CN-122018555-A - Unmanned aerial vehicle and ground inspection vehicle collaborative operation method and system based on dynamic task allocation

CN122018555ACN 122018555 ACN122018555 ACN 122018555ACN-122018555-A

Abstract

The invention discloses a collaborative operation system and a collaborative operation method for an unmanned aerial vehicle and a ground inspection vehicle based on dynamic task allocation. The system comprises a task scheduling server, an unmanned aerial vehicle and an inspection vehicle operation unit. The method comprises the steps of maintaining a global road section state table by a server, calculating a dynamic environment risk quantification value, inquiring a target road section state and a risk value after receiving a terminal task request, selecting an arbitration mode according to a threshold value interval to which the risk value belongs, wherein the arbitration mode comprises low-risk standard collaborative arbitration, enabling a patrol vehicle to request priority authorization by giving dynamic priority addition in medium risk, only authorizing the patrol vehicle in high risk, and executing conflict coordination or safe task migration if the road section is occupied. According to the invention, the self-adaptive coordination of the unmanned aerial vehicle and the inspection vehicle is realized in a dynamic environment, the operation safety is effectively ensured, the equipment conflict is avoided, and the overall inspection efficiency and the system reliability are improved through intelligent arbitration driven by risks.

Inventors

ZHONG YINGXIN
HUANG HANHUA
ZHU GUILIN

Assignees

广东科陆智泊信息科技有限公司
广东中维智泊停车服务有限公司

Dates

Publication Date: 20260512
Application Date: 20260127

Claims (10)

1. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation is characterized by comprising a task scheduling server, at least one unmanned aerial vehicle operation unit and at least one patrol vehicle operation unit; The unmanned aerial vehicle operation unit comprises an unmanned aerial vehicle and a control terminal thereof, and the inspection vehicle operation unit comprises an inspection vehicle and a control terminal thereof; The unmanned aerial vehicle control terminal and the inspection vehicle control terminal are respectively in communication connection with the task scheduling server and are used for sending task requests to the server and receiving scheduling instructions; The task scheduling server maintains a global shared road section state table, the road section state table records the real-time occupation state of each inspection road section, and the real-time occupation state comprises an idle state, an occupied state of an unmanned plane and an occupied state of an inspected vehicle; The task scheduling server is also used for calculating a dynamic environment risk quantification value for each inspection road section; The task scheduling server is configured to receive a task request from the unmanned aerial vehicle control terminal or the patrol vehicle control terminal, wherein a target road section and a requested operation equipment type are indicated in the task request; The task scheduling server is configured to respond to the task request by executing the following processing flow: inquiring the current real-time occupation state of the target road section and the environmental risk quantization value of the target road section; if the target road section is in an idle state currently, selecting a corresponding arbitration mode to carry out authorization judgment according to a preset threshold interval to which the environmental risk quantization value belongs; If the target road section is currently in an occupied state, executing conflict coordination processing according to the environment risk quantification value and the type of the currently occupied equipment, and returning a task rejection, waiting or migration instruction to a control terminal sending a request; and the task scheduling server is further configured to push the state change information to all online control terminals in real time after the road section state table is updated.
2. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation according to claim 1, wherein the unmanned aerial vehicle control terminal is configured to: inquiring an air inspection road section list which can be distributed currently and a corresponding environment risk quantization value from the task scheduling server; generating a flight routing inspection route for the unmanned aerial vehicle by adopting a path optimization algorithm based on the list and the environmental risk quantification value; Before the unmanned aerial vehicle executes a task, the task request executed by the unmanned aerial vehicle for a specific road section is sent to the task scheduling server.
3. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation according to claim 1, wherein the arbitration mode configured in the task scheduling server comprises: A standard collaborative arbitration mode is started when the environmental risk quantification value of the target road section is lower than a first risk threshold value, and the task scheduling server arbitrates only according to the request priority or the time sequence; The inspection vehicle priority arbitration mode is started when the environmental risk quantification value of the target road section is between a first risk threshold value and a second risk threshold value, and the task scheduling server authorizes the inspection vehicle task request in preference to the unmanned aerial vehicle task request; And the patrol vehicle monopolizing arbitration mode is started when the environmental risk quantification value of the target road section is higher than a second risk threshold value, and the task scheduling server refuses a new task request from the unmanned aerial vehicle control terminal and only accepts and arbitrates the request of the patrol vehicle control terminal.
4. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation according to claim 3, wherein the environmental risk quantization value R is calculated by the following model: R = w1 * f(W) + w2 * g(V) + w3 * h(P); wherein f (W) is a risk contribution function based on wind speed and direction information, g (V) is a risk contribution function based on visibility and rainfall intensity information, h (P) is a risk contribution function based on lightning probability and road adhesion coefficient, and W1, W2 and W3 are dynamic configuration weight coefficients corresponding to the functions.
5. The unmanned aerial vehicle and ground patrol vehicle co-operating system based on dynamic task allocation of claim 3, wherein in the patrol vehicle priority arbitration mode, the task scheduling server is configured to: assigning a dynamic priority addition value to a task request from a patrol vehicle control terminal; and based on the dynamic priority addition value, arbitrating the conflicting task requests to ensure that the patrol vehicle task requests are preferentially authorized in the arbitration.
6. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation according to claim 3, wherein in the patrol vehicle exclusive arbitration mode, if a target road section is occupied by an unmanned aerial vehicle, the task scheduling server executes a safe task migration flow, specifically: Sending a task suspension and data feedback instruction to the unmanned aerial vehicle control terminal; receiving and verifying data returned by the unmanned aerial vehicle control terminal; And after the verification is passed, authorizing the inspection task of the target road section to the inspection vehicle control terminal which makes a request.
7. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation according to claim 5, wherein the dynamic priority addition value Δp is calculated by the following formula: ΔP = k * (R - R_t1); wherein R is an environmental risk quantization value, R_t1 is a first risk threshold, and k is a preset gain coefficient greater than zero.
8. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation according to claim 1, wherein the task scheduling server is further configured to dynamically modify the calculated weight coefficient of the environmental risk quantification value to optimize the response accuracy of the arbitration mode based on a trend comparison of historical environmental data with current real-time data.
9. The unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation according to claim 1, wherein the task scheduling server is configured to send an environmental risk early warning to a control terminal of an associated work unit that is on a particular patrol road segment or planning to go to the road segment and suggest or trigger a reevaluation of a task plan when there is a sharp change in the environmental risk quantified value of the particular patrol road segment.
10. A method for collaborative operation of an unmanned aerial vehicle and a ground inspection vehicle based on dynamic task allocation, applied to the system according to any one of claims 1 to 9, characterized in that the method comprises: S1, the task scheduling server maintains a global shared road section state table, and calculates a dynamic environment risk quantization value for each road section; s2, the unmanned aerial vehicle control terminal or the patrol vehicle control terminal sends a task request to the task scheduling server, wherein the request indicates a target road section and a type of operation equipment; s3, the task scheduling server inquires the real-time occupation state of the target road section and the environment risk quantification value of the target road section; S4, selecting a corresponding arbitration mode according to the environment risk quantized value, and judging by combining a real-time occupied state: if the state is idle, determining an authorized object according to the selected arbitration mode; if the state is occupied, performing conflict coordination according to the selected arbitration mode and the environment risk; s5, the task scheduling server sends the judgment result and the state update information to the related control terminal; S6, after receiving the task permission, the control terminal controls the corresponding unmanned aerial vehicle or the patrol vehicle to drive to the target road section to execute the task; And S7, after the task execution is finished, the control terminal sends a task completion notification to a task scheduling server, and the server updates the real-time occupied state of the corresponding road section into an idle state.

Description

Unmanned aerial vehicle and ground inspection vehicle collaborative operation method and system based on dynamic task allocation Technical Field The invention belongs to the technical field of intelligent traffic management and automatic inspection, and particularly relates to a method and a system for collaborative operation of an unmanned aerial vehicle and a ground inspection vehicle based on dynamic task allocation. Background With the fine and intelligent development of urban management, the unmanned aerial vehicle and the ground inspection vehicle are utilized to carry out cooperative operation, so that the method has become an important technical means in the fields of traffic inspection, facility inspection, parking management and the like. One common implementation mode is that the unmanned aerial vehicle and the inspection vehicle are respectively provided with an independent control system and a task planning module, and the unmanned aerial vehicle and the inspection vehicle respectively execute inspection and evidence obtaining tasks according to a preset or manually appointed area. However, the method has the obvious defect that due to the lack of a unified task scheduling and real-time state synchronization mechanism, the unmanned aerial vehicle and the patrol vehicle are very easy to repeatedly shoot the same road section or the target vehicle, so that unnecessary consumption of calculation, storage and communication resources is caused. More importantly, when the two task areas overlap, potential conflict or "robbery list" phenomenon on physical space can be caused, so that not only is the operation efficiency affected, but also safety risks are brought. In addition, existing collaborative scheduling logic is often based on fixed device capabilities or preset static priorities, failing to adequately account for dynamic impact of external environmental factors, particularly weather conditions, on device applicability. Unmanned aerial vehicle operation highly depends on weather conditions, and flight safety and operation efficiency of unmanned aerial vehicle can obviously decline or even be completely limited under severe weather such as strong wind, low visibility, rainfall or thunder and lightning, and patrol vehicle is less influenced by the type. When meteorological conditions are suddenly changed, the existing system cannot intelligently sense environmental risks and dynamically adjust task allocation strategies, so that potential safety hazards of forced operation of the unmanned aerial vehicle under risky weather or efficiency problems of task response interruption can occur, and the system is insufficient in self-adaptability and robustness. Therefore, a collaborative system capable of realizing dynamic task allocation and environment adaptive scheduling is needed to solve the problems of resource conflict and job safety and improve the overall job efficiency. Disclosure of Invention Aiming at the problems of resource conflict caused by independent operation of an unmanned aerial vehicle and a patrol vehicle in the prior art and incapability of adapting to dynamic environment change, the invention provides a collaborative operation method and a collaborative operation system of the unmanned aerial vehicle and the ground patrol vehicle based on dynamic task allocation, which ensure that only one operation device is authorized to execute tasks in any period of time for any patrol road section from a system level, dynamically adjust a device scheduling strategy according to real-time environment risks, thereby fundamentally avoiding task conflict and repeated labor, ensuring operation safety under severe weather, realizing optimal configuration and self-adaptive management of calculation, communication and patrol resources, and remarkably improving the overall operation efficiency, safety and intelligent level of the collaborative patrol system of the air space. The technical scheme of the invention is realized by that the unmanned aerial vehicle and ground patrol vehicle collaborative operation system based on dynamic task allocation is characterized by comprising a task scheduling server, at least one unmanned aerial vehicle operation unit and at least one patrol vehicle operation unit; The unmanned aerial vehicle operation unit comprises an unmanned aerial vehicle and a control terminal thereof, and the inspection vehicle operation unit comprises an inspection vehicle and a control terminal thereof; The unmanned aerial vehicle control terminal and the inspection vehicle control terminal are respectively in communication connection with the task scheduling server and are used for sending task requests to the server and receiving scheduling instructions; The task scheduling server maintains a global shared road section state table, the road section state table records the real-time occupation state of each inspection road section, and the real-time occupation state comprises an idle stat