CN113947925A - Green wave evaluation method, device and equipment based on electronic police data - Google Patents
Green wave evaluation method, device and equipment based on electronic police data Download PDFInfo
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Abstract
The invention discloses a green wave evaluation method, a device and equipment based on electronic police data, aiming at the problem of increasingly serious traffic jam at present, the travel time of a vehicle between signalized intersections is obtained by obtaining the electronic police data and comparing the license plate data of matched vehicles between adjacent signalized intersections; dividing time periods, and obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time and the different time periods; and then, analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times, and judging whether the green wave signal of the current road section at the current time interval needs to be optimized. Therefore, the traffic management department can conveniently perform coordination control on the signal lamp, and the traffic jam problem is further relieved or solved.
Description
Technical Field
The invention belongs to the technical field of intelligent traffic control, and particularly relates to a green wave evaluation method, device and equipment based on electronic police data.
Background
With the continuous development of social productivity and the continuous progress of human society, the urbanization level of China is higher and higher, the number of motor vehicles is rapidly increased, the urban traffic problem is more and more serious, and the serious traffic jam phenomenon is seen and experienced by everyone. The reasons for this are mainly: the traffic flow management system has the advantages that firstly, the traffic capacity of the existing road network is insufficient, secondly, the road orientation of the existing road network is unreasonable, and thirdly, the management and control on the traffic flow are weak. There are two fundamental approaches to solving the urban traffic problem: firstly, the construction of traffic facilities is accelerated; secondly, strengthen the traffic management. However, the possibility of building or extending existing roads in cities is becoming less and less, and thus enhancing the rational utilization of existing roads and the effective control and management of traffic lights is becoming an important way to improve traffic conditions.
The intelligent traffic system is suitable for needs, the quality of traffic cooperative control is important in the intelligent traffic system, the traffic light state of the intersection can be timely and accurately acquired, the change process of road smoothness and road congestion can be reflected in real time, a reference value is provided for management and optimization of traffic signal control, the traffic efficiency of urban road network traffic can be better evaluated, and the traffic efficiency evaluation method is a key factor for measuring the urban traffic service level. The appearance of electronic police provides huge space for the development of urban traffic, the conventional detection equipment (such as geomagnetic induction coil data, RFID data, GPS data and the like) has the defects of detection error, signal loss, interference, limited equipment coverage and the like, the traffic flow condition of continuous intersections needs to be considered sometimes, the required data amount is huge, and the defects exist in practical application. With the change of the detection mode, the electronic police develops rapidly, can better solve the situations of signal loss, unstable data and the like in the past, can provide the track information of the vehicle, and can be used as important data support in green wave optimization research.
Disclosure of Invention
The invention aims to provide a green wave evaluation method, a green wave evaluation device and green wave evaluation equipment based on electronic police data, which realize evaluation of green wave signals of road sections by using indexes such as travel time, segmentation time periods and saturated traffic flow calculation of vehicles and have better applicability and operability.
In order to solve the problems, the technical scheme of the invention is as follows:
a green wave evaluation method based on electronic police data comprises the following steps:
acquiring electronic police data, wherein the electronic police data at least comprise a license plate number of a vehicle, a vehicle type and the time when the vehicle leaves a stop line; comparing the license plate data of matched vehicles between adjacent signalized intersections to obtain the travel time of the vehicles between the signalized intersections; the matched vehicles are vehicles captured by an electronic police at an upstream signalized intersection and a current signalized intersection;
obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time at different time intervals;
and analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times, and judging whether the green wave signal of the current road section at the current time interval needs to be optimized.
According to an embodiment of the present invention, the obtaining the number of times of stopping the vehicle on the current road section according to the distribution of the vehicle travel time at different time intervals further includes:
if the travel time T epsilon of the vehicle (T)0+(n-1)C,T0+ nC), the number of times of stopping the vehicle is recorded as n; if the travel time T epsilon of the vehicle (T)0+nC+g,T0+ (n +1) C), recording the number of times of parking of the vehicle as n + 1; if the travel time T epsilon of the vehicle (T)0+nC,T0+ nC + g), the number of times of parking of the vehicle is n or n + 1;
wherein C represents the time from the start of a red light to the end of a green light, g represents the duration of a green light, T0Representing the free road travel time of the current road segment.
According to an embodiment of the present invention, the obtaining the number of times of stopping the vehicle on the current road section according to the distribution of the vehicle travel time at different time intervals further includes:
according to the calculation formula:
obtaining the average parking times of the vehicles on the current road section; where ST represents the average number of stops, tx-t0 is the vehicle travel time, and Ts represents the total travel time of the current road segment.
According to an embodiment of the present invention, the method for acquiring electronic police data further comprises:
and (3) carrying out data cleaning on the electronic police data, and correcting abnormal values and supplementing missing values by using a mode of combining statistics and machine learning.
According to an embodiment of the present invention, the analyzing the traffic flow of the current road segment at each time interval according to the vehicle travel time and the vehicle parking times further includes:
when the number qC of vehicles on the current road section is greater than the number sg of discharged vehicles in the green light period in a signal period C, the current intersection is in an oversaturation state, and vehicle detention occurs; where C denotes the time from the start of the red light to the end of the green light, q denotes the vehicle arrival rate, s denotes the vehicle saturation flow rate, and g denotes the effective green light period.
A green wave evaluation device based on electronic police data comprises:
the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring electronic police data, and the electronic police data at least comprise a license plate number of a vehicle, a vehicle type and the time when the vehicle drives off a stop line; comparing the license plate data of matched vehicles between adjacent signalized intersections to obtain the travel time of the vehicles between the signalized intersections; the matched vehicles are vehicles captured by an electronic police at an upstream signalized intersection and a current signalized intersection;
the first data analysis module is used for obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time at different time intervals;
and the second data analysis module is used for analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times and judging whether the green wave signal of the current road section at the current time interval needs to be optimized.
A green wave evaluation device based on electronic police data, comprising:
a memory having instructions stored therein and a processor, the memory and the processor interconnected by a line;
the processor calls the instruction in the memory to realize the green wave evaluation method based on the electronic police data in one embodiment of the invention.
A computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements an electronic police data-based green wave evaluation method in an embodiment of the present invention.
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects:
aiming at the current increasingly serious traffic jam problem, the green wave evaluation method based on the electronic police data obtains the travel time of the vehicle between the signalized intersections by obtaining the electronic police data and comparing the license plate data of the matched vehicles between the adjacent signalized intersections; dividing time periods, and obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time and the different time periods; and then, analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times, and judging whether the green wave signal of the current road section at the current time interval needs to be optimized. Therefore, the traffic management department can conveniently perform coordination control on the signal lamp, and the traffic jam problem is further relieved or solved.
Drawings
FIG. 1 is a flow diagram of a green wave evaluation method based on electronic police data in an embodiment of the present invention;
FIG. 2 is a schematic view of an electronic police officer installation in one embodiment of the present invention;
FIG. 3 is a schematic view of an intersection number according to an embodiment of the present invention;
FIG. 4 is a graph of the number of parked vehicles versus the number of vehicles in an embodiment of the present invention;
FIG. 5 is a block diagram of an electronic police data based green wave evaluation device in an embodiment of the present invention;
fig. 6 is a schematic diagram of a green wave evaluation device based on electronic police data according to an embodiment of the invention.
Detailed Description
The following describes a green wave evaluation method, device and apparatus based on electronic police data in detail with reference to the accompanying drawings and specific embodiments. Advantages and features of the present invention will become apparent from the following description and from the claims.
Example one
The embodiment provides a green wave evaluation method based on electronic police data aiming at the current increasingly serious traffic jam problem, complex data such as signal timing, traffic flow, traffic starting waves and parking waves are not required to be acquired, and evaluation of green wave signals of a road section is achieved only by analyzing vehicle travel time data of key nodes and vehicle departure and intersection time data. Therefore, the traffic management department can conveniently perform coordination control on the signal lamp, and the traffic jam problem is further relieved or solved.
Specifically, referring to fig. 1, the green wave evaluation method based on electronic police data includes the following steps:
s1: acquiring electronic police data, wherein the electronic police data at least comprise a license plate number of a vehicle, a vehicle type and the time when the vehicle leaves a stop line; comparing the license plate data of matched vehicles between adjacent signalized intersections to obtain the travel time of the vehicles between the signalized intersections; the matched vehicles are vehicles captured by an electronic police at the upstream signalized intersection and the current signalized intersection;
s2: obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time at different time intervals;
s3: and analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times, and judging whether the green wave signal of the current road section at the current time interval needs to be optimized.
In step S1, the present embodiment uses the data of the electronic police officer as the data base for evaluation of the green wave signal. Generally, electronic police officers are installed at intersections, crossing gates, main and auxiliary road entrances and exits, and the like. Referring to fig. 2, "●" in the drawing indicates the installation location of an electronic police, and the license plate recognition information detected by a bayonet type electronic police is used. When a vehicle passes through a stop line, the high-definition digital camera shoots a picture of the tail part of the vehicle, and the electronic police system can process the picture according to the picture and extract vehicle information, so that refined electronic warning and wiping data are obtained. The data recorded in real time in all weather of the electronic police data comprises the following fields: collection location, lane number, vehicle direction of travel, time (timestamp), license plate type, license plate number, etc.
For a section of road L from the intersection a to BabFor example, a vehicle exits the stop line at intersection A and exits the stop line at intersection B, with a segment travel time Tab＝tb-ta. In the research process, the average value of the first 5 percent of the minimum travel time in the electricity alarm data in one day is taken as the free popular travel time T of the section0. The time at which the vehicle is driven off from the intersection stop line is referred to as a vehicle drive-off time, and the time elapsed from the drive-off of the upstream intersection stop line to the drive-off of the intersection stop line is referred to as a vehicle travel time.
Due to the fact that vehicles in actual road conditions have many accidents, electronic police data are abnormal or missing, and follow-up research and analysis on queuing length are affected. Therefore, data cleaning needs to be carried out on the electronic police data, and abnormal data and missing data are processed in an important mode. Situations where abnormal or missing data may be generated include:
firstly, in the midway running process of the vehicle, the time delay of stopping the vehicle (vehicle breaking, carrying passengers midway and the like) is higher than that of normally running the vehicle due to some special reasons;
secondly, the vehicle leaves the detection area from a branch without detection equipment during running, so that the electronic police system cannot match the license plate identification data;
thirdly, the vehicle travels for two or more times in the road section, so that the same license plate data appears in the electronic police system for multiple times;
and fourthly, an electronic police is not installed at the upstream intersection, so that the detection of the downstream intersection is inaccurate.
All above can lead to the electronic police data inaccurate, so this embodiment need do data washing to the electronic police data who gathers, guarantees the reliability of data. Abnormal data and missing data can be compensated and corrected by combining statistics and machine learning. If part of missing values are compensated by taking the mean value of adjacent points, the whole missing of the intersection data is compensated by using a machine learning algorithm, and abnormal data is corrected by using the mean value.
In step S2, the number of vehicle stops on the current road segment is obtained according to the distribution of the travel time of the vehicle in different time periods.
Because the vehicle travel time does not completely correspond to the time interval, the cleaned electronic police data can be divided into a plurality of traffic flow orders of magnitude, namely 100-200 traffic flows, 200-300 traffic flows, 300-400 traffic flows and saturated traffic flows. The division can be specifically performed according to the following rules:
A. the traffic flow is very little. The number of vehicles passing through the road section in unit time is between 0 and 100. The traffic flow at this time is said to be very low, most often occurring at night, as well as in the early morning. In this case, the vehicle speed is significantly greater than the link average vehicle speed. Many vehicles traveling in the green band may cause the vehicle to overrun, thereby losing the green band and catching up with the red light.
B. In the traffic stream, etc. The number of vehicles passing through the road section in unit time is between 100 and 500. The traffic flow at this time is called medium traffic flow, and most often occurs at noon. In most cases, the green wave band of the urban traffic lights is designed according to the design, in this case, the speed of the vehicle is basically equal to that of the lane-regulation vehicle, and the green wave coordination is basically stable.
C. The traffic flow is extremely large. The number of vehicles passing through the link per unit time is between 500 and the saturated number of vehicles. The traffic flow at this time is called as the maximum traffic flow, and most often occurs at the peak time in the morning and evening, and the traffic flow is too large, so that the normal green wave cannot be effectively coordinated.
And determining the number of times of parking of the vehicle in the driving process according to the travel time data acquired by the electronic police. If the travel time T epsilon of the vehicle (T)0+(n-1)C,T0+ nC), the number of times of stopping the vehicle is recorded as n; if the travel time T epsilon of the vehicle (T)0+nC+g,T0+ (n +1) C), recording the number of times of parking of the vehicle as n + 1; if the travel time T epsilon of the vehicle (T)0+nC,T0+ nC + g), the number of times of parking of the vehicle is n or n + 1; wherein C represents the time from the start of a red light to the end of a green light, g represents the duration of a green light, T0Representing the free road travel time of the current road segment.
In practical application, because the whole road network has a large data volume, one main road in a city is selected for analysis, and data is segmented. In electronic police data, each intersection has its own number. The road network numbering sequence is based on the main road and the continuous numbers, the main intersection numbering schematic diagram is shown in figure 3, the longest road section is selected according to the main road section number dividing conditions, and the road section with the number of 261 plus 264 is selected.
In the vehicle travel data of the link, traffic flow data through which the vehicle passes per unit travel time is divided. The data of the intercepted portion are shown in the following table:
| time stamp | License plate number | Direction of travel | LGID |
| 2018/10/5 0:01:36 | BRR725 | -1 | 19-1-20-1 |
| 2018/10/5 0:01:45 | E66612 | -1 | 25-3-24-5 |
| 2018/10/5 0:01:59 | EBG255 | -1 | 176-1-177-1 |
| 2018/10/5 0:01:40 | EMA715 | -1 | 183-3-191-5 |
| 2018/10/5 0:01:53 | MHW303 | -1 | 67-3-59-3 |
| 2018/10/5 0:01:32 | FY3308 | -1 | 145-5-202-5 |
| 2018/10/5 0:01:09 | E1Z81K | -1 | 81-7-96-7 |
By analyzing the travel time of the signal lights and the timing signals, the average number of stops of the vehicle can be obtained. ST is used to represent the number of times the vehicle stops, tx-t0 is the vehicle travel time, and Ts represents the total travel time of the current link. The calculation formula is as follows:
in this case, one dimension, that is, the number of stops, is added to the evaluation data of the green wave signal.
In step S3, the traffic flow of the current road segment at each time interval is analyzed according to the vehicle travel time and the vehicle parking times, and it is determined whether the green wave signal of the current road segment at the current time interval needs to be optimized.
Through the parking times of different time periods at the current intersection obtained in step S2, a relationship diagram of the parking times and the number of passing vehicles is drawn, as shown in fig. 4.
As can be seen from the figure, for the current intersection, when the number of vehicles is below 110, the vehicles can be basically ensured to run without resistance. After the number of vehicles is more than 210, the number of times of parking of the vehicles exceeds 3 times or is unequal, and is already larger than the number of intersections. At this time, the traffic is already in a very congested state, the traffic lights basically cannot show the traffic control effect, and the green wave signals at the current intersection need to be optimized.
Through the method, the green wave signals with the traffic flow of 0-100 can be found to have a good coordination control effect, but when the traffic flow is larger than 200, namely the traffic index is larger than 3.5, the coordination control capability of the green wave signals is poor, and the phase of the green wave signals is properly adjusted to achieve the best effect.
Example two
The present embodiment provides a green wave evaluation device based on electronic police data, please refer to fig. 5, the green wave evaluation device based on electronic police data includes:
the system comprises a data acquisition module 1, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring electronic police data, and the electronic police data at least comprise a license plate number of a vehicle, a vehicle type and the time when the vehicle drives off a stop line; comparing the license plate data of matched vehicles between adjacent signalized intersections to obtain the travel time of the vehicles between the signalized intersections; the matched vehicles are vehicles captured by an electronic police at the upstream signalized intersection and the current signalized intersection;
the first data analysis module 2 is used for obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time at different time intervals;
and the second data analysis module 3 is used for analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times and judging whether the green wave signal of the current road section at the current time interval needs to be optimized.
The data acquisition module 1 provides an interface for receiving data from an electronic police, and the data recorded by the electronic police in all-weather and real-time comprises the following fields: the electronic police data are transmitted to the first data analysis module 2 by collecting the location, the lane number, the vehicle driving direction, the time (time stamp), the license plate type, the license plate number and the like.
The first data analysis module 2 preprocesses the received electronic police data, corrects abnormal values and supplement missing values in a mode of combining statistics and machine learning, divides the time period and traffic flow of the data, and obtains the vehicle parking times of the current road section according to the distribution conditions of vehicle travel time in different time periods.
The second data analysis module 3 draws a relation schematic diagram of the parking times and the number of passing vehicles according to the parking times of different time periods obtained by the first data analysis module 2, so that the green wave signals of traffic flow of 0-100 have a good coordination control effect, when the traffic flow is larger than 200, namely the traffic index is larger than 3.5, the coordination control capability of the green wave signals is poor, and the phase of the green wave should be properly adjusted to achieve the best effect.
The functions and implementation manners of the data obtaining module 1, the first data analysis module 2, and the second data analysis module 3 are as described in the first embodiment, and are not described herein again.
EXAMPLE III
The embodiment provides a green wave evaluation device based on electronic police data. Referring to fig. 6, the electronic police data based green wave evaluation apparatus 500 may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 510 (e.g., one or more processors) and a memory 520, one or more storage media 530 (e.g., one or more mass storage devices) storing applications 533 or data 532. Memory 520 and storage media 530 may be, among other things, transient or persistent storage. The program stored on the storage medium 530 may include one or more modules (not shown), each of which may include a series of instructions operating on the green wave evaluation device 500 based on electronic police data.
Further, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the electronic police data based green wave evaluation device 500.
The electronic police data-based green wave evaluation device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input-output interfaces 560, and/or one or more operating systems 531, such as Windows service, Vista, and the like.
Those skilled in the art will appreciate that the configuration of the electronic police data based green wave evaluation device shown in fig. 6 does not constitute a limitation of the electronic police data based green wave evaluation device and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, and which may also be a volatile computer-readable storage medium. The computer readable storage medium has stored therein instructions which, when run on a computer, cause the computer to perform the steps of the green wave evaluation method based on electronic police data in the first embodiment.
The modules in the second embodiment, if implemented in the form of software functional modules and sold or used as independent products, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be substantially or partially implemented in software, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and devices may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments. Even if various changes are made to the present invention, it is still within the scope of the present invention if they fall within the scope of the claims of the present invention and their equivalents.
Claims (8)
1. A green wave evaluation method based on electronic police data is characterized by comprising the following steps:
acquiring electronic police data, wherein the electronic police data at least comprise a license plate number of a vehicle, a vehicle type and the time when the vehicle leaves a stop line; comparing the license plate data of matched vehicles between adjacent signalized intersections to obtain the travel time of the vehicles between the signalized intersections; the matched vehicles are vehicles captured by an electronic police at an upstream signalized intersection and a current signalized intersection;
obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time at different time intervals;
and analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times, and judging whether the green wave signal of the current road section at the current time interval needs to be optimized.
2. The green wave evaluation method based on electronic police data as claimed in claim 1, wherein the obtaining of the number of times of vehicle parking on the current road section according to the distribution of the vehicle travel time and the different time periods further comprises:
if the travel time T epsilon of the vehicle (T)0+(n-1)C,T0+ nC), the number of times of stopping the vehicle is recorded as n; if the travel time T epsilon of the vehicle (T)0+nC+g,T0+(n+1)C) If so, recording the number of times of parking of the vehicle as n + 1; if the travel time T epsilon of the vehicle (T)0+nC,T0+ nC + g), the number of times of parking of the vehicle is n or n + 1;
wherein C represents the time from the start of a red light to the end of a green light, g represents the duration of a green light, T0Representing the free road travel time of the current road segment.
3. The green wave evaluation method based on electronic police data as claimed in claim 1, wherein the obtaining of the number of times of vehicle parking on the current road section according to the distribution of the vehicle travel time and the different time periods further comprises:
according to the calculation formula:
obtaining the average parking times of the vehicles on the current road section; where ST represents the average number of stops, tx-t0 is the vehicle travel time, and Ts represents the total travel time of the current road segment.
4. The green wave evaluation method based on electronic police data as claimed in claim 1, wherein the step of obtaining the electronic police data further comprises:
and (3) carrying out data cleaning on the electronic police data, and correcting abnormal values and supplementing missing values by using a mode of combining statistics and machine learning.
5. The green wave evaluation method based on electronic police data as claimed in claim 1, wherein the analyzing the traffic flow of the current road section in each time period according to the vehicle travel time and the vehicle parking times further comprises:
when the number qC of vehicles on the current road section is greater than the number sg of discharged vehicles in the green light period in a signal period C, the current intersection is in an oversaturation state, and vehicle detention occurs; where C denotes the time from the start of the red light to the end of the green light, q denotes the vehicle arrival rate, s denotes the vehicle saturation flow rate, and g denotes the effective green light period.
6. A green wave evaluation device based on electronic police data is characterized by comprising:
the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring electronic police data, and the electronic police data at least comprise a license plate number of a vehicle, a vehicle type and the time when the vehicle drives off a stop line; comparing the license plate data of matched vehicles between adjacent signalized intersections to obtain the travel time of the vehicles between the signalized intersections; the matched vehicles are vehicles captured by an electronic police at an upstream signalized intersection and a current signalized intersection;
the first data analysis module is used for obtaining the vehicle parking times of the current road section according to the distribution conditions of the vehicle travel time at different time intervals;
and the second data analysis module is used for analyzing the traffic flow of the current road section at each time interval according to the vehicle travel time and the vehicle parking times and judging whether the green wave signal of the current road section at the current time interval needs to be optimized.
7. A green wave evaluation device based on electronic police data, comprising:
a memory having instructions stored therein and a processor, the memory and the processor interconnected by a line;
the processor invokes the instructions in the memory to implement the electronic police data-based green wave evaluation method of any of claims 1-5.
8. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the electronic police data-based green wave evaluation method according to any one of claims 1 to 5.
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| CN112885089A (en) * | 2021-01-25 | 2021-06-01 | 合肥学院 | Main line green wave intelligent diagnosis model based on multi-dimensional indexes |
| CN113380036A (en) * | 2021-06-16 | 2021-09-10 | 上海应用技术大学 | Queuing length calculation method based on electronic police data |
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