An intelligent traffic command and dispatching system based on artificial intelligence

Abstract

This invention relates to the field of intelligent transportation technology, and more particularly to an artificial intelligence-based intelligent traffic command and dispatch system, comprising: a traffic command module for adjusting and setting timing parameters such as phase overflow buffer duration coefficient, phase interception pre-activation coefficient, and intersection phase clearing margin coefficient; a duration statistics module for selecting vehicles passing through a specific road segment within a preset duration to determine the monitored vehicles and obtain the average road network travel delay time; an intelligent analysis module for determining whether traffic command and dispatch meet standards based on the average road network communication delay time and generating corresponding processing instructions; and a parameter adjustment module for adjusting the preset duration, baseline travel duration, phase overflow buffer duration coefficient, phase interception pre-activation coefficient, and intersection phase clearing margin coefficient. This invention effectively achieves precise monitoring of traffic command and significantly improves the efficiency of traffic command and dispatch.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to an intelligent traffic command and dispatch system based on artificial intelligence. Background Technology

[0002] Traffic command refers to the actions taken by traffic management departments to control road traffic flow, intersection signals, vehicles and pedestrians, and sudden road conditions. Its core is to control traffic status. Traffic command and dispatch refers to the addition of overall coordination, resource allocation, and collaborative linkage on the basis of traffic command. It not only includes directing traffic lights at intersections and guiding traffic flow, but also dynamically allocating traffic police forces, rescue vehicles, public transportation, ride-hailing vehicles, emergency supplies, and lane resources across road sections and regions. The intelligent traffic command and dispatch system based on artificial intelligence uses artificial intelligence technology as its core. It collects data such as road conditions, traffic flow, video, accidents, and weather in real time. Through AI, it automatically identifies congestion, captures violations, predicts traffic flow, intelligently times traffic lights, automatically analyzes accidents, and intelligently allocates police forces and rescue vehicles. It realizes an integrated platform for intelligent traffic command and dynamic resource dispatch with no or minimal human intervention on all road sections and at all times. With the development of the times, research on intelligent traffic command and dispatch based on artificial intelligence has important practical significance.

[0003] Chinese Patent Publication No. CN115330138B discloses a method, apparatus, and system for constructing a traffic management platform. The method involves acquiring basic traffic data and performing digital analysis to construct a traffic management semantic library. A periodic table of traffic management elements is then constructed from this semantic library. This periodic table consists of various preset traffic management elements and the corresponding basic traffic data for each type of element. Traffic management elements are randomly combined to generate a corresponding traffic management scenario library. Traffic management scenarios in the scenario library are then randomly combined to generate a traffic management business library. Based on the traffic management semantic library, the periodic table of traffic management elements, the scenario library, and the business library, a traffic management platform for digital traffic management is constructed. This platform enables programmable and computable operation across the entire traffic management chain, providing a template and demonstration for the construction of traffic management command centers in various regions.

[0004] Therefore, the above-mentioned solution utilizes a well-constructed and comprehensive traffic management platform to generate corresponding traffic management strategies based on traffic management needs, thus achieving better traffic management. However, this solution cannot accurately monitor traffic control, thereby failing to guarantee the efficiency of traffic dispatching. Summary of the Invention

[0005] To address this issue, the present invention provides an intelligent traffic command and dispatch system based on artificial intelligence, which overcomes the problem of low dispatch efficiency in existing technologies due to the inability to accurately monitor traffic command.

[0006] To achieve the above objectives, the present invention provides an intelligent traffic command and dispatch system based on artificial intelligence, comprising: The traffic control module is used to adjust and set timing parameters for phase overflow buffer duration coefficient, phase interception pre-activation coefficient, and intersection phase clearance margin coefficient. The duration statistics module, which is connected to the traffic control module, is used to select vehicles passing through a specific road segment within a preset duration to determine the monitored vehicles. The duration statistics module is also used to determine the actual travel time of each of the monitored vehicles in sequence; the duration statistics module is also used to calculate the difference between each actual travel time and the benchmark travel time respectively; The duration statistics module is also used to calculate the average of the differences to obtain the average travel delay time of the road network; The intelligent analysis module, connected to the duration statistics module, is used to determine whether traffic command and dispatch meet the standards based on the average communication delay time of the road network, and to generate corresponding processing instructions if the standards are not met. The parameter adjustment module is connected to the traffic control module, the duration statistics module, and the intelligent analysis module, respectively. It is used to adjust the preset duration based on the generated processing instructions, increase the baseline passage duration, adjust the phase overflow buffer duration coefficient, increase the phase interception pre-activation coefficient, adjust the intersection phase clearance margin coefficient, and issue traffic situation optimization scheduling instructions.

[0007] Furthermore, the intelligent analysis module is used to determine whether traffic command and dispatch meets the standards based on the average traffic delay time of the road network, and to adjust the preset time based on the delay time difference if the traffic command and dispatch does not meet the standards.

[0008] Furthermore, the parameter adjustment module is used to increase the preset duration based on the delay duration difference, and the increase in the preset duration is proportional to the delay duration difference.

[0009] Furthermore, the parameter adjustment module is also used to increase the baseline passage time based on the increase of the preset time, and the increase of the baseline passage time is proportional to the increase of the preset time.

[0010] Furthermore, the intelligent analysis module is also used to determine whether traffic command and dispatch meets the standard based on the average traffic delay time of the road network after the increase of the benchmark travel time is completed, and to adjust the phase overflow buffer duration coefficient based on the increase of the preset duration if the traffic command and dispatch does not meet the standard.

[0011] Furthermore, the parameter adjustment module is also used to increase the phase overflow buffer duration coefficient based on the increase of the preset duration, and the increase of the phase overflow buffer duration coefficient is proportional to the increase of the preset duration.

[0012] Furthermore, the parameter adjustment module is also used to increase the phase cut-off pre-lighting coefficient based on the increase of the phase overflow buffer duration coefficient, and the increase of the phase cut-off pre-lighting coefficient is proportional to the increase of the phase overflow buffer duration coefficient.

[0013] Furthermore, the intelligent analysis module is also used to determine whether traffic command and dispatch meets the standard based on the average traffic delay time of the road network after the phase interception pre-lighting coefficient is increased, and to adjust the intersection phase clearance margin coefficient based on the delay time ratio if the traffic command and dispatch does not meet the standard.

[0014] Furthermore, the parameter adjustment module is also used to increase the intersection phase clearance margin coefficient based on the proportion of delay time, and the increase in the intersection phase clearance margin coefficient is inversely proportional to the proportion of delay time.

[0015] Furthermore, the intelligent analysis module is also used to determine whether traffic command and dispatch meets the standard based on the average traffic delay time of the road network after the phase clearance margin coefficient of the intersection, and to issue a traffic situation optimization dispatch instruction if the traffic command and dispatch does not meet the standard.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: by setting up an intelligent analysis module and a parameter adjustment module, the intelligent analysis module determines whether traffic command and dispatch meet the standards based on the average communication delay time of the road network. It can quickly and accurately complete the determination of whether traffic command and dispatch meet the standards. If it is determined that the traffic command and dispatch does not meet the standards, it generates corresponding processing instructions. The parameter adjustment module adjusts the corresponding parameters or issues corresponding instructions in a targeted manner. While effectively realizing accurate monitoring of traffic command, it also effectively improves the dispatch efficiency of traffic command.

[0017] Furthermore, the intelligent analysis module of this invention is used to determine whether traffic command and dispatch meet the standards based on the average traffic delay time of the road network, and to determine in a timely and accurate manner whether the preset time needs to be adjusted based on the delay time difference, so as to ensure the accuracy of the judgment. While further realizing the precise monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0018] Furthermore, the parameter adjustment module of this invention is used to increase the preset duration based on the delay duration difference, effectively judging the preset duration and avoiding the situation where the traffic command and dispatch are judged to be non-compliant due to the preset duration not meeting the standard. While further realizing the accurate monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0019] Furthermore, the parameter adjustment module of this invention is also used to increase the benchmark passage time based on the increase of the preset duration, effectively judging the benchmark passage time and avoiding the situation where the traffic command and dispatch are judged to be non-standard due to the benchmark passage time not meeting the standard. While further realizing the accurate monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0020] Furthermore, the intelligent analysis module of this invention is also used to determine whether traffic command and dispatch meet the standards based on the average traffic delay time of the road network after the benchmark travel time has been increased, and to determine in a timely manner whether the phase overflow buffer time coefficient needs to be adjusted based on the increase of the preset time, so as to ensure the accuracy of the judgment. While further realizing the accurate monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0021] Furthermore, the parameter adjustment module of this invention is also used to increase the phase overflow buffer duration coefficient based on the increase of a preset duration, effectively judging the phase overflow buffer duration coefficient, avoiding the situation where the traffic command and dispatch are judged to be non-standard due to the phase overflow buffer duration coefficient not meeting the standard. While further realizing the accurate monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0022] Furthermore, the parameter adjustment module of this invention is also used to increase the phase interception pre-activation coefficient based on the increase of the phase overflow buffer duration coefficient, effectively judging the phase interception pre-activation coefficient, avoiding the situation where the traffic command and dispatch are judged to be non-standard due to the phase interception pre-activation coefficient not meeting the standard. While further realizing the accurate monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0023] Furthermore, the intelligent analysis module of this invention is also used to determine whether traffic command and dispatch meet the standards based on the average traffic delay time of the road network after the phase interception pre-lighting coefficient is increased, and to determine in a timely manner whether the intersection phase clearing margin coefficient needs to be adjusted based on the delay time ratio, so as to ensure the accuracy of the judgment. While further realizing the accurate monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0024] Furthermore, the parameter adjustment module of this invention is also used to increase the intersection phase clearance margin coefficient based on the proportion of delay time, effectively judging the intersection phase clearance margin coefficient, avoiding the situation where the traffic command and dispatch are judged to be non-standard due to the intersection phase clearance margin coefficient not meeting the standard. While further realizing the accurate monitoring of traffic command, it further improves the dispatch efficiency of traffic command.

[0025] Furthermore, the intelligent analysis module of this invention is also used to determine whether traffic command and dispatch meets the standards based on the average traffic delay time of the road network after the phase clearance margin coefficient at the intersection. If the traffic command and dispatch does not meet the standards, it will issue a traffic situation optimization dispatch instruction in a timely manner. This not only further realizes the accurate monitoring of traffic command, but also further improves the dispatch efficiency of traffic command. Attached Figure Description

[0026] Figure 1 This is a structural block diagram of an artificial intelligence-based intelligent traffic command and dispatch system according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the workflow of an artificial intelligence-based intelligent traffic command and dispatch system according to an embodiment of the present invention. Figure 3 This is a flowchart illustrating whether traffic command and dispatch in this invention conforms to standards and the reasons why they do not. Figure 4 This is a flowchart illustrating the reasons why traffic command and dispatch do not meet the standards in an embodiment of the present invention. Detailed Implementation

[0027] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0028] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0029] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0030] Please see Figure 1The diagram shown is a structural block diagram of an artificial intelligence-based intelligent traffic command and dispatch system according to an embodiment of the present invention. The artificial intelligence-based intelligent traffic command and dispatch system described in this embodiment includes a traffic command module, a duration statistics module, an intelligent analysis module, and a parameter adjustment module; wherein, The traffic control module is used to adjust and set timing parameters for the phase overflow buffer duration coefficient, the phase interception pre-activation coefficient, and the intersection phase clearance margin coefficient. The duration statistics module is connected to the traffic control module and is used to select vehicles passing through a specific road segment within a preset duration to determine the monitored vehicles. The duration statistics module is also used to determine the actual travel time of each of the monitored vehicles in sequence; The duration statistics module is also used to calculate the difference between each actual travel time and the benchmark travel time; The duration statistics module is also used to calculate the average of the differences to obtain the average travel delay time of the road network; The intelligent analysis module is connected to the duration statistics module, and is used to determine whether traffic command and dispatch meet the standards based on the average communication delay time of the road network, and to generate corresponding processing instructions if the standards are not met. The parameter adjustment module is connected to the traffic control module, the duration statistics module and the intelligent analysis module respectively, and is used to adjust the preset duration based on the generated processing instructions, increase the baseline passage duration, adjust the phase overflow buffer duration coefficient, increase the phase interception pre-activation coefficient, adjust the intersection phase clearance margin coefficient, and issue traffic situation optimization scheduling instructions. Specifically, the benchmark travel time is the travel time for a road segment with smooth traffic, no red traffic lights, no congestion, and a constant speed.

[0031] Please see Figure 2The diagram shown is a flowchart of the intelligent traffic command and dispatch system based on artificial intelligence, according to an embodiment of the present invention. When the AI-based intelligent traffic command and dispatch system described in this embodiment of the invention is running, the traffic command module adjusts and sets the timing parameters for the phase overflow buffer duration coefficient, the phase interception pre-activation coefficient, and the intersection phase clearing margin coefficient. The duration statistics module selects vehicles passing through a specific road segment within a preset duration to determine the monitored vehicles. The duration statistics module sequentially determines the actual travel duration of each monitored vehicle. The duration statistics module calculates the difference between each actual travel duration and the baseline travel duration. The duration statistics module calculates the average value of each difference to obtain the average road network travel delay time. The intelligent analysis module determines whether the traffic command and dispatch meets the standards based on the average road network communication delay time. If the intelligent analysis module determines that the standards are not met, it generates corresponding processing instructions. The parameter adjustment module adjusts the preset duration based on the generated processing instructions, increases the baseline travel duration, adjusts the phase overflow buffer duration coefficient, increases the phase interception pre-activation coefficient, adjusts the intersection phase clearing margin coefficient, and issues traffic situation optimization dispatch instructions.

[0032] Please see Figure 3 The diagram shows a flowchart illustrating whether traffic control and dispatching in accordance with standards and the reasons for non-compliance, according to an embodiment of the present invention. The intelligent analysis module described in this embodiment is used to determine whether traffic control and dispatching meets standards based on the average travel delay time of the road network. If the average road network delay time is less than or equal to the preset average road network communication delay time H set in the intelligent analysis module, the intelligent analysis module determines that the traffic command and dispatch meets the standard, completes the periodic monitoring of traffic command and dispatch, and monitors the traffic command and dispatch for the next cycle. In this embodiment, the preset average road network communication delay time H = 35S. If the average travel delay time of the road network is greater than the preset average communication delay time H of the road network, the intelligent analysis module determines that the traffic command and dispatch does not meet the standard, and adjusts the preset time based on the delay time difference; Specifically, the preset average communication delay time of the road network is 35 seconds, which is a threshold based on industry engineering experience. The delay duration difference is the difference between the average communication delay duration of the road network and the preset average communication delay duration of the road network.

[0033] Please continue reading. Figure 3 As shown, the parameter adjustment module of the present invention is used to increase the preset duration based on the delay duration difference: If the delay time difference is greater than the second preset delay time difference △D2 set in the intelligent analysis module, the parameter adjustment module increases the preset time to 1.33 times the initial preset time, wherein, in this embodiment, the second preset delay time difference △D2 = 10.8S; If the delay time difference is less than or equal to the second preset delay time difference △D2 and greater than the first preset delay time difference △D1 set in the intelligent analysis module, the parameter adjustment module increases the preset time to 1.26 times the initial preset time. In this embodiment, the first preset delay time difference △D1 = 5.2S. If the delay time difference is less than or equal to the first preset delay time difference △D1, the parameter adjustment module increases the preset time to 1.14 times the initial preset time; Specifically, the values ​​of the delay time difference and the preset time are both derived from the actual debugging results.

[0034] Please continue reading. Figure 3 As shown, the parameter adjustment module of the present invention is further used to increase the baseline passage time based on the increase of the preset duration: If the preset duration is increased to 1.33 times the initial preset duration, the parameter adjustment module will increase the baseline passage duration to 1.37 times the initial baseline passage duration; If the preset duration is increased to 1.26 times the initial preset duration, the parameter adjustment module will increase the baseline passage duration to 1.28 times the initial baseline passage duration; If the preset duration is increased to 1.14 times the initial preset duration, the parameter adjustment module will increase the baseline passage duration to 1.19 times the initial baseline passage duration; Specifically, the value of the benchmark passage time is derived from the actual debugging results.

[0035] Please continue reading. Figure 3 As shown, the intelligent analysis module of this invention is also used to determine whether traffic command and dispatch meet the standards based on the average road network delay time after the baseline travel time has been increased. If the average traffic delay time of the road network is less than or equal to the preset average communication delay time H of the road network, the intelligent analysis module determines that the traffic command and dispatch meets the standard, completes the periodic monitoring of traffic command and dispatch, and monitors the traffic command and dispatch for the next cycle. If the average traffic delay time of the road network is greater than the preset average communication delay time H of the road network, the intelligent analysis module determines that the traffic command and dispatch does not meet the standard, and adjusts the phase overflow buffer duration coefficient based on the increase of the preset duration.

[0036] Please continue reading. Figure 3 As shown, the parameter adjustment module of the present invention is further used to increase the phase overflow buffer duration coefficient based on the increase in the preset duration: If the preset duration is increased to 1.33 times the initial preset duration, the parameter adjustment module will increase the phase overflow buffer duration coefficient to 1.34 times the initial phase overflow buffer duration coefficient; If the preset duration is increased to 1.26 times the initial preset duration, the parameter adjustment module will increase the phase overflow buffer duration coefficient to 1.21 times the initial phase overflow buffer duration coefficient; If the preset duration is increased to 1.14 times the initial preset duration, the parameter adjustment module will increase the phase overflow buffer duration coefficient to 1.11 times the initial phase overflow buffer duration coefficient; Specifically, the phase overflow buffer duration coefficient refers to the multiplier used to adjust the additional clearance time of the congested phase after the green light ends; The value of the phase overflow buffer duration coefficient is derived from the actual debugging results.

[0037] Please see Figure 4 The diagram shows a flowchart illustrating the reasons why traffic command and dispatch do not meet standards according to an embodiment of the present invention. The parameter adjustment module described in this embodiment is further used to increase the phase cutoff pre-activation coefficient based on the increase in the phase overflow buffer duration coefficient: If the phase overflow buffer duration coefficient is increased to 1.34 times the initial phase overflow buffer duration coefficient, the parameter adjustment module will increase the phase cut-off pre-activation coefficient to 1.42 times the initial phase cut-off pre-activation coefficient. If the phase overflow buffer duration coefficient is increased to 1.21 times the initial phase overflow buffer duration coefficient, the parameter adjustment module will increase the phase cut-off pre-activation coefficient to 1.38 times the initial phase cut-off pre-activation coefficient. If the phase overflow buffer duration coefficient is increased to 1.11 times the initial phase overflow buffer duration coefficient, the parameter adjustment module will increase the phase cut-off pre-activation coefficient to 1.24 times the initial phase cut-off pre-activation coefficient. Specifically, the phase interception pre-activation coefficient refers to the multiplier adjustment coefficient used to control the early switching activation time of red traffic lights for lateral traffic flow perpendicular to the congestion phase and oncoming traffic flow at intersections. The value of the phase cutoff pre-activation coefficient is obtained from the actual debugging results.

[0038] Please continue reading. Figure 4As shown, the intelligent analysis module described in this embodiment of the invention is also used to determine whether traffic command and dispatch meet the standards based on the average road network delay time after the phase interception pre-activation coefficient is increased. If the average traffic delay time of the road network is less than or equal to the preset average communication delay time H of the road network, the intelligent analysis module determines that the traffic command and dispatch meets the standard, completes the periodic monitoring of traffic command and dispatch, and monitors the traffic command and dispatch for the next cycle. If the average traffic delay time of the road network is greater than the preset average communication delay time H of the road network, the intelligent analysis module determines that the traffic command and dispatch does not meet the standard, and adjusts the intersection phase clearance margin coefficient based on the proportion of delay time. Specifically, the delay duration percentage is the ratio of the preset average communication delay duration of the road network to the average communication delay duration of the road network.

[0039] Please continue reading. Figure 4 As shown, the parameter adjustment module in this embodiment of the invention is also used to increase the intersection phase clearance margin coefficient based on the proportion of delay time: If the percentage of the delay time is greater than the second preset delay time percentage R2 set in the intelligent analysis module, the parameter adjustment module will increase the intersection phase clearance margin coefficient to 1.09 times the initial intersection phase clearance margin coefficient. In this embodiment, the second preset delay time percentage R2 = 0.85. If the percentage of delay time is less than or equal to the second preset percentage of delay time R2 and greater than the first preset percentage of delay time R1 set in the intelligent analysis module, the parameter adjustment module increases the intersection phase clearance margin coefficient to 1.31 times the initial intersection phase clearance margin coefficient, wherein, in this embodiment, the first preset percentage of delay time R1 = 0.69; If the percentage of the delay time is less than or equal to the first preset percentage of the delay time R1, the parameter adjustment module increases the intersection phase clearance margin coefficient to 1.47 times the initial intersection phase clearance margin coefficient. Specifically, the intersection phase clearance margin coefficient refers to the multiplier adjustment coefficient used to regulate the total duration of the yellow traffic light and the total duration of the red traffic light after the congestion phase has ended; The values ​​of the delay duration percentage and the intersection phase clearance margin coefficient are both derived from actual debugging results.

[0040] Please continue reading. Figure 4 As shown, the intelligent analysis module described in this embodiment of the invention is also used to determine whether traffic command and dispatch meets the standard based on the average travel delay time of the road network after the phase clearance margin coefficient at the intersection: If the average traffic delay time of the road network is less than or equal to the preset average communication delay time H of the road network, the intelligent analysis module determines that the traffic command and dispatch meets the standard, completes the periodic monitoring of traffic command and dispatch, and monitors the traffic command and dispatch for the next cycle. If the average travel delay time of the road network is greater than the preset average communication delay time H of the road network, the intelligent analysis module determines that the traffic command and dispatch does not meet the standard and issues a traffic situation optimization dispatch instruction.

[0041] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0042] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent traffic command and dispatch system based on artificial intelligence, characterized in that, include: The traffic control module is used to adjust and set timing parameters for phase overflow buffer duration coefficient, phase interception pre-activation coefficient, and intersection phase clearance margin coefficient. The duration statistics module, which is connected to the traffic control module, is used to select vehicles passing through a specific road segment within a preset duration to determine the monitored vehicles. The duration statistics module is also used to determine the actual travel time of each of the monitored vehicles in sequence; The duration statistics module is also used to calculate the difference between each actual travel time and the benchmark travel time; The duration statistics module is also used to calculate the average of the differences to obtain the average travel delay time of the road network; The intelligent analysis module, connected to the duration statistics module, is used to determine whether traffic command and dispatch meet the standards based on the average communication delay time of the road network, and to generate corresponding processing instructions if the standards are not met. The parameter adjustment module is connected to the traffic control module, the duration statistics module, and the intelligent analysis module, respectively. It is used to adjust the preset duration based on the generated processing instructions, increase the baseline passage duration, adjust the phase overflow buffer duration coefficient, increase the phase interception pre-activation coefficient, adjust the intersection phase clearance margin coefficient, and issue traffic situation optimization scheduling instructions.

2. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 1, characterized in that, The intelligent analysis module is used to determine whether traffic command and dispatch meets the standards based on the average traffic delay time of the road network, and to adjust the preset time based on the delay time difference if the traffic command and dispatch does not meet the standards.

3. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 2, characterized in that, The parameter adjustment module is used to increase the preset duration based on the delay duration difference, and the increase in the preset duration is proportional to the delay duration difference.

4. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 3, characterized in that, The parameter adjustment module is also used to increase the baseline passage time based on the increase of the preset time, and the increase of the baseline passage time is proportional to the increase of the preset time.

5. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 4, characterized in that, The intelligent analysis module is also used to determine whether traffic command and dispatch meets the standard based on the average traffic delay time of the road network after the increase of the benchmark travel time is completed, and to adjust the phase overflow buffer duration coefficient based on the increase of the preset duration if the traffic command and dispatch does not meet the standard.

6. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 5, characterized in that, The parameter adjustment module is also used to increase the phase overflow buffer duration coefficient based on the increase of the preset duration, and the increase of the phase overflow buffer duration coefficient is proportional to the increase of the preset duration.

7. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 6, characterized in that, The parameter adjustment module is also used to increase the phase cut-off pre-lighting coefficient based on the increase of the phase overflow buffer duration coefficient, and the increase of the phase cut-off pre-lighting coefficient is proportional to the increase of the phase overflow buffer duration coefficient.

8. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 7, characterized in that, The intelligent analysis module is also used to determine whether traffic command and dispatch meets the standard based on the average traffic delay time of the road network after the phase interception pre-lighting coefficient is increased, and to adjust the intersection phase clearance margin coefficient based on the delay time ratio if the traffic command and dispatch does not meet the standard.

9. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 8, characterized in that, The parameter adjustment module is also used to increase the intersection phase clearance margin coefficient based on the proportion of delay time, and the increase in the intersection phase clearance margin coefficient is inversely proportional to the proportion of delay time.

10. The intelligent traffic command and dispatch system based on artificial intelligence according to claim 9, characterized in that, The intelligent analysis module is also used to determine whether traffic command and dispatch meets the standard based on the average traffic delay time of the road network after the phase clearance margin coefficient of the intersection, and to issue a traffic situation optimization dispatch instruction if the traffic command and dispatch does not meet the standard.

Images