Scheduling method and device applied to large-scale unmanned vehicle cluster and cloud control platform

Abstract

The invention provides a scheduling method and device applied to a large-scale unmanned vehicle cluster, and a cloud control platform. The method comprises the steps of obtaining operation state information of a scheduled unmanned vehicle cluster in a preset operation area; when it is determined that a traffic jam event occurs according to the operation state information, determining a first area range where the traffic jam event occurs; a second area range is determined according to the first area range, the unmanned vehicle running in the second area range is controlled to be switched from the first working mode to a second working mode, and under the same working condition, the energy consumption of the unmanned vehicle under the second working mode is lower than that of the first working mode. According to the invention, the load of the congested area is reduced, and the operation efficiency is improved at the same time.

Description

Technical Field

[0001] The present disclosure relates to the field of unmanned driving technology, and in particular to a scheduling method, device and cloud control platform applied to large-scale unmanned vehicle clusters. Background Art

[0002] In the process of large-scale unmanned vehicle cluster production operations in mining areas, traffic congestion often occurs in some areas. Traditionally, in order to alleviate the congestion in the traffic congestion area, the departure frequency of the departure point is usually reduced. For example, the loading frequency of the excavator is reduced to reduce the departure frequency of the loading area. However, this method will lead to a significant decrease in operating efficiency and may cause new congestion in other areas. No effective solution has been proposed for the above problems. Summary of the invention

[0003] The embodiments of the present disclosure provide a scheduling method, device and cloud control platform for large-scale unmanned vehicle clusters to solve the problems existing in the related technologies.

[0004] Based on the above problems, in a first aspect, an embodiment of the present disclosure provides a scheduling method applied to a large-scale unmanned vehicle cluster, including:

[0005] Obtain the operating status information of the unmanned vehicle cluster dispatched in the preset operation area;

[0006] In the case where a traffic congestion event is determined to have occurred according to the operating status information, determining a first area range where the traffic congestion event has occurred;

[0007] A second area range is determined based on the first area range, and an unmanned vehicle traveling in the second area range is controlled to switch from a first working mode to a second working mode, wherein under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that in the first working mode.

[0008] In combination with the first aspect, in a possible implementation manner, determining the second area range according to the first area range includes:

[0009] Determine the area category corresponding to the preset operation area;

[0010] Determining a corresponding preset energy-saving strategy according to the area category corresponding to the preset operation area;

[0011] A second area range is determined according to the first area range and the determined preset energy-saving strategy.

[0012] In combination with the first aspect, in a possible implementation manner, the area category corresponding to the preset operation area includes at least one of the following: a local road driving area, a loading and unloading operation area, and a unloading operation area.

[0013] In combination with the first aspect, in a possible implementation manner, when the area category is a local road driving area, the first area range is a road range occupied by a vehicle queue where congestion occurs;

[0014] The determining the second area range according to the first area range includes:

[0015] Determining a first starting position of a congestion location according to a road range occupied by the congested vehicle queue;

[0016] Determine a second area range according to the first starting position and a first preset energy-saving area range;

[0017] The first preset energy-saving area range is a predefined area range starting from the traffic congestion location and extending upstream by a first preset distance.

[0018] In combination with the first aspect, in a possible implementation manner, when the area category is a mining and loading operation area, the first area range is the mining and loading operation area;

[0019] The determining the second area range according to the first area range includes:

[0020] The scope of the second area is determined according to the working status of the collection and loading operation area and the unmanned vehicle outside the collection and loading operation area.

[0021] In combination with the first aspect, in a possible implementation manner, determining the second area range according to the working status of the collection and loading operation area and the unmanned vehicle outside the collection and loading operation area includes:

[0022] The area where the unmanned unmanned vehicle is located outside the collection and loading operation area is determined as the second area range.

[0023] In combination with the first aspect, in a possible implementation, the loading and unloading operation area includes: all path topologies starting from the most downstream intersection before the divergence on the path from the unloading operation area to the loading area and passing through all loading areas, as well as all loading areas.

[0024] In combination with the first aspect, in a possible implementation manner, when the area category is an unloading operation area, the first area range includes the unloading operation area, or an entrance area of ​​the unloading operation area;

[0025] The determining the second area range according to the first area range includes:

[0026] Determine the entrance of the unloading operation area as the second starting position of the congestion position;

[0027] Determine a second area range according to the second starting position and a second preset energy-saving area range;

[0028] The second preset energy-saving area range is a predefined area range that takes the entrance of the unloading operation area as the starting position and extends upstream by a second preset distance.

[0029] In combination with the first aspect, in a possible implementation, when the area category corresponding to the preset operation area is a local road driving area, the operation status information includes: current position information and current vehicle speed information; determining the occurrence of a traffic congestion event based on the operation status information includes: based on the current position information and the current vehicle speed information, if there are at least two unmanned vehicles, the vehicle speed is zero and the front and rear distance of the two unmanned vehicles is not greater than a preset following distance, then determining the occurrence of a traffic congestion event; or,

[0030] In the case where the area category corresponding to the preset operation area is an unloading operation area, the operation status information includes: current vehicle speed information and real-time operation information; determining the occurrence of a traffic congestion event based on the operation status information includes: determining the occurrence of a traffic congestion event based on the current vehicle speed information and the real-time operation information if there are at least two unmanned vehicles in the unloading operation area, the vehicle speed is zero and no unloading operation is currently being performed; or

[0031] When the area category corresponding to the preset operation area is the mining and loading operation area, the operating status information includes current load information; determining the occurrence of a traffic congestion event based on the operating status information includes: determining a first number of empty-loaded unmanned vehicles located in the mining and loading operation area based on the current load information; when the first number is greater than or equal to a preset saturation value, determining the occurrence of a traffic congestion event; and / or determining a second number of empty-loaded unmanned vehicles per excavator located in the mining and loading operation area on average based on the current load information; when the second number is greater than or equal to the preset saturation value of the excavator, determining the occurrence of a traffic congestion event.

[0032] In combination with the first aspect, in a possible implementation manner, the method further includes:

[0033] Marking the map area corresponding to the second area range on the map; and

[0034] The marked map is sent to the unmanned vehicle so that the unmanned vehicle determines the working mode to be adopted according to the marked map and its own position, and the working mode includes the first working mode or the second working mode.

[0035] In a second aspect, a dispatching device for a large-scale unmanned vehicle cluster is provided, comprising:

[0036] An acquisition module is used to obtain the operating status information of the unmanned vehicle cluster scheduled in the preset operation area;

[0037] A congestion determination module, configured to determine a first area range where a traffic congestion event occurs when it is determined that a traffic congestion event occurs according to the operating state information;

[0038] A mode switching module is used to determine a second area range based on the first area range, and control the unmanned vehicle traveling in the second area range to switch from a first working mode to a second working mode, wherein under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that in the first working mode.

[0039] In a third aspect, a cloud control platform is provided, including: a scheduling device applied to a large-scale unmanned vehicle cluster as described in the second aspect.

[0040] The beneficial effects of the embodiments of the present disclosure include:

[0041] The present disclosure provides a scheduling method, device and cloud control platform for large-scale unmanned vehicle clusters, including: obtaining the operating status information of the unmanned vehicle clusters scheduled in a preset operating area; determining the first area range where the traffic congestion event occurs according to the operating status information; determining the second area range according to the first area range, and controlling the unmanned vehicle traveling in the second area range to switch from the first working mode to the second working mode, wherein under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that of the first working mode. The scheduling method for large-scale unmanned vehicle clusters provided by the embodiment of the present disclosure obtains the real-time operating status information of the unmanned vehicles in each preset operating area, determines the first area range where the traffic congestion event occurs, and controls the unmanned vehicles in the relevant area to travel in an energy-saving manner without affecting the operating efficiency, thereby realizing energy-saving driving of the unmanned vehicle in the congested scene, reducing energy consumption while reducing the load of the congested area, and improving the operating efficiency, providing technical support for realizing a green and intelligent mining area operating environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A flowchart of a scheduling method for a large-scale unmanned vehicle cluster provided in an embodiment of the present disclosure;

[0043] Figure 2 One of the road topology relationship diagrams provided in the embodiment of the present disclosure;

[0044] Figure 3 The second schematic diagram of road topology provided in the embodiment of the present disclosure;

[0045] Figure 4 The third schematic diagram of road topology provided in the embodiment of the present disclosure;

[0046] Figure 5 A fourth schematic diagram of a road topology relationship provided in an embodiment of the present disclosure;

[0047] Figure 6 A fifth schematic diagram of road topology provided in an embodiment of the present disclosure;

[0048] Figure 7 The sixth schematic diagram of road topology provided in the embodiment of the present disclosure;

[0049] Figure 8 A schematic diagram of the structure of a dispatching device for large-scale unmanned vehicle clusters provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0050] The embodiments of the present disclosure provide a scheduling method, device and cloud control platform for large-scale unmanned vehicle clusters. The preferred embodiments of the present disclosure are described below in conjunction with the drawings of the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present disclosure, and are not used to limit the present disclosure. In addition, the embodiments and features in the embodiments of the present application can be combined with each other if there is no conflict.

[0051] The present disclosure provides a scheduling method for a large-scale unmanned vehicle cluster. Figure 1 As shown, including:

[0052] S101, obtaining the operation status information of the unmanned vehicle cluster scheduled in the preset operation area;

[0053] S102, when it is determined according to the operation status information that a traffic congestion event has occurred, determining a first area range where the traffic congestion event has occurred;

[0054] S103. Determine a second area range based on the first area range, and control the unmanned vehicle traveling in the second area range to switch from the first working mode to the second working mode, wherein under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that in the first working mode.

[0055] In the disclosed embodiment, the execution subject may be a server or a terminal. Optionally, the execution subject may be a cloud control platform. The cloud control platform may provide detailed map information in a preset operation area through a production map management module, including road conditions and operation points, etc.; the cloud control platform may communicate with the unmanned vehicle through a production scheduling module to control the working mode and task allocation of a large-scale unmanned vehicle cluster, thereby completing the transportation operation task.

[0056] The unmanned vehicle can be a mining vehicle with unmanned transportation in mines. It can obtain its own operating status information through a combination of multiple devices and sensors. For example, a combined navigation device can be configured as a positioning module to obtain real-time position information within the preset working area. In addition, a variety of sensors can be configured. For example, a weight sensor installed on the vehicle suspension system or axle can measure its own load in real time. This type of sensor can accurately measure the weight difference between the vehicle in a heavy load and an empty load state, thereby providing load information. For example, sensors such as cameras, lidar, and millimeter-wave radars can be used to identify traffic signs, vehicles, obstacles, and other information on the road ahead.

[0057] However, due to the complex environment of the mining area, some special situations often cause traffic congestion. For example, there are often obstacles such as falling rocks and bulk materials in the mining area. When encountering obstacles ahead, unmanned vehicles usually slow down or stop. As the scale of unmanned vehicle clusters increases, traffic congestion is inevitable on the working roads or working points.

[0058] In the embodiment of the present disclosure, by communicating with the unmanned vehicle cluster, the real-time operation status information of the unmanned vehicle cluster dispatched in the preset operation area is obtained. Based on this operation status information, it can be determined whether a traffic congestion event occurs in the preset operation area, and then in the event of a traffic congestion event, the first area range where the traffic congestion event occurs is determined. For example, Figure 2 As shown, in the preset operation area, the cloud control platform communicates with the unmanned vehicle cluster to obtain the operating status information of the unmanned vehicle a and the unmanned vehicle b traveling in the x direction, and determines that a traffic congestion incident has occurred in the area where the unmanned vehicle a and the unmanned vehicle b are located, and then determines the first area range AB where the traffic congestion incident has occurred.

[0059] Furthermore, if Figure 2 As shown, the cloud control platform determines the second area range BC upstream of the first area range AB according to the first area range AB, and controls the unmanned vehicle c traveling in the second area range BC to switch from the first working mode to the second working mode, wherein, under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that in the first working mode, so as to achieve the purpose of energy-saving driving of the unmanned vehicle in the second area range without affecting the operating efficiency. And after the traffic congestion event is over, the unmanned vehicles in the second area range are controlled to switch to the first working mode. Exemplarily, after the special situation is handled, for example, after the auxiliary vehicle removes the obstacle, the unmanned vehicle a and the unmanned vehicle b resume the transportation operation, and the intelligent cloud control platform determines that the traffic congestion event is over according to the acquired operating status information of the unmanned vehicle a and the unmanned vehicle b, deletes the second area range BC, and controls the unmanned vehicle c to switch to the first working mode.

[0060] In the embodiment of the present application, by obtaining the real-time operating status information of the unmanned vehicle cluster dispatched in the preset operating area, the initial area where the traffic congestion occurs can be accurately located. Then, the unmanned vehicles upstream of the congested area are controlled to drive in a working mode that saves the most energy without reducing work efficiency. This can not only reduce energy consumption, but also ease the pressure in the traffic congestion area, improve overall operating efficiency, and help build a more environmentally friendly and intelligent mining operating environment.

[0061] In another embodiment of the present disclosure, in the above step S103, determining the second area range according to the first area range includes:

[0062] Step 1: Determine the area category corresponding to the preset operation area;

[0063] Step 2: Determine a corresponding preset energy-saving strategy according to the area category corresponding to the preset operation area;

[0064] Step 3: Determine the second area range according to the first area range and the determined preset energy-saving strategy.

[0065] In the disclosed embodiment, during the planning and construction of the mining area, the preset operation area can be divided into different area categories in combination with the actual environment, and the unmanned vehicles perform different operation tasks in different area categories. For step 1, first determine the area category corresponding to the preset operation area; for step 2, a preset energy-saving strategy is pre-set based on each area category, and then determine the corresponding preset energy-saving strategy according to the area category corresponding to the determined preset operation area; for step 3, finally, determine the second area range according to the first area range where the traffic congestion incident occurs and the determined corresponding preset energy-saving strategy. By classifying and refining the preset operation area and the corresponding preset energy-saving strategy, the first area range where the traffic congestion incident occurs and the corresponding second area range of energy-saving driving can be more accurately confirmed.

[0066] In another embodiment of the present disclosure, the area category corresponding to the preset operation area includes at least one of the following: a local road driving area, a loading and unloading operation area, and a unloading operation area.

[0067] In the disclosed embodiment, the area categories divided according to the functions of the preset operation areas in the mine include at least one of the following: local road driving areas, mining and loading operation areas, and unloading operation areas. Exemplarily, the mining and loading operation areas mainly include large-scale excavation equipment, such as excavators and loaders, which perform mining operations and load ore and other materials into unmanned vehicles for transportation; the unloading operation area can be a place where unmanned vehicles unload ore and other materials transported from the mining and loading operation area, and it is also an important connection point between mining and subsequent processing and treatment links. It usually includes multiple unloading points to meet the needs of different material storage and custody; the local road driving area can be a road connecting the mining and loading operation area and the unloading operation area for unmanned vehicle cluster transportation operations. By reasonably dividing the preset operation areas of the mine, preventing interference between the various operation areas, facilitating the optimization of the work process, and facilitating the dispatch of unmanned vehicles, the safety and efficiency of mine operations can be improved to a certain extent.

[0068] In yet another embodiment of the present disclosure, when the area category is a local road driving area, the first area range is a road range occupied by a vehicle queue where congestion occurs.

[0069] In the above step S103, determining the second area range according to the first area range includes:

[0070] Step 1: Determine the first starting position of the congestion location according to the road range occupied by the vehicle queue where the congestion occurs;

[0071] Step 2: Determine a second area range based on the first starting position and the first preset energy-saving area range; wherein the first preset energy-saving area range is a predefined area range starting from the traffic congestion position and extending upstream by a first preset distance.

[0072] In the embodiment of the present disclosure, when the area category is a local road driving area, the road range occupied by the congested vehicle queue is determined as the first area range where the traffic congestion event occurs, so as to accurately locate the initial area range where the traffic congestion event occurs. In a possible implementation, the local road can be a road between various operating areas in a mining area, for example, a road connecting a mining and loading area and an unloading area. For example, Figure 3 As shown, the cloud control platform obtains that unmanned vehicles a and b are traveling on a local road driving area extending from the unloading operation area to the loading area in the x direction, and determines that a traffic congestion event has occurred, then the road range AB occupied by unmanned vehicles a and b in the vehicle queue where the congestion occurred is determined as the first area range.

[0073] For step 1, a first starting position of the congestion position is determined according to the road range occupied by the vehicle queue where the congestion occurs. The first starting position may be the position of the head vehicle of the vehicle queue where the congestion occurs, or the position of the tail vehicle of the vehicle queue where the congestion occurs, or any position in the road range occupied by the vehicle queue where the congestion occurs; for example, Figure 3 As shown, the road range AB occupied by the vehicle queue where congestion occurs, the first starting position for determining the congestion position can be point A of the leading vehicle position, point B of the trailing vehicle position, or any position in the road range AB occupied by the vehicle queue where congestion occurs.

[0074] For step 2, first define a first preset distance, then take the traffic congestion location as the starting location, and extend the area range of the first preset distance upstream as the first preset energy-saving area range. If the road where the first area range is located can cover the first preset energy-saving area range, the first preset energy-saving area range is determined as the second area range. For example, Figure 3 As shown, starting from the tail vehicle position of the vehicle queue in the first area range AB (here, the congestion position is determined as the tail vehicle as an example), the area range BC of the first preset distance is extended upstream as the first preset energy-saving area range. If the length of the road where the first area range AB is located is long enough, and the first preset energy-saving area range BC is still within the road range where the first area range AB is located, the first preset energy-saving area range BC is determined as the second area range.

[0075] In the case where the road in the first area range cannot cover the first preset energy-saving area range, for example, there is an intersection within the first preset energy-saving area range, it is determined whether there is a road other than the road where the traffic congestion event occurs that can be reached from the intersection to the downstream preset operation area, and no traffic congestion event occurs; for example, Figure 4 As shown, according to the congestion in the first area range AB where the unmanned vehicle a and the unmanned vehicle b are located, the vehicle is traveling in the x direction, from the unloading operation area to the loading area. According to the topological relationship of the road, it can be determined whether there is a road from the intersection to the downstream loading area other than the road where the first area range AB is located that can reach the loading area, and there is no traffic congestion on this road.

[0076] If present, exemplary, such as Figure 4 As shown, there is a road FG that can reach the second loading area, and there is no traffic congestion on this road, then the road BE between the starting point B of the first preset energy-saving area and the intersection is determined as the second area. In this case, the length of the second area is less than or equal to the length of the first preset distance. In this way, the unmanned vehicle c traveling on the road from the intersection to the upstream still drives in the first working mode when going to the second loading area, ensuring the working efficiency.

[0077] If not present, an example such as Figure 4 As shown, if a traffic jam occurs on the road FG, or there is no road other than the road where the first area range AB is located that can reach the loading area, a first distance range BE from the starting point B of the first preset energy-saving area range to the intersection is determined, and for each upstream road entering the intersection, a second distance range is extended from the entrance of the intersection to the upstream direction of the upstream road, such as Figure 4 As shown, the second distance range is CD and C'D'. Finally, the first distance range BE and the second distance range CD and C'D' of each upstream road are jointly determined as the second area range. And the sum of the length of the first distance range and each second distance range can be greater than or equal to the length of the first preset energy-saving area range.

[0078] In another embodiment of the present disclosure, when the area category is a mining and loading operation area, the first area range is the mining and loading operation area.

[0079] In the above step S103, determining the second area range according to the first area range includes:

[0080] The scope of the second area is determined based on the working status of the unmanned vehicle in the collection and loading operation area and outside the collection and loading operation area.

[0081] In the embodiment of the present disclosure, when the area category is the mining and loading operation area, the mining and loading operation area is determined as the first area range where the traffic congestion incident occurs. This can reduce the impact on other areas, maintain the overall production order, and the cloud control platform can quickly dispatch to facilitate timely handling of congestion incidents in the mining and loading operation area.

[0082] The second area is determined according to the working status of the unmanned vehicle cluster outside the collection and installation operation area and the collection and installation operation area. For example, the cloud control platform can obtain the working status of the unmanned vehicle cluster outside the collection and installation operation area, and then determine the second area according to the working status.

[0083] In another embodiment of the present disclosure, determining the second area range according to the working status of the collection and loading operation area and the unmanned vehicle outside the collection and loading operation area includes:

[0084] The area where the unmanned unmanned vehicles operating without loads are located outside the collection and loading operation area is determined as the second area range.

[0085] In the disclosed embodiment, the second area is determined based on the working status of the unmanned vehicle in the mining and loading operation area and outside the mining and loading operation area, including: the area where the unmanned vehicle with no load is located outside the mining and loading operation area is determined as the second area. Exemplarily, the cloud control platform can obtain the load information and working mode of the unmanned vehicle. When a traffic jam occurs in the mining and loading operation area, the number of unmanned vehicles with no load in the area is saturated, and there is no need for unmanned vehicles with no load in other areas to quickly go to the mining and loading operation area. Therefore, the area where the unmanned vehicle with no load is located outside the mining and loading operation area is determined as the second area. At this time, if the unmanned vehicle with no load in the second area is in the first working mode, the cloud control platform controls the unmanned vehicle to switch to the second working mode.

[0086] In another embodiment of the present disclosure, the loading and unloading operation area includes: all path topologies starting from the most downstream intersection before the divergence on the path from the unloading operation area to the loading area and passing through all loading areas, as well as all loading areas.

[0087] In the embodiment of the present disclosure, the loading and unloading operation area includes: all path topologies starting from the most downstream intersection before the diversion on the path from the unloading operation area to the loading area and all loading areas, as well as all loading areas. Figure 5 As shown, the unmanned vehicle passes through intersection A and intersection B respectively on the path from the unloading operation area to the loading area, wherein intersection A connects the first loading area, and intersection B connects the second loading area and the third loading area. The unmanned vehicle traveling along the x direction first passes through intersection A, and intersection A is determined to be the most downstream intersection before the diversion on the path from the unloading operation area to the loading area. The topology of all paths starting from intersection A to all loading areas, as well as all loading areas, together constitute the loading and unloading operation area 100.

[0088] In yet another embodiment of the present disclosure, when the area category is an unloading operation area, the first area range includes the unloading operation area, or an entrance area of ​​the unloading operation area.

[0089] In the above step S103, determining the second area range according to the first area range includes:

[0090] Step 1: determining the entrance of the unloading operation area as the second starting position of the congestion position;

[0091] Step 2: determine the second area range according to the second starting position and the second preset energy-saving area range; wherein the second preset energy-saving area range is a predefined area range that takes the entrance of the unloading operation area as the starting position and extends upstream by a second preset distance.

[0092] In the embodiment of the present disclosure, when the area category is an unloading operation area, the unloading operation area or the entrance area of ​​the unloading operation area is determined as the first area range where the traffic congestion event occurs. Here, the entrance area of ​​the unloading operation area includes a certain range, and the range of X meters from the entrance in the unloading operation area can be determined as the entrance area range. X can be set to a default distance, the distance from the nearest available unloading position to the entrance of the unloading operation area to the entrance of the unloading operation area, or the maximum value of the two.

[0093] With respect to step 1, when entering within a certain range of the entrance of the unloading operation area or when there is a traffic congestion event in the unloading operation area, the entrance of the unloading operation area may be determined as the second starting position of the congestion position.

[0094] For step 2, first define the second preset distance, then take the entrance of the unloading operation area as the starting position, and extend the area range of the second preset distance upstream as the second preset energy-saving area range. If the road where the entrance of the unloading operation area is located can cover the second preset energy-saving area range, the second preset energy-saving area range is determined as the second area range. For example, Figure 6 As shown, the area range AB extending from the entrance position of the unloading operation area to the upstream direction for a second preset distance is the second preset energy-saving area range. If the length of the road where the entrance of the unloading operation area is located is long enough, the second preset energy-saving area range AB is still within the road range where the entrance of the unloading operation area is located, then the second preset energy-saving area range AB is determined as the second area range.

[0095] In the case where the road at the entrance of the unloading operation area cannot cover the second preset energy-saving area, for example, there is an intersection within the second preset energy-saving area, it is determined whether there is a road from the intersection to the downstream preset operation area that can be reached except the road where the traffic congestion event occurs, and no traffic congestion event occurs; for example, Figure 7 As shown, congestion occurs in the first unloading operation area. The vehicle travels in the y direction from the loading area to the unloading operation area. According to the topological relationship of the road, it can be determined whether there is a road from the intersection to the downstream unloading operation area except the road where the entrance of the first unloading operation area is located that can reach the unloading operation area, and there is no traffic congestion in the unloading operation area within this road.

[0096] If present, exemplary, such as Figure 7As shown, if there is a road CD that can reach the second unloading operation area, and there is no traffic congestion in the second unloading operation area, the road AE between the starting point A of the second preset energy-saving area range and the intersection is determined as the second area range. In this case, the length of the second area range is less than or equal to the length of the first preset distance. In this way, the unmanned vehicle a traveling on the road from the intersection to the upstream still travels in the first working mode when going to the second unloading operation area, ensuring the operation efficiency.

[0097] If not present, an example such as Figure 7 As shown, if a traffic jam occurs in the second unloading operation area, or there is no road other than the road where the entrance to the first unloading operation area is located to reach the unloading operation area, a third distance range AE from the starting point A of the second preset energy-saving area range to the intersection is determined, and for each upstream road entering the intersection, a fourth distance range is extended from the intersection to the upstream direction on the upstream road, as shown in FIG. Figure 7 As shown, the fourth distance range is BF and B'F'. Finally, the third distance range AE and the fourth distance range BF and B'F' of each upstream road are jointly determined as the second area range. And the sum of the length of the third distance range and each fourth distance range can be greater than or equal to the length of the second preset energy-saving area range.

[0098] In another embodiment of the present disclosure, when the area category corresponding to the preset operation area is a local road driving area, the operation status information includes: current position information and current vehicle speed information; in the above step S102, determining the occurrence of a traffic congestion event according to the operation status information includes: according to the current position information and the current vehicle speed information, if there are at least two unmanned vehicles, the vehicle speed is zero and the front and rear distance of the two unmanned vehicles is not greater than the preset following distance, then determining the occurrence of a traffic congestion event; or,

[0099] In the case where the area category corresponding to the preset operation area is an unloading operation area, the operation status information includes: current vehicle speed information and real-time operation information; in the above step S102, determining the occurrence of a traffic congestion event according to the operation status information includes: according to the current vehicle speed information and the real-time operation information, if there are at least two unmanned vehicles in the unloading operation area or the entrance area of ​​the unloading operation area, the vehicle speed is zero and no unloading operation is currently being performed, determining the occurrence of a traffic congestion event; or,

[0100] In the case where the area category corresponding to the preset operation area is a collection and loading operation area, the operation status information includes the current load information; in the above step S102, determining the occurrence of a traffic congestion event based on the operation status information includes: determining the first number of empty unmanned vehicles located in the collection and loading operation area based on the current load information; determining the occurrence of a traffic congestion event when the first number is greater than or equal to a preset saturation value; assuming that the first number of empty unmanned vehicles currently existing in the entire collection and loading operation area is 20, and the preset saturation value that the entire collection and loading operation area can accommodate empty unmanned vehicles is 15, then determining that a traffic congestion event has occurred; and / or

[0101] According to the current load information, the second number of unloaded unmanned vehicles per excavator located in the mining and loading area is determined on average; when the second number is greater than or equal to the preset saturation value of the excavator, a traffic jam is determined to have occurred; assuming that the first number of unloaded unmanned vehicles currently in the entire mining and loading area is 20, the number of excavators is 5, and the preset saturation value of each excavator is 3 unmanned vehicles, then the second number of unloaded unmanned vehicles per excavator is currently 4, which is greater than the preset saturation value of the excavator, then a traffic jam is determined to have occurred.

[0102] In the embodiment of the present disclosure, when the area category corresponding to the preset operation area is a local road driving area, the current position information and current vehicle speed information of the unmanned vehicle cluster in the local road driving area are first obtained, and then a judgment is made based on the above current position information and current vehicle speed information. If there are at least two unmanned vehicles with zero speed in the local road driving area, and the distance between the front and the rear is not greater than the preset following distance, it is determined that a traffic congestion event has occurred; for example, Figure 2 As shown, unmanned vehicles a, b, and c are driving in a local road driving area. After obtaining the current position information and current speed information of unmanned vehicles a, b, and c, the cloud control platform determines that unmanned vehicles a and b meet the conditions that the speed is zero and the distance between the front and the rear is not greater than the preset following distance, so it is confirmed that a traffic congestion event has occurred on the road where unmanned vehicles a and b are located; or,

[0103] When the area category corresponding to the preset operation area is the unloading operation area, first obtain the current speed information and real-time operation information of the unmanned vehicle in the unloading operation area. Exemplarily, the cloud control platform can obtain the real-time operation information of the unmanned vehicle through the production scheduling module; the real-time operation information shows the ongoing operation status of the unmanned vehicle, for example, the unmanned vehicle is performing unloading operations or loading operations. Then, based on the current speed information and real-time operation information, a judgment is made. If there are at least two unmanned vehicles with a speed of zero in the unloading operation area and no unloading operation is currently being performed, it is determined that a traffic congestion event has occurred; or,

[0104] In the case where the area category corresponding to the preset operation area is the mining and loading operation area, the current load information of the unmanned vehicle in the mining and loading operation area is first obtained. Exemplarily, the unmanned vehicle can obtain its own current load information through a weight sensor or a load sensing device, such as a laser radar. According to the current load information of the unmanned vehicle in the mining and loading operation area, the first number of unmanned vehicles operating without load is determined; according to the above first number, if the first number is greater than or equal to the preset saturation value, it indicates that the number of unmanned vehicles operating without load at this time is saturated, and then it is determined that a traffic congestion event has occurred; and / or according to the current load information of the unmanned vehicle in the mining and loading operation area, the first number of unmanned vehicles operating without load is determined, and the number of excavators in the mining and loading operation area is obtained, and then the second number of unmanned vehicles operating without load per excavator (i.e., the average number of unmanned vehicles operating without load corresponding to each excavator) is determined; according to the above second number, if the second number is greater than or equal to the preset saturation value of the excavator, it indicates that the number of unmanned vehicles operating without load at this time is saturated, and then it is determined that a traffic congestion event has occurred.

[0105] In another embodiment of the present disclosure, it also includes: marking the map area corresponding to the second area range on the map; and sending the marked map to the unmanned vehicle, so that the unmanned vehicle determines the working mode to be adopted according to the marked map and its own position, and the working mode includes the first working mode or the second working mode.

[0106] In the disclosed embodiment, the production map management module of the cloud control platform marks the map area corresponding to the second area on the map, and sends the marked map to the unmanned vehicle through communication with the unmanned vehicle, so that the unmanned vehicle determines the working mode to be adopted according to the marked map and its own position. In this case, the working mode of the unmanned vehicle can be controlled by the cloud control platform or by the unmanned vehicle itself.

[0107] Further, the working mode may include a first working mode or a second working mode. The speed of the unmanned vehicle in the second working mode is lower than the speed in the first working mode, so that the unmanned vehicle can save more energy when driving in the second working mode, and it takes longer to reach the traffic congestion area, thereby reducing the load of the traffic congestion area; and / or, the braking distance of the unmanned vehicle in the second working mode is greater than the braking distance in the first working mode, and the braking force of the unmanned vehicle in the second working mode is lower, and it relies more on sliding for deceleration braking, thereby reducing the energy loss caused by braking; and / or, the starting acceleration of the unmanned vehicle in the second working mode is less than the starting acceleration in the first working mode, and slow acceleration can reduce energy consumption, thereby saving energy. In addition, when the unmanned vehicle is driving in the non-intersection area within the second area, the second working mode is adopted, and when driving in the intersection area, it is restored to the first working mode, so as to avoid interfering with the normal passage of other vehicles, thereby ensuring the safe passage of the vehicle through the intersection.

[0108] Optionally, in any of the above embodiments, the first preset distance and / or the second preset distance are related to environmental information, and the environmental information includes any one of a slippery environment and a dusty environment. The first preset distance and / or the second preset distance are positively correlated with the severity of the slippery environment, or the severity of the dusty environment. Through a large number of experimental verifications, this embodiment can further improve energy saving effects and operating efficiency.

[0109] Optionally, when any of the vehicles is in the second working mode, it can transmit broadcast information to other vehicles within a specified distance range around it, and the broadcast information includes its own vehicle driving parameters in the second working mode. After receiving the broadcast information, other vehicles parse the information, obtain its vehicle driving parameters, and adjust their own vehicle driving parameters according to its vehicle driving parameters. Optionally, the broadcast information may also include the driving length or coordinates of the energy-saving section corresponding to the second working mode in this case (for example, the first preset distance and / or the second preset distance mentioned above). Other vehicles obtain their vehicle driving parameters and the corresponding driving length or coordinates of the energy-saving section, and adjust their own vehicle driving parameters based on this. This embodiment can be separated from the control of the cloud platform to a certain extent, especially in areas with poor network signals, and can effectively improve data processing speed and effectiveness.

[0110] Optionally, after the target vehicle obtains the broadcast information including vehicle driving parameters and vehicle environmental attributes sent by other vehicles, the target vehicle driving parameters of the target vehicle are adjusted based on the current vehicle driving parameters and environmental attribute information of the target vehicle. Specifically, the target vehicle collects its own current perception data and / or combines the map information to obtain the current environmental attribute information, compares the current environmental attributes with the vehicle environmental attributes sent by other vehicles, and directly uses the vehicle driving parameters of other vehicles as its own target vehicle driving parameters when the rating of the current environmental attributes is not lower than the vehicle environmental attributes sent by the other vehicles; when the rating of the current environmental attributes is lower than the vehicle environmental attributes sent by the other vehicles, the target vehicle driving parameters of the target vehicle are determined according to the current environmental attributes of the target vehicle, the vehicle model, the vehicle driving parameters of the other vehicles, and the vehicle model of the other vehicles. For example, it can be obtained by looking up a table, or it can be realized by pre-training a deep learning model in a deep learning manner. This embodiment connects the energy-saving adjustment methods of each vehicle in series, which can more effectively realize the energy-saving scheduling of the entire vehicle cluster.

[0111] Based on the same inventive concept, the embodiments of the present disclosure also provide a scheduling device and a cloud control platform applied to large-scale unmanned vehicle clusters. Since the principles of the problems solved by these devices and the cloud control platform are similar to the aforementioned scheduling method applied to large-scale unmanned vehicle clusters, the implementation of the device and the cloud control platform can refer to the implementation of the aforementioned method, and the repeated parts will not be repeated.

[0112] The present disclosure provides a scheduling device for a large-scale unmanned vehicle cluster, such as Figure 8 As shown, including:

[0113] The acquisition module 801 is used to obtain the operation status information of the unmanned vehicle cluster scheduled in the preset operation area;

[0114] A congestion determination module 802 is used to determine a first area range where a traffic congestion event occurs when it is determined that a traffic congestion event occurs according to the operating state information;

[0115] The mode switching module 803 is used to determine the second area range based on the first area range, and control the unmanned vehicle traveling in the second area range to switch from the first working mode to the second working mode, wherein under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that in the first working mode.

[0116] In another embodiment of the present disclosure, the mode switching module 803 is used to determine the area category corresponding to the preset operation area; determine the corresponding preset energy-saving strategy according to the area category corresponding to the preset operation area; determine the second area range according to the first area range and the determined preset energy-saving strategy.

[0117] In another embodiment of the present disclosure, the area category corresponding to the preset operation area includes at least one of the following: a local road driving area, a loading and unloading operation area, and a unloading operation area.

[0118] In another embodiment of the present disclosure, when the area category is a local road driving area, the first area range is a road range occupied by a vehicle queue where congestion occurs;

[0119] The mode switching module 803 is used to determine a first starting position of a congestion location according to a road range occupied by the vehicle queue where the congestion occurs; and to determine a second area range according to the first starting position and a first preset energy-saving area range; wherein the first preset energy-saving area range is a predefined area range that takes the traffic congestion location as the starting position and extends upstream by a first preset distance.

[0120] In another embodiment of the present disclosure, when the area category is a collection and loading operation area, the first area range is the collection and loading operation area;

[0121] The mode switching module 803 is used to determine the second area range according to the working status of the collection and loading operation area and the unmanned vehicle outside the collection and loading operation area.

[0122] In another embodiment of the present disclosure, the mode switching module 803 is used to determine the area where the unmanned vehicle is located outside the collection and loading operation area as the second area range.

[0123] In another embodiment of the present disclosure, the loading and unloading operation area includes: all path topologies starting from the most downstream intersection before the divergence on the path from the unloading operation area to the loading area and passing through all loading areas, as well as all loading areas.

[0124] In yet another embodiment of the present disclosure, when the area category is an unloading operation area, the first area range includes the unloading operation area, or an entrance area of ​​the unloading operation area;

[0125] The mode switching module 803 is used to determine the entrance of the unloading operation area as the second starting position of the congestion position; determine the second area range according to the second starting position and the second preset energy-saving area range; wherein the second preset energy-saving area range is a predefined area range with the entrance of the unloading operation area as the starting position and extending upstream by a second preset distance.

[0126] In another embodiment of the present disclosure, when the area category corresponding to the preset operation area is a local road driving area, the operation status information includes: current position information and current vehicle speed information; a congestion determination module 802 is used to determine that a traffic congestion event occurs if there are at least two unmanned vehicles, the vehicle speed is zero and the distance between the two unmanned vehicles is not greater than a preset following distance, according to the current position information and the current vehicle speed information; or,

[0127] In the case where the area category corresponding to the preset operation area is an unloading operation area, the operation status information includes: current vehicle speed information and real-time operation information; a congestion determination module 802 is used to determine that a traffic congestion event occurs based on the current vehicle speed information and real-time operation information if there are at least two unmanned vehicles in the unloading operation area, the vehicle speed is zero, and no unloading operation is currently being performed; or,

[0128] When the area category corresponding to the preset operation area is the mining and loading operation area, the operating status information includes the current load information; the congestion determination module 802 is used to determine the first number of empty-loaded unmanned vehicles located in the mining and loading operation area according to the current load information; when the first number is greater than or equal to the preset saturation value, it is determined that a traffic congestion event has occurred; and / or according to the current load information, determine the second number of empty-loaded unmanned vehicles on average for a single excavator located in the mining and loading operation area; when the second number is greater than or equal to the preset saturation value of the excavator, it is determined that a traffic congestion event has occurred.

[0129] In another embodiment of the present disclosure, the mode switching module 803 is also used to mark the map area corresponding to the second area range on the map; and send the marked map to the unmanned vehicle, so that the unmanned vehicle determines the working mode to be adopted according to the marked map and its own position, and the working mode includes the first working mode or the second working mode.

[0130] A cloud control platform provided by an embodiment of the present disclosure includes: a scheduling device applied to a large-scale unmanned vehicle cluster as described in any of the above embodiments.

[0131] Through the description of the above implementation methods, those skilled in the art can clearly understand that the embodiments of the present disclosure can be implemented by hardware, or by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.

[0132] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes in the accompanying drawings are not necessarily required for implementing the present disclosure.

[0133] Those skilled in the art can understand that the modules in the device in the embodiment can be distributed in the device in the embodiment according to the description of the embodiment, or can be changed accordingly and located in one or more devices different from the present embodiment. The modules in the above embodiment can be combined into one module, or can be further divided into multiple sub-modules.

[0134] The serial numbers of the above-mentioned embodiments of the present disclosure are only for description and do not represent the advantages or disadvantages of the embodiments.

[0135] Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A scheduling method for large-scale unmanned vehicle clusters, characterized in that: include: Obtain the operating status information of the unmanned vehicle cluster dispatched in the preset operation area; In the case where a traffic congestion event is determined to have occurred according to the operating status information, determining a first area range where the traffic congestion event has occurred; A second area range is determined based on the first area range, and an unmanned vehicle traveling in the second area range is controlled to switch from a first working mode to a second working mode, wherein under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that in the first working mode.

2. The method according to claim 1, characterized in that The determining the second area range according to the first area range includes: Determine the area category corresponding to the preset operation area; Determining a corresponding preset energy-saving strategy according to the area category corresponding to the preset operation area; A second area range is determined according to the first area range and the determined preset energy-saving strategy.

3. The method according to claim 2, characterized in that The area category corresponding to the preset operation area includes at least one of the following: a local road driving area, a loading and unloading operation area, and a unloading operation area.

4. The method according to claim 2 or 3, characterized in that When the area category is a local road driving area, the first area range is the road range occupied by the vehicle queue where congestion occurs; The determining the second area range according to the first area range includes: Determining a first starting position of a congestion location according to a road range occupied by the congested vehicle queue; Determine a second area range according to the first starting position and a first preset energy-saving area range; The first preset energy-saving area range is a predefined area range starting from the traffic congestion location and extending upstream by a first preset distance.

5. The method according to claim 2 or 3, characterized in that: When the area category is a collection and loading operation area, the first area range is the collection and loading operation area; The determining the second area range according to the first area range includes: The scope of the second area is determined according to the working status of the collection and loading operation area and the unmanned vehicle outside the collection and loading operation area.

6. The method according to claim 5, characterized in that The determining of the second area range according to the working status of the collection and loading operation area and the unmanned vehicle outside the collection and loading operation area includes: The area where the unmanned unmanned vehicle is located outside the collection and loading operation area is determined as the second area range.

7. The method according to claim 5, characterized in that The loading and unloading operation area includes: all path topologies starting from the most downstream intersection before the divergence on the path from the unloading operation area to the loading area and passing through all loading areas, as well as all loading areas.

8. The method according to claim 2 or 3, characterized in that: In the case where the area category is an unloading operation area, the first area range includes the unloading operation area, or an entrance area of ​​the unloading operation area; The determining the second area range according to the first area range includes: Determine the entrance of the unloading operation area as the second starting position of the congestion position; Determine a second area range according to the second starting position and a second preset energy-saving area range; The second preset energy-saving area range is a predefined area range that takes the entrance of the unloading operation area as the starting position and extends upstream by a second preset distance.

9. The method according to claim 1, characterized in that In the case where the area category corresponding to the preset operation area is a local road driving area, the operation status information includes: current position information and current vehicle speed information; the determining that a traffic congestion event occurs according to the operation status information includes: according to the current position information and the current vehicle speed information, if there are at least two unmanned vehicles, the vehicle speed is zero and the distance between the two unmanned vehicles is not greater than a preset following distance, then determining that a traffic congestion event occurs; or, In the case where the area category corresponding to the preset operation area is an unloading operation area, the operation status information includes: current vehicle speed information and real-time operation information; determining the occurrence of a traffic congestion event based on the operation status information includes: determining the occurrence of a traffic congestion event based on the current vehicle speed information and the real-time operation information if there are at least two unmanned vehicles in the unloading operation area, the vehicle speed is zero and no unloading operation is currently being performed; or When the area category corresponding to the preset operation area is the mining and loading operation area, the operating status information includes current load information; determining the occurrence of a traffic congestion event based on the operating status information includes: determining a first number of empty-loaded unmanned vehicles located in the mining and loading operation area based on the current load information; when the first number is greater than or equal to a preset saturation value, determining the occurrence of a traffic congestion event; and / or determining a second number of empty-loaded unmanned vehicles per excavator located in the mining and loading operation area on average based on the current load information; when the second number is greater than or equal to the preset saturation value of the excavator, determining the occurrence of a traffic congestion event.

10. The method according to claim 1, characterized in that Also includes: Marking a map area corresponding to the second area range on a map; and The marked map is sent to the unmanned vehicle so that the unmanned vehicle determines the working mode to be adopted according to the marked map and its own position, and the working mode includes the first working mode or the second working mode.

11. A dispatching device for large-scale unmanned vehicle clusters, characterized in that: include: An acquisition module is used to obtain the operating status information of the unmanned vehicle cluster scheduled in the preset operation area; A congestion determination module, configured to determine a first area range where a traffic congestion event occurs when it is determined that a traffic congestion event occurs according to the operating state information; A mode switching module is used to determine a second area range based on the first area range, and control the unmanned vehicle traveling in the second area range to switch from a first working mode to a second working mode, wherein under the same working conditions, the energy consumption of the unmanned vehicle in the second working mode is lower than that in the first working mode.

12. A cloud control platform, characterized in that: include: A dispatching device for large-scale unmanned vehicle clusters as described in claim 11.

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