Mixed weaving operation method and device and unmanned vehicle

Abstract

The present disclosure provides a mixed operation method and device and unmanned vehicle, the method comprising: the unmanned vehicle located in the mixed operation area detects the driving information of the manned vehicle in the detection range in real time; according to the driving information of the manned vehicle, it is determined whether there is a manned vehicle that meets the in-coding operation condition; in the case where there is a manned vehicle that meets the in-coding operation condition, the unmanned vehicle is controlled to enter the mixed operation mode; in the case where the driving information of the manned vehicle in the detection range of the unmanned vehicle indicates that the manned vehicle meets the out-coding condition, the unmanned vehicle is controlled to exit the mixed operation mode.

Description

Technical Field

[0001] This disclosure relates to the fields of smart mining, autonomous driving, and vehicle control technology, and in particular to a hybrid operation method, device, and unmanned vehicle. Background Technology

[0002] With the rapid growth of unmanned driving operations in mining areas, it is impractical to require dedicated operating areas for unmanned vehicles. Furthermore, most mining areas adopt a phased deployment model for unmanned vehicles, which cannot replace all manned vehicles at once. Therefore, mixed operation of unmanned and manned vehicles has become an inevitable trend in the unmanned transformation of mining areas. Traditional mixed operation methods typically involve installing dedicated onboard terminals with positioning capabilities on manned vehicles, combined with a cloud-based intelligent dispatch system to uniformly schedule manned and unmanned vehicles for mixed operations. However, this method suffers from additional terminal costs, potential terminal malfunctions due to faults, offline status, network fluctuations, and the difficulty of managing drivers solely based on terminal instructions, making large-scale application difficult. Summary of the Invention

[0003] This disclosure provides a hybrid operation method, apparatus, and unmanned vehicle to solve the problems of high cost, poor stability, and high management difficulty caused by the need to install a dedicated vehicle terminal in existing hybrid operation methods.

[0004] In view of the above problems, firstly, the present disclosure provides a mixed programming method, including:

[0005] Unmanned vehicles located within the mixed operation area perform real-time detection of driving information of manned vehicles within the detection range;

[0006] Based on the driving information of the manned vehicles, determine whether there are any manned vehicles that meet the conditions for inclusion in the operational staff;

[0007] When there are manned vehicles that meet the conditions for joining the operation, the unmanned vehicles are controlled to enter the mixed operation mode;

[0008] If the driving information of the manned vehicles within the detection range of the unmanned vehicle indicates that all manned vehicles meet the conditions for leaving the formation, the unmanned vehicle is controlled to exit the mixed formation operation mode.

[0009] In conjunction with the first aspect, in one possible implementation, determining whether a manned vehicle meets the requirements for being included in the operational staffing list based on the vehicle's driving information includes:

[0010] Obtain the status information of the manned vehicle, including its motion state or stationary state;

[0011] The target indicator information corresponding to the status information of the manned vehicle is determined as the driving information;

[0012] Based on the driving information of the manned vehicle, determine whether the manned vehicle meets the conditions for being included in the operational staff.

[0013] In conjunction with the first aspect, in one possible implementation, the target indicator information includes at least one of the following: location information, driving speed, and driving direction.

[0014] In conjunction with the first aspect, in one possible implementation, determining the target indicator information corresponding to the status information of the manned vehicle as the driving information includes:

[0015] When the status information of the manned vehicle indicates that the manned vehicle is stationary, the location information of the manned vehicle is used as the driving information; or,

[0016] When the status information of the manned vehicle indicates that the manned vehicle is in motion, the position information, speed and direction of travel of the manned vehicle are used as the driving information.

[0017] In conjunction with the first aspect, in one possible implementation, determining whether a manned vehicle meets the requirements for being included in the operational staff based on its driving information includes:

[0018] When the status information of the manned vehicle indicates that the manned vehicle is in a stationary state:

[0019] If the location information of the manned vehicle indicates that the manned vehicle is on the planned trajectory of the unmanned vehicle, and prevents the unmanned vehicle from proceeding to the next task point according to the current planned trajectory, then the manned vehicle is determined to meet the conditions for being included in the operational staff; or,

[0020] If the location information of the manned vehicle indicates that the manned vehicle is located on the planned trajectory of the unmanned vehicle or on the extension of the planned trajectory, and the distance between the manned vehicle and the end point of the planned trajectory of the unmanned vehicle is less than a first preset value, then the manned vehicle is determined to meet the conditions for inclusion in the work schedule.

[0021] In conjunction with the first aspect, in one possible implementation, determining whether a manned vehicle meets the requirements for being included in the operational staff based on its driving information includes:

[0022] When the status information of the manned vehicle indicates that the manned vehicle is in motion:

[0023] Based on the location information, speed and direction of travel of the manned vehicle, the trajectory of the manned vehicle is predicted to obtain the predicted trajectory.

[0024] Based on the positional relationship between the predicted trajectory and the planned trajectory of the unmanned vehicle, the position information and driving speed of the manned vehicle, it is determined whether the manned vehicle meets the conditions for inclusion in the operational staff.

[0025] In conjunction with the first aspect, in one possible implementation, determining whether the manned vehicle meets the conditions for inclusion in the operational schedule based on the positional relationship between the predicted trajectory and the planned trajectory of the unmanned vehicle, the position information of the manned vehicle, and its driving speed includes:

[0026] If the location information of the manned vehicle indicates that the manned vehicle is not on the planned trajectory of the unmanned vehicle, based on the location information of the manned vehicle and the driving speed, it is determined whether the manned vehicle has arrived at the trajectory intersection point earlier than the unmanned vehicle.

[0027] If the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory and the planned trajectory of the unmanned vehicle at the trajectory intersection point is less than a first preset angle, then the manned vehicle is determined to meet the conditions for inclusion in the operational schedule.

[0028] In conjunction with the first aspect, in one possible implementation, the method further includes:

[0029] If the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory and the planned trajectory of the unmanned vehicle at the trajectory intersection point is greater than or equal to a first preset angle, the unmanned vehicle is controlled to decelerate and brake to avoid the collision.

[0030] In conjunction with the first aspect, in one possible implementation, controlling the unmanned vehicle to enter the mixed-operation mode when there are manned vehicles meeting the conditions for joining the operation includes:

[0031] If there are manned vehicles that meet the conditions for being assigned to the work, and the unmanned vehicle is stationary, control the unmanned vehicle to continue to remain stationary;

[0032] When there are manned vehicles that meet the conditions for being assigned to the work, and the unmanned vehicle is in motion, control the unmanned vehicle to decelerate and brake to a stationary state.

[0033] In conjunction with the first aspect, in one possible implementation, when the driving information of the manned vehicles within the detection range of the unmanned vehicle indicates that all manned vehicles meet the separation criteria, controlling the unmanned vehicle to exit the mixed operation mode includes:

[0034] If, based on the driving information of the manned vehicles, it is determined that none of the manned vehicles within the detection range of the unmanned vehicle meet the conditions for joining the operation, the unmanned vehicle is controlled to exit the mixed operation mode and start to continue operation.

[0035] In conjunction with the first aspect, in one possible implementation, the unmanned vehicle located within the mixed operation area performs real-time detection of driving information of manned vehicles within the detection range, including: when the unmanned vehicle enters the first task state corresponding to the mixed operation task point within the operation area, triggering the unmanned vehicle to activate the mixed operation function switch to perform real-time detection of driving information of manned vehicles within the detection range; or,

[0036] The method further includes: when the unmanned vehicle enters the second task state corresponding to the mixed operation task point in the operation area, triggering the unmanned vehicle to turn off the mixed operation function switch, so as to stop the real-time detection of the driving information of human vehicles within the detection range and exit the mixed operation mode.

[0037] In conjunction with the first aspect, in one possible implementation, the method further includes:

[0038] The map of the work area is pre-structured to determine the mixed-operation task points;

[0039] The work area includes a loading area and / or an unloading area; the loading area is structured as at least one of the following task points: loading area entrance, reversal completion point, waiting-to-load position, and loading position; the unloading area is structured as at least one of the following task points: unloading area entrance, waiting-to-unload position, and unloading position; the mixed operation task points include the waiting-to-load position and loading position of the loading area, and the unloading area entrance, waiting-to-unload position, and unloading position of the unloading area.

[0040] In conjunction with the first aspect, in one possible implementation,

[0041] For the loading area, the first task status includes: entering the loading position, waiting in the loading position, and entering the loading position; for the unloading area, the first task status includes: entering the unloading area entrance, waiting in the unloading position, and entering the unloading position; and / or,

[0042] For the loading area, the second task state includes: performing a loading operation at the loading position; for the unloading area, the second task state includes: performing an unloading operation at the unloading position.

[0043] In conjunction with the first aspect, in one possible implementation, the method further includes:

[0044] When the unmanned vehicle enters the mixed operation mode and the unmanned vehicle is stationary, a prompt message is sent to the control terminal, the prompt message indicating that the unmanned vehicle is stationary due to the mixed operation mode;

[0045] After receiving the command to exit the mixed operation mode from the control terminal, the unmanned vehicle exits the mixed operation mode.

[0046] Secondly, a mixed-processing device is provided, comprising:

[0047] The manned vehicle detection module is used by unmanned vehicles located in the mixed operation area to detect the driving information of manned vehicles within the detection range in real time.

[0048] The manned vehicle entry operation determination module is used to determine whether there are manned vehicles that meet the entry operation conditions based on the driving information of the manned vehicles;

[0049] The mixed operation module is used to control the unmanned vehicle to enter the mixed operation mode when there are manned vehicles that meet the conditions for entering the operation; and to control the unmanned vehicle to exit the mixed operation mode when the driving information of the manned vehicles within the detection range of the unmanned vehicle indicates that both manned and unmanned vehicles meet the conditions for leaving the operation.

[0050] Thirdly, an unmanned vehicle is provided, including: a mixed operation device as described in the second aspect.

[0051] The beneficial effects of the embodiments disclosed herein include:

[0052] This disclosure provides a mixed operation method, apparatus, and unmanned vehicle, comprising: an unmanned vehicle located within a mixed operation area performing real-time detection of the driving information of manned vehicles within its detection range; determining, based on the driving information of manned vehicles, whether any manned vehicles meet the conditions for joining the mixed operation; if any manned vehicles meet the conditions for joining the mixed operation, controlling the unmanned vehicle to enter the mixed operation mode; and if the driving information of manned vehicles within the detection range of the unmanned vehicle indicates that all manned vehicles meet the conditions for leaving the mixed operation, controlling the unmanned vehicle to exit the mixed operation mode. The mixed-operation method provided in this disclosure eliminates the need for manned vehicles to install dedicated onboard terminals. It leverages the autonomous vehicles' own detection capabilities to achieve mixed-operation, effectively avoiding the additional costs associated with equipment procurement and maintenance in traditional methods. It also eliminates the management of manned vehicle drivers operating according to terminal instructions, significantly lowering the implementation threshold and facilitating the large-scale promotion of the mixed-operation model. By collecting real-time driving information from manned vehicles, it accurately determines entry and exit conditions, preventing unreasonable driving behavior by autonomous vehicles due to information lag. This reduces collision and operational interference risks throughout the entire process of manned vehicle entry, mixed-operation collaboration, and exit, making it adaptable to all mining "mining, transportation, and dispatching" scenarios and fully ensuring operational safety. Furthermore, it accurately identifies the operational intrusion intent of manned vehicles, automatically switching between autonomous vehicle mixed-operation modes without manual intervention. It dynamically adjusts operational strategies based on actual manned vehicle driving information, perfectly adapting to the gradual deployment of autonomous vehicles and the changing operational scenarios in mining areas. This enhances the flexibility of mixed-operation while further improving overall operational efficiency. Attached Figure Description

[0053] Figure 1This is one of the flowcharts for the mixed programming method provided in the embodiments of this disclosure;

[0054] Figure 2 A second flowchart of the mixed programming method provided in this embodiment of the disclosure;

[0055] Figure 3 The third flowchart of the mixed programming method provided in the embodiments of this disclosure;

[0056] Figure 4 This is a schematic diagram of mixed-process task points provided in an embodiment of the present disclosure;

[0057] Figure 5 This is a structural diagram of the mixed-processing device provided in an embodiment of this disclosure. Detailed Implementation

[0058] This disclosure provides a method, apparatus, and unmanned vehicle for mixed-operation processes. Preferred embodiments of this disclosure are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustrative and explanatory purposes only and are not intended to limit the scope of this disclosure. Furthermore, the embodiments and features described herein can be combined with each other unless otherwise specified.

[0059] This disclosure provides a method for mixed programming operations, such as... Figure 1 As shown, it includes:

[0060] S101. Unmanned vehicles located in the mixed operation area perform real-time detection of the driving information of manned vehicles within the detection range;

[0061] S102. Based on the driving information of manned vehicles, determine whether there are manned vehicles that meet the conditions for inclusion in the operational staff.

[0062] S103. When there are manned vehicles that meet the conditions for joining the operation, control the unmanned vehicles to enter the mixed operation mode.

[0063] S104. If the driving information of both manned and unmanned vehicles within the detection range of the unmanned vehicle meets the conditions for leaving the formation, control the unmanned vehicle to exit the mixed operation mode.

[0064] In this embodiment of the disclosure, with the rapid expansion of unmanned driving operations in mining areas, the model of requiring mining areas to allocate separate operating sites for unmanned vehicles has gradually revealed its impractical limitations. On the one hand, most mining areas adopt a strategy of gradually deploying unmanned vehicles when promoting unmanned transformation, making it difficult to replace all manned vehicles at once; on the other hand, the planning and construction of independent sites not only requires high cost investment but may also be limited by the existing terrain and facility layout of the mining area, making large-scale promotion difficult. Against this backdrop, realizing the mixed operation of unmanned and manned vehicles has become an inevitable trend in promoting the unmanned transformation of mining areas. Therefore, in the traditional approach, a mixed operation method of manned and unmanned vehicles with dedicated vehicle-mounted terminals has been proposed. This method involves uniformly installing dedicated vehicle-mounted terminals with positioning functions on all manned vehicles participating in the mixed operation, and then using a cloud-based intelligent scheduling system to uniformly schedule manned and unmanned vehicles, thereby realizing mixed operation. However, this method has the following obvious disadvantages, making it difficult to apply on a large scale:

[0065] 1. High cost: Installing vehicle-mounted terminals on all manned vehicles involved in the mixed operation will incur additional equipment procurement, installation and maintenance costs, putting pressure on the mining area's operating budget;

[0066] 2. Poor stability: The normal operation of the dedicated vehicle terminal depends on multiple factors such as the performance of the equipment itself and the network signal. Once the equipment fails, the signal goes offline or the network fluctuates, the dedicated vehicle terminal will be unable to transmit data normally, which will directly affect the accuracy of the intelligent dispatch system and thus interfere with the operation process.

[0067] 3. High management difficulty: The driver of the vehicle and personnel is required to perform the operation in strict accordance with the terminal instructions. However, in actual operation, the driver may have difficulty strictly following the instructions due to factors such as operating habits and judgment of emergencies, which increases the complexity of on-site management and may also cause problems in operation coordination.

[0068] Therefore, achieving efficient mixed operation of manned and unmanned vehicles in mining operations remains a key issue that the industry urgently needs to address.

[0069] In this embodiment, the unmanned vehicle can be an unmanned mining truck, typically equipped with a dedicated onboard terminal. Through vehicle-to-vehicle communication (V2V), it communicates with other unmanned vehicles within its detection or communication range to obtain their driving information. Manned vehicles can include common mining vehicle types such as production command vehicles (pickups or SUVs), bulldozers, graders, water trucks, fuel trucks, excavators, and manned mining trucks. These vehicles do not necessarily require a dedicated onboard terminal. Without a dedicated onboard terminal, communication with unmanned vehicles to obtain driving information is impossible. The unmanned vehicle can be configured with a navigation system as a positioning module to obtain its current location. Additionally, various types of sensing devices, such as cameras, lidar, millimeter-wave radar, and ultrasonic radar, can be configured to detect obstacles in real time, including manned vehicles. For example, the unmanned vehicle can utilize various types of sensing devices to detect the driving information of manned vehicles in real time. Mixed operation areas can be areas within a mining area where both manned and unmanned vehicles (UAVs) operate simultaneously, such as loading areas, unloading areas, and transport roads. UAVs located within these mixed operation areas monitor the driving information of manned vehicles within their detection range in real time to ensure operational safety. Based on the manned vehicle driving information, and against preset entry conditions, each manned vehicle within the detection range is assessed to determine whether it meets the mixed operation requirements. These entry conditions can be designed to identify whether manned vehicles intend to intrude on the planned trajectories of UAVs.

[0070] Furthermore, if manned vehicles meet the criteria for inclusion in the operational group, the unmanned vehicle (UAV) is controlled to enter the mixed-group operation mode. Once in this mode, the UAV can optimize its operational logic to ensure driving safety. For example, it can increase the safety distance, enhance dynamic tracking of manned vehicles, adjust operational priorities (prioritizing avoidance of manned vehicles meeting the inclusion criteria to prevent conflicts), and initiate collaborative operations with manned vehicles (e.g., using lights, horns, etc., to signal the intentions of manned vehicles and assist the driver in judgment). The core purpose of the mixed-group operation mode is to enable the UAV to quickly adapt to mixed-group scenarios, achieving safe and efficient collaboration with eligible manned vehicles by adjusting its operational logic to complete tasks such as data collection, transportation, and sorting. The UAV continuously monitors the driving information of manned vehicles within its detection range in real time. If it determines that all manned vehicles within the detection range meet the criteria for leaving the group, the UAV exits the mixed-group operation mode, restoring its efficient operational parameters (e.g., increasing driving speed, shortening the safety distance) to improve operational efficiency and avoid resource waste.

[0071] This application embodiment eliminates the need for manned vehicles to install dedicated onboard terminals. Unmanned vehicles can achieve mixed-operation through their own detection, avoiding the equipment costs, maintenance costs, and driver management difficulties of traditional methods, thus facilitating the large-scale implementation of mixed-operation solutions. By detecting the driving information of manned vehicles in real time, it determines the conditions for entering and leaving the mixed-operation system, reducing unreasonable driving behavior of unmanned vehicles due to information lag, and lowering the risk of collisions and interference between manned vehicles and unmanned vehicles during entry, mixed-operation, and departure. It is applicable to all scenarios and ensures operational safety. By accurately judging the intrusion intent of manned vehicles, it eliminates the need for manual intervention in switching the mixed-operation mode of unmanned vehicles. It dynamically adjusts according to the actual situation of manned vehicles, adapting to the characteristics of gradual deployment of unmanned vehicles in mining areas and the changing operational scenarios, thereby improving operational efficiency and enhancing the flexibility of mixed-operation.

[0072] In another embodiment of this disclosure, step S102 above, determining whether there are manned vehicles that meet the conditions for inclusion in the operational schedule based on the vehicle's driving information, includes:

[0073] Step 1: Obtain the status information of the person and vehicle, including whether they are in motion or stationary.

[0074] Step 2: Determine the target indicator information corresponding to the status information of people and vehicles, as driving information;

[0075] Step 3: Based on the driving information of the manned vehicle, determine whether the manned vehicle meets the conditions for inclusion in the operational staff.

[0076] In this embodiment, the status information of manned vehicles is clearly defined. For both moving and stationary states, corresponding target indicator information is determined to determine whether the manned vehicle meets the conditions for inclusion in the operational schedule. Regarding step 1 above, the unmanned vehicle can detect whether the manned vehicle is in a moving or stationary state through sensing devices, for example, by judging changes in the manned vehicle's position using point cloud data. If the position coordinates of the manned vehicle do not change significantly within multiple consecutive detection cycles, the manned vehicle's status information is determined to be stationary; otherwise, it is in a moving state. In mining operations, the status of manned vehicles is highly variable, such as parking, changing lanes, and turning. By identifying moving and stationary states, the status changes of manned vehicles can be comprehensively covered. Regarding step 2 above, corresponding target indicator information is determined for both moving and stationary states as driving information. For example, for moving states, the focus is on position, speed, and direction of travel; for stationary states, the focus is on stopping location and duration. Regarding step 3 above, based on the driving information of the manned vehicle, it is determined whether the manned vehicle meets the conditions for inclusion in the operational schedule. By distinguishing between manned and stationary vehicles in motion or at rest, differentiated entry conditions can be formulated, and targeted target indicators can be determined as driving information to ensure that only manned and stationary vehicles with genuine collaborative capabilities can be included in the fleet, further reducing the risk of mixed operations.

[0077] In another embodiment of this disclosure, the target indicator information includes at least one of the following: location information, driving speed, and driving direction.

[0078] In this embodiment, location information helps the autonomous vehicle determine its relative distance to a manned vehicle, ensuring a safe distance and avoiding collision risks. Driving speed ensures the autonomous vehicle remains within the speed range where the manned vehicle can cooperate, preventing speeding. Combining location information, driving speed, and driving direction prevents operational conflicts caused by intersecting paths, allowing the autonomous vehicle to take proactive measures, such as entering a mixed-operation mode or replanning its route. By detecting the location information, driving speed, and driving direction of the manned vehicle, the conditions for entering the mixed-operation mode can be determined, reducing data processing complexity and improving system response speed.

[0079] In another embodiment of this disclosure, step 2 above, determining the target indicator information corresponding to the status information of the person and vehicle as driving information, includes:

[0080] Step 1: If the status information of the person and vehicle indicates that the person and vehicle are stationary, use the location information of the person and vehicle as the driving information; or,

[0081] Step 2: When the status information of the manned vehicle indicates that the manned vehicle is in motion, the position information, speed and direction of travel of the manned vehicle are used as driving information.

[0082] In this embodiment, the position information of the manned vehicle is determined when it is stationary, and its position, speed, and direction are determined when it is in motion. This on-demand determination provides accurate and efficient driving information support for subsequent operational condition assessment. Regarding step one, when the unmanned vehicle (UAV) determines that the manned vehicle is stationary via its sensing devices, its position information is used as driving information. The UAV can assess the position of the manned vehicle to prevent it from obstructing its operational route. Regarding step two, when the manned vehicle is in motion, its position, speed, and direction are used as driving information. By using these information, the vehicle's trajectory can be identified, and combined with the UAV's own planned trajectory, a safe distance is maintained to avoid rear-end collisions or scrapes. Determining driving information separately for stationary and moving states reduces the processing load on the UAV's sensing devices and the system's computational load, allowing data processing to focus more on core target indicators and improving judgment response speed. It accurately matches the actual status of personnel and vehicles in mixed operations in mining areas, comprehensively covers the key dimensions required for collaborative judgment, and is more in line with real operation scenarios, ensuring the completeness and accuracy of subsequent judgment on inclusion conditions.

[0083] In another embodiment of this disclosure, step 3 above, determining whether a manned vehicle meets the conditions for being included in the operational staffing list based on the vehicle's driving information, includes:

[0084] When the status information of a person and vehicle indicates that the person and vehicle are stationary:

[0085] Step 1: If the location information of the manned vehicle indicates that the manned vehicle is on the planned trajectory of the unmanned vehicle, and prevents the unmanned vehicle from proceeding to the next task point according to the current planned trajectory, then the manned vehicle meets the conditions for being assigned to the task; or,

[0086] Step 2: If the location information of the manned vehicle indicates that the manned vehicle is located on the planned trajectory of the unmanned vehicle or on the extension of the planned trajectory, and the distance from the end point of the planned trajectory of the unmanned vehicle is less than the first preset value, then it is determined that the manned vehicle meets the conditions for being included in the operation.

[0087] In this embodiment, the core criterion is whether the location information of manned vehicles affects the planned trajectory of unmanned vehicles (UAVs). This determines whether a manned vehicle intends to intrude on the UAV's planned trajectory, ensuring that the UAV can coordinate its operational relationship with stationary manned vehicles through a mixed-operation mode. Regarding step one above, the UAV generates a planned trajectory as it travels to various task points to perform its tasks. The UAV follows this trajectory to complete its tasks. The UAV uses its positioning module and sensing devices to compare the location information (e.g., coordinates) of stationary manned vehicles with its own current planned trajectory to determine if the manned vehicle is on the planned trajectory. If a manned vehicle is confirmed to be on the planned trajectory and prevents the UAV from proceeding to the next task point (e.g., the UAV's planned trajectory is to travel straight to the loading position at 500 meters, but the manned vehicle is stopped at 200 meters, obstructing the UAV's task), then the stationary manned vehicle meets the conditions for inclusion in the mixed-operation mode. The UAV then needs to enter the mixed-operation mode to mitigate risks. Regarding step two above, if a manned vehicle is stationary and does not directly obstruct the current planned trajectory of the unmanned vehicle, but its location information is close to the endpoint of the unmanned vehicle's planned trajectory, then the unmanned vehicle and the manned vehicle need to work together. The unmanned vehicle first compares the location information of the stationary manned vehicle with its own planned trajectory to determine whether the manned vehicle is on or extended from the planned trajectory. If these conditions are met, and the distance between the manned vehicle and the endpoint of the unmanned vehicle's planned trajectory is calculated using the location information, and compared with a first preset value, if the distance is less than the first preset value, then the stationary manned vehicle meets the conditions for being included in the operational group. The magnitude of the first preset value is related to the type of unmanned vehicle, which is related to the vehicle's length. The setting of the first preset value must ensure that the unmanned vehicle and the manned vehicle maintain a safe distance. For example, if the endpoint of the unmanned vehicle's planned trajectory is located at the unloading position, and the stationary manned vehicle is 5 meters away from the unloading position, possibly waiting to unload or waiting to leave after unloading, and this distance is less than the first preset value, then the stationary manned vehicle meets the conditions for being included in the operational group, and the unmanned vehicle needs to enter a mixed operational mode to avoid risks. When manned vehicles are stationary, their location information can be used to determine whether they intend to intrude on the planned trajectory of unmanned vehicles. This helps determine whether unmanned vehicles should enter a mixed operation mode, preventing them from blindly changing their planned trajectories when encountering stationary manned vehicles, reducing on-site conflicts such as collisions and route blockages, and ensuring operational safety.

[0088] In another embodiment of this disclosure, step 3 above, determining whether a manned vehicle meets the conditions for being included in the operational staffing list based on the vehicle's driving information, includes:

[0089] When the status information of a person and a vehicle indicates that the person and the vehicle are in motion:

[0090] Step 1: Based on the location information, speed, and direction of travel of the vehicle and its passengers, predict the trajectory of the vehicle and its passengers to obtain the predicted trajectory.

[0091] Step 2: Based on the positional relationship between the predicted trajectory and the planned trajectory of the unmanned vehicle, the positional information and driving speed of the manned vehicle, determine whether the manned vehicle meets the conditions for being included in the operational schedule.

[0092] In this embodiment, the predicted trajectory of the manned vehicle is compared and analyzed with the planned trajectory of the unmanned vehicle to determine whether the manned vehicle intends to intrude on the planned trajectory of the unmanned vehicle, and to comprehensively assess whether there are potential collaborative needs or conflict risks between the two. Regarding step one, when the manned vehicle is in motion, based on its current location, speed, and direction, and considering the constraints of the mining area road network, trajectory prediction algorithms, such as Kalman filtering and multinomial prediction, are used to generate a predicted trajectory for the manned vehicle over a future period, such as 5-10 seconds. This transforms the current instantaneous state information of the manned vehicle into a future behavior prediction, providing a time lead for subsequent collaborative judgments, allowing the unmanned vehicle sufficient time to make decisions and adjustments. Regarding step two, based on the positional relationship between the predicted trajectory and the planned trajectory of the unmanned vehicle, the location information and speed of the manned vehicle are used to determine whether the manned vehicle meets the conditions for inclusion in the operational group. For example, it is determined whether there is a trajectory intersection point between the predicted trajectory and the planned trajectory of the unmanned vehicle. Based on the location information and speed of the manned vehicle, it is assessed whether there is a collision risk at the trajectory intersection point, thereby determining whether the manned vehicle meets the conditions for inclusion in the operational group and whether the unmanned vehicle needs to enter the mixed operational group mode to avoid risks. By predicting trajectories, manned vehicles that may intersect with autonomous vehicles can be identified in advance, avoiding operational chaos caused by last-minute discoveries requiring coordination. Potential trajectory intersections and high-risk scenarios such as rear-end collisions can be identified promptly, allowing for early entry into mixed-vehicle operation modes to reduce collision risks. Furthermore, speed matching is performed on manned vehicles traveling in the same direction, enabling timely integration into the fleet and forming an orderly convoy. Early warnings are issued for vehicles with potential conflicts, preventing traffic congestion.

[0093] In another embodiment of this disclosure, step two above, determining whether a manned vehicle meets the conditions for being included in the operational schedule based on the positional relationship between the predicted trajectory and the planned trajectory of the unmanned vehicle, the position information of the manned vehicle, and its driving speed, includes:

[0094] Step (1): If the location information of the manned vehicle indicates that the manned vehicle is not on the planned trajectory of the unmanned vehicle, determine whether the manned vehicle has arrived at the trajectory intersection point earlier than the unmanned vehicle based on the location information and driving speed of the manned vehicle.

[0095] Step (2): If the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory and the planned trajectory of the unmanned vehicle at the trajectory intersection point is less than the first preset angle, it is determined that the manned vehicle meets the conditions for being included in the operation.

[0096] In this embodiment, in a scenario where a manned vehicle in motion is not on the planned trajectory of an unmanned vehicle, the location information and driving speed are used to determine whether the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle. Then, it is verified whether the angle formed by the driving direction vectors of the two vehicles at the intersection point is less than a first preset angle to determine whether the manned vehicle meets the conditions for inclusion in the fleet, ensuring that the inclusion judgment takes into account both timing safety and directional coordination. Regarding step (i), for a manned vehicle in motion, if the location information of the manned vehicle indicates that it is on the planned trajectory of the unmanned vehicle, then the manned vehicle does not meet the conditions for inclusion in the fleet. The unmanned vehicle can maintain a safe distance from the vehicle in front and does not need to enter the mixed-fleet operation mode, thus improving transportation efficiency. If the location information of the manned vehicle indicates that it is not on the planned trajectory of the unmanned vehicle, based on the location information and driving speed of the manned vehicle, it is determined whether the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, thereby determining whether the manned vehicle has any intention to intrude on the planned trajectory of the unmanned vehicle. Regarding step (ii), if the unmanned vehicle arrives at the trajectory intersection point earlier than the manned vehicle, then the manned vehicle does not meet the conditions for inclusion in the fleet. The unmanned vehicle can maintain its planned trajectory and driving speed and continue driving without collision risk. If a manned vehicle arrives at the trajectory intersection point earlier than an unmanned vehicle, there may be a collision risk. Further analysis of the angle formed by the predicted trajectory of the manned vehicle and the planned trajectory of the unmanned vehicle at the trajectory intersection point determines whether the manned vehicle is attempting to cut in, overtake, or reverse. If the angle is less than a first preset angle (e.g., 60 degrees), the above conditions are met, and the manned vehicle meets the requirements for being included in the operational schedule. The "early arrival" judgment avoids congestion or collisions caused by both vehicles arriving at the intersection simultaneously. The angle formed by the driving direction vectors eliminates directional conflicts, such as high-risk situations like driving in the opposite direction. This meets the requirements for manned vehicles to be included in operational schedules and can satisfy scenarios such as mining area intersections, multiple forks in the road, cutting in, overtaking, and reversing. It accurately determines the coordination needs of manned vehicles in different trajectories, improving adaptability to complex scenarios.

[0097] In another embodiment of this disclosure, the method further includes:

[0098] Step 1: If the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory and the unmanned vehicle's planned trajectory at the trajectory intersection point is greater than or equal to the first preset angle, control the unmanned vehicle to decelerate and brake to avoid the collision.

[0099] In this embodiment, although a manned vehicle arrives at the trajectory intersection point ahead of time, if the deviation in its driving direction is too large and it does not meet the conditions for joining the operational group, making mixed-group collaborative operation impossible, the unmanned vehicle is directly controlled to decelerate and brake to avoid the manned vehicle and prevent operational conflicts or safety risks at the intersection point. Regarding step 1 above, the manned vehicle, in motion, arrives at the trajectory intersection point ahead of the unmanned vehicle. The angle formed by the driving direction vectors corresponding to the predicted trajectory and the planned trajectory of the unmanned vehicle at the trajectory intersection point is greater than or equal to a first preset angle. For example, the predicted trajectory of the manned vehicle and the planned trajectory of the unmanned vehicle may be traveling in opposite directions. If the unmanned vehicle considers the manned vehicle to be in a departing state, then the manned vehicle does not meet the conditions for joining the operational group. Another example is when a manned vehicle crosses the road in front of the unmanned vehicle but does not merge into the predicted trajectory of the unmanned vehicle; in this case, the manned vehicle does not meet the conditions for joining the operational group. The unmanned vehicle initiates deceleration and braking according to the established deceleration strategy to avoid the manned vehicle. Simultaneously, the system continuously monitors changes in the position of manned and vehicle vehicles using sensing devices. If a manned or vehicle passes the trajectory intersection prematurely, the unmanned vehicle can prematurely end its deceleration and braking, resuming its original planned speed. If a manned or vehicle remains stationary for an extended period, the unmanned vehicle can maintain a low speed or briefly stop until the manned or vehicle leaves the safe area of ​​the intersection. By identifying scenarios where manned or vehicle vehicles do not meet the conditions for being included in the operational schedule, the system controls the unmanned vehicle to autonomously and smoothly decelerate and brake, providing manned or vehicle vehicles with the space and time to safely pass through trajectory intersections. This ensures the safety and controllability of the unmanned vehicle's own operation, balancing operational safety and process efficiency.

[0100] In another embodiment of this disclosure, step S103 above, where a manned vehicle meets the conditions for joining a fleet, controls the unmanned vehicle to enter a mixed-fleet operation mode, including:

[0101] Step 1: If there are manned vehicles that meet the conditions for being assigned to the work group, and the unmanned vehicles are stationary, control the unmanned vehicles to continue to remain stationary;

[0102] Step 2: When there are manned vehicles that meet the conditions for being included in the operation and unmanned vehicles are in motion, control the unmanned vehicles to decelerate and brake to a standstill.

[0103] In this embodiment of the disclosure, when a manned vehicle meeting the entry requirements is detected, the unmanned vehicle will take corresponding measures based on its current state and eventually enter a stationary state. Regarding step 1 above, if a manned vehicle meets the entry requirements, for example, if a manned vehicle is parked on the unmanned vehicle's planned trajectory, or if a manned vehicle is changing lanes to merge into the unmanned vehicle's planned trajectory, and the unmanned vehicle is stationary, it will be controlled to remain stationary to avoid collisions with manned vehicles. Regarding step 2 above, if the unmanned vehicle is moving, it will be controlled to decelerate and brake to a stationary state to yield to manned vehicle drivers and avoid interfering with their operation, reducing the risk of collision. For example, under the premise of ensuring safety, it will begin deceleration and stop at a speed of -1 m / s², then shift to neutral (N) and engage the handbrake to maintain the stationary state. Figure 2 As shown, Figure 2 The second flowchart for the mixed-process operation method includes the following steps:

[0104] S201. Process obstacle information one by one; if the obstacle is stationary, proceed to step S205; if the obstacle is moving, proceed to step S202.

[0105] S202. Process each predicted trajectory one by one;

[0106] S203. Predict whether the trajectory indicates an intent to intrude; if yes, proceed to step S204; if no, proceed to step S205.

[0107] S204. Identification of intrusion intent;

[0108] S205. Make a decision on mixed-work behavior, whether to enter the mixed-work mode;

[0109] S206, Execute the mixed-system behavior decision results; process ends.

[0110] In another embodiment of this disclosure, in step S104 above, when the driving information of manned vehicles within the detection range of the unmanned vehicle indicates that all manned vehicles meet the conditions for leaving the mixed operation mode, controlling the unmanned vehicle to exit the mixed operation mode includes:

[0111] Step 1: Based on the driving information of the manned vehicles, if it is determined that none of the manned vehicles within the detection range of the unmanned vehicle meet the conditions for joining the operation, control the unmanned vehicle to exit the mixed operation mode and start to continue the operation.

[0112] In this embodiment, if all manned vehicles within the detection range of the unmanned vehicle (UAV) fail to meet the conditions for joining the mixed operation, the UAV is controlled to exit the mixed operation mode. For step 1 above, for example, if a stationary manned vehicle is not located on the planned trajectory of the UAV, then the manned vehicle does not meet the conditions for joining the mixed operation; if a stationary manned vehicle is located on the planned trajectory of the UAV, but its stationary state does not hinder the UAV's operation tasks (e.g., the UAV can proceed to the next task point according to the current planned trajectory), then the manned vehicle does not meet the conditions for joining the mixed operation; if a moving manned vehicle is located on the planned trajectory of the UAV, then the manned vehicle does not meet the conditions for joining the mixed operation, and the UAV can maintain a safe distance from the vehicle in front while operating. After entering the mixed operation mode, the UAV continuously assesses the predicted trajectory, location information, speed, and direction of the manned vehicles participating in the mixed operation, and decides whether to remove them from the mixed operation mode based on their behavior. For example, if the UAV determines that the driving information of all manned vehicles within the detection range for multiple consecutive frames no longer meets the conditions for joining the mixed operation, the manned vehicle leaves the mixed operation mode. After a manned vehicle leaves the mixed operation mode, the UAV is controlled to exit the mixed operation mode, and the UAV starts moving again to continue operating. To avoid unmanned vehicles operating in mixed-operation modes when no manned vehicles are needed, timely withdrawal and resumption of operations can improve the driving speed and operational efficiency of unmanned vehicles, reducing wasted time. It is crucial to ensure that the operational mode of unmanned vehicles always matches the actual needs of the scenario.

[0113] In another embodiment of this disclosure, in step S101 above, the unmanned vehicle located within the mixed operation area performs real-time detection of the driving information of manned vehicles within the detection range, including:

[0114] Step 1: When the unmanned vehicle enters the work area and enters the first task state corresponding to the mixed-operation task point, trigger the unmanned vehicle to activate the mixed-operation function switch to perform real-time detection of the driving information of vehicles with people within the detection range; or,

[0115] The method may further include:

[0116] Step 2: When the unmanned vehicle enters the second task state corresponding to the mixed operation task point in the operation area, trigger the unmanned vehicle to turn off the mixed operation function switch to stop the real-time detection of the driving information of manned vehicles within the detection range and exit the mixed operation mode.

[0117] In this embodiment, if the unmanned vehicle is in the first task state, the mixed-vehicle function switch is activated to detect the driving information of manned vehicles in real time; if the unmanned vehicle is in the second task state, the mixed-vehicle function switch is deactivated to stop detection and exit the mixed-vehicle mode, achieving precise matching between the mixed-vehicle function and the task state. Regarding step 1 above, the work area is further divided into multiple mixed-vehicle task points. For example, the loading area is divided into waiting-to-load positions and loading positions. The unmanned vehicle performs various tasks at the corresponding mixed-vehicle task points, such as waiting at the waiting-to-load position. When the unmanned vehicle is in the first task state, the mixed-vehicle function switch is activated. For example, the unmanned vehicle is driving in a mixed-vehicle task point where manned vehicles are densely shared, preparing to participate in multi-vehicle collaborative transportation tasks. In this first task state, it is necessary to monitor the dynamics of manned vehicles in real time to ensure collaborative safety. Regarding step 2 above, when the unmanned vehicle enters the second task state corresponding to a mixed-vehicle task point within the work area, the mixed-vehicle function switch is deactivated. For example, in the second task state, the unmanned vehicle can stop at the loading position and load materials without entering the mixed-vehicle operation mode, and can stop real-time detection of the driving information of manned vehicles within the detection range. The hybrid function switch should only be activated in the first task state where hybridization is required. This avoids wasting resources in the second task state where hybridization is not needed, ensuring that the activation of the hybrid function switch is highly aligned with task requirements. In the second task state, the hybrid function switch should be deactivated, so the autonomous vehicle does not need to continuously process manned vehicle detection data, reducing sensor operation, data transmission, and computing power consumption, thereby reducing hardware wear and tear and system operating pressure. Figure 3 As shown, Figure 3 The third flowchart for the mixed-operation method includes the following steps:

[0118] S301. The autonomous vehicle triggers the hybrid programming function switch based on the scene in which the vehicle is located;

[0119] S302, Registration: The unmanned vehicle identifies the intrusion intent of the manned vehicle and decides whether the registration conditions are met;

[0120] S303, Mixed Operation: Manned vehicles meet the conditions for joining the operation, and unmanned vehicles enter the mixed operation mode;

[0121] S304, Departure: The unmanned vehicle recognizes the intention of the manned vehicle to depart, exits the mixed operation mode, begins the start-up action, and enters the next task point; the process ends.

[0122] In another embodiment of this disclosure, the method further includes:

[0123] Step 1: Perform pre-structuring processing on the map of the work area to determine the mixed-operation task points;

[0124] The work area includes a loading area and / or an unloading area. The loading area is structured into at least one of the following task points: loading area entrance, reversal completion point, waiting position for loading, and loading position. The unloading area is structured into at least one of the following task points: unloading area entrance, waiting position for unloading, and unloading position. The mixed operation task points include the waiting position for loading and the loading position in the loading area, and the unloading area entrance, waiting position for unloading, and unloading position in the unloading area.

[0125] In this embodiment of the disclosure, the map of the work area is structured to determine the mixed-task work points. For example... Figure 4 As shown, in step 1 above, the map of the work area is pre-structured to determine the mixed-operation task points. The work area is divided into loading area 401 and unloading area 402. Since loading and unloading operations involve numerous business interactions, if the operational intentions of manned vehicles cannot be accurately determined, unmanned vehicles may exhibit unreasonable driving behavior, affecting the normal operation of manned vehicles. Achieving mixed-operation of unmanned and manned vehicles across the entire "collection, transportation, and sorting" scenario remains challenging. Therefore, the task points in loading area 401 and unloading area 402 are structured.

[0126] Loading area 401 is used to complete loading tasks, and unloading area 402 is used to complete unloading tasks.

[0127] The loading area 401 is structured and divided into at least one or more standard task points, including:

[0128] Loading area entrance 4011: The starting point for vehicles to enter the loading operation process.

[0129] Reversal completion point 4012: The vehicle has completed the U-turn and adjusted to the confirmation point for entering the loading position.

[0130] Loading position 4013: Vehicles are queuing up and waiting to enter the designated area of ​​the loading position.

[0131] Loading position 4014: The precise location where the vehicle performs actual loading operations.

[0132] Unloading area 402 structured: It is divided into at least one or more standard task points, including:

[0133] Unloading area entrance 4021: The starting point for vehicles entering the unloading operation process.

[0134] 4022: Vehicles are queuing up and waiting to enter the designated area of ​​the unloading station.

[0135] Unloading position 4023: The precise location where the vehicle actually performs unloading operations.

[0136] From the aforementioned task points, locations most likely to involve interaction between unmanned and manned vehicles and require collaborative operations were selected as mixed-operation task points. These mixed-operation task points include: loading positions 4013 and 4014 in loading area 401, and unloading area entrance 4021, unloading positions 4022 and 4023 in unloading area 402. Through map structuring, the complex physical environment is transformed into a machine-understandable and computable node network. By clearly defining these mixed-operation task points, unmanned vehicles can accurately and automatically trigger the mixed-operation function switch when entering these key areas, laying a solid foundation for the intelligence and safety of the entire mixed-operation process.

[0137] In another embodiment of this disclosure, for the loading area, the first task state includes: entering the loading position, waiting in the loading position, and entering the loading position; for the unloading area, the first task state includes: entering the unloading area entrance, entering the unloading position, and waiting in the unloading position; and / or,

[0138] For the loading area, the second task state includes: performing loading operations at the loading position; for the unloading area, the second task state includes: performing unloading operations at the unloading position.

[0139] In this embodiment of the disclosure, the task states of the loading and unloading areas are divided into a first task state and a second task state based on whether the operation phase requires coordination with manned vehicles. For example... Figure 4As shown, when operating in loading area 401, unmanned vehicle a travels along the x-direction. After changing direction, unmanned vehicle a can activate the mixed-train function switch and then maintain a queue position before changing direction. Therefore, the first task states include: entering loading position 411, waiting at loading position 412, and entering loading position 413. When operating in unloading area 402, unmanned vehicle a travels along the x-direction. Because unloading area 402 is small and the operating position is fixed, unmanned vehicle a can activate the mixed-train function switch after entering unloading area 402. Therefore, the first task states include: entering unloading area entrance 421, waiting at unloading position 422, and entering unloading position 423. Loading operations 414 at the loading position and unloading operations 424 at the unloading position will not interfere with manned vehicle operations. Therefore, for loading area 401, the second task states include: loading operations 414 at the loading position; for unloading area 402, the second task states include: unloading operations 424 at the unloading position. Clearly define the operational phases that require and do not require collaboration, avoiding the activation of the mixed-operation function in the second task state where it is not needed, thus reducing resource waste; at the same time, ensure that the mixed-operation function is activated in the first task state to guarantee collaborative safety. The first and second task states are closely linked to the operational phases. The first task state focuses on high-frequency interaction scenarios such as "vehicle convergence and queuing," and specifically activating the mixed-operation function can reduce the risk of collisions and position disputes; the second task state focuses on "independent operation" scenarios, and disabling the mixed-operation function allows the autonomous vehicle to focus on loading and unloading, improving operational efficiency. The division of task states is consistent with on-site operating habits, reducing the difficulty of system implementation and improving practicality.

[0140] In another embodiment of this disclosure, the method may further include:

[0141] Step 1: When the unmanned vehicle enters the mixed operation mode and is stationary, send a prompt message to the control terminal. The prompt message indicates that the unmanned vehicle is stationary due to the mixed operation mode.

[0142] Step 2: After receiving the command to exit the mixed operation mode from the control terminal, the unmanned vehicle exits the mixed operation mode.

[0143] In this embodiment, when the unmanned vehicle enters the mixed operation mode and is stationary, it actively sends a prompt message to the control terminal to ensure that the control terminal has real-time control over the vehicle's status. Furthermore, the unmanned vehicle can respond to the control terminal's command to exit the mixed operation mode, flexibly exiting the mode. This achieves transparent feedback on the mixed operation status while retaining flexibility for human intervention, balancing automation and controllability. Regarding step 1 above, the unmanned vehicle has entered the mixed operation mode, and due to the triggering of the entry conditions, such as detecting a manned vehicle that meets the entry requirements, the unmanned vehicle is therefore stationary. For example, it may remain stationary or decelerate and brake to a stationary state after movement, requiring it to synchronize its current status information to the control terminal. The control terminal can be a cloud control platform or a dispatcher. Regarding step 2 above, after receiving the command to exit the mixed operation mode from the control terminal, the unmanned vehicle exits the mixed operation mode. For example, if an autonomous vehicle is in a mixed-operation mode, but due to special circumstances, such as the control system detecting that all human and human vehicles have left, the autonomous vehicle needing to prioritize emergency transport tasks, or an anomaly in the mixed-operation coordination, the control system issues a command to exit the mixed-operation mode. The autonomous vehicle must respond to the command and exit the mixed-operation mode. By responding to the control system's commands, a channel for manual intervention in the mixed-operation process is provided. When the automated process cannot handle special scenarios, adjustments can be made quickly through the control system, ensuring the flexibility and reliability of the operation and avoiding operational stagnation or risks caused by the limitations of automation.

[0144] Based on the same disclosed concept, this disclosure also provides a mixed programming device. Since these devices and the principles of the problems they solve are similar to the aforementioned mixed programming method, the implementation of this device can refer to the implementation of the aforementioned method, and the repeated parts will not be described again.

[0145] This disclosure provides a mixed-processing device, such as... Figure 5 As shown, it includes:

[0146] The manned vehicle detection module 501 is used by unmanned vehicles located in the mixed operation area to detect the driving information of manned vehicles within the detection range in real time.

[0147] The manned vehicle entry operation determination module 502 is used to determine whether there are manned vehicles that meet the entry operation conditions based on the driving information of the manned vehicles;

[0148] The mixed operation module 503 is used to control the unmanned vehicle to enter the mixed operation mode when there are manned vehicles that meet the conditions for entering the mixed operation; and to control the unmanned vehicle to exit the mixed operation mode when the driving information of the manned vehicles within the detection range of the unmanned vehicle indicates that all manned vehicles meet the conditions for leaving the mixed operation.

[0149] In another embodiment of this disclosure, the manned vehicle entry operation determination module 502 is used for

[0150] Obtain the status information of the manned vehicle, including its motion state or stationary state;

[0151] The target indicator information corresponding to the status information of the manned vehicle is determined as the driving information;

[0152] Based on the driving information of the manned vehicle, determine whether the manned vehicle meets the conditions for being included in the operational staff.

[0153] In another embodiment of this disclosure, the target indicator information includes at least one of the following: location information, driving speed, and driving direction.

[0154] In another embodiment of this disclosure, the manned vehicle entry operation determination module 502 is used for

[0155] When the status information of the manned vehicle indicates that the manned vehicle is stationary, the location information of the manned vehicle is used as the driving information; or,

[0156] When the status information of the manned vehicle indicates that the manned vehicle is in motion, the position information, speed and direction of travel of the manned vehicle are used as the driving information.

[0157] In another embodiment of this disclosure, the manned vehicle entry operation determination module 502 is used for

[0158] When the status information of the manned vehicle indicates that the manned vehicle is in a stationary state:

[0159] If the location information of the manned vehicle indicates that the manned vehicle is on the planned trajectory of the unmanned vehicle, and prevents the unmanned vehicle from proceeding to the next task point according to the current planned trajectory, then the manned vehicle is determined to meet the conditions for being included in the operational staff; or,

[0160] If the location information of the manned vehicle indicates that the manned vehicle is located on the planned trajectory of the unmanned vehicle or on the extension of the planned trajectory, and the distance between the manned vehicle and the end point of the planned trajectory of the unmanned vehicle is less than a first preset value, then the manned vehicle is determined to meet the conditions for inclusion in the work schedule.

[0161] In another embodiment of this disclosure, the manned vehicle entry operation determination module 502 is used for

[0162] When the status information of the manned vehicle indicates that the manned vehicle is in motion:

[0163] Based on the location information, speed and direction of travel of the manned vehicle, the trajectory of the manned vehicle is predicted to obtain the predicted trajectory.

[0164] Based on the positional relationship between the predicted trajectory and the planned trajectory of the unmanned vehicle, the position information and driving speed of the manned vehicle, it is determined whether the manned vehicle meets the conditions for inclusion in the operational staff.

[0165] In another embodiment of this disclosure, the manned vehicle entry operation determination module 502 is used for

[0166] If the location information of the manned vehicle indicates that the manned vehicle is not on the planned trajectory of the unmanned vehicle, based on the location information of the manned vehicle and the driving speed, it is determined whether the manned vehicle has arrived at the trajectory intersection point earlier than the unmanned vehicle.

[0167] If the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory and the planned trajectory of the unmanned vehicle at the trajectory intersection point is less than a first preset angle, then the manned vehicle is determined to meet the conditions for inclusion in the operational schedule.

[0168] In another embodiment of this disclosure, the mixed programming module 503 is further configured to:

[0169] If the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory and the planned trajectory of the unmanned vehicle at the trajectory intersection point is greater than or equal to a first preset angle, the unmanned vehicle is controlled to decelerate and brake to avoid the collision.

[0170] In another embodiment of this disclosure, the mixed programming module 503 is used for:

[0171] If there are manned vehicles that meet the conditions for being assigned to the work, and the unmanned vehicle is stationary, control the unmanned vehicle to continue to remain stationary;

[0172] When there are manned vehicles that meet the conditions for being assigned to the work, and the unmanned vehicle is in motion, control the unmanned vehicle to decelerate and brake to a stationary state.

[0173] In another embodiment of this disclosure, the mixed programming module 503 is used for:

[0174] If, based on the driving information of the manned vehicles, it is determined that none of the manned vehicles within the detection range of the unmanned vehicle meet the conditions for joining the operation, the unmanned vehicle is controlled to exit the mixed operation mode and start to continue operation.

[0175] In another embodiment of this disclosure, the manned vehicle detection module 501 is used to trigger the unmanned vehicle to activate the mixed-operation function switch when the unmanned vehicle enters the first task state corresponding to the mixed-operation task point within the work area, so as to perform real-time detection of the driving information of manned vehicles within the detection range; or,

[0176] The manned vehicle detection module 501 is further configured to: trigger the unmanned vehicle to turn off the mixed operation function switch when the unmanned vehicle enters the second task state corresponding to the mixed operation task point in the operation area, so as to stop the real-time detection of the driving information of manned vehicles within the detection range and exit the mixed operation mode.

[0177] In another embodiment of this disclosure, the manned vehicle detection module 501 is further configured to:

[0178] The map of the work area is pre-structured to determine the mixed-operation task points;

[0179] The work area includes a loading area and / or an unloading area; the loading area is structured as at least one of the following task points: loading area entrance, reversal completion point, waiting-to-load position, and loading position; the unloading area is structured as at least one of the following task points: unloading area entrance, waiting-to-unload position, and unloading position; the mixed operation task points include the waiting-to-load position and loading position of the loading area, and the unloading area entrance, waiting-to-unload position, and unloading position of the unloading area.

[0180] In another embodiment of this disclosure, for the loading area, the first task state includes: entering the loading position, waiting in the loading position, and entering the loading position; for the unloading area, the first task state includes: entering the unloading area entrance, waiting in the unloading position, and entering the unloading position; and / or,

[0181] For the loading area, the second task state includes: performing a loading operation at the loading position; for the unloading area, the second task state includes: performing an unloading operation at the unloading position.

[0182] In another embodiment of this disclosure, the mixed programming module 503 is further configured to:

[0183] When the unmanned vehicle enters the mixed operation mode and the unmanned vehicle is stationary, a prompt message is sent to the control terminal, the prompt message indicating that the unmanned vehicle is stationary due to the mixed operation mode;

[0184] After receiving the command to exit the mixed operation mode from the control terminal, the unmanned vehicle exits the mixed operation mode.

[0185] Based on the same disclosed concept, this disclosure also provides an unmanned vehicle. Since the principle by which the unmanned vehicle solves the problem is similar to the aforementioned mixed operation method, the implementation of the unmanned vehicle can refer to the implementation of the aforementioned method, and the repeated parts will not be described again.

[0186] Through the above description of the embodiments, those skilled in the art can clearly understand that the embodiments of this disclosure can be implemented in hardware or by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of this disclosure.

[0187] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes in the drawings are not necessarily essential for implementing this disclosure.

[0188] Those skilled in the art will understand that the modules in the apparatus of the embodiments can be distributed in the apparatus of the embodiments as described in the embodiments, or they can be located in one or more devices different from this embodiment with corresponding changes. The modules of the above embodiments can be combined into one module, or they can be further divided into multiple sub-modules.

[0189] The sequence numbers of the embodiments disclosed above are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0190] Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from its spirit and scope. Therefore, if such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, this disclosure is also intended to include such modifications and variations.

Claims

1. A method for mixed-process operations, characterized in that, include: Unmanned vehicles located within the mixed operation area perform real-time detection of driving information of manned vehicles within the detection range; Based on the driving information of the manned vehicles, determine whether any manned vehicles meet the conditions for being included in the operational staff, including: Obtain the status information of the manned vehicle, including its motion state or stationary state; The target indicator information corresponding to the status information of the manned vehicle is determined as the driving information; the target indicator information includes at least one of the following: location information, driving speed, and driving direction. Based on the driving information of the manned vehicle, determine whether the manned vehicle meets the conditions for inclusion in the operational schedule, including: if the status information of the manned vehicle indicates that the manned vehicle is in motion, and if the position information of the manned vehicle indicates that the manned vehicle is not on the planned trajectory of the unmanned vehicle, determine whether the manned vehicle has arrived at the trajectory intersection point earlier than the unmanned vehicle based on the position information of the manned vehicle and the driving speed; if the manned vehicle has arrived at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory of the manned vehicle and the planned trajectory of the unmanned vehicle at the trajectory intersection point is less than a first preset angle, determine that the manned vehicle meets the conditions for inclusion in the operational schedule; When there are manned vehicles that meet the conditions for joining the operation, the unmanned vehicles are controlled to enter the mixed operation mode; If the driving information of the manned vehicles within the detection range of the unmanned vehicle indicates that all manned vehicles meet the conditions for leaving the formation, the unmanned vehicle is controlled to exit the mixed formation operation mode.

2. The method as described in claim 1, characterized in that, The step of determining the target indicator information corresponding to the status information of the manned vehicle as the driving information includes: When the status information of the manned vehicle indicates that the manned vehicle is stationary, the location information of the manned vehicle is used as the driving information; or, When the status information of the manned vehicle indicates that the manned vehicle is in motion, the position information, speed and direction of travel of the manned vehicle are used as the driving information.

3. The method as described in claim 2, characterized in that, The step of determining whether a manned vehicle meets the requirements for inclusion in the operational staff based on its driving information includes: When the status information of the manned vehicle indicates that the manned vehicle is in a stationary state: If the location information of the manned vehicle indicates that the manned vehicle is on the planned trajectory of the unmanned vehicle, and prevents the unmanned vehicle from proceeding to the next task point according to the current planned trajectory, then the manned vehicle is determined to meet the conditions for being included in the operational staff; or, If the location information of the manned vehicle indicates that the manned vehicle is located on the planned trajectory of the unmanned vehicle or on the extension of the planned trajectory, and the distance between the manned vehicle and the end point of the planned trajectory of the unmanned vehicle is less than a first preset value, then the manned vehicle is determined to meet the conditions for inclusion in the work schedule.

4. The method as described in claim 1, characterized in that, The predicted trajectory of the manned vehicle is determined using the following method: Based on the location information, speed, and direction of travel of the manned vehicle, the trajectory of the manned vehicle is predicted to obtain the predicted trajectory.

5. The method as described in claim 4, characterized in that, The method further includes: If the manned vehicle arrives at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory and the planned trajectory of the unmanned vehicle at the trajectory intersection point is greater than or equal to a first preset angle, the unmanned vehicle is controlled to decelerate and brake to avoid the collision.

6. The method as described in claim 1, characterized in that, When there are manned vehicles that meet the conditions for joining the operation, controlling the unmanned vehicles to enter the mixed operation mode includes: If there are manned vehicles that meet the conditions for being assigned to the work, and the unmanned vehicle is stationary, control the unmanned vehicle to continue to remain stationary; When there are manned vehicles that meet the conditions for being assigned to the work, and the unmanned vehicle is in motion, control the unmanned vehicle to decelerate and brake to a stationary state.

7. The method as described in claim 1, characterized in that, When the driving information of the manned vehicles within the detection range of the unmanned vehicle indicates that all manned vehicles meet the conditions for leaving the fleet, the unmanned vehicle is controlled to exit the mixed operation mode, including: If, based on the driving information of the manned vehicles, it is determined that none of the manned vehicles within the detection range of the unmanned vehicle meet the conditions for joining the operation, the unmanned vehicle is controlled to exit the mixed operation mode and start to continue operation.

8. The method as described in claim 1, characterized in that, The unmanned vehicle located within the mixed operation area performs real-time detection of driving information of manned vehicles within its detection range, including: when the unmanned vehicle enters the first task state corresponding to the mixed operation task point within the operation area, triggering the unmanned vehicle to activate the mixed operation function switch to perform real-time detection of driving information of manned vehicles within its detection range; or, The method further includes: when the unmanned vehicle enters the second task state corresponding to the mixed operation task point in the operation area, triggering the unmanned vehicle to turn off the mixed operation function switch, so as to stop the real-time detection of the driving information of human vehicles within the detection range and exit the mixed operation mode.

9. The method as described in claim 8, characterized in that, The method further includes: The map of the work area is pre-structured to determine the mixed-operation task points; The work area includes a loading area and / or an unloading area; the loading area is structured as at least one of the following task points: loading area entrance, reversal completion point, waiting-to-load position, and loading position; the unloading area is structured as at least one of the following task points: unloading area entrance, waiting-to-unload position, and unloading position; the mixed operation task points include the waiting-to-load position and loading position of the loading area, and the unloading area entrance, waiting-to-unload position, and unloading position of the unloading area.

10. The method as described in claim 8 or 9, characterized in that, For the loading area, the first task status includes: entering the loading position, waiting in the loading position, and entering the loading position; for the unloading area, the first task status includes: entering the unloading area entrance, waiting in the unloading position, and entering the unloading position; and / or, For the loading area, the second task state includes: performing a loading operation at the loading position; for the unloading area, the second task state includes: performing an unloading operation at the unloading position.

11. The method as described in claim 1, characterized in that, The method further includes: When the unmanned vehicle enters the mixed operation mode and the unmanned vehicle is stationary, a prompt message is sent to the control terminal, the prompt message indicating that the unmanned vehicle is stationary due to the mixed operation mode; After receiving the command to exit the mixed operation mode from the control terminal, the unmanned vehicle exits the mixed operation mode.

12. A mixed-batch operation device, characterized in that, include: The manned vehicle detection module is used by unmanned vehicles located in the mixed operation area to detect the driving information of manned vehicles within the detection range in real time. The manned vehicle registration and operation determination module is used to determine whether there are manned vehicles that meet the registration and operation conditions based on the driving information of the manned vehicles, including: Obtain the status information of the manned vehicle, including its motion state or stationary state; The target indicator information corresponding to the status information of the manned vehicle is determined as the driving information; the target indicator information includes at least one of the following: location information, driving speed, and driving direction. Based on the driving information of the manned vehicle, determine whether the manned vehicle meets the conditions for inclusion in the operational schedule, including: if the status information of the manned vehicle indicates that the manned vehicle is in motion, and if the position information of the manned vehicle indicates that the manned vehicle is not on the planned trajectory of the unmanned vehicle, determine whether the manned vehicle has arrived at the trajectory intersection point earlier than the unmanned vehicle based on the position information of the manned vehicle and the driving speed; if the manned vehicle has arrived at the trajectory intersection point earlier than the unmanned vehicle, and the angle formed by the driving direction vectors corresponding to the predicted trajectory of the manned vehicle and the planned trajectory of the unmanned vehicle at the trajectory intersection point is less than a first preset angle, determine that the manned vehicle meets the conditions for inclusion in the operational schedule; The mixed operation module is used to control the unmanned vehicle to enter the mixed operation mode when there are manned vehicles that meet the conditions for entering the operation; and to control the unmanned vehicle to exit the mixed operation mode when the driving information of the manned vehicles within the detection range of the unmanned vehicle indicates that both manned and unmanned vehicles meet the conditions for leaving the operation.

13. An unmanned vehicle, characterized in that, Includes the mixed-processing device as described in claim 12.

Images