Unmanned roadway wrong vehicle scheduling method, system and equipment based on vehicle and road cloud

Abstract

The invention provides an unmanned roadway wrong vehicle scheduling method, system and device based on vehicle and road cloud, and belongs to the technical field of unmanned wrong vehicle scheduling. The method comprises the steps that a target vehicle scheduling target is determined, and an expected track is generated according to the scheduling target; determining a drivable first road section on the expected track by using the first stop line; if the first road section is idle, receiving a first passing command, and driving the target vehicle to a first position; if the distance between the first position and the first stop line is smaller than the preset distance, determining a travelable second road section according to the first stop line and the second stop line; if the second road section is not idle, whether a wrong vehicle chamber is bound in the first stop line or not is judged, and if yes, the vehicle enters the wrong vehicle chamber to give way to the wrong vehicle; and driving out of the wrong car chamber until the second road section is idle and continuously driving. Based on the method, the invention further provides an unmanned roadway wrong vehicle dispatching system and equipment. According to the invention, accurate scheduling and mistaking of the unmanned vehicle in the roadway are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned driving lane passing scheduling, and in particular relates to an unmanned driving lane passing scheduling method, system and equipment based on vehicle-road cloud. Background Art

[0002] Unmanned driving in mining areas has become a new trend in the development of smart mines, but the application of unmanned driving technology is currently mainly concentrated in open-pit mining scenarios. In underground mining scenarios, due to the particularity of the environment, dim light, poor network coverage, and the limitations of lanes, most of which are single lanes, there are many problems when multiple unmanned vehicles are carrying out transportation operations. Among them, when multiple unmanned mining trucks are working together, because the lanes are single lanes and the lanes are relatively narrow, when unmanned mining trucks are traveling towards each other, they cannot pull over to avoid, or even if they can pull over to avoid, the other mining truck cannot pass smoothly, and it is even more impossible to turn around in the narrow lanes, which is likely to cause traffic conflicts and seriously affect the safety of mining operations.

[0003] In the traditional underground mining transportation system, vehicle transportation scheduling mainly relies on manual operation or semi-automatic scheduling system. The manual scheduling method requires the dispatcher to manually adjust the vehicle staggering arrangement according to the real-time situation underground. The semi-automatic system performs simple time scheduling and intersection management through pre-set rules.

[0004] Therefore, the prior art relies on manual operation for the missed vehicle scheduling scheme. The dispatcher needs to monitor the underground vehicle flow and driving conditions in real time, and then manually schedule. This not only increases the work pressure of the dispatcher, but also easily leads to untimely scheduling due to human misjudgment, congestion and even safety accidents. With the increase in underground transportation tasks, the efficiency of manual scheduling is obviously insufficient, and delays, errors and omissions are prone to occur. The rules of the semi-automatic scheduling system are usually fixed and difficult to flexibly adjust according to actual traffic conditions. When encountering emergencies such as vehicle failures or road obstructions, it is impossible to quickly re-plan the missed vehicle arrangements. Therefore, in the existing rule-based scheduling mode, it is impossible to fully utilize all available lanes and vehicle resources, which is easy to cause local congestion or idle transportation resources. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes an unmanned driving lane passing scheduling method, system and equipment based on vehicle-road-cloud. Through the collaboration of vehicle-road-cloud, accurate scheduling and passing of unmanned vehicles in the lane are realized.

[0006] To achieve the above object, the present invention adopts the following technical solutions: The unmanned driving lane passing scheduling method based on vehicle-road-cloud includes the following steps: Collect the map required for dispatching and the environmental information of the lane where the target vehicle is located, and determine the dispatching target and the location of the target vehicle; Receive a dispatch task signal, generate an expected trajectory according to a dispatch map and a dispatch target; determine a first drivable road section on the expected trajectory using a first stop line; if the first road section is idle, receive a first pass command, and the target vehicle drives to a first position; If the distance between the first position and the first stop line is less than the preset distance, the second drivable section on the expected trajectory is determined according to the first stop line and the second stop line; if at least one of the second sections is occupied or locked, it is determined whether the first stop line is bound to a passing chamber, and if it is bound to a passing chamber, the target vehicle enters the passing chamber and gives way to the other vehicle; the target vehicle continues to travel until the second sections are all idle and the passing chamber is entered.

[0007] Further, the process of determining the first drivable road section on the expected trajectory by using the first stop line on the expected trajectory includes: If the first stop line is found along the expected trajectory from the current position of the target vehicle, all sections between the current position and the first stop line are marked as the first section; If the first stop line is not found along the expected trajectory from the current position of the target vehicle, all sections on the expected trajectory are marked as first sections.

[0008] Furthermore, the process of receiving the first pass command and the target vehicle driving to the first position includes: The target vehicle occupies all the first road sections and locks the opposite conflicting lane of the first road section at the same time, receives the first passing command, and the target vehicle drives to the first position.

[0009] Further, the determining that if the distance between the first position and the first stop line is less than a preset distance, determining the second drivable section on the desired trajectory according to the first stop line and the second stop line specifically includes: Along the expected trajectory, if a second stop line is found after the first stop line, mark all sections between the first stop line and the second stop line as the second section; If the second stop line after the first stop line is not found along the expected trajectory, the last section from the first stop line to the expected trajectory is marked as the second section.

[0010] Furthermore, the method also includes: when the second road section is idle, releasing the occupation relationship of the first road section and releasing the locking relationship of the opposite conflicting lanes.

[0011] Furthermore, if a passing chamber is bound, the specific steps for entering the passing chamber and giving way to passing vehicles are as follows: After receiving the command to pass the other vehicle, the target vehicle occupies all sections of the passing chamber, and then performs local path planning according to the map required for scheduling, and enters the passing chamber to pass the other vehicle.

[0012] Furthermore, the method also includes: when the target vehicle is located in the passing chamber, after the oncoming vehicle passes, receiving a command from the oncoming vehicle to release the lock on the second road section, at which time the second road section is idle and the target vehicle drives out of the passing chamber.

[0013] Furthermore, the method also includes locking the opposite conflicting lane of the second section of road after the target vehicle enters the missed vehicle chamber, receiving a second pass command, crossing the first stop line and continuing to drive, and executing missed vehicle dispatching through the second stop line.

[0014] The present invention also proposes an unmanned laneway vehicle passing dispatching system based on vehicle-road cloud, comprising: a collection module, a first dispatching module and a second dispatching module; The acquisition module is used to acquire the map required for dispatching and the environmental information of the lane where the target vehicle is located, and to determine the dispatching target of the target vehicle and the position of the target vehicle; The first dispatch module is used to receive a dispatch task signal, generate an expected trajectory according to a dispatch required map and a dispatch target; determine a first drivable road section on the expected trajectory using a first stop line; if the first road section is idle, receive a first pass command, and the target vehicle drives to a first position; The second scheduling module is used to determine a second drivable section on the expected trajectory based on the first stop line and the second stop line if the distance between the first position and the first stop line is less than a preset distance; if at least one of the second sections is occupied or locked, determine whether a passing chamber is bound within the first stop line; if a passing chamber is bound, drive into the passing chamber and give way to the passing vehicle; until the second sections are all idle and the target vehicle drives out of the passing chamber, the target vehicle continues to drive.

[0015] The present invention also proposes an unmanned driving lane passing scheduling device based on vehicle-road-cloud, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor can implement the unmanned driving lane passing scheduling method based on vehicle-road-cloud when executing the program.

[0016] The effects provided in the content of the invention are only the effects of the embodiments, not all the effects of the invention. One of the above technical solutions has the following advantages or beneficial effects: The present invention proposes an unmanned lane passing scheduling method, system and equipment based on vehicle-road cloud, which belongs to the technical field of unmanned lane passing scheduling. The method comprises the following steps: collecting a map required for scheduling and environmental information of the lane where a target vehicle is located, and determining a scheduling target of the target vehicle and a position of the target vehicle; receiving a scheduling task signal, and generating an expected trajectory according to the map required for scheduling and the scheduling target; determining a first road section that can be driven on the expected trajectory using a first stop line on the expected trajectory; if the first road section is idle, receiving a first pass command, and the target vehicle drives to a first position; if the distance between the first position and the first stop line is less than a preset distance, determining a second road section that can be driven on the expected trajectory according to the first stop line and the second stop line; if at least one of the second road sections is occupied or locked, determining whether a passing chamber is bound within the first stop line, and if a passing chamber is bound, driving into the passing chamber to give way to the passing vehicle; until the second road sections are idle and the passing chamber is driven into, the target vehicle continues to drive. An unmanned lane passing dispatching method based on vehicle-road-cloud is also proposed, and an unmanned lane passing dispatching system and equipment based on vehicle-road-cloud are also proposed. The present invention uses high-precision maps as road data sources through both vehicle-road-cloud and vehicle-road-cloud, and realizes accurate dispatching and passing of unmanned vehicles in lanes through the collaborative work between vehicles, roadsides and the cloud. Compared with traditional manual dispatching methods, the present invention can greatly improve the efficiency and accuracy of dispatching, reduce dispatching errors and conflicts caused by human factors, and does not require manual intervention, greatly reducing the workload of dispatchers.

[0017] Through global optimization scheduling in the cloud, the system can reasonably allocate tunnel resources, reduce the waiting time of vehicles, and flexibly adjust the operation route and operation time of vehicles according to actual production needs, thereby optimizing resource utilization. This can not only improve the production efficiency of mines, but also reduce unnecessary energy consumption and emissions, which is in line with the development trend of green mines and improves overall transportation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of the unmanned lane passing scheduling method based on vehicle-road cloud proposed in Example 1 of the present invention; Figure 2 A schematic diagram of a map for passing other vehicles proposed in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of an unmanned lane passing scheduling system based on vehicle-road cloud proposed in Example 2 of the present invention; Figure 4 This is a schematic diagram of the unmanned lane passing scheduling equipment based on vehicle-road cloud proposed in Example 3 of the present invention. DETAILED DESCRIPTION

[0019] In order to clearly illustrate the technical features of the present solution, the present invention is described in detail below through specific implementation methods and in conjunction with the accompanying drawings. The disclosure below provides many different embodiments or examples for realizing different structures of the present invention. In order to simplify the disclosure of the present invention, the components and settings of specific examples are described below. In addition, the present invention may repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed. It should be noted that the components illustrated in the accompanying drawings are not necessarily drawn to scale. The present invention omits the description of known components and processing techniques and processes to avoid unnecessary limitations on the present invention.

[0020] Example 1 Embodiment 1 of the present invention proposes an unmanned lane passing scheduling method based on vehicle-road cloud, which is used to solve the technical problems existing in the prior art of passing scheduling.

[0021] The present invention coordinates and dispatches multiple vehicles on a cloud platform, with roadside equipment as a supplement and the vehicles as the execution; in underground mines, the cloud platform's vehicle-passing dispatching algorithm is utilized, with the assistance of roadside equipment to realize accurate dispatch and vehicle-passing of unmanned vehicles in lanes.

[0022] The process of executing the unmanned driving lane passing scheduling method based on vehicle-road cloud proposed in Example 1 of the present invention includes: Collect the map required for dispatching and the environmental information of the lane where the target vehicle is located, and determine the dispatching target and the location of the target vehicle; Receive a dispatch task signal, generate an expected trajectory according to a dispatch map and a dispatch target; determine a first drivable road section on the expected trajectory using a first stop line; if the first road section is idle, receive a first pass command, and the target vehicle drives to a first position; If the distance between the first position and the first stop line is less than the preset distance, the second drivable section on the expected trajectory is determined according to the first stop line and the second stop line; if at least one of the second sections is occupied or locked, it is determined whether the first stop line is bound to a passing chamber, and if it is bound to a passing chamber, the target vehicle enters the passing chamber and gives way to the other vehicle; the target vehicle continues to travel until the second sections are all idle and the passing chamber is entered.

[0023] Figure 1 A flow chart of the unmanned lane passing scheduling method based on vehicle-road cloud proposed in Example 1 of the present invention; In step S100, the process starts.

[0024] Collect the map required for dispatching and the environmental information of the lane where the target vehicle is located, and determine the dispatching target and the location of the target vehicle.

[0025] High-precision map information is read and imported through SDK, and stored synchronously in the database and cache. The main information used includes high-precision map section information, high-precision map section connection relationship, high-precision map POI point information, high-precision map stop line information, etc.

[0026] In this application, the target vehicle is an unmanned mining truck. The scope of protection of the present invention is not limited to unmanned mining trucks.

[0027] After the unmanned mining truck is started, it connects to the cloud control platform through TCP and performs authentication and status data upload according to the specified communication protocol. After receiving the status data, the cloud control platform continuously determines whether the unmanned mining truck is in a ready state. When the unmanned mining truck is in a ready state, the cloud control platform finds the corresponding loading point according to the vehicle's marshaling, and uses this loading point as the scheduling target of the unmanned mining truck.

[0028] Roadside equipment obtains the actual situation in the tunnel in real time through communication base stations, radars, cameras and other equipment deployed in the tunnel, and obtains the location and status information of unmanned mining trucks in real time through V2X.

[0029] In step S101, a scheduling task signal is received, and an expected trajectory [lane1, ..., laneN] is generated according to the map required for scheduling and the scheduling target. After the expected trajectory [lane1, ..., laneN] is obtained, starting from the current position of the unmanned mining truck, the first stop line M1 is found along the expected trajectory.

[0030] Figure 2 This is a map diagram for passing vehicles proposed in Example 1 of the present invention. The first stop line is used on the expected trajectory to determine the first drivable section on the expected trajectory. The specific process includes: if the first stop line M1 is found along the expected trajectory from the current position of the unmanned mining truck, all sections between the current position and the first stop line M1 are marked as the first section A; if the first stop line M1 is not found along the expected trajectory from the current position of the unmanned mining truck, all sections on the expected trajectory are marked as the first section A. In this application, the first section set is the first section list A[A1,...,An].

[0031] In step S102, it is determined whether all the first sections A are free, that is, whether any of the first sections from A1 to An is occupied or locked by other mining trucks. If at least one of the first sections is occupied or locked, a loop determination is performed. If all the sections of the first section A are not occupied or locked, step S103 is performed.

[0032] In step S103, the unmanned mining truck occupies all sections of the first section A, locks the opposite conflicting lane of the first section A, and issues a first pass command. After receiving the first pass command, the unmanned mining truck starts to travel. The unmanned mining truck travels to the first position.

[0033] In step S104, it is determined whether the distance S between the unmanned mining truck at the first position and the first stop line M1 is less than a preset distance. In this application, the preset distance is set to 30 meters. The scope of protection of this application is not limited to the values ​​listed in Example 1. Personnel in this field can make reasonable settings according to actual conditions. If the distance S is greater than 30 meters, step S104 is executed repeatedly. If the distance S is less than or equal to 30 meters, step S105 is executed.

[0034] In step S105, a second drivable section on the desired trajectory is determined according to the first stop line and the second stop line. The specific process is: along the desired trajectory, if a second stop line M2 is found after the first stop line M1, all sections between the first stop line M1 and the second stop line M2 are marked as second sections B; If the second stop line M2 after the first stop line M1 is not found along the expected trajectory, the last section lane N from the first stop line M1 to the expected trajectory is marked as the second section B. In this application, the second section set is the first section list B[B1, ..., Bn].

[0035] Determine whether all the second sections B are free, that is, whether any of the second sections from B1 to Bn is occupied or locked by other mining trucks. If all the sections of the second section B are not occupied or locked, execute step S112. If at least one section of the second section B is occupied or locked, execute step S106.

[0036] In step S106, it is determined whether the first stop line M1 is bound to the entry section of the passing chamber. If it is bound to the entry section of the passing chamber, step S107 is executed, otherwise, it returns to step S105.

[0037] In step S107, the passing chamber is occupied and a passing entry command is received.

[0038] At this time, a command to pass the vehicle is issued to the unmanned mining truck, and the unmanned mining truck occupies all sections of the passing vehicle chamber.

[0039] In step S108, the unmanned mining truck enters the passing chamber and gives way to other vehicles.

[0040] After receiving the command to pass the vehicle, the unmanned mining truck plans the local path according to the high-precision map and drives into the passing chamber to pass the vehicle.

[0041] In step S109, it is determined again whether all sections of the second section B are idle. If at least one section of the second section B is occupied or locked, step S109 is executed in a loop. If all sections of the second section B are not occupied or locked, step S110 is executed.

[0042] In step S110, a vehicle-missing output instruction is received.

[0043] When the target vehicle is located in the passing chamber, after the oncoming vehicle passes, it receives a command from the oncoming vehicle to release the lock on the second road section B. At this time, the second road section B is idle, and the target vehicle drives out of the passing chamber.

[0044] In step S111, the unmanned mining truck enters the wrong chamber.

[0045] In step S112, the occupation relationship of all sections of the first section A in step S103 is canceled, the locking relationship of the opposite lane is canceled, all sections of the second section B are occupied, the opposite conflicting lanes of all sections of the second section B are locked, and a pass command is issued at the same time. After receiving the pass command, the unmanned mining truck will not stop when it reaches the first stop line M1 and continue to drive. At this time, the second stop line M2 is used to continue driving.

[0046] In underground mining environments, due to factors such as narrow tunnels and insufficient light, drivers have greater difficulty in operation and potential safety hazards. The present invention, through unmanned driving technology, can significantly reduce the safety risks brought by human operation. At the same time, through vehicle-road-cloud collaboration, the system can monitor vehicles and obstacles in the tunnel in real time, and provide early warning and obstacle avoidance, thereby further enhancing safety.

[0047] The vehicle-road-cloud-based unmanned laneway passing scheduling method proposed in Example 1 of the present invention uses high-precision maps as road data sources through both the vehicle-road-cloud and the vehicle, roadside and cloud to achieve accurate scheduling and passing of unmanned vehicles in lanes through the collaborative work between vehicles, roadsides and the cloud. Compared with the traditional manual scheduling method, the present invention can greatly improve the efficiency and accuracy of scheduling, reduce scheduling errors and conflicts caused by human factors, and does not require manual intervention, greatly reducing the workload of dispatchers.

[0048] The vehicle-road-cloud-based unmanned laneway scheduling method proposed in Example 1 of the present invention can reasonably allocate laneway resources and reduce the waiting time of vehicles through global optimization scheduling on the cloud. It can flexibly adjust the vehicle's operation route and operation time according to actual production needs, thereby optimizing resource utilization. This can not only improve the production efficiency of mines, but also reduce unnecessary energy consumption and emissions, which is in line with the development trend of green mines and improves overall transportation efficiency.

[0049] Example 2 Based on the vehicle-road-cloud-based unmanned driving lane passing scheduling method proposed in Example 1 of the present invention, Example 2 of the present invention further proposes an unmanned driving lane passing scheduling system based on vehicle-road-cloud. Figure 3 This is a schematic diagram of an unmanned laneway vehicle passing scheduling system based on vehicle-road cloud proposed in Example 2 of the present invention, the system comprising: a collection module, a first scheduling module and a second scheduling module; The acquisition module is used to collect the map required for dispatching and the environmental information of the lane where the target vehicle is located, as well as to determine the dispatching target of the target vehicle and the location of the target vehicle; The first dispatch module is used to receive a dispatch task signal, generate an expected trajectory according to the map required for dispatch and the dispatch target; determine the first drivable road section on the expected trajectory using the first stop line; if the first road section is idle, receive a first pass command, and the target vehicle drives to the first position; The second scheduling module is used to determine a second drivable section on the expected trajectory based on the first stop line and the second stop line if the distance between the first position and the first stop line is less than a preset distance; if at least one of the second sections is occupied or locked, determine whether a passing chamber is bound within the first stop line; if so, drive into the passing chamber to give way to the passing vehicle; and continue to drive until the second sections are all idle and the passing chamber is driven out.

[0050] In the first scheduling module: the process of using the first stop line on the expected trajectory to determine the first drivable section on the expected trajectory includes: if the first stop line is found along the expected trajectory from the current position of the target vehicle, all sections between the current position and the first stop line are marked as the first section; if the first stop line is not found along the expected trajectory from the current position of the target vehicle, all sections on the expected trajectory are marked as the first section.

[0051] The process of receiving the first pass command and the target vehicle driving to the first position includes: the target vehicle occupies all the first road sections and locks the opposite conflicting lanes of the first road sections, and receives the first pass command and the target vehicle drives to the first position.

[0052] In the second scheduling module: if the distance between the first position and the first stop line is less than the preset distance, determining the second drivable section on the expected trajectory based on the first stop line and the second stop line specifically includes: along the expected trajectory, if the second stop line after the first stop line is found, marking all sections between the first stop line and the second stop line as the second section; along the expected trajectory, if the second stop line after the first stop line is not found, marking the last section from the first stop line to the expected trajectory as the second section.

[0053] When the second road section is idle, the occupation relationship of the first road section is released, and the locking relationship of the opposite conflicting lanes is released.

[0054] If a passing chamber is bound, then enter the passing chamber and give way to other vehicles. The specific steps are as follows: receive the passing entry command, the target vehicle occupies all sections of the passing chamber, and then perform local path planning according to the map required for scheduling, and enter the passing chamber to give way to other vehicles.

[0055] When the target vehicle is located in the passing chamber, after the oncoming vehicle passes, the target vehicle receives a command from the oncoming vehicle to release the lock on the second road section. At this time, the second road section is idle, and the target vehicle drives out of the passing chamber.

[0056] After the target vehicle enters the missed lane, it locks the opposite conflicting lane of the second section, receives the second passing command, crosses the first stop line and continues to drive, and executes the missed vehicle dispatch through the second stop line.

[0057] The description of the relevant parts of the unmanned driving lane passing scheduling system based on vehicle-road cloud provided in Example 2 of the present application can be found in the detailed description of the corresponding parts of the unmanned driving lane passing scheduling method based on vehicle-road cloud provided in Example 1 of the present application, and will not be repeated here.

[0058] The vehicle-road-cloud-based unmanned laneway passing dispatching system proposed in Example 2 of the present invention uses high-precision maps as road data sources through both the vehicle-road-cloud and the vehicle, roadside and cloud to achieve accurate dispatching and passing of unmanned vehicles in lanes through the collaborative work between vehicles, roadsides and the cloud. Compared with the traditional manual dispatching method, the present invention can greatly improve the efficiency and accuracy of dispatching, reduce dispatching errors and conflicts caused by human factors, and does not require manual intervention, greatly reducing the workload of dispatchers.

[0059] The vehicle-road-cloud-based unmanned laneway scheduling system proposed in Example 2 of the present invention can reasonably allocate laneway resources and reduce the waiting time of vehicles through global optimization scheduling on the cloud. It can flexibly adjust the operation route and operation time of vehicles according to actual production needs, thereby optimizing resource utilization. This can not only improve the production efficiency of mines, but also reduce unnecessary energy consumption and emissions, which is in line with the development trend of green mines and improves overall transportation efficiency.

[0060] Example 3 Embodiment 3 of the present invention also proposes an unmanned laneway vehicle dispatching device based on vehicle-road cloud. Figure 4 A schematic diagram of an unmanned lane passing dispatching device based on a vehicle-road cloud proposed in Embodiment 3 of the present invention includes: Memory for storing computer programs; The processor is used to implement the following method steps when executing the computer program: In step S100, the process starts.

[0061] Collect the map required for dispatching and the environmental information of the lane where the target vehicle is located, and determine the dispatching target and the location of the target vehicle.

[0062] In step S101, a scheduling task signal is received, and an expected trajectory [lane1, ..., laneN] is generated according to the map required for scheduling and the scheduling target. After the expected trajectory [lane1, ..., laneN] is obtained, starting from the current position of the unmanned mining truck, the first stop line M1 is found along the expected trajectory.

[0063] The first stop line is used on the expected trajectory to determine the first drivable road section on the expected trajectory. The specific process includes: if the first stop line M1 is found along the expected trajectory from the current position of the unmanned mining truck, all sections between the current position and the first stop line M1 are marked as the first road section A; if the first stop line M1 is not found along the expected trajectory from the current position of the unmanned mining truck, all sections on the expected trajectory are marked as the first road section A. In this application, the first road section set is the first road section list A[A1,...,An].

[0064] In step S102, it is determined whether all the first sections A are free, and if at least one of the first sections is occupied or locked, a loop determination is performed. If all the sections of the first section A are not occupied or locked, step S103 is performed.

[0065] In step S103, the unmanned mining truck occupies all sections of the first section A, locks the opposite conflicting lane of the first section A, and issues a first pass command. After receiving the first pass command, the unmanned mining truck starts to travel. The unmanned mining truck travels to the first position.

[0066] In step S104, it is determined whether the distance between the unmanned mining truck at the first position and the first stop line M1 is less than a preset distance. If it is greater than the preset distance, step S104 is executed repeatedly; if it is less than or equal to the preset distance, step S105 is executed.

[0067] In step S105, a second drivable section on the desired trajectory is determined according to the first stop line and the second stop line. The specific process is: along the desired trajectory, if a second stop line M2 is found after the first stop line M1, all sections between the first stop line M1 and the second stop line M2 are marked as second sections B; If the second stop line M2 after the first stop line M1 is not found along the expected trajectory, the last section lane N from the first stop line M1 to the expected trajectory is marked as the second section B. In this application, the second section set is the first section list B[B1, ..., Bn].

[0068] Determine whether all the second sections B are free, that is, whether any of the second sections from B1 to Bn is occupied or locked by other mining trucks. If all the sections of the second section B are not occupied or locked, execute step S112. If at least one section of the second section B is occupied or locked, execute step S106.

[0069] In step S106, it is determined whether the first stop line M1 is bound to the entry section of the passing chamber. If it is bound to the entry section of the passing chamber, step S107 is executed, otherwise, it returns to step S105.

[0070] In step S107, the vehicle-passing chamber is occupied and a vehicle-passing entry command is received. At this time, a vehicle-passing entry command is issued to the unmanned mining truck, and the unmanned mining truck occupies all sections of the vehicle-passing chamber.

[0071] In step S108, the unmanned mining truck enters the passing chamber to give way to other vehicles. After receiving the passing command, the unmanned mining truck performs local path planning according to the high-precision map and enters the passing chamber to give way to other vehicles.

[0072] In step S109, it is determined again whether all sections of the second section B are idle. If at least one section of the second section B is occupied or locked, step S109 is executed in a loop. If all sections of the second section B are not occupied or locked, step S110 is executed.

[0073] In step S110, a passing vehicle output command is received. When the target vehicle is in the passing vehicle chamber, after the oncoming vehicle passes, a command is received from the oncoming vehicle to release the lock on the second road section B. At this time, the second road section B is idle, and the target vehicle drives out of the passing vehicle chamber.

[0074] In step S111, the unmanned mining truck enters the wrong chamber.

[0075] In step S112, the occupation relationship of all sections of the first section A in step S103 is canceled, the locking relationship of the opposite lane is canceled, all sections of the second section B are occupied, the opposite conflicting lanes of all sections of the second section B are locked, and a pass command is issued at the same time. After receiving the pass command, the unmanned mining truck will not stop when it reaches the first stop line M1 and continue to drive. At this time, the second stop line M2 is used to continue driving.

[0076] The vehicle-road-cloud-based unmanned laneway passing dispatching device proposed in Example 3 of the present invention uses high-precision maps as road data sources through both the vehicle-road-cloud and the vehicle, roadside and cloud to achieve accurate dispatching and passing of unmanned vehicles in lanes through the collaborative work between vehicles, roadsides and the cloud. Compared with the traditional manual dispatching method, the present invention can greatly improve the efficiency and accuracy of dispatching, reduce dispatching errors and conflicts caused by human factors, and does not require manual intervention, greatly reducing the workload of dispatchers.

[0077] The vehicle-road-cloud-based unmanned laneway vehicle scheduling device proposed in Example 3 of the present invention can reasonably allocate laneway resources and reduce the waiting time of vehicles through global optimization scheduling in the cloud. It can flexibly adjust the vehicle's operation route and operation time according to actual production needs, thereby optimizing resource utilization. This can not only improve the production efficiency of mines, but also reduce unnecessary energy consumption and emissions, which is in line with the development trend of green mines and improves overall transportation efficiency.

[0078] For the description of the relevant parts of the unmanned driving lane passing scheduling device based on vehicle-road cloud provided in Example 3 of the present application, please refer to the detailed description of the corresponding parts of the unmanned driving lane passing scheduling method based on vehicle-road cloud provided in Example 1 of the present application, and will not be repeated here.

[0079] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment that includes a series of elements are inherent to the elements. In the absence of more restrictions, the elements limited by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or equipment that includes the elements. In addition, the above-mentioned technical solution provided in the embodiment of the present application is consistent with the corresponding technical solution in the prior art in principle, and the part is not described in detail, so as not to repeat too much.

[0080] Although the above describes the specific implementation of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. For those skilled in the art, other different forms of modifications or deformations can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. On the basis of the technical solution of the present invention, various modifications or deformations that can be made by those skilled in the art without creative work are still within the scope of protection of the present invention.

Claims

1. The unmanned driving lane passing scheduling method based on vehicle-road cloud is characterized by: The following steps are involved: Collect the map required for dispatching and the environmental information of the lane where the target vehicle is located, and determine the dispatching target and the location of the target vehicle; Receive a dispatch task signal, generate an expected trajectory according to a dispatch map and a dispatch target; determine a first drivable road section on the expected trajectory using a first stop line; if the first road section is idle, receive a first pass command, and the target vehicle drives to a first position; If the distance between the first position and the first stop line is less than a preset distance, determining a second drivable section on the desired trajectory according to the first stop line and the second stop line; If at least one section in the second section is occupied or locked, determine whether the first stop line is bound to a passing chamber. If it is bound to a passing chamber, drive into the passing chamber and give way to other vehicles; until the second sections are all idle and drive out of the passing chamber, the target vehicle continues to drive.

2. The unmanned lane passing scheduling method based on vehicle-road cloud according to claim 1 is characterized in that: The process of determining a first drivable road section on the expected trajectory by using a first stop line on the expected trajectory includes: If the first stop line is found along the expected trajectory from the current position of the target vehicle, all sections between the current position and the first stop line are marked as the first section; If the first stop line is not found along the expected trajectory from the current position of the target vehicle, all sections on the expected trajectory are marked as first sections.

3. The unmanned driving lane passing scheduling method based on vehicle-road cloud according to claim 2 is characterized in that: The process of receiving the first pass command and driving the target vehicle to the first position includes: The target vehicle occupies all the first road sections and locks the opposite conflicting lane of the first road section at the same time, receives the first passing command, and the target vehicle drives to the first position.

4. The unmanned driving lane passing scheduling method based on vehicle-road cloud according to claim 1 is characterized in that: The determining that if the distance between the first position and the first stop line is less than a preset distance, determining the second drivable section on the desired trajectory according to the first stop line and the second stop line specifically includes: Along the expected trajectory, if a second stop line is found after the first stop line, mark all sections between the first stop line and the second stop line as the second section; If the second stop line after the first stop line is not found along the expected trajectory, the last section from the first stop line to the expected trajectory is marked as the second section.

5. The unmanned driving lane passing scheduling method based on vehicle-road cloud according to claim 1 is characterized in that: The method further comprises: when all the second road sections are idle, releasing the occupation relationship of the first road section and releasing the locking relationship of the opposite conflicting lanes.

6. The unmanned driving lane passing scheduling method based on vehicle-road cloud according to claim 1 is characterized in that: If a passing chamber is bound, the specific steps for driving into the passing chamber and giving way to other vehicles are as follows: After receiving the command to pass the other vehicle, the target vehicle occupies all sections of the passing chamber, and then performs local path planning according to the map required for scheduling, and enters the passing chamber to pass the other vehicle.

7. The unmanned laneway vehicle passing scheduling method based on vehicle-road cloud according to claim 1 is characterized in that: The method further includes: when the target vehicle is located in the passing chamber, after the oncoming vehicle passes, receiving a command from the oncoming vehicle to release the lock on the second road section, at which time the second road section is idle and the target vehicle drives out of the passing chamber.

8. The unmanned driving lane passing scheduling method based on vehicle-road cloud according to claim 7 is characterized in that: The method also includes, after the target vehicle exits the missed lane chamber, locking the opposite conflicting lane of the second road section, receiving a second passing command, crossing the first stop line and continuing to drive, and executing missed vehicle dispatching through the second stop line.

9. An unmanned driving lane passing scheduling system based on vehicle-road cloud, used to execute the unmanned driving lane passing scheduling method based on vehicle-road cloud as claimed in any one of claims 1 to 8, characterized in that: include: It includes a collection module, a first scheduling module and a second scheduling module; The acquisition module is used to acquire the map required for dispatching and the environmental information of the lane where the target vehicle is located, and to determine the dispatching target of the target vehicle and the position of the target vehicle; The first dispatch module is used to receive a dispatch task signal, generate an expected trajectory according to a dispatch required map and a dispatch target; determine a first drivable road section on the expected trajectory using a first stop line; if the first road section is idle, receive a first pass command, and the target vehicle drives to a first position; The second scheduling module is used to determine a second drivable section on the desired trajectory according to the first stop line and the second stop line if the distance between the first position and the first stop line is less than a preset distance; If at least one section in the second section is occupied or locked, determine whether the first stop line is bound to a passing chamber. If it is bound to a passing chamber, drive into the passing chamber and give way to other vehicles; until the second sections are all idle and drive out of the passing chamber, the target vehicle continues to drive.

10. The unmanned laneway vehicle dispatching equipment based on vehicle-road cloud is characterized by: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it can implement the vehicle-road-cloud-based unmanned driving lane passing scheduling method as described in any one of claims 1 to 8.

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