Intelligent traffic light traffic control system

Abstract

The invention discloses an intelligent traffic light traffic management system. The system comprises a rotatable camera installed on a traffic light rod; comprising an intelligent control unit installed on a traffic light pole. The intelligent control unit obtains the number of queuing vehicles at the corresponding traffic lights and the number of waiting people at the two sides of a sidewalk at the corresponding traffic lights in real time through a camera, and obtains the duration and phase of the current traffic lights in a traffic control system through a network; if no waiting vehicle exists before the green light time ends, the intelligent control unit sends a yellow light turning request to a traffic control system, and the green light time of the vehicle ends in advance. And if no pedestrian is waiting before the green light time ends, the intelligent control unit sends a red light turning request to a traffic control system to end the pedestrian green light time in advance. The advantages of the unmanned aerial vehicle and the intelligent traffic control system are combined, and the problem that pedestrians at the intersection wait for too long time is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent transportation, and particularly relates to an intelligent traffic light management system. Background Art

[0002] The intelligent traffic management system effectively integrates information technology, data communication and transmission technology, electronic sensing technology, control technology, computer technology, etc. into the entire transportation management system, and establishes a comprehensive transportation management system that plays a role in a large range and in all aspects, and is real-time, accurate and efficient. Intelligent transportation is reflected in many aspects. For example, in terms of traffic light control, compared with the traditional countdown traffic light control, intelligent traffic light control is to collect real-time traffic flow data at intersections through intersection cameras, monitors, etc., including information such as the number, speed, and driving direction of vehicles. Then, computer algorithms and intelligent control systems are used to analyze and process the collected data, and according to preset rules and models, calculate the traffic conditions in all directions at the current intersection and predict the future traffic flow change trend for a period of time. Finally, based on the data analysis results, the intelligent control system automatically adjusts the duration and phase of the traffic lights to optimize the traffic passing capacity of the intersection.

[0003] However, the above intelligent traffic light control has the following deficiencies: 1. The information collection depends on fixed devices such as intersection cameras and monitors, and the viewable range for collection is small. The traffic congestion situation of a section of road or the whole road is inferred from local data, and there are defects of "generalizing from part to whole" in information sources and calculations.

[0004] 2. Most algorithms adjust the duration and phase of traffic lights according to the traffic flow on the road to reduce the "idle period" of green lights. For example, the patent with the application number 201911414567.2 discloses a traffic signal intelligent control method, storage medium, and traffic signal, which controls the green light of the traffic signal group to turn off and the yellow light to turn on or the red light to turn off and the green light to turn on according to the number of waiting pedestrians. However, such traffic light control methods lack real-time changes in traffic rules according to the change in the flow of people at special locations. For example, the traffic flow near office buildings increases significantly during the morning and evening rush hours. The traffic flow near schools increases significantly during school arrival and dismissal times. Therefore, the problems mainly manifest in two aspects. On the one hand, the existing algorithms lack real-time monitoring of dynamic pedestrian flow data and cannot automatically adjust the duration and phase of traffic lights by combining pedestrian flow data and vehicle volume data during special time periods. On the other hand, a route with a dense flow of people is formed between bus stops (light rail stations, subway stations, etc.) and office buildings (schools, business districts, etc.). This route shows obvious characteristics of changing pedestrian flow at different time nodes. The existing traffic light control methods cannot link the traffic lights on the route with a dense flow of people to temporarily create a "green channel" for rapid passage. In addition, some of the existing algorithms are complex. Especially in densely populated cities, data collection and processing significantly increase the load on the intelligent traffic management system and the computing power cost is high.

[0005] With the rapid development of drone technology, drone elements are incorporated into the unmanned intelligent traffic management system. Some existing drone aerial photography technologies can alleviate the above problems. For example, the patent with the application number 202310858179.3 discloses a method, system, and device for obtaining the cause of road congestion based on intelligent traffic lights. Its intelligent drone generally stays on the charging base set on the fixed pole of the intelligent traffic light for charging. However, once the intelligent drone receives the drone aerial photography instruction sent by the background server, it conducts cruise aerial photography based on the shooting area corresponding to the drone aerial photography instruction and sends the aerial traffic picture set obtained from the aerial photography to the background server for the background server to determine the cause of road congestion based on the aerial traffic picture set.

[0006] The principle is to quickly obtain the cause of road congestion by using drones to photograph congestion points or areas. The shooting range is expanded and the shooting is more flexible. However, it still does not fully solve the above problem 2 for the following reasons: The solution of the above patent is that the background server sends a drone aerial photography instruction, and the drone conducts cruise aerial photography on the shooting area corresponding to the drone shooting instruction. The drone aerial photography instruction is generated with the current road intersection as the congestion point, that is, the location of the drone aerial photography is the congestion point. It cannot photograph the sidewalks around the traffic lights, cannot capture the direction of pedestrian flow, and cannot create the above "green channel" either.

[0007] In addition, the above patent also has the following technical problems: The existing automatic return of drones relies on existing GPS positioning and navigation systems, visual positioning systems or wireless communication links, but in the actual return process, it is easily interfered by factors such as weather and signal strength, resulting in the take-off point and the return point not coinciding, making it difficult to achieve precise landing. This is also the technical difficulty of the current automatic return function of drones, which hinders the organic integration of drones and unmanned intelligent traffic control systems. Summary of the invention

[0008] In view of the deficiencies of the prior art, the advantages of drones and intelligent traffic control systems are combined to solve the problem of long waiting time for pedestrians at intersections. The present invention provides an intelligent traffic light traffic control system, including a rotatable camera installed on a traffic light pole; including an intelligent control unit installed on the traffic light pole; the intelligent control unit obtains the number of vehicles queuing at the corresponding traffic light and the number of people waiting on both sides of the sidewalk at the corresponding traffic light in real time through the camera, and obtains the duration and phase of the current traffic light in the traffic control system through the network; if there is no waiting vehicle before the end of the green light time, the intelligent control unit sends a yellow light change request to the traffic control system to end the green light time of the vehicle in advance; if there is no waiting pedestrian before the end of the green light time, the intelligent control unit sends a red light change request to the traffic control system to end the green light time of the pedestrian in advance; if the number of waiting people ÷ the number of vehicles ≥ N, and N ≥ 3, the intelligent control unit sends a request to the traffic control system to increase the green light passage time of pedestrians by 2N-10 seconds, otherwise the duration and phase of the current traffic light are maintained; including a drone take-off and landing platform installed on the traffic light pole and electromagnetic lower positioning parts located on both sides of the drone take-off and landing platform; including a drone, a drone An aerial photography component and an electromagnetic upper positioning component are provided; when 2N-10>60, the drone takes off, takes the traffic light as the center, obtains the pedestrian distribution data of all pedestrian roads within a range of 50-500 meters, and sends the data to the intelligent control unit. If pedestrians are concentrated on one or more pedestrian roads, the drone follows the flow direction of the concentrated crowd, and the intelligent control unit simulates the flow route of the concentrated crowd and sends a request to the traffic control system that the light change phases of all pedestrian traffic lights in the route are consistent and the green light time is increased by 60 seconds, until 2N-10≤60; after the drone follows the filming, it returns to the top of the drone landing platform through satellite positioning and inertial navigation, and the electromagnetic upper positioning component and the electromagnetic lower positioning component are energized to generate a magnetic field. The electromagnetic upper positioning component and the electromagnetic lower positioning component attract each other to pull the drone to land on the drone landing platform, and the drone is charged and on standby; during the period of 2N-10>60, the intelligent control unit re-obtains the pedestrian distribution data and flow direction through the drone every 3 minutes.

[0009] The preferred solution of the intelligent traffic light management system in the present invention is as follows: The UAV take-off and landing platform includes a chassis, an intermediate adjustment disc, and a start-stop charging disc; the chassis is fixed on the crossbar of the traffic light pole, and the start-stop charging disc is connected above the chassis through the intermediate adjustment disc, and the start-stop charging disc can be rotated and tilted relative to the chassis through the intermediate adjustment disc. Further, the intermediate adjustment disc includes a disc body, a steering motor, and an inclination angle motor; a circular ring groove is provided on the upper surface of the chassis, three steering motors and three inclination angle motors are respectively provided, and the three steering motors and the three inclination angle motors are respectively installed on the lower and upper surfaces of the disc body along the circumferential direction of the circular ring groove. The output shaft of each steering motor is provided with a roller rolling in the circular ring groove, the output shaft of each inclination angle motor is provided with a crank, and the end of each crank is connected to the lower surface of the start-stop charging disc through a cross shaft.

[0010] During the landing process of the UAV, it may be necessary to adjust the position of the start-stop charging disc relative to the landing gear of the UAV. In this case, the three steering motors can be rotated synchronously and in the same direction to adjust the angle in the horizontal plane, and the three inclination angle motors can be rotated to adjust the levelness, so as to enable the UAV to be in a stable and effective charging state.

[0011] The preferred solution of the intelligent traffic light management system in the present invention is as follows: A plurality of charging contact strips extending along the radial direction are provided on the upper surface of the start-stop charging disc, and all the charging contact strips are evenly distributed along the circumferential direction; charging contacts corresponding to the charging contact strips are provided at the lower ends of the landing gears of the UAV. The number of charging contact strips is an even number, and every two opposite charging contact strips are one positive and one negative. The landing gear is provided with four support legs, and two charging contacts are provided at the lower end of each support leg. The charging contacts of every two opposite support legs are also one positive and one negative. As long as two paired support legs are in contact with any two opposite charging contact strips, charging can be carried out, while the other two support legs are disconnected and not connected to the charging circuit, without affecting charging. The distributed plurality of charging contact strips can significantly improve the charging success rate after the UAV lands.

[0012] The preferred solution of the intelligent traffic light management system in the present invention is as follows: Each electromagnetic lower positioning member includes a coil and an iron core connected inside the coil. The iron core is longitudinally installed on the crossbar. Each electromagnetic upper positioning member includes an electric winch, a flexible wire, and an electromagnet. The electric winch is connected to the unmanned aerial vehicle (UAV) through a horizontal bracket. The flexible wire is wound around the drum of the electric winch, and the end of the flexible wire is connected to the electromagnet. The two electromagnets correspond to the two iron cores one by one, and the magnetic pole of each electromagnet facing down is opposite to the magnetic pole of the iron core facing up. In fact, both the electromagnetic lower positioning member and the electromagnetic upper positioning member are electromagnet structures. The difference is that the coil of the electromagnetic lower positioning member has a large diameter, a large number of turns, and a large current. The corresponding iron core is made of nickel-iron alloy with high magnetic permeability, which can increase the effective magnetic force of the electromagnetic lower positioning member to dozens of centimeters. Due to the limitation of the UAV itself, the magnetic force of the electromagnetic upper positioning member is relatively weak. After the magnetic fields of the electromagnetic lower positioning member and the electromagnetic upper positioning member overlap, the effective magnetic force range can be further improved. When the UAV flies above the start-stop charging plate through satellite positioning, it then descends in height through inertial navigation. Finally, the electromagnet is lowered by the electric winch into the effective magnetic field range of the electromagnetic lower positioning member, pulling the UAV to accurately land on the start-stop charging plate. At the same time, each landing can calibrate the inertial navigation.

[0013] The preferred solution of the intelligent traffic light management system in the present invention is as follows: The longitudinal rod of the traffic light pole is provided with a speed reduction motor assembly. The output shaft of the speed reduction motor assembly is provided with a sunshade for covering above the UAV takeoff and landing platform. The sunshade is fixedly connected to the output shaft of the speed reduction motor assembly through a connecting rod, and the sunshade is driven by the speed reduction motor assembly to swing in the vertical plane. After the UAV stops on the UAV takeoff and landing platform and after it takes off, the speed reduction motor assembly drives the sunshade to swing to directly above the UAV takeoff and landing platform. Before the UAV takes off and before it lands, the speed reduction motor assembly drives the sunshade to swing 90° to the left or right, exposing the UAV takeoff and landing platform to prepare for takeoff or landing. The sunshade can prevent the UAV and the UAV takeoff and landing platform from being exposed to long-term sunlight or rain, slow down the aging speed, and reduce the failure rate.

[0014] The beneficial effects of the intelligent traffic light management system in the present invention are as follows: 1. The UAV takeoff and landing platform is combined with the traffic light pole to provide a specific start and stop position for the UAV. Each traffic light serves as a dynamic monitoring point, and dynamic traffic light change rules are customized for this monitoring point. UAVs can also be added to all the traffic light poles in a certain area to associate all the traffic lights in this area to form a dynamic monitoring area, and dynamic traffic light change rules are customized for this area, effectively solving the problems of low traffic efficiency, energy waste, and lack of dynamic response ability caused by too long green light time in the case of no cars and no people.

[0015] 2. In special areas such as schools and office buildings, where the pedestrian flow varies greatly at different times, when it is impossible to solve the problem of unsmooth traffic by simply increasing the green light time during the period of extremely large pedestrian flow, drones can be used to obtain the pedestrian density and flow direction in real time in this area, and a "green channel" conducive to the rapid passage of special groups can be customized to meet the requirements of a large number of pedestrians to pass first within a short time, and relieve problems such as traffic congestion, red light running accidents, and driver waiting anxiety caused by the sharp increase in pedestrian flow during special time periods.

[0016] 3. Adopt the 3:1 traffic rule, extend the pedestrian passage time for areas with large pedestrian flow, and the green light time increases step by step. While appropriately increasing the green light time, take into account the pedestrian crossing time and vehicle passage time to avoid chain delays caused by empty running at intersections, which is conducive to reducing the waiting time of pedestrians and vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 is the principle flow of the intelligent traffic light management system in the present invention Figure 1 ; Figure 2 is the principle flow of the intelligent traffic light management system in the present invention Figure 2 ; Figure 3 is the structural schematic diagram of the intelligent traffic light management system in the present invention; Figure 4 is the schematic diagram of the intelligent traffic light management system in the present invention after the drone takes off or before it lands; Figure 5 is the schematic diagram of the intelligent traffic light management system in the present invention after the left side of the drone is positioned; Figure 6 is the schematic diagram of the intelligent traffic light management system in the present invention after both the left and right sides of the drone are positioned; Figure 7 is the schematic diagram of the intelligent traffic light management system in the present invention after the drone lands.

[0019] Reference numerals: longitudinal rod 1, cross bar 2, camera 3, intelligent control unit 4, UAV takeoff and landing platform 5, chassis 501, intermediate adjustment disk 502, start / stop charging disk 503, disk body 504, steering motor 505, tilt motor 506, circular groove 507, roller 508, crank 509, cross shaft 510, charging contact strip 511, charging contact 512, electromagnetic lower positioning member 6, coil 601, iron core 602, UAV 7, electromagnetic upper positioning member 8, electric winch 801, flexible wire 802, electromagnet 803, transverse bracket 804, speed reduction motor assembly 9, sunshade 901, connecting rod 902. Detailed implementation manners

[0020] In view of the deficiencies in the prior art, the inventors of this case have proposed the technical solution of the present invention through long-term research and a large number of practices. The following will further explain the technical solution, its implementation process and principle in combination with the drawings in the embodiments of the present application and specific implementation cases.

[0021] As Figure 3 shown, this embodiment provides an intelligent traffic light management system, including a rotatable camera 3 installed on the traffic light pole. The lens of the camera 3 can face the sidewalk or the vehicle lane, and the camera orientation can be switched in real time.

[0022] In this embodiment, an intelligent control unit 4 is installed on the longitudinal rod 1 of the traffic light pole. The intelligent control unit 4 obtains the number of queuing vehicles at the corresponding traffic light in real time through the camera 3 and obtains the number of waiting people on both sides of the sidewalk at the corresponding traffic light. The intelligent control unit 4 obtains the duration and phase of the current traffic light in the traffic management system through the network. The intelligent control unit 4 specifically uses an industrial computer, which is responsible for independently processing the information at this traffic light. It has logical judgment ability and makes logical judgments based on the obtained information. The judgment result is sent to the traffic management system, and then the traffic management system judges whether to execute it, avoiding directly interfering with the traffic light changing permission.

[0023] For areas with large changes in the flow of people, appropriately extend the green light time of the sidewalk according to the flow of people, reduce the waiting time of pedestrians, and at the same time reduce the impact on passing vehicles. The following variable light method is adopted in this embodiment: As Figure 1 shown, if there are no waiting vehicles before the end of the green light time, the intelligent control unit 4 sends a request to turn the light yellow to the traffic management system, ending the vehicle green light time in advance; if there are no waiting pedestrians before the end of the green light time, the intelligent control unit 4 sends a request to turn the light red to the traffic management system, ending the pedestrian green light time in advance; if the number of waiting people ÷ the number of vehicles ≥ N, and N ≥ 3, the intelligent control unit 4 sends a request to the traffic management system to increase the pedestrian green light passing time by 2N - 10 seconds, otherwise the current traffic light duration and phase are maintained.

[0024] From the above formula, it can be seen that if the number of waiting people is more than three times the number of vehicles, the green light time of the sidewalk will be increased. This can effectively solve the problem of a large number of students waiting for passage during school and after school, as well as the gathering of working people on the sidewalk during peak hours in the morning and evening. The green light time increases step by step. While appropriately increasing the green light time, the pedestrian crossing time and vehicle passing time are taken into account, reducing the probability of pedestrians running red lights and improving road safety. For example, the intelligent control unit 4 obtains the data of 10 waiting people on the sidewalk and 3 waiting vehicles on the road through the camera 3. The intelligent control unit 4 formulates a request of "increasing the green light time of the sidewalk by 5 seconds next time" and sends it to the traffic control system. If the traffic control system determines that the request is feasible, it will issue an instruction to extend the green light time of the sidewalk through the network. Through this method, pedestrian traffic lights in areas with large traffic changes can be used for on-demand passage, avoiding chain delays caused by empty intersections, which is conducive to reducing pedestrians. After each modification of the pedestrian green light time, the intelligent control unit 4 will collect the current number of waiting pedestrians through the camera 3 again, and change the light as needed, which is conducive to reducing the waiting time of vehicles.

[0025] In addition to the above-mentioned areas where the flow of people varies greatly, there are also some special areas where the flow of people varies greatly in different time periods, such as traffic lights around office buildings, where the flow of people during peak hours and evening peaks varies greatly. For these special areas, this embodiment provides the following methods: like Figure 2As shown in the figure, this embodiment includes a drone takeoff and landing platform 5 installed on the traffic light pole and electromagnetic lower positioning parts 6 located on both sides of the drone takeoff and landing platform 5; it includes a drone 7, and the drone 7 is equipped with an aerial photography component and an electromagnetic upper positioning part 8. Among them, the aerial photography component and other necessary parts of the drone 7 are not drawn in the figure. When 2N - 10 > 60, that is, when the increased green light time of the pedestrian passage exceeds 60 seconds, the problem of too many waiting pedestrians still cannot be solved. At this time, the following method is executed: The drone 7 takes off, takes the traffic light as the center, and obtains the pedestrian distribution data of all pedestrian roads within a range of 50 - 500 meters around. Specifically, the flight range is based on the distance between two adjacent traffic lights on the same road. For example, if the distance between two adjacent traffic lights is 300 meters, then the flight radius is 150 meters, and the flight radius of the drone 7 where the next traffic light is located is also 150 meters. The sum of the flight distances of the two drones is equal to 300 meters, thus avoiding the problem of overlapping flight ranges. Specifically, the flight coverage area is based on the distance between two adjacent traffic lights. The coverage area is not necessarily circular and is divided according to the distance. The image data captured by the drone 7 is sent to the intelligent control unit 4 by wireless transmission methods such as Bluetooth, 4G, or 5G. The intelligent control unit 4 finds the pedestrians in the image data. If the pedestrians on one or more sidewalks are concentrated, the drone 7 follows the flow direction of the concentrated crowd. The intelligent control unit 4 simulates the flow route of the concentrated crowd and sends a request to the traffic management system that the traffic light change phases of all pedestrian traffic lights in this route are the same and the green light time is increased by 60 seconds until 2N - 10 ≤ 60. That is, by using the drone 7 to obtain the pedestrian density and flow direction in real time in this area, a "green channel" that is conducive to the rapid passage of special groups is customized, and the requirements of a large number of pedestrians to pass first are met within a short time, alleviating problems such as traffic congestion caused by the sudden increase in the flow of people during special periods and the anxiety of drivers waiting.

[0026] From the above formula 2N - 10 ≤ 60, it can be seen that when the green light time for pedestrians is increased by 60 seconds, this passing time is already very long. If the number of waiting people still cannot be reduced, it can be judged that relying solely on extending the pedestrian passing time of a single pedestrian passage cannot solve the congestion problem. Multiple drones adjacent to the pedestrian-intensive point cooperate to obtain the pedestrian distribution in the area near the congestion point, rather than just the traffic conditions of the driving roads at the congestion point. Then, the intelligent control unit judges the main flow direction of most pedestrians in this area, and creates a "green channel" in this way, which can effectively avoid the need for the crowd to wait in turn to pass through all traffic lights. This is especially suitable for the requirements of pedestrians to have priority in passing in special sections during special periods. After allowing the concentrated crowd to pass first in these sections, the vehicle passing time can be appropriately extended, which is conducive to alleviating vehicle congestion.

[0027] After the follow-up shooting of the drone 7 ends, it returns above the drone takeoff and landing platform 5 through satellite positioning and inertial navigation. The electromagnetic upper positioning member 8 and the electromagnetic lower positioning member 6 are both powered on to generate a magnetic field. The electromagnetic upper positioning member 8 and the electromagnetic lower positioning member 6 attract each other to tow the drone 7 to land on the drone takeoff and landing platform 5, and the drone 7 charges and standby; during the period when 2N - 10 > 60, every 3 minutes, the intelligent control unit 4 re-obtains the pedestrian distribution data and flow direction through the drone 7. Since satellite positioning is easily affected by signal quality and affects the return accuracy, and inertial navigation itself has inherent sensor errors, such as gyroscope drift: the zero bias accumulates over time, and there are also factors such as accelerometer zero bias and scale factor error, resulting in the return accuracy getting worse each time, and the error needs to be calibrated. In this embodiment, the takeoff and landing location of the drone 7 is fixed, and the drone 7 is automatically controlled to start and stop by the intelligent control unit 4. Without failure, it does not require human intervention throughout the year. In order to accurately return to the centimeter level each time, this embodiment is implemented through the following structure: As Figure 3 shown, the electromagnetic lower positioning members 6 each include a coil 601 and an iron core 602 connected inside the coil 601. The iron core 602 is longitudinally installed on the cross bar 2; the electromagnetic upper positioning members 8 each include an electric winch 801, a flexible wire 802 and an electromagnet 803. A flexible steel wire rope is clamped in the flexible wire 802 to improve the tensile strength. The electric winch 801 is connected to the drone 7 through a transverse bracket 804. The flexible wire 802 is wound around the drum of the electric winch 801, and the end of the flexible wire 802 is connected to the electromagnet 803; the two electromagnets 803 correspond to the two iron cores 602 one by one, and the magnetic pole of each electromagnet 803 facing down is opposite to the magnetic pole of the iron core 602 facing up. In fact, both the electromagnetic lower positioning member 6 and the electromagnetic upper positioning member 8 are electromagnet 803 structures. However, the difference is that the coil 601 of the electromagnetic lower positioning member 6 has a large diameter, a large number of turns, and a large current. The corresponding iron core 602 is made of nickel-iron alloy with high magnetic permeability, which can increase the effective magnetic force of the electromagnetic lower positioning member 6 to dozens of centimeters. The electromagnetic upper positioning member 8 is limited by the drone 7 itself, and its magnetic force is relatively weak. After the magnetic fields of the electromagnetic lower positioning member 6 and the electromagnetic upper positioning member 8 overlap, the effective magnetic force range can be further improved. The specific method of landing is as follows: As Figures 4 to 7As shown in the figure, when the drone 7 flies above the start-stop charging plate 503 through satellite positioning and then descends in height through inertial navigation, the distance between the drone 7 and the drone takeoff and landing platform 5 is reduced to within one meter. For example, the electric winch 801 on the right side of the drone 7 lowers the electromagnet 803. Since the upward magnetic field distribution released by the electromagnetic downward positioning member 6 is in the shape of a divergent curve, similar to a "dumbbell shape" or an "apple shape" distribution, the axial magnetic field intensity at the upper and lower ends of the iron core 602 reaches the peak of the external magnetic field. When the electromagnet 803 enters the magnetic field of one of the electromagnetic downward positioning members 6, it is attracted to the upper end of the iron core 602 and attracted by the influence of the magnetic force strength, and precise positioning is achieved on the right side of the drone 7. Then, the electric winch 801 on the left side of the drone 7 lowers the electromagnet 803 and rotates around the electromagnetic downward positioning member 6 on the right side until the electromagnet 803 on the left side enters the magnetic field of another electromagnetic downward positioning member 6 and is attracted to the upper end of the iron core 602 and attracted by the influence of the magnetic force strength, and precise positioning is achieved on the left side of the drone 7. Then, the two electric winches 801 slowly retract, and at the same time, the drone 7 descends synchronously until the landing gear of the drone 7 just touches the upper surface of the start-stop charging plate 503, but the drone 7 is in a hovering state and does not completely stop on the start-stop charging plate 503. Finally, the steering motor 505 rotates to adjust the horizontal angle of the start-stop charging plate 503 so that a set of charging contacts 512 of the drone 7 contacts two of the charging strips 511. After the drone 7 enters the charging mode, it stops and lands. In addition, in order to avoid the influence of the magnetic field on the electronic components of the drone 7, a layer of magnetic shielding material is sprayed on the lower surface of the drone 7, which can avoid the interference of the magnetic field on the drone 7 itself during the landing process.

[0028] The above method can accurately improve the landing accuracy to within 1 centimeter, greatly improving the landing accuracy, solving the technical problem that the automatic return point of the current drone does not coincide with the takeoff point, and promoting the organic combination of the drone and the unmanned intelligent traffic management system. In addition, the method also has the following effects: 1. Each time the drone 7 lands, the inertial navigation automatically calibrates the initial alignment error and the integration error, thus overcoming the defect of cumulative error existing in the existing inertial navigation.

[0029] 2. Since the drone 7 stops on the drone takeoff and landing platform 5 on the traffic light pole, which is several meters above the ground. In bad weather such as strong wind and heavy rain, the two electromagnets 803 are respectively attracted to the two electromagnetic downward positioning members 6, tightly pulling and fixing the drone 7 on the drone takeoff and landing platform 5, effectively preventing it from being blown off by strong wind. In windless weather, the two electromagnets 803 are both powered off from the two electromagnetic downward positioning members 6, saving electric energy. The two electromagnets 803 are retracted by the electric winch 801 before takeoff.

[0030] In order to make the drone 7 land smoothly, the following optimizations are made to the drone takeoff and landing platform 5 in this embodiment: The UAV takeoff and landing platform 5 includes a chassis 501, an intermediate adjustment disk 502, and a start / stop charging disk 503; the chassis 501 is fixed to the cross bar 2 of the traffic signal pole, and the start / stop charging disk 503 is connected above the chassis 501 through the intermediate adjustment disk 502. The start / stop charging disk 503 can be rotated and tilted relative to the chassis 501 through the intermediate adjustment disk 502. Further, the intermediate adjustment disk 502 includes a disk body 504, a steering motor 505, and an inclination motor 506; a circular ring groove 507 is provided on the upper surface of the chassis 501. There are three steering motors 505 and three inclination motors 506 respectively. The three steering motors 505 and the three inclination motors 506 are respectively installed on the lower and upper surfaces of the disk body 504 along the circumferential direction of the circular ring groove 507. A roller 508 that rolls in the circular ring groove 507 is provided on the output shaft of each steering motor 505. By synchronously rotating the three steering motors 505 in the same direction in the circular ring groove 507, the angle of the start / stop charging disk 503 in the horizontal plane is adjusted. A crank 509 is provided on the output shaft of each inclination motor 506, and the end of each crank 509 is connected to the lower surface of the start / stop charging disk 503 through a cross shaft 510. The functions of the three groups of inclination motors 506 and the cross shafts 510 are as follows: First: During the landing process of the UAV 7, it may be tilted at a certain angle to one side due to traction. In order to meet the inclined landing of the UAV 7, the three groups of inclination motors 506 drive the corresponding cross shafts 510 to tilt the start / stop charging disk 503, and the start / stop charging disk 503 is kept parallel to the UAV 7, that is, the UAV 7 lands vertically relative to the start / stop charging disk 503. After the UAV 7 lands on the start / stop charging disk 503, the start / stop charging disk 503 returns to the horizontal state, thereby reducing the landing requirements and difficulties of the UAV 7.

[0031] Second: In strong wind weather, the three groups of inclination motors 506 drive the corresponding cross shafts 510 to tilt the start / stop charging disk 503, and then cooperate with the tension of the two flexible wires 802 to reduce the windward area of the UAV 7 and reduce the risk of the UAV 7 falling.

[0032] In addition, the control and communication module, power management module, sensors and positioning module, safety and auxiliary module, etc. of the UAV takeoff and landing platform 5 are all installed on the upper surface of the intermediate adjustment disc 502. Among them, the charging contact strips 511 for charging of the power management module are arranged on the upper surface of the start-stop charging disc 503. The specific structure is as follows: multiple charging contact strips 511 extending along the radial direction are provided on the upper surface of the start-stop charging disc 503, and all the charging contact strips 511 are evenly distributed along the circumferential direction; charging contacts 512 corresponding to the charging contact strips 511 are provided at the lower ends of the landing gears of the UAV 7. The number of the charging contact strips 511 is an even number, and every two opposite charging contact strips 511 are one positive and one negative. The landing gear has four support legs, and two charging contacts 512 are provided at the lower end of each support leg. The charging contacts 512 of every two opposite support legs are also one positive and one negative. As long as the two paired support legs are in contact with any two opposite charging contact strips 511, charging can be carried out, while the other two support legs are disconnected and not connected to the charging circuit, without affecting charging. The multiple distributed charging contact strips 511 can significantly improve the charging success rate after the UAV 7 lands.

[0033] To prevent the UAV 7 from being exposed to the sun or rained on for a long time, a speed reduction motor assembly 9 is provided on the longitudinal rod 1 of the traffic signal pole. A sunshade 901 for covering above the UAV takeoff and landing platform 5 is provided on the output shaft of the speed reduction motor assembly 9. The sunshade 901 is fixedly connected to the output shaft of the speed reduction motor assembly 9 through a connecting rod 902, and the sunshade 901 is driven by the speed reduction motor assembly 9 to swing in the vertical plane. After the UAV 7 lands on the UAV takeoff and landing platform 5 and after the UAV 7 takes off, the speed reduction motor assembly 9 drives the sunshade 901 to swing to directly above the UAV takeoff and landing platform 5. Before the UAV 7 takes off and before the UAV 7 lands, the speed reduction motor assembly 9 drives the sunshade 901 to swing 90° to the left or right, exposing the UAV takeoff and landing platform 5 to prepare for takeoff or landing. The sunshade 901 can prevent the UAV 7 and the UAV takeoff and landing platform 5 from being exposed to the sun or rained on for a long time, slow down the aging speed, and reduce the failure rate.

[0034] The above optimizes the UAV takeoff and landing platform, which can greatly reduce the takeoff and landing failures of the UAV and improve the ability to resist bad weather, providing hardware guarantee for the stable and safe operation of the intelligent traffic signal management system. If the normal takeoff and landing operations of the UAV cannot be ensured and the UAV often falls from the takeoff and landing platform, this not only cannot capture the information of people and vehicles near the traffic signal in real time, but also increases the maintenance work of the UAV, losing the meaning of the unattended intelligent traffic management system itself.

[0035] It should be understood that the above embodiments are only for illustrating the technical concept and features of the present invention, and the purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. It cannot be determined that the specific implementation of the present invention is only limited to these descriptions. For those of ordinary skill in the technical field to which the present invention belongs, without departing from the concept of the present invention, several simple deductions or substitutions can also be made. All equivalent changes or modifications made according to the spirit and essence of the present invention should be covered within the protection scope of the present invention.

Claims

1. An intelligent traffic light management system, comprising a rotatable camera installed on a traffic light pole; characterized in that: It includes an intelligent control unit installed on the traffic signal pole; The intelligent control unit obtains the number of queuing vehicles at the corresponding traffic light in real time through a camera and obtains the number of waiting people on both sides of the sidewalk at the corresponding traffic light. The intelligent control unit obtains the duration and phase of the current traffic light in the traffic management system through the network; If there are no waiting vehicles before the end of the green light time, the intelligent control unit sends a request to turn the light yellow to the traffic management system to end the green light time for vehicles in advance; If the number of waiting people ÷ the number of vehicles ≥ N, and N ≥ 3, the intelligent control unit sends a request to the traffic management system to increase the green light passing time for pedestrians by 2N - 10 seconds. Otherwise, the duration and phase of the current traffic light are maintained; It includes a drone takeoff and landing platform installed on the traffic signal pole and electromagnetic lower positioning parts on both sides of the drone takeoff and landing platform; it includes a drone, and the drone is equipped with an aerial photography component and an electromagnetic upper positioning part; When 2N - 10 > 60, the drone takes off. Centering on this traffic light, it obtains the pedestrian distribution data of all sidewalks within a range of 50 - 500 meters around, and sends this data to the intelligent control unit. If pedestrians gather on one or more sidewalks, the drone follows the flow direction of the concentrated crowd. The intelligent control unit simulates the flow route of the concentrated crowd and sends a request to the traffic management system that the traffic light change phases of all pedestrian traffic lights in this route are the same and the green light time is increased by 60 seconds until 2N - 10 ≤ 60; After the drone finishes following, it returns above the drone takeoff and landing platform through satellite positioning and inertial navigation. The electromagnetic upper positioning part and the electromagnetic lower positioning part are both powered on to generate a magnetic field, and the drone is attracted by the electromagnetic upper positioning part and the electromagnetic lower positioning part to land on the drone takeoff and landing platform, and the drone charges and standby; During the period when 2N - 10 > 60, every 3 minutes, the intelligent control unit obtains the pedestrian distribution data and flow direction again through the drone.

2. The intelligent traffic light management system according to claim 1, characterized in that: The drone takeoff and landing platform includes a chassis, an intermediate adjustment disk and a start-stop charging disk; the chassis is fixed on the crossbar of the traffic signal pole, and the start-stop charging disk is connected above the chassis through the intermediate adjustment disk. The start-stop charging disk can be rotated and tilted relative to the chassis through the intermediate adjustment disk.

3. An intelligent traffic light management system according to claim 2, characterized in that: The intermediate adjustment disk includes a disk body, a steering motor and an inclination motor; there is a circular ring groove on the upper surface of the chassis. There are three steering motors and three inclination motors respectively. The three steering motors and the three inclination motors are respectively installed on the lower and upper surfaces of the disk body along the circumferential direction of the circular ring groove. The output shaft of each steering motor is provided with a roller rolling in the circular ring groove, and the output shaft of each inclination motor is provided with a crank. The end of each crank is connected to the lower surface of the start-stop charging disk through a cross shaft.

4. An intelligent traffic light management system according to claim 3, characterized in that: The upper surface of the start-stop charging disk is provided with a plurality of charging contact strips extending along the radial direction, and all the charging contact strips are evenly distributed along the circumferential direction; the lower end of the landing gear of the drone is provided with charging contacts corresponding to the charging contact strips.

5. An intelligent traffic light management system according to claim 4, characterized in that: The electromagnetic lower positioning members all include coils and iron cores connected inside the coils, and the iron cores are longitudinally installed on the cross bars; the electromagnetic upper positioning members all include electric winches, flexible wires and electromagnets; the electric winches are connected to the unmanned aerial vehicle through transverse brackets, the flexible wires are wound around the drums of the electric winches, and the ends of the flexible wires are connected to the electromagnets; the two electromagnets correspond to the two iron cores one by one, and the magnetic poles of each electromagnet facing downwards are opposite to the magnetic poles of the iron cores facing upwards.

6. An intelligent traffic light management system according to claim 5, characterized in that: The longitudinal rod of the traffic signal pole is provided with a reduction motor assembly, and the output shaft of the reduction motor assembly is provided with a sunshade for covering above the take-off and landing platform of the unmanned aerial vehicle. The sunshade is fixedly connected to the output shaft of the reduction motor assembly through a connecting rod, and the sunshade is driven by the reduction motor assembly to swing in the vertical plane.

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