Regional traffic intelligent green wave control method and system based on cloud side-end cooperation

Abstract

The invention provides a regional traffic intelligent green wave control method and system based on cloud side end collaboration, and the method comprises the steps that a cloud server obtains a green wave route where green waves need to run, green wave cooperative control units are constructed according to the green wave route, and each green wave cooperative control unit corresponds to a green wave section of the green wave route; calculating application side phase shortest green time of all intersections in the green wave section, calculating response side phase opening time of all the green wave section, and calculating response side phase shortest green time of all the intersections in all the green wave section; constructing a time factor of a phase of an applicant and a time factor of a phase of a responder, constructing a periodic change of a green wave cooperative control unit, and sending data of the periodic change to edge end equipment corresponding to all intersections of a green wave section; and each edge end device performs green time adjustment on the current phase according to the received periodically changed data. The system realizes the method. According to the invention, dynamic adjustment of green waves can be realized, and the traffic efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic light control, and in particular to a method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration and a system for implementing the method. Background Art

[0002] With the development of social economy, the number of urban population and motor vehicles is increasing, and the problem of urban traffic congestion is becoming more and more serious. At present, there are a large number of intersections on urban roads, and many intersections are equipped with traffic lights. Motor vehicles and pedestrians pass according to the signals of the traffic lights. If the release time of the traffic lights at multiple intersections is not set reasonably, the roads will become more congested. Therefore, reasonable urban traffic signal control can effectively alleviate traffic congestion, but traditional control methods are difficult to apply to complex traffic control problems.

[0003] Some existing traffic coordination control systems use cloud servers, edge devices, and device-side device system control to coordinate the processing of traffic lights at each intersection to improve the traffic efficiency of the area. For example, the invention patent application with publication number CN116884248A discloses a traffic signal phase control method based on intelligent cycles. The scheme collects vehicle data at each intersection and phase, and performs vehicle benchmarking and standardization operations, and then intelligently adjusts the phase sequence of each intersection and phase according to the traffic flow of each intersection, so as to improve the traffic efficiency of each intersection.

[0004] With the changes in traffic organization, by implementing green wave control on some routes in the region, especially the trunk routes, so that the trunk routes can run in green wave mode for a period of time, the traffic efficiency of the trunk routes can be greatly improved, which is of great help to improve the traffic efficiency of the entire area. However, when setting the green wave operation mode, the existing traffic control system often fixes the operation time of the green wave, that is, after certain routes are set in the green wave mode, the phase sequence of the corresponding intersection and the travel time of each phase are fixed.

[0005] However, due to the great randomness and contingency of traffic operation, if the operation time of the green wave is fixed, it is easy for fewer vehicles to pass through the green wave route during a certain period of time, resulting in a long period of time when the green wave route is in a state of sparse vehicles, which in turn affects the traffic efficiency of other routes in the area and reduces the overall traffic efficiency of the area. Summary of the invention

[0006] The first objective of the present invention is to provide a regional traffic intelligent green wave control method based on cloud-edge-end collaboration that can dynamically control green wave routes.

[0007] The second objective of the present invention is to provide a regional traffic intelligent green wave control system based on cloud-edge-end collaboration that can improve the traffic efficiency of regional routes.

[0008] To achieve the above-mentioned first purpose, the regional traffic intelligent green wave control method based on cloud-edge-end collaboration provided by the present invention includes a cloud server obtaining a green wave route that needs to run a green wave, constructing a green wave collaborative control unit according to the green wave route, and each green wave collaborative control unit corresponds to a green wave section of the green wave route; calculating the shortest green time of the applicant phase of all intersections in the green wave section, and calculating the responder phase opening time of all green wave sections, and calculating the shortest green time of the responder phase of all intersections in all green wave sections; constructing the time factor of the applicant phase and the time factor of the responder phase, constructing the periodic change of the green wave collaborative control unit according to the time factor of the applicant phase and the time factor of the responder phase, and sending the data of the periodic change to the edge devices corresponding to all intersections of the green wave section; each edge device adjusts the green time of the current phase according to the received periodic change data.

[0009] It can be seen from the above scheme that the green wave route is split into multiple green wave sections, and each green wave section constructs a corresponding green wave collaborative control unit. When the green wave is running on the green wave section, the time factor of the applicant phase and the time factor of the responder phase are calculated, and the corresponding time factor of the applicant phase and the time factor of the responder phase are sent according to the actual situation of each intersection, so that each edge device can adjust the current phase according to the received periodic data, thereby realizing the dynamic adjustment of the green wave operation time. In this way, the green wave operation time of each intersection and phase is not fixed, but dynamically adjusted according to the actual situation, thereby improving the traffic efficiency of the route in the entire area.

[0010] A preferred solution is that each edge device adjusts the green time of the current phase according to the received periodic changing data, including: the edge device adjusts the green time of the current phase according to the received periodic changing data based on the pre-calculated intelligent phase sequence or intelligent cycle.

[0011] Since each edge device has been operating the intelligent phase sequence or intelligent cycle according to the pre-set rules, after receiving the data of cycle changes, the green time of the current phase is adjusted according to the received data of cycle changes, which can avoid sudden changes in the operating phase sequence and reduce the impact on traffic operations.

[0012] A further solution is that the edge device of an intersection only receives the time factor of one applicant phase; the edge device of an intersection can receive the time factors of more than one responder phase.

[0013] It can be seen that an intersection can only receive the time factor of one applicant phase, that is, an intersection can only be set with one applicant phase, but can be set to multiple responder phases, which can avoid the problem of operating phase sequence conflict caused by running multiple applicant phases at the same intersection.

[0014] A further solution is that the time factor of the applicant phase includes the applicant phase and the shortest green time of the applicant phase.

[0015] A further solution is that the time factor of the responder phase includes the applicant's intersection unique identifier, the applicant's phase, the responder phase opening time, the responder phase and the shortest green time of the responder phase.

[0016] It can be seen that by setting multiple parameters of the applicant's phase time factor and the responder's phase time factor, the corresponding edge device can calculate the periodic change data based on the applicant's phase time factor and the responder's phase time factor, thereby making precise adjustments to the current phase sequence and green wave communication time.

[0017] A further solution is that the shortest green time of the applicant phase is calculated in the following way: shortest green time of the applicant phase = the distance from the threshold-th traffic participant of the applicant phase to the entrance stop line - the distance from the first traffic participant of the applicant phase to the entrance stop line / average vehicle speed of the green wave section + compensation value of the shortest green time of the green wave phase; among which the compensation value of the shortest green time of the green wave phase is a preset value.

[0018] A further solution is that the responder phase opening time is calculated in the following way: responder phase opening time = (distance from the first traffic participant of the applicant phase to the entrance stop line + distance of the green wave section) / average vehicle speed of the green wave section.

[0019] A further solution is that the shortest green time of the responder phase is calculated in the following way: the shortest green time of the responder phase = (the distance from the threshold-th traffic participant of the applicant phase to the entrance stop line + the distance of the green wave section) / the average vehicle speed of the green wave section - the responder phase opening time + the green wave phase shortest green time compensation value.

[0020] It can be seen that the above formula can accurately calculate parameters such as the applicant's phase shortest green time, the responder's phase opening time and the responder's phase shortest green time, providing a basis for accurately adjusting the green wave operation time of each intersection.

[0021] To achieve the above-mentioned second purpose, the regional traffic intelligent green wave control system based on cloud-edge-end collaboration provided by the present invention includes a cloud server and one or more edge devices; wherein the cloud server is provided with a dynamic green wave control engine, which is used to obtain the green wave route where the green wave needs to be run, and construct a green wave collaborative control unit according to the green wave route, each green wave collaborative control unit corresponds to a green wave section of the green wave route; calculate the shortest green time of the applicant phase of all intersections in the green wave section, and calculate the responder phase opening time of all green wave sections, and calculate the shortest green time of the responder phase of all intersections in all green wave sections; construct the time factor of the applicant phase and the time factor of the responder phase, construct the periodic change of the green wave collaborative control unit according to the time factor of the applicant phase and the time factor of the responder phase, and send the data of the periodic change to the edge devices corresponding to all intersections of the green wave section; each edge device is used to adjust the green time of the current phase according to the received periodic change data.

[0022] A preferred solution is that the cloud server stores a green wave parameter model, a green wave scheme model and a green wave scheduling scheme model.

[0023] It can be seen from the above scheme that the green wave parameter model, the green wave scheme model and the green wave scheduling scheme model are stored on the cloud server, and the cloud server can quickly calculate the appropriate green wave travel time under the current road conditions through the above models. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a structural block diagram of an embodiment of the regional traffic intelligent green wave control system based on cloud-edge-end collaboration of the present invention.

[0025] Figure 2 It is a structural block diagram of the dynamic green wave model in the embodiment of the regional traffic intelligent green wave control system based on cloud-edge-end collaboration of the present invention.

[0026] Figure 3 This is a schematic diagram of multiple green wave intersections.

[0027] Figure 4 It is a structural block diagram of the edge device in an embodiment of the regional traffic intelligent green wave control system based on cloud-edge-end collaboration of the present invention.

[0028] Figure 5 It is a flow chart of an embodiment of the regional traffic intelligent green wave control method based on cloud-edge-end collaboration of the present invention.

[0029] The present invention is further described below in conjunction with the accompanying drawings and embodiments. DETAILED DESCRIPTION

[0030] The present invention collects real-time images of road traffic participants through cameras installed at intersections, analyzes the traffic flow conditions at various intersections and routes, and calculates the green wave timing of various intersections on routes that need to run green waves in combination with a pre-set green wave model, thereby achieving dynamic green wave timing adjustment to improve regional traffic efficiency.

[0031] Example of regional traffic intelligent green wave control system based on cloud-edge-end collaboration:

[0032] See also Figure 1 The regional traffic intelligent green wave control system based on cloud-edge-end collaboration of the present invention comprises a cloud server 100, an edge device 200 and a device-end device 300. An edge device 200 is arranged at a traffic intersection. A traffic intersection includes multiple directions, and each direction has multiple lanes. Usually, the traffic directions of different lanes are different. For example, there are four lanes in one direction, the leftmost lane is a left turn lane, the two middle lanes are through lanes, and the rightmost lane is a right turn lane.

[0033] At least one set of traffic lights needs to be set for each direction. Multiple sets of traffic lights at an intersection are usually controlled by a traffic light. Usually, the device-side device 300 includes a traffic light, a camera set at the intersection, etc. In addition, the edge-end device 200 can communicate with the cloud server 100 on the one hand and obtain the traffic configuration model from the cloud server 100. On the other hand, the edge-end device 200 also communicates with the device-side device 300, for example, to obtain the runtime data of the traffic light, send control instructions to the traffic light, etc. Usually, a cloud server 100 can communicate with multiple edge-end devices 200, and the cloud server 100 can coordinate the work of multiple edge-end devices 200.

[0034] The cloud server 100 includes a dynamic green wave control engine 110 and a rule engine 180 , wherein the dynamic green wave control engine 110 includes a dynamic green wave evaluator 120 , a dynamic green wave lifecycle manager 130 , a dynamic green wave coordinator 140 , a dynamic green wave time factor 150 , a dynamic green wave operation monitor 160 , and a dynamic green wave model 170 .

[0035] The dynamic green wave evaluator 120 is provided with an intersection control mode evaluation module 121, an edge device monitoring state evaluation module 122, and a telemetry data real-time evaluation module 123, wherein the intersection control mode evaluation module 121 is used to evaluate whether each intersection has the conditions to enter the dynamic green wave control according to the current actual situation of each intersection, and the edge device monitoring state evaluation module 122 is used to obtain the status data of each edge device 200, and judge whether each edge device 200 is ready to enter the dynamic green wave control conditions according to the status data of each edge device 200. The telemetry data real-time evaluation module 123 is used to obtain telemetry data, such as obtaining data such as the traffic volume on the road through a camera, and evaluate whether the conditions for entering the dynamic green wave control are met according to the telemetry data.

[0036] The dynamic green wave lifecycle manager 130 includes an intersection ready state module 131, a section ready state module 132, a trunk ready state module 133 and a region ready state module 134, wherein the intersection ready state module 131 is used to determine whether each intersection is ready and can enter the dynamic green wave control mode, while the section ready state module 132 is used to determine whether each section is ready, the trunk ready state module 133 is used to determine whether each trunk is ready, and the region ready state module 134 is used to determine whether each intersection and section of the entire region is ready. If the entire region is ready, the dynamic green wave control mode can be entered.

[0037] The dynamic green wave coordinator 140 includes a trunk coordinator 141 and a regional coordinator 142, wherein the trunk coordinator 141 is used to coordinately control the edge devices 200 set at multiple intersections on the trunk, and the regional coordinator 142 is used to coordinately control the edge devices 200 set at multiple intersections in the entire area.

[0038] The dynamic green wave time factor 150 stores the applicant phase 151, the applicant phase shortest green time 152, the responder phase 153 and the responder phase shortest green time 154. The green wave phase is the phase of the designated intersection set as the green wave phase on the cloud server 100. These green wave phases will generate green wave routes. When a certain intersection enters the green wave phase, the phase becomes the applicant phase 151. When the threshold number of traffic participants in a certain intersection leaves the applicant phase of the intersection, some phases that can reach other intersections are called responder phases 153. The dynamic green wave time factor 150 needs to store which phases of which intersections are in the applicant phase 151 and the responder phase 153.

[0039] The dynamic green wave operation monitor 160 is provided with a dynamic green wave monitor 161 for monitoring the operation of the dynamic green wave. Once an abnormality occurs, an abnormality report is issued to facilitate manual adjustment of the operation parameters of the dynamic green wave or exit from the operation mode of the dynamic green wave.

[0040] The dynamic green wave model 170 stores a plurality of different parameter models, see Figure 2 The dynamic green wave model 170 stores a green wave parameter model 171, a green wave scheme model 174 and a green wave scheduling scheme model 177, wherein the green wave parameter model 171 includes a static parameter model 172 and a dynamic parameter model 173, the green wave scheme model 174 includes a phase model 175 and a phase timing model 176, and the green wave scheduling scheme model 177 includes a scheduling method 178 and a traffic scheme worksheet model 179. The above parameters and models are all pre-set and stored in the cloud server 100.

[0041] The dynamic green wave control engine 110 communicates with the edge device 200 through the rule engine 180. A device reporting rule node 181 and a device sending rule node 182 are set in the rule engine 180. The data of the edge device 200 is sent to the dynamic green wave control engine 110 through the reporting rule node 181, and the data of the dynamic green wave control engine 110 is sent to the edge device 200 through the device sending rule node 182.

[0042] When this embodiment performs dynamic green wave control on routes within a region, it is necessary to pre-set multiple parameters. Specifically, it is necessary to calculate the average speed of the region, which is the average speed of all vehicles traveling in the region. This embodiment sets the concept of "pass threshold percentage", which indicates the proportion of the number of traffic participants who can successfully pass through a certain intersection according to the dynamic green wave algorithm at each release, that is, the number of traffic participants who can successfully pass through a certain intersection can be obtained by calculating the total number of traffic participants in the queue × the pass threshold percentage.

[0043] For a certain green wave section, a starting entrance and an end entrance are set, such as Figure 3 As shown, assuming that a traffic participant at a certain entrance of intersection 401 can reach a certain entrance of intersection 402, the entrance of intersection 401 is called a starting entrance, and the entrance of intersection 402 is called a terminal entrance.

[0044] For a certain intersection, the concepts of the first traffic participant and the threshold-th traffic participant are set, where the traffic participant who is closest to the entrance and in the queue is called the first traffic participant, and the last traffic participant of the traffic participant queue threshold number calculated according to the pass threshold percentage is called the threshold-th traffic participant. For example, according to the pass threshold percentage, it is calculated that 50 traffic participants should be able to pass through the intersection at a certain time, then the 50th traffic participant is called the threshold-th traffic participant.

[0045] In addition, this embodiment introduces the concept of a green wave route, and a green wave route can be generated according to the green wave phase. A green wave route can include any number of intersections. Figure 3 As shown, assuming that the green wave phase of intersection 401 is north-south straight driving, and the green wave phase of intersection 402 is north-south straight driving, these two green wave phases will generate two green wave routes: the first green wave route is from the northbound straight road of intersection 401 to the southbound straight road of intersection 402, and the second green wave route is from the southbound straight road of intersection 403 to the northbound straight road of intersection 402.

[0046] According to the green wave routes generated by the green wave phase, any two interconnected intersections constitute a green wave coordinated control unit. For example, the green wave phase of intersection 401 is north-south straight driving, the green wave phase of intersection 402 is north-south straight driving, and the green wave phase of intersection 403 is north-south straight driving. These two green wave phases will generate two green wave routes: the first green wave route is from the northbound straight road of intersection 401 to the southbound straight road of intersection 402 + the northbound straight road of intersection 402 to the southbound straight road of intersection 403; the second green wave route is from the southbound straight road of intersection 403 to the northbound straight road of intersection 402 + the southbound straight road of intersection 402 to the northbound straight road of intersection 401.

[0047] According to the above green wave route, four green wave coordinated control units can be constructed, which are as follows: the first green wave coordinated control unit includes: the northbound straight road of intersection 401 to the southbound straight road of intersection 402; the second green wave coordinated control unit includes: the northbound straight road of intersection 402 to the southbound straight road of intersection 403; the third green wave coordinated control unit: from the southbound straight road of intersection 403 to the northbound straight road of intersection 402; the fourth green wave coordinated control unit: from the southbound straight road of intersection 402 to the northbound straight road of intersection 401.

[0048] In addition, in order to avoid the calculated phase running green time being too short, the system configures the shortest green time compensation mechanism, that is, setting a green wave phase shortest green time compensation value, which is a pre-set value. Of course, the green wave phase shortest green time compensation value set for each intersection can be different according to the actual situation of different intersections.

[0049] If a certain intersection enters the applicant phase, the shortest time required for the threshold-th traffic participant in the phase to successfully leave the applicant phase is called the applicant phase shortest green time. The time required for the first traffic participant in a certain intersection to get from the applicant phase of the intersection to its corresponding responder phase is called the responder phase opening time. After the first traffic participant in a certain intersection has experienced the responder phase opening time and arrived at the responder phase, the shortest time required for the threshold-th traffic participant to successfully leave the responder phase is called the responder phase shortest green time.

[0050] See also Figure 4 The edge device 200 has a green wave scheme scheduler 210, a visual acquisition and AI reasoning engine 220, and a dynamic green wave phase control unit 230, wherein the green wave scheme scheduler 210 is provided with system configuration parameters 211, system context 212, traffic scheme work table 213, traffic scheme time table 214 and a scheduling engine 215. The visual acquisition and AI reasoning engine 220 is provided with a visual acquisition module 221 of a traffic camera at an intersection, a visual AI reasoning task module 222 and structured vehicle data and pedestrian data 223.

[0051] The dynamic green wave phase control unit 230 is provided with a real-time traffic condition collector 240, a phase timer 250, a dynamic green wave optimizer 260 and a traffic phase actuator 270. Among them, the real-time traffic condition collector 240 is provided with a real-time vehicle data collector 241 at the intersection, a signal operation information collector 242 and a real-time traffic condition model synthesizer 243. The real-time vehicle data collector 241 at the intersection obtains the vehicle data of each intersection by obtaining the data of the visual acquisition and AI reasoning engine 220. The signal operation information collector 242 is used to obtain the data of the signal of each device end device 300. The real-time traffic condition model synthesizer 243 synthesizes the real-time traffic model of each intersection according to the vehicle data of each intersection and the data of the signal.

[0052] The phase timer 250 has a vehicle acquisition device 251, a vehicle data benchmarking 252, a phase vehicle standardization 253 and a phase time table 254, wherein the vehicle acquisition device 251 is used to acquire vehicle data of each entrance of each intersection, the vehicle data benchmarking 252 and the phase vehicle standardization 253 respectively benchmark and standardize the vehicle data of each entrance, and the vehicle standardization and benchmarking calculation are disclosed in CN116884248A and will not be repeated. The phase time table 254 is used to record the execution order and running time of each phase of the intersection.

[0053] The dynamic green wave optimizer 260 has a dynamic green wave application / response manager 261, a phase cycle adjuster 262, and a phase sequence / phase time adjuster 263. The dynamic green wave application / response manager 261 is used to accept the application request of the dynamic green wave and respond to the application request, such as performing response management, the phase cycle adjuster 262 adjusts the cycle of each phase according to the application of the dynamic green wave, such as increasing the passing time or reducing the passing time, etc., and the phase sequence / phase time adjuster 263 is used to adjust the time of each phase sequence and phase.

[0054] The traffic phase executor 270 has a current operation context 271, a phase ready waiting queue 27, a run phase queue 273, a phase ready waiting queue 274, a phase execution instruction mapper 275, and a signal machine instruction executor 276. The current operation context 271 is the previous phase information and the following phase data of the phase currently run by the edge device 200, the phase ready waiting queue 27 is the phase queue that is about to be run, the run phase queue 273 is the phase data that has been run before the current phase, the phase ready waiting queue 274 is the phase queue information that is ready to run, the phase execution instruction mapper 275 is used to realize the mapping of phase execution instructions, and the signal machine instruction executor 276 is used to control the execution instructions of the signal machine.

[0055] An embodiment of a method for controlling regional traffic intelligent green waves based on cloud-edge-end collaboration:

[0056] Combine the following Figure 5 The invention introduces a method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration. The procedure executes step S11, the cloud server obtains a green wave route on which the green wave needs to be operated, preferably, the green wave route is split into multiple green wave sections, for example, the green wave route is split into multiple green wave sections according to a certain distance or according to a certain number of intersections, each green wave section can correspond to a green wave collaborative control unit, therefore, a green wave collaborative control unit involves at least two edge devices at the intersections.

[0057] Then, step S12 is executed to calculate the shortest green time of the applicant phase of all intersections in all green wave sections. Specifically, the shortest green time of the applicant phase of an intersection = the distance from the threshold-th traffic participant of the applicant phase to the entrance stop line - the distance from the first traffic participant of the applicant phase to the entrance stop line / the average speed of the green wave section + the compensation value of the shortest green time of the green wave phase. The shortest green time of the applicant phase of each intersection is calculated by the above formula. By setting the compensation value of the shortest green time of the green wave phase, the problem of too short green wave passage time at a certain intersection can be avoided.

[0058] Next, step S13 is executed to calculate the responder phase opening time of all green wave sections. Specifically, the responder phase opening time of a green wave section is calculated using the following formula: responder phase opening time = (distance from the first traffic participant of the applicant phase to the entrance stop line + distance of the green wave section) / average vehicle speed of the green wave section.

[0059] Then, execute step S14 to calculate the shortest green time of the responder phase at all intersections in all green wave sections. Specifically, the shortest green time of the responder phase at the intersection is calculated using the following calculation: Shortest green time of the responder phase = (the distance from the threshold-th traffic participant of the applicant phase to the entrance stop line + the distance of the green wave section) / average vehicle speed of the green wave section - the responder phase opening time + the shortest green time compensation value of the green wave phase.

[0060] Then, execute step S15 to construct the applicant phase time factor. In this embodiment, the applicant phase time factor includes the applicant phase and the applicant phase shortest green time. After obtaining the above-mentioned applicant phase time factor, the cloud server needs to send the applicant phase time factor to the intersection that is currently in the application stage.

[0061] Next, execute step S16 to construct the responder phase time factor. The responder phase time factor includes the applicant's unique identifier, the applicant's phase, the responder phase opening time, the responder phase, and the responder phase's shortest green time. After constructing the responder phase time factor, the cloud server also needs to send the constructed responder phase time factor to the intersection that is currently in the response stage. It should be noted that an intersection can be in the application stage and the response stage at the same time, and at any time, only one applicant phase time factor will be received, but multiple responder phase time factors can be received. In other words, the edge device of an intersection only receives the time factor of one applicant phase, but can receive more than one responder phase time factor.

[0062] Then, step S17 is executed, and the cloud server constructs the periodic change data of all green wave collaborative control units according to the phase time factor of the applicant and the phase time factor of the responder, and sends the periodic change data to the edge devices of all green wave intersections.

[0063] Finally, the edge devices at each intersection execute step S18, and adjust the green time of the current phase after receiving the data of the cycle change based on the original intelligent cycle / intelligent phase sequence to adapt to the dynamic green wave control mode. For example, the edge device adjusts the cycle of each phase sequence and phase according to the data of the cycle change based on the original calculated basic data of the intelligent cycle or intelligent phase sequence.

[0064] Since the present invention can dynamically set the green wave according to the actual situation of the green wave route, for example, according to the vehicle conditions at each intersection and the main line, for example, various parameters of the applicant phase time factor and the responder phase time factor at each intersection can be calculated, the phase of each intersection can be dynamically adjusted, thereby improving the traffic efficiency of the green wave section, thereby improving the traffic efficiency of the entire area.

[0065] Finally, it should be emphasized that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various changes and modifications. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A regional traffic intelligent green wave control method based on cloud-edge-end collaboration, characterized in that: include: The cloud server obtains a green wave route on which a green wave needs to be operated, and constructs a green wave cooperative control unit according to the green wave route, wherein each of the green wave cooperative control units corresponds to a green wave section of the green wave route; Calculate the shortest green time of the applicant phase at all intersections in the green wave section, calculate the phase opening time of the responder phase at all green wave sections, and calculate the shortest green time of the responder phase at all intersections in all green wave sections; Constructing a time factor of the applicant phase and a time factor of the responder phase, constructing a periodic change of the green wave collaborative control unit according to the time factor of the applicant phase and the time factor of the responder phase, and sending data of the periodic change to edge devices corresponding to all intersections of the green wave section; Each of the edge devices adjusts the green time of the current phase according to the received periodically changing data.

2. The method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration according to claim 1 is characterized by: Each of the edge devices adjusts the green time of the current phase according to the received periodic change data, including: The edge device adjusts the green time of the current phase according to the received periodic change data based on the pre-calculated intelligent phase sequence or intelligent cycle.

3. The method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration according to claim 1 or 2 is characterized in that: The edge device of an intersection only receives the time factor of the phase of the applicant; The edge device of an intersection can receive more than one time factor of the responder phase.

4. The method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration according to claim 1 or 2 is characterized in that: The time factor of the applicant phase includes the applicant phase and the shortest green time of the applicant phase.

5. The method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration according to claim 4 is characterized in that: The time factor of the responder phase includes the applicant intersection unique identifier, the applicant phase, the responder phase opening time, the responder phase and the shortest green time of the responder phase.

6. The method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration according to claim 1 or 2 is characterized in that: The applicant's shortest green time is calculated in the following way: The shortest green time of the applicant phase = the distance from the threshold-th traffic participant of the applicant phase to the entrance stop line - the distance from the first traffic participant of the applicant phase to the entrance stop line / the average speed of the green wave section + the shortest green time compensation value of the green wave phase; The shortest green time compensation value of the green wave phase is a preset value.

7. The method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration according to claim 6 is characterized by: The responder phase opening time is calculated in the following way: The responder phase opening time=(the distance from the first traffic participant in the applicant phase to the entrance stop line+the distance of the green wave section) / the average vehicle speed of the green wave section.

8. The method for intelligent green wave control of regional traffic based on cloud-edge-end collaboration according to claim 7 is characterized by: The shortest green time of the responder phase is calculated in the following way: The shortest green time of the responding phase = (the distance from the threshold-th traffic participant of the applicant phase to the entrance stop line + the distance of the green wave section) / the average vehicle speed of the green wave section - the opening time of the responding phase + the shortest green time compensation value of the green wave phase.

9. Regional traffic intelligent green wave control system based on cloud-edge-end collaboration, including a cloud server and one or more edge devices; Features: The cloud server is provided with a dynamic green wave control engine, which is used to obtain a green wave route where a green wave needs to be operated, and construct a green wave cooperative control unit according to the green wave route, each of which corresponds to a green wave section of the green wave route; Calculate the shortest green time of the applicant phase at all intersections in the green wave section, calculate the phase opening time of the responder phase at all green wave sections, and calculate the shortest green time of the responder phase at all intersections in all green wave sections; Constructing a time factor of the applicant phase and a time factor of the responder phase, constructing a periodic change of the green wave collaborative control unit according to the time factor of the applicant phase and the time factor of the responder phase, and sending data of the periodic change to edge devices corresponding to all intersections of the green wave section; Each of the edge devices is used to adjust the green time of the current phase according to the received periodically changing data.

10. The regional traffic intelligent green wave control system based on cloud-edge-end collaboration according to claim 9 is characterized in that ； The cloud server stores a green wave parameter model, a green wave scheme model and a green wave scheduling scheme model.

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