Calculating a congestion index e2 of the road segment P2 within the evaluation period,
calculating a congestion index e3 of the road segment P3 within the evaluation period,
calculating a congestion index e4 of the road segment P4 within the evaluation period,
calculating a weight w of the contribution of the road segment P1 to the congestion condition of all selected road segments1，
Calculating a weight w of the contribution of the road segment P2 to the congestion condition of all selected road segments2，
Calculating a weight w of the contribution of the road segment P3 to the congestion condition of all selected road segments3，
Calculating a weight w of the contribution of the road segment P4 to the congestion condition of all selected road segments4，
Calculating the congestion index E for all selected road segments according to the following formula:
E＝w1×e1+w2×e2+w3×e3+w4×e4。
and/or calculating the congestion index E of all selected road segments according to the following formula:
E＝k1×w1×e1+k2×w2×e2+k3×w3×e3+k4×w4×e4。
in the examples of the present application, k1For the weight adjustment parameter of the road segment P1, k1 is 0.8. k is a radical of3Adjusting a parameter, k, for the weight of the road section P330.8 is taken. k is a radical of2Adjusting a parameter, k, for the weight of the road section P22Take 0.5. k is a radical of4Adjusting a parameter, k, for the weight of the road section P44Take 0.5.
Fig. 5 is a schematic diagram of a road network in a geographic area according to another embodiment of the present application.
As illustrated in fig. 5, this embodiment is mainly used to explain the road congestion degree evaluation method applied in the present application to a route composed of a plurality of road segments whose traffic directions are consistent.
A branch circuit is not arranged between the road bayonet j1 and the road bayonet j2 and serves as a road section Q1; a branch circuit is not arranged between the road bayonet j2 and the road bayonet j3 and serves as a road section Q2; there is no branch between the road bayonet j3 and the road bayonet j4 as a section Q3. The traffic directions of the section Q1, the section Q2 and the section Q3 are consistent.
As described in the embodiment corresponding to fig. 4, the maximum traffic flow Bi of the road segment Q1, the road segment Q2 and the road segment Q3 in the preset time period is respectively obtained from the traffic flow database. Then, the traffic flow Ai of the section Q1, the section Q2 and the section Q3 in the evaluation period is obtained from a traffic flow database. Then, the congestion indexes ei of the road segment Q1, the road segment Q2, and the road segment Q3 in the evaluation time period are calculated, respectively. The weights wi of the contribution of the road segment Q1, the road segment Q2 and the road segment Q3 to the congestion status of all selected road segments are then calculated, respectively. Finally according to the formula
And/or formulas
The congestion index E for all selected road segments is calculated.
The above examples of the method for evaluating road congestion degree in the present application illustrate that the method for evaluating road congestion degree can be used for evaluating not only the congestion degree of a route road but also the congestion degree of a road network road in a geographic area.
An embodiment of the application discloses evaluation device of road congestion degree.
Fig. 6 is a diagram illustrating an example of the apparatus for evaluating road congestion degree according to an embodiment of the present application.
As illustrated in fig. 6, the apparatus for evaluating a degree of road congestion includes:
a road segment selection module 10, configured to determine N selected road segments in a road network database, where N is a positive integer.
The first traffic flow acquiring module 20 is configured to acquire a maximum traffic flow Bi (i ═ 1, i ═ 2, i · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·.
And a second traffic acquiring module 30, configured to acquire, from the traffic database, the traffic Ai (i ═ 1, i ═ 2, i · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·.
And the road section congestion index calculation module 40 is used for calculating a congestion index ei of each selected road section in the evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi.
And the weight calculation module 50 is configured to calculate a weight wi that each selected road section contributes to the congestion conditions of all the selected road sections according to the acquired maximum traffic flow Bi.
And the overall congestion index calculation module 60 is used for calculating the congestion index E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi of the congestion condition contribution of all the selected road sections.
In some embodiments of the present application, the link congestion index calculation module 40 is configured to calculate the congestion index ei for each selected link in an evaluation time period according to the following formula;
in some embodiments of the present application, the weight calculation module 50 will be configured to calculate the weight wi of each selected road segment contributing to the congestion condition of all selected road segments according to the following formula;
referring to fig. 7, a schematic diagram of the overall congestion index calculation module 60 according to an embodiment of the present application is shown.
As illustrated in fig. 7, the overall congestion index calculation module 60 includes a first congestion index calculation unit 61 and/or a second congestion index calculation unit 62.
The first congestion index calculation unit 61 is configured to calculate congestion indexes E of all selected road segments according to the following formula;
the second congestion index calculation unit 62 is configured to calculate congestion indexes E of all selected road segments according to the following formula;
it should be noted that the overall congestion index calculation module 60 may only include the first congestion index calculation unit 61 or the second congestion index calculation unit 62. When the overall congestion index calculation module 60 includes the first congestion index calculation unit 61 and the second congestion index calculation unit 62, the congestion indexes E of all selected links may be calculated by only the first congestion index calculation unit 61, may be calculated by only the second congestion index calculation unit 62, and may also be calculated by only the first congestion index calculation unit 61 and the second congestion index calculation unit 62.
Referring to fig. 8, a schematic diagram of a weight adjustment parameter module 70 according to another embodiment of the present application is shown.
In some embodiments of the present application, the device for evaluating road congestion degree further includes a weight adjustment parameter module 70.
As illustrated in fig. 8, the weight adjustment parameter module 70 includes:
a mapping table unit 71, configured to establish a mapping table of the number of lanes, the road width value, the road length value, and the value of the weight adjustment parameter ki.
A road information obtaining unit 72 for obtaining the number of lanes, the road width value, and the road length value of each selected road section.
And the weight adjustment parameter obtaining unit 73 is configured to obtain a value of a corresponding weight adjustment parameter ki in the mapping table according to the number of lanes, the road width value, and the road length value of each selected road segment.
An embodiment of the present application discloses a computer device. Referring to fig. 9, a block diagram of a basic structure of a computer device 100 according to an embodiment of the present application is shown.
As illustrated in fig. 9, the computer apparatus 100 includes a memory 101, a processor 102, and a network interface 103 communicatively connected to each other through a system bus. It is noted that only a computer device 100 having components 101 and 103 is shown in FIG. 9, but it is understood that not all of the illustrated components are required and that more or fewer components may alternatively be implemented. It should be understood by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculation and/or information processing according to instructions set or stored in advance, and the hardware includes but is not limited to a microprocessor, an Application Specific Integrated Circuit (ASIC), a Programmable Gate Array (FPGA), a Digital Signal Processor (DSP), an embedded device, and the like.
The computer device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The computer equipment can carry out man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch panel or voice control equipment and the like.
The memory 101 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the storage 101 may be an internal storage unit of the computer device 100, such as a hard disk or a memory of the computer device 100. In other embodiments, the memory 101 may also be an external storage device of the computer device 100, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the computer device 100. Of course, the memory 101 may also include both internal and external storage devices of the computer device 100. In this embodiment, the memory 101 is generally used for storing an operating system installed in the computer device 100 and various types of application software, such as program codes of the above-mentioned road congestion degree evaluation method. Further, the memory 101 may also be used to temporarily store various types of data that have been output or are to be output.
The processor 102 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 102 is generally operative to control overall operation of the computer device 100. In this embodiment, the processor 102 is configured to run a program code stored in the memory 101 or process data, for example, a program code of the above-mentioned method for estimating the degree of road congestion.
The network interface 103 may comprise a wireless network interface or a wired network interface, and the network interface 103 is generally used for establishing communication connection between the computer device 100 and other electronic devices.
The present application provides yet another embodiment, which is to provide a computer-readable storage medium storing a document information entry program, which is executable by at least one processor to cause the at least one processor to perform the steps of any one of the above methods for assessing road congestion level.
Finally, it should be noted that the above-mentioned embodiments illustrate only some of the embodiments of the present application, and are therefore not to be considered limiting of its scope, for the invention may admit to other equally effective embodiments. This application is capable of embodiments in many different forms and is provided for the purpose of enabling a thorough understanding of the disclosure of the application. Although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to one skilled in the art that the present application may be practiced without modification or with equivalents of some of the features described in the foregoing embodiments. All equivalent structures made by using the contents of the specification and the drawings of the present application are directly or indirectly applied to other related technical fields and are within the protection scope of the present application.
Claims (8)
1. A method for evaluating a road congestion degree, comprising:
determining N selected road sections in a road network database, wherein N is a positive integer, the selected road sections refer to road units which do not contain branches and have directionality, and road bayonets are arranged at intersections of the roads and used for collecting information data of each passing vehicle and sending the information data to the road network database for storage;
obtaining the maximum traffic flow Bi (i ═ 1, i ═ 2, i ═ 3 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·;
acquiring the traffic flow Ai (i ═ 1, i ═ 2, i ═ 3 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · N) of each selected road section;
calculating a congestion index ei of each selected road section in the evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi;
calculating the weight wi of contribution of each selected road section to the congestion conditions of all the selected road sections according to the obtained maximum traffic flow Bi;
calculating the congestion indexes E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi contributing to the congestion conditions of all the selected road sections;
wherein the step of calculating the congestion index E for all selected road segments in combination with the congestion index ei for each selected road segment and the weight wi of contribution to congestion conditions for all selected road segments comprises:
calculating the congestion index E for all selected road segments according to the following formula:
or
Calculating the congestion index E for all selected road segments according to the following formula:
wherein ei is a congestion index of each selected road section in the evaluation time period, wi is a weight contributed by each selected road section to the congestion conditions of all selected road sections, ki is a weight adjustment parameter, 0<ki<1; when the mutual correlation degree of all the selected road sections is low, selecting the selected road section
Calculating congestion indexes E of all selected road sections; when the mutual correlation degree of all the selected road sections is higher, selecting the selected road section
The congestion index E for all selected road segments is calculated.
2. The method for evaluating a road congestion degree according to claim 1, wherein the step of calculating a congestion index ei of each selected section in the evaluation time period based on the acquired traffic flow Ai and the maximum traffic flow Bi comprises:
calculating the congestion index ei of each selected road segment in the evaluation time period according to the following formula:
3. the method for evaluating the degree of road congestion according to claim 1 or 2, wherein the step of calculating the weight wi of each selected link contributing to the congestion status of all the selected links according to the obtained maximum traffic flow Bi comprises:
calculating the weight wi that each selected road segment contributes to the congestion condition of all selected road segments according to the following formula:
4. the method for evaluating a road congestion degree according to claim 3, further comprising:
and acquiring a weight adjustment parameter ki.
5. The method for evaluating road congestion degree according to claim 4, wherein the step of obtaining the weight adjustment parameter comprises:
establishing a mapping table of the number of lanes, the road width value, the road length value and the value of the weight adjustment parameter ki;
acquiring the number of lanes, the road width value and the road length value of each selected road section;
and acquiring the value of the corresponding weight adjustment parameter ki in the mapping table according to the number of the lanes, the road width value and the road length value of each selected road section.
6. An apparatus for evaluating a degree of road congestion, comprising:
the system comprises a road section selection module, a road network database and a traffic information acquisition module, wherein the road section selection module is used for determining N selected road sections in the road network database, N is a positive integer, the selected road sections refer to road units which do not contain branches and have directionality, and road bayonets are arranged at intersections of roads and are used for acquiring information data of each passing vehicle and sending the information data to the road network database for storage;
the first traffic flow acquiring module is used for acquiring the maximum traffic flow Bi (i ═ 1, i ═ 2, i · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·;
a second traffic acquiring module, configured to acquire traffic flow Ai (i ═ 1, i ═ 2, i · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · ·;
the road section congestion index calculation module is used for calculating a congestion index ei of each selected road section in an evaluation time period according to the acquired traffic flow Ai and the maximum traffic flow Bi;
the weight calculation module is used for calculating the weight wi of the contribution of each selected road section to the congestion conditions of all the selected road sections according to the acquired maximum traffic flow Bi;
the overall congestion index calculation module is used for calculating the congestion indexes E of all the selected road sections by combining the congestion index ei of each selected road section and the weight wi contributing to the congestion conditions of all the selected road sections;
wherein the step of calculating the congestion index E for all the selected road segments in combination with the congestion index ei for each selected road segment and the weight wi of the contribution to the congestion conditions for all the selected road segments comprises:
calculating the congestion index E for all selected road segments according to the following formula:
or
Calculating the congestion index E for all selected road segments according to the following formula:
wherein ei is a congestion index of each selected road section in the evaluation time period, wi is a weight contributed by each selected road section to the congestion conditions of all selected road sections, ki is a weight adjustment parameter, 0<ki<1; when the mutual correlation degree of all the selected road sections is low, selecting the selected road section
Calculating congestion indexes E of all selected road sections; when the mutual correlation degree of all the selected road sections is higher, selecting the selected road section
The congestion index E for all selected road segments is calculated.
7. A computer device comprising a memory and a processor, characterized in that the memory has stored therein a computer program which, when executed by the processor, carries out the steps of the method of assessing a degree of road congestion as claimed in any one of claims 1 to 5.
8. A computer-readable storage medium, characterized in that a computer program is stored thereon, which, when being executed by a processor, carries out the steps of the method for assessing a degree of road congestion according to any one of claims 1 to 5.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103593976A (en) * | 2013-11-28 | 2014-02-19 | 青岛海信网络科技股份有限公司 | Road traffic state determining method and system based on detector |
| CN105023434A (en) * | 2015-07-03 | 2015-11-04 | 信融源大数据科技(北京)有限公司 | Method for obtaining congestion index of motorway |
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|---|---|---|---|---|
| CN103280098B (en) * | 2013-05-23 | 2015-06-10 | 北京交通发展研究中心 | Traffic congestion index calculation method |
| CN105405294A (en) * | 2015-12-30 | 2016-03-16 | 杭州中奥科技有限公司 | Early warning method of traffic congestion roads |
| CN107749165A (en) * | 2017-12-06 | 2018-03-02 | 四川九洲视讯科技有限责任公司 | Computational methods based on urban road congestion index |
| CN108847025A (en) * | 2018-08-28 | 2018-11-20 | 电子科技大学 | A kind of traffic congestion determination method |
| CN109087509B (en) * | 2018-09-04 | 2020-03-31 | 重庆交通大学 | Road network traffic running state prediction method |
| CN109147329B (en) * | 2018-09-18 | 2020-11-03 | 银江股份有限公司 | Regional traffic running state index calculation and visualization method based on traffic capacity |
-
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103593976A (en) * | 2013-11-28 | 2014-02-19 | 青岛海信网络科技股份有限公司 | Road traffic state determining method and system based on detector |
| CN105023434A (en) * | 2015-07-03 | 2015-11-04 | 信融源大数据科技(北京)有限公司 | Method for obtaining congestion index of motorway |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP4064239A3 (en) * | 2021-06-30 | 2023-01-04 | Apollo Intelligent Connectivity (Beijing) Technology Co., Ltd. | Method and apparatus of determining state of intersection, storage medium, and program product |
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