A smart traffic management method and system based on data analysis

Abstract

The present invention discloses a smart traffic management method and system based on data analysis, which belongs to the field of traffic. The smart traffic management method based on data analysis comprises the following steps: obtaining road data and obtaining speed limit information of the road; dividing the collected average vehicle speed in the road by the speed limit information set for the road to obtain a division value, wherein the larger the division value is, the better the congestion condition is judged to be, and the smaller the division value is, the beneficial effects of the present invention are as follows: the present invention judges the congestion condition by the average vehicle speed and speed limit information in the road, and arranges the priorities of the congestion conditions in a database table, and finally adjusts the duration of the signal light at the intersection based on the priority to increase the road traffic efficiency, thereby reducing traffic congestion; when it is found that adjusting the duration of the signal light cannot effectively increase the road traffic efficiency, it will be judged whether the road is abnormal, and timely feedback will be given to the map service provider to reduce the number of vehicles entering the road and reduce the occurrence of traffic congestion.

Description

Technical Field

[0001] The present invention relates to the field of transportation, and in particular to an intelligent transportation management method and system based on data analysis. Background Art

[0002] Some cities lack the support of key data such as traffic flow and vehicle speed when planning traffic lights, resulting in a lack of scientific basis for the planning. In addition, some cities do not fully consider the future growth of traffic flow when planning traffic lights, resulting in traffic light settings that are difficult to meet actual needs.

[0003] However, traditional traffic light control systems have technical limitations and cannot be adjusted in real time to adapt to changes in traffic flow. Unreasonable traffic light settings may cause vehicles to stop and start frequently, reduce road traffic efficiency, and cause traffic congestion, which needs to be improved. Summary of the invention

[0004] Based on this, it is necessary to provide a smart traffic management method and system based on data analysis to address the above problems.

[0005] The embodiment of the present invention is implemented as follows: a smart traffic management method based on data analysis, comprising the following steps:

[0006] Obtain road data and obtain road speed limit information;

[0007] Divide the collected average speed on the road by the speed limit information set on the road to obtain a division value. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be, thus completing the judgment of the road congestion situation;

[0008] Control the traffic lights at traffic intersections based on road congestion conditions.

[0009] In one embodiment, the present invention provides a smart traffic management method based on data analysis, wherein the step of obtaining road data and obtaining road speed limit information specifically includes:

[0010] Obtain road data. The sources of road data include but are not limited to government transportation departments, map service providers (such as Amap, Baidu Map, etc.), and professional geographic information system (GIS) data providers; road data includes road name, location, and type (such as expressways, national roads, provincial roads, etc.);

[0011] Obtaining the speed limit information of the road, including by checking the official website and identifying the road sign; associating the speed limit information with the corresponding road;

[0012] Use database software (such as MySQL, PostgreSQL, etc.) or GIS software (such as ArcGIS, QGIS, etc.) to store and manage road data and speed limit information data, create a database table containing road and speed limit information, ensure that each road has corresponding speed limit information, and the database table is expandable.

[0013] In one embodiment, the present invention provides a smart traffic management method based on data analysis, wherein the collected average vehicle speed on the road is divided by the speed limit information set for the road to obtain a division value, the larger the division value, the better the congestion condition is judged, and the smaller the division value, the more serious the congestion condition is judged, and the step of completing the judgment of the road congestion condition specifically includes:

[0014] Collect the average speed of vehicles on the road, using sensor collection and camera collection; import the average speed of vehicles on the road into a database table containing road and speed limit information;

[0015] The average vehicle speed collected on the same road is divided by the speed limit information to obtain a division value in the data table. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be. The road congestion is prioritized in the data table based on the division value;

[0016] When the average vehicle speeds collected from multiple roads are divided by the speed limit information and the resulting values ​​are the same, resulting in the same priority, sub-priority levels are set for the roads with the same priority level. By judging the speed limit information of multiple roads, the sub-priority levels between the multiple roads are determined to complete the judgment of the road congestion situation.

[0017] In one embodiment, the present invention provides a smart traffic management method based on data analysis, wherein the step of controlling the traffic lights at the traffic intersection based on the road congestion condition specifically includes:

[0018] Based on the congestion priority of the current road and the congestion priority of the subsequent roads, the congestion priority of each driving direction at the traffic intersection is obtained;

[0019] According to the real-time congestion priority of each driving direction at the traffic intersection, adjust the changing timing of traffic lights and the traffic light cycle, and adjust the green light duration, red light duration, and traffic light switching time at the traffic intersection.

[0020] In one embodiment, the present invention provides a smart traffic management method based on data analysis, after the step of controlling the traffic lights at the traffic intersection based on the road congestion condition, the method further includes:

[0021] If after adjusting the traffic lights at the intersection, the change in the average vehicle speed on the road corresponding to the intersection does not exceed the set value, adjust the traffic lights at the intersection, and reduce the duration of the green light and increase the duration of the red light while the switching time of the traffic lights remains unchanged;

[0022] When the green light duration is lower than the preset value, the road abnormality information is fed back to the map service provider.

[0023] In one embodiment, the present invention provides a smart traffic management system based on data analysis, comprising:

[0024] A data acquisition module is used to acquire road data and obtain road speed limit information;

[0025] The congestion judgment module is used to divide the collected average speed of the road by the speed limit information set for the road to obtain a division value. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be, thereby completing the judgment of the road congestion situation;

[0026] The signal light control module is used to control the signal lights at traffic intersections based on road congestion conditions.

[0027] In one embodiment, the present invention provides a smart traffic management system based on data analysis, and the data acquisition module includes:

[0028] Road data acquisition unit, used to acquire road data. The sources of road data include but are not limited to government transportation departments, map service providers (such as Amap, Baidu Map, etc.), and professional geographic information system (GIS) data providers; road data includes road name, location, and type (such as expressway, national highway, provincial highway, etc.);

[0029] A speed limit information acquisition unit is used to acquire the speed limit information of the road by checking the official website and identifying the road sign; and associate the speed limit information with the corresponding road;

[0030] The database table creation unit is used to use database software (such as MySQL, PostgreSQL, etc.) or GIS software (such as ArcGIS, QGIS, etc.) to store and manage road data and speed limit information data, create a database table containing road and speed limit information, ensure that each road has corresponding speed limit information, and the database table is expandable.

[0031] In one embodiment, the present invention provides an intelligent traffic management system based on data analysis, and the congestion judgment module includes:

[0032] The average vehicle speed processing unit is used to collect the average vehicle speed on the road, and the collection method includes sensor collection and camera collection; the average vehicle speed on the road is imported into a database table containing road and speed limit information;

[0033] A road priority judgment unit is used to divide the average vehicle speed collected on the same road by the speed limit information to obtain a division value in a data table. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be. The road congestion is prioritized in the data table based on the division value;

[0034] The road sub-priority judgment unit is used to set sub-priorities for roads with the same priority when the average vehicle speeds collected from multiple roads are divided by the speed limit information and the divisor obtained is the same, resulting in the same priority. By judging the size of the speed limit information of multiple roads, the sub-priority between the multiple roads is determined to complete the judgment of the road congestion situation.

[0035] In one embodiment, the present invention provides a smart traffic management system based on data analysis, wherein the signal light control module includes:

[0036] A driving direction priority determination unit, used to obtain the congestion priority of each driving direction at the traffic intersection based on the congestion priority of the current road and the congestion priority of the subsequent road;

[0037] The traffic light adjustment unit is used to adjust the change timing of traffic lights and the traffic light cycle according to the real-time congestion priority of each driving direction at the traffic intersection, and adjust the green light duration, red light duration, and traffic light switching time at the traffic intersection.

[0038] In one embodiment, the present invention provides a smart traffic management system based on data analysis, and the smart traffic management system based on data analysis also includes:

[0039] A time adjustment module is used to adjust the traffic lights at the traffic intersection, if the change in the average vehicle speed on the road corresponding to the traffic intersection does not exceed the set value after the traffic lights at the traffic intersection are adjusted, and reduce the duration of the green light and increase the duration of the red light when the switching time of the traffic lights remains unchanged;

[0040] The abnormality feedback module is used to feedback road abnormality information to the map service provider when the green light duration is lower than a preset value.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention determines the congestion condition by the average speed of vehicles on the road and the speed limit information, and prioritizes the congestion conditions in a database table, and finally adjusts the duration of traffic lights at intersections based on the priority to increase road traffic efficiency, thereby reducing traffic congestion; when it is found that adjusting the duration of traffic lights cannot effectively increase road traffic efficiency, it will determine whether the road is abnormal, and provide timely feedback to the map service provider to reduce the number of vehicles entering the road and reduce the occurrence of traffic congestion. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of the first part of the flow chart of a smart traffic management method based on data analysis provided in an embodiment of the present invention.

[0043] Figure 2 A schematic diagram of a process for obtaining and processing road data and speed limit data provided by an embodiment of the present invention.

[0044] Figure 3 A schematic diagram of a flow chart for determining road congestion conditions according to an embodiment of the present invention.

[0045] Figure 4 A schematic diagram of a flow chart of adjusting the duration of a signal light provided in an embodiment of the present invention.

[0046] Figure 5 A flowchart of the second part of a smart traffic management method based on data analysis provided in an embodiment of the present invention.

[0047] Figure 6 A schematic diagram of the first part of a smart traffic management system based on data analysis provided in an embodiment of the present invention.

[0048] Figure 7 A schematic diagram of a data acquisition module provided in an embodiment of the present invention.

[0049] Figure 8 A schematic diagram of a congestion determination module provided in an embodiment of the present invention.

[0050] Fig. 9 A schematic diagram of a signal light control module provided in an embodiment of the present invention.

[0051] Fig.10 A schematic diagram of the second part of an intelligent traffic management system based on data analysis provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

[0054] In one embodiment, Figure 1 As shown, a smart traffic management method based on data analysis (applied to a smart traffic management system based on data analysis) comprises the following steps:

[0055] Step S1, obtaining road data and obtaining road speed limit information;

[0056] Step S2, dividing the collected average speed on the road by the speed limit information set for the road to obtain a division value, wherein the larger the division value, the better the congestion condition is judged to be, and the smaller the division value, the more serious the congestion condition is judged to be, thereby completing the judgment of the road congestion condition;

[0057] Step S3, controlling the traffic lights at the traffic intersection based on the road congestion condition.

[0058] Obtain road data from government transportation departments, map service providers (such as Amap, Baidu Map, etc.), professional geographic information system (GIS) data providers, etc., and obtain the speed limit information corresponding to the road through official website consultation, road sign identification, etc.; divide the speed limit information corresponding to the road by the average speed of vehicles traveling on the collected road to determine the priority of different road congestion conditions. For example, the speed limit of road A is 50, and the average speed is 40; the speed limit of road B is 70, and the average speed is 20. The average speed of road A is divided by the speed limit information set for the road, and the obtained value is 80%. The average speed of road B is divided by the speed limit information set for the road, and the obtained value is 28.6%. Obviously, the road utilization efficiency of road A is higher than that of road B, and it is judged that the congestion condition of road B is more serious. Assuming that road A is the north-south driving route of the intersection, and road B is the east-west driving route of the same intersection, based on the low road utilization efficiency of road B, the duration of the green light in the east-west direction will be increased, and the duration of the green light in the north-south direction will be reduced, so as to increase the road traffic efficiency. On this basis, there are left-turn and right-turn routes in the east-west direction, and left-turn and right-turn routes in the north-south direction. In actual use, the same intersection will consider all driving routes to adjust the duration of the red light, green light, and traffic light switching (yellow light).

[0059] In a preferred implementation of the present invention, in step S1, the intelligent traffic management system obtains road data through government traffic departments, map service providers (such as Amap, Baidu Map, etc.), professional geographic information system (GIS) data providers, etc., and obtains road speed limit information by checking official websites and identifying road signs.

[0060] In a preferred implementation manner of the present invention, in step S2, the intelligent traffic management system divides the collected average vehicle speed on the road by the speed limit information set for the road to obtain a division value. The larger the division value, the better the congestion condition is judged to be, and the smaller the division value, the more serious the congestion condition is judged to be. The road utilization efficiency is judged by the size of the division value to complete the judgment of the road congestion condition.

[0061] In a preferred implementation manner of the present invention, in step S3, the intelligent traffic management system controls the traffic lights at the traffic intersection based on the road congestion conditions and adjusts the duration of switching between the red light, the green light, and the traffic light.

[0062] In one embodiment, Figure 2 As shown, a smart traffic management method based on data analysis, the step S1, obtaining road data and obtaining road speed limit information, specifically includes:

[0063] Step S11, obtaining road data, where the sources of road data include but are not limited to government transportation departments, map service providers (such as Amap, Baidu Map, etc.), and professional geographic information system (GIS) data providers; road data includes road name, location, and type (such as expressway, national highway, provincial highway, etc.);

[0064] Step S12, obtaining the speed limit information of the road, including checking the official website and identifying the road sign; associating the speed limit information with the corresponding road;

[0065] Step S13, using database software (such as MySQL, PostgreSQL, etc.) or GIS software (such as ArcGIS, QGIS, etc.) to store and manage road data and speed limit information data, creating a database table containing road and speed limit information, ensuring that each road has corresponding speed limit information, and the database table is expandable.

[0066] Here we take the database software MySQL as an example. Use the CREATE DATABASE statement to create a new database, use the CREATE TABLE statement to define and create a database table, and use the ALTER TABLE statement to modify the table structure, such as adding and deleting columns, changing column properties, etc. That is, through the ALTER TABLE statement, the database table contains road and speed limit information, and other types of data can be imported later, such as average speed, divisor, etc.

[0067] In one embodiment, Figure 3 As shown, a smart traffic management method based on data analysis, in step S2, the collected average speed on the road is divided by the speed limit information set on the road to obtain a division value, the larger the division value, the better the congestion condition is judged, and the smaller the division value, the more serious the congestion condition is judged, and the step of completing the judgment of the road congestion condition specifically includes:

[0068] Step S21, collecting the average speed of vehicles on the road, the collecting method includes sensor collection and camera collection; importing the average speed of vehicles on the road into a database table containing road and speed limit information;

[0069] Step S22, dividing the average vehicle speed collected on the same road by the speed limit information, and obtaining a division value in the data table. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be. The road congestion is prioritized in the data table based on the division value;

[0070] Step S23, when the average vehicle speeds collected from multiple roads are divided by the speed limit information and the resulting division values ​​are the same, resulting in the same priority, sub-priority levels are set for the roads with the same priority level, and the sub-priority levels between the multiple roads are determined by judging the speed limit information of the multiple roads, thereby completing the judgment of the road congestion condition.

[0071] Taking camera acquisition as an example, by setting up cameras at the entrance and exit of the road, the average speed of the vehicle on the road is judged by observing the entry and exit time of the same vehicle and the length of the road. The average speed of multiple vehicles is collected and processed to obtain the average speed on the road. In addition, the speed of the vehicle can also be measured by equipment such as radar speed guns. Radar speed guns calculate the speed of the vehicle by emitting radio waves (usually electromagnetic waves in the microwave frequency band) and receiving the reflected signals. It is based on the principle of the Doppler effect. When the radar wave encounters a moving vehicle, the frequency of the reflected wave changes. The speed of the vehicle can be calculated by measuring the frequency change. The principle of the laser speed gun is similar to that of the radar speed gun.

[0072] The average vehicle speed is divided by the speed limit information to obtain a division value in the data table. The closer the division value is to 1, the higher the road utilization efficiency is, and the smaller the division value is, the lower the road utilization efficiency is.

[0073] In one embodiment, Figure 4 As shown, a smart traffic management method based on data analysis, the step S3, the step of controlling the traffic lights at the traffic intersection based on the road congestion condition, specifically includes:

[0074] Step S31, based on the congestion priority of the current road and the congestion priority of the subsequent roads, the congestion priority of each driving direction at the traffic intersection is obtained;

[0075] Step S32, according to the real-time traffic intersection congestion priority of each driving direction, adjust the traffic light change sequence and traffic light cycle, and adjust the green light duration, red light duration, and traffic light switching time at the traffic intersection.

[0076] Based on the congestion priority of the current road, the corresponding traffic light of the current road can be adjusted to change the road utilization efficiency of the current road. However, considering the driving route, the congestion of subsequent roads must be considered. For example, the current road utilization efficiency is 20%, the subsequent straight road utilization efficiency is 80%, the left turn road utilization efficiency is 60%, and the right turn road utilization efficiency is 40%. The road utilization efficiency can be determined by dividing the value, which will increase the green light time of the straight road, maintain the green light time of the left turn road, and reduce the green light time of the right turn road, so as to avoid too many vehicles on the road and low road utilization efficiency.

[0077] In one embodiment, Figure 5As shown, a smart traffic management method based on data analysis, the step S3, after the step of controlling the traffic lights at the traffic intersection based on the road congestion condition, further includes:

[0078] Step S4, if after adjusting the traffic lights at the traffic intersection, the change in the average vehicle speed on the road corresponding to the traffic intersection does not exceed the set value, adjust the traffic lights at the traffic intersection, and reduce the duration of the green light and increase the duration of the red light when the traffic light switching time remains unchanged;

[0079] Step S5: when the green light duration is less than a preset value, feedback of road abnormality information is sent to the map service provider.

[0080] Taking into account the possibility of accidents on the road, resulting in slow traffic flow, the accident road has a high priority and the green light time is longer. After adjusting the duration of the traffic lights, the average vehicle speed is still slow. In order to maintain the overall road utilization efficiency, the green light time of the accident road will be reduced. After multiple adjustments, it is determined that the accident has caused the efficiency of road utilization to not be effectively improved. The abnormal information will be fed back to the map service provider so that car owners who are navigating can drive through other navigation routes to increase the overall road utilization efficiency.

[0081] In one embodiment, Figure 6 As shown, a smart traffic management system based on data analysis includes:

[0082] Data acquisition module 1, used to acquire road data and obtain road speed limit information;

[0083] The congestion judgment module 2 is used to divide the collected average speed of the road by the speed limit information set for the road to obtain a division value. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be, thereby completing the judgment of the road congestion situation;

[0084] The signal light control module 3 is used to control the signal lights at the traffic intersection based on the road congestion situation.

[0085] After obtaining the road data and speed limit information, the average vehicle speed on the road is collected, and the average vehicle speed is divided by the speed limit information set for the road to obtain a division value. The closer the division value is to 1, the higher the road utilization efficiency is, and the smaller the division value is, the lower the road utilization efficiency is. The size of the division value is an absolute priority of road congestion, and the duration of the traffic light is adjusted accordingly.

[0086] In one embodiment, Figure 7 As shown, in a smart traffic management system based on data analysis, the data acquisition module 1 includes:

[0087] The road data acquisition unit 11 is used to acquire road data. The sources of road data include but are not limited to government transportation departments, map service providers (such as Amap, Baidu Map, etc.), and professional geographic information system (GIS) data providers; the road data includes road name, location, and type (such as expressway, national highway, provincial highway, etc.);

[0088] The speed limit information acquisition unit 12 is used to acquire the speed limit information of the road, including checking the official website and identifying the road sign; and associating the speed limit information with the corresponding road;

[0089] The database table creation unit 13 is used to use database software (such as MySQL, PostgreSQL, etc.) or GIS software (such as ArcGIS, QGIS, etc.) to store and manage road data and speed limit information data, create a database table containing road and speed limit information, ensure that each road has corresponding speed limit information, and the database table is expandable.

[0090] GIS stands for Geographic Information System. GIS software is a software used to capture, store, manage, analyze, display and share geographic data.

[0091] In one embodiment, Figure 8 As shown, in a smart traffic management system based on data analysis, the congestion judgment module 2 includes:

[0092] The average vehicle speed processing unit 21 is used to collect the average vehicle speed on the road, and the collection method includes sensor collection and camera collection; the average vehicle speed on the road is imported into a database table containing road and speed limit information;

[0093] The road priority determination unit 22 is used to divide the average vehicle speed collected on the same road by the speed limit information to obtain a division value in the data table. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be. The road congestion is prioritized in the data table based on the division value;

[0094] The road sub-priority judgment unit 23 is used to set sub-priorities for roads with the same priority when the average vehicle speeds collected from multiple roads are divided by the speed limit information and the divisor obtained is the same, resulting in the same priority. By judging the size of the speed limit information of multiple roads, the sub-priority between the multiple roads is determined to complete the judgment of the road congestion situation.

[0095] Taking into account the problem of calculation amount, the average vehicle speed will not be measured on a large scale for all vehicles on the current road, but will often be randomly sampled, and there will be problems with measurement accuracy. In addition, the subsequent priority judgment problem is also taken into consideration. If the average vehicle speed is too precise, such as 51.45KM / H, if the present invention is applied to the entire city, it will lead to excessive traffic light calculations. If the calculation time is long, it will lead to the inability to adjust the traffic lights in real time. Therefore, the average vehicle speed will be roughly divided, for example, divided into 5KM / H intervals, 51.45KM / H will be identified as 50KM / H, and 53.77KM / H will be identified as 55KM / H, to reduce the amount of calculation and ensure that the traffic lights can be adjusted in real time.

[0096] Roughly distinguishing between average vehicle speeds will result in the same priority problem. In this case, the speed limit information of the roads is used to determine the sub-priority between multiple roads. For example, driving 40KM / H in a 50KM / H area and driving 80KM / H in a 100KM / H area, although the road utilization efficiency is the same, the difference between 40KM / H and 50KM / H is 10KM / H, and the difference between 80KM / H and 100KM / H is 20KM / H. The latter has a greater speed increase, so the sub-priority can be judged by the road speed limit information.

[0097] In one embodiment, Fig. 9 As shown, in a smart traffic management system based on data analysis, the signal light control module 3 includes:

[0098] A driving direction priority determination unit 31 is used to obtain the congestion priority of each driving direction at the traffic intersection based on the congestion priority of the current road and the congestion priority of the subsequent road;

[0099] The traffic light adjustment unit 32 is used to adjust the change sequence of traffic lights and the traffic light cycle according to the real-time congestion priority of each driving direction at the traffic intersection, and adjust the green light duration, red light duration, and traffic light switching time at the traffic intersection.

[0100] The traffic light duration adjustment can be based on either local adjustment or overall adjustment. The congestion conditions of subsequent roads are not taken into consideration during local adjustment, while the congestion conditions of subsequent roads are taken into consideration during overall adjustment.

[0101] In one embodiment, Fig.10 As shown, a smart traffic management system based on data analysis also includes:

[0102] The time adjustment module 4 is used to adjust the traffic lights at the traffic intersection, if the change in the average vehicle speed on the road corresponding to the traffic intersection does not exceed the set value after the traffic lights at the traffic intersection are adjusted, and reduce the duration of the green light and increase the duration of the red light when the switching time of the traffic lights remains unchanged;

[0103] The abnormality feedback module 5 is used to feedback road abnormality information to the map service provider when the green light duration is lower than a preset value.

[0104] If it is determined that the road is unavailable for driving due to an accident, the average speed of vehicles on the road is 0 or close to 0, and the traffic lights at the intersection remain red, thereby increasing the overall road utilization efficiency.

[0105] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0106] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0107] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0108] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0110] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A smart traffic management method based on data analysis, characterized in that: The intelligent traffic management method based on data analysis includes the following steps: Obtain road data and obtain road speed limit information; Divide the collected average speed on the road by the speed limit information set on the road to obtain a division value. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be, thus completing the judgment of the road congestion situation; Control the traffic lights at traffic intersections based on road congestion conditions; If after adjusting the traffic lights at the intersection, the change in the average vehicle speed on the road corresponding to the intersection does not exceed the set value, adjust the traffic lights at the intersection, and reduce the duration of the green light and increase the duration of the red light while the switching time of the traffic lights remains unchanged; When the green light duration is lower than the preset value, the road abnormality information is fed back to the map service provider.

2. The intelligent traffic management method based on data analysis according to claim 1 is characterized in that: The step of obtaining road data and obtaining road speed limit information specifically includes: Obtain road data, the sources of which include but are not limited to government transportation departments, map service providers, and professional geographic information system data providers; road data includes road name, location, and type; Obtaining the speed limit information of the road, including by checking the official website and identifying the road sign; associating the speed limit information with the corresponding road; Use database software or GIS software to store and manage road data and speed limit information data, create a database table containing road and speed limit information, ensure that each road has corresponding speed limit information, and the database table is expandable.

3. The intelligent traffic management method based on data analysis according to claim 1 is characterized in that: The collected average speed on the road is divided by the speed limit information set on the road to obtain a division value. The larger the division value, the better the congestion condition is judged to be, and the smaller the division value, the more serious the congestion condition is judged to be. The step of judging the road congestion condition specifically includes: Collect the average speed of vehicles on the road, using sensor collection and camera collection; import the average speed of vehicles on the road into a database table containing road and speed limit information; The average vehicle speed collected on the same road is divided by the speed limit information to obtain a division value in the data table. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be. The road congestion is prioritized in the data table based on the division value; When the average vehicle speeds collected from multiple roads are divided by the speed limit information and the resulting values ​​are the same, resulting in the same priority, sub-priority levels are set for the roads with the same priority level. By judging the speed limit information of multiple roads, the sub-priority levels between the multiple roads are determined to complete the judgment of the road congestion situation.

4. The intelligent traffic management method based on data analysis according to claim 1 is characterized in that: The step of controlling the traffic lights at the traffic intersection based on the road congestion condition specifically includes: Based on the congestion priority of the current road and the congestion priority of the subsequent roads, the congestion priority of each driving direction at the traffic intersection is obtained; According to the real-time congestion priority of each driving direction at the traffic intersection, adjust the changing timing of traffic lights and the traffic light cycle, and adjust the green light duration, red light duration, and traffic light switching time at the traffic intersection.

5. A smart traffic management system based on data analysis, characterized in that: The smart traffic management system based on data analysis includes: A data acquisition module is used to acquire road data and obtain road speed limit information; The congestion judgment module is used to divide the collected average speed of the road by the speed limit information set for the road to obtain a division value. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be, thereby completing the judgment of the road congestion situation; A signal light control module, used to control the signal lights at traffic intersections based on road congestion conditions; A time adjustment module is used to adjust the traffic lights at the traffic intersection, if the change in the average vehicle speed on the road corresponding to the traffic intersection does not exceed the set value after the traffic lights at the traffic intersection are adjusted, and reduce the duration of the green light and increase the duration of the red light when the switching time of the traffic lights remains unchanged; The abnormality feedback module is used to feedback road abnormality information to the map service provider when the green light duration is lower than a preset value.

6. The intelligent traffic management system based on data analysis according to claim 5 is characterized in that: The data acquisition module includes: A road data acquisition unit is used to acquire road data. The sources of road data include but are not limited to government transportation departments, map service providers, and professional geographic information system data providers; road data includes road name, location, and type; A speed limit information acquisition unit is used to acquire the speed limit information of the road by checking the official website and identifying the road sign; and associate the speed limit information with the corresponding road; The database table creation unit is used to store and manage road data and speed limit information data using database software or GIS software, and to create a database table containing road and speed limit information to ensure that each road has corresponding speed limit information. The database table is expandable.

7. The intelligent traffic management system based on data analysis according to claim 5 is characterized in that: The congestion judgment module includes: The average vehicle speed processing unit is used to collect the average vehicle speed on the road, and the collection method includes sensor collection and camera collection; the average vehicle speed on the road is imported into a database table containing road and speed limit information; A road priority judgment unit is used to divide the average vehicle speed collected on the same road by the speed limit information to obtain a division value in a data table. The larger the division value, the better the congestion situation is judged to be, and the smaller the division value, the more serious the congestion situation is judged to be. The road congestion is prioritized in the data table based on the division value; The road sub-priority judgment unit is used to set sub-priorities for roads with the same priority when the average vehicle speeds collected from multiple roads are divided by the speed limit information and the divisor obtained is the same, resulting in the same priority. By judging the size of the speed limit information of multiple roads, the sub-priority between the multiple roads is determined to complete the judgment of the road congestion situation.

8. The intelligent traffic management system based on data analysis according to claim 5 is characterized in that: The signal light control module includes: A driving direction priority determination unit, used to obtain the congestion priority of each driving direction at the traffic intersection based on the congestion priority of the current road and the congestion priority of the subsequent road; The traffic light adjustment unit is used to adjust the change timing of traffic lights and the traffic light cycle according to the real-time congestion priority of each driving direction at the traffic intersection, and adjust the green light duration, red light duration, and traffic light switching time at the traffic intersection.

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