Vehicle meeting scheduling method and device applied to two-way bicycle road network and electronic equipment

Abstract

The invention discloses a meeting scheduling method and device applied to a two-way bicycle road network and electronic equipment. The method comprises the steps of determining a target network flow model of a target area in response to a meeting scheduling request event; according to the target network flow model, analyzing a preset driving path and vehicle driving information of at least one to-be-processed vehicle in the target area, and determining at least one to-be-processed scheduling information; performing simulation scheduling processing on the at least one to-be-processed vehicle according to the target network flow model so as to determine vehicle prediction trajectory information and vehicle waiting total duration corresponding to the at least one to-be-processed vehicle under each kind of to-be-processed scheduling information; and determining target scheduling information according to the vehicle prediction trajectory information and the vehicle waiting total time length of each kind of scheduling information to be processed, and performing vehicle meeting scheduling processing on at least one vehicle to be processed based on the target scheduling information, thereby realizing global vehicle meeting scheduling processing of all vehicles in the target area, and ensuring the overall passing efficiency of the target area.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, and electronic device for scheduling passing vehicles on a two-way single-vehicle road network. Background Technology

[0002] In transportation scenarios, environments with multiple two-way single-lane roads are common, and these environments can be called two-way single-vehicle road networks. A two-way single-lane road network consists of only one lane, allowing vehicles to travel alternately in both directions. For example, in mining operations, due to the unique underground working environment or the actual needs of production and transportation, two-way single-vehicle road networks are often present. In two-way single-vehicle road networks, vehicle scheduling is typically required to avoid conflicts between vehicles traveling in both directions.

[0003] Currently, traditional methods of traffic meeting scheduling mainly rely on drivers' experience and judgment. However, these methods suffer from problems such as judgment errors and low efficiency. Furthermore, relying on human experience cannot meet the needs of global traffic meeting scheduling in a given area, easily leading to new traffic conflicts or congestion, which is detrimental to the overall traffic efficiency of the area. Summary of the Invention

[0004] This invention provides a method, device, and electronic equipment for traffic scheduling in a two-way single-vehicle road network, which realizes global traffic scheduling for all vehicles in the target area and ensures the overall traffic efficiency of the area.

[0005] According to one aspect of the present invention, a method for scheduling passing vehicles in a two-way single-vehicle road network is provided, the method comprising:

[0006] In response to a vehicle meeting scheduling request event, a target network flow model corresponding to a target area is determined; wherein, the target network flow model includes: multiple nodes, reverse directed edge pairs associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the reverse directed edge pairs, the nodes correspond to the vehicle meeting scheduling area of ​​the target area, the reverse directed edge pairs correspond to the two-way single lanes of the target area, the node attribute information changes with the area usage information of the vehicle meeting scheduling area, and the edge attribute information changes with the road usage information of the two-way single lanes;

[0007] Based on the target network flow model, the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of scheduling information to be processed; wherein, the vehicle driving information includes at least: the driving position information, driving speed information, driving direction information and driving sequence information of the vehicle to be processed in the two-way single lane, and each type of scheduling information to be processed includes scheduling sub-information corresponding to the at least one vehicle to be processed.

[0008] For the at least one pending scheduling information, simulated scheduling processing is performed on the at least one pending vehicle according to the target network flow model to determine the vehicle prediction trajectory information and the total vehicle waiting time corresponding to the at least one pending vehicle under each pending scheduling information.

[0009] Based on the vehicle prediction trajectory information corresponding to each type of pending scheduling information and the total waiting time of the vehicles corresponding to the vehicle prediction trajectory information, target scheduling information is determined, so as to perform meeting scheduling processing on the at least one pending vehicle based on the target scheduling information.

[0010] According to another aspect of the present invention, a vehicle passing scheduling device for a two-way single-vehicle road network is provided, the device comprising:

[0011] A network flow model determination module is used to determine a target network flow model corresponding to a target area in response to a vehicle meeting scheduling request event. The target network flow model includes: multiple nodes, pairs of reverse directed edges associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the pairs of reverse directed edges. The nodes correspond to the vehicle meeting scheduling area of ​​the target area, the pairs of reverse directed edges correspond to the two-way single lanes of the target area, the node attribute information changes with the area usage information of the vehicle meeting scheduling area, and the edge attribute information changes with the road usage information of the two-way single lanes.

[0012] The scheduling information determination module is used to analyze the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area based on the target network flow model, and determine at least one scheduling information to be processed; wherein, the vehicle driving information includes at least: the driving position information, driving speed information, driving direction information and driving sequence information of the vehicle to be processed in the two-way single lane, and each type of scheduling information to be processed includes scheduling sub-information corresponding to the at least one vehicle to be processed.

[0013] The vehicle simulation scheduling module is used to simulate scheduling the at least one vehicle to be processed according to the target network flow model for the at least one scheduling information to be processed, so as to determine the vehicle prediction trajectory information and the total vehicle waiting time corresponding to the at least one vehicle to be processed under each scheduling information to be processed.

[0014] The vehicle meeting scheduling module is used to determine target scheduling information based on the vehicle prediction trajectory information corresponding to each type of scheduling information to be processed and the total waiting time of the vehicles corresponding to the vehicle prediction trajectory information, so as to perform vehicle meeting scheduling processing on the at least one vehicle to be processed based on the target scheduling information.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory that is communicatively connected to at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to execute the meeting scheduling method for a two-way single-vehicle road network according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement a meeting scheduling method for a two-way single-vehicle road network according to any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer program product is provided, comprising a computer program, characterized in that, when executed by a processor, the computer program implements a vehicle passing scheduling method for a two-way single-vehicle road network as described in any embodiment of the present invention.

[0021] The technical solution of this invention, in response to a meeting dispatch request event, determines a target network flow model corresponding to the target area, ensuring that the target network flow model is completely consistent with the actual road network state of the target area, providing accurate data support for subsequent dispatch decisions. Based on the target network flow model, the preset travel paths and vehicle travel information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of dispatch information to be processed. For each type of dispatch information to be processed, a dispatch simulation is performed on the at least one vehicle to be processed according to the target network flow model to determine the predicted vehicle trajectory information and the total waiting time corresponding to the predicted vehicle trajectory information for each type of dispatch information in the target area. Based on the predicted vehicle trajectory information and the total waiting time corresponding to each type of dispatch information to be processed, target dispatch information is determined, and meeting dispatch processing is performed on at least one vehicle to be processed according to the target dispatch information. This invention solves the problems of judgment errors, low dispatch efficiency, and inability to meet the global meeting dispatch requirements of the area caused by prior art relying on driver experience for meeting dispatch, achieving global meeting dispatch processing for all vehicles in the target area and ensuring the overall traffic efficiency of the target area.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of a meeting scheduling method applied to a two-way single-vehicle road network provided by an embodiment of the present invention;

[0025] Figure 2 This is a flowchart of a meeting scheduling method applied to a two-way single-vehicle road network provided by an embodiment of the present invention;

[0026] Figure 3 This is a schematic diagram of a vehicle passing scheduling device applied to a two-way single-vehicle road network provided by an embodiment of the present invention;

[0027] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the vehicle meeting scheduling method for a two-way single-vehicle road network according to an embodiment of the present invention. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] Before introducing the technical solutions provided by the embodiments of the present invention, the application scenarios corresponding to the embodiments of the present invention can be described first. The embodiments of the present invention can be applied to any scenario that requires the scheduling of vehicles meeting in a two-way single-vehicle road network. Optionally, the embodiments of the present invention can be applied to a two-way single-vehicle road network in an underground mining transportation scenario. The technical solutions provided by the embodiments of the present invention can recursively determine the chain of vehicle meeting conflicts in multiple two-way single-lane roads (roadways) underground, and perform reasonable global scheduling of multiple mining cars underground, effectively avoiding the problem of mining cars being "repeatedly locked" and unable to pass normally, improving the situation of mining car transportation delays, and ensuring the safety of underground transportation. At the same time, the technical solutions provided by the embodiments of the present invention can update the parking status of underground chambers (meeting scheduling areas) in real time, improve the efficiency of mining car transportation, and increase the amount of ore transported. This invention can also be applied to two-way single-vehicle road networks in mountainous rural highway scenarios. In these scenarios, the two-way single lanes are mostly curved and narrow. The technical solution provided by this invention can accurately predict oncoming traffic conflicts and, based on target scheduling information, achieve overall oncoming traffic scheduling for multiple vehicles. This reduces sudden oncoming traffic conflicts, avoids disorderly reversing and congestion when vehicles meet, improves road safety, shortens average travel time, and enhances the travel experience. Optionally, this invention can also be applied to two-way single-vehicle road networks in industrial park logistics scenarios. The technical solution provided by this invention can simultaneously handle oncoming traffic conflicts for various types of vehicles in industrial parks, achieving overall oncoming traffic scheduling for multiple vehicles and improving transportation efficiency. The closed-loop scheduling mechanism adapts to the changes in traffic flow during morning and evening peak hours in the park, improving logistics turnover efficiency and reducing logistics operating costs.

[0031] Example 1

[0032] Figure 1 This is a flowchart of a vehicle passing scheduling method applied to a two-way single-vehicle road network according to Embodiment 1 of the present invention. This embodiment is applicable to the overall vehicle passing scheduling of multiple vehicles in a two-way single-vehicle road network. The method can be executed by a vehicle passing scheduling device applied to a two-way single-vehicle road network. This vehicle passing scheduling device can be implemented in hardware and / or software, and can be configured in electronic devices such as mobile phones, computers, or servers. Figure 1 As shown, the method includes:

[0033] S110, In response to the meeting scheduling request event, determine the target network flow model corresponding to the target area.

[0034] The vehicle passing dispatch request event can be an event that receives a vehicle passing dispatch request for the overall vehicle passing in a target area. The target area can be the area corresponding to a two-way single-vehicle road network. A two-way single-vehicle road network can be a road network composed of multiple crisscrossing two-way single lanes. A two-way single lane can be a road with only one lane, but allows vehicles to travel in both directions, and vehicles traveling in the two directions need to alternate using the lane. For example, taking the underground transportation scenario in a mine as an example, the target area can be an underground area, which is a tunnel area including multiple crisscrossing two-way single lanes.

[0035] The target network flow model can be used to characterize the actual road conditions in a target region. The target network flow model includes: multiple nodes, pairs of reverse directed edges associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the pairs of reverse directed edges.

[0036] In this model, nodes in the target network flow correspond to the vehicle dispatching area of ​​the target region. The vehicle dispatching area can be an area in the target region associated with a two-way single-lane road, capable of accommodating multiple vehicles for parking and dispatching. Optionally, the vehicle dispatching area can include at least one parking space to allow vehicles to be dispatched and parked. For example, taking an underground area as the target region, the vehicle dispatching area could be an underground chamber, intersection, etc. The reverse directed edge pairs associated with the nodes correspond to the two-way single-lane road in the target region. It should be noted that a reverse directed edge pair is a pair of directed edges with opposite directions; these two directed edges correspond to opposite travel directions but belong to the same two-way single-lane road. Optionally, a two-way single-lane road can be abstracted as a reverse directed edge pair, which can be represented as... ,in, express The direction of travel, express The direction of travel.

[0037] The node attribute information corresponding to a node changes with the area usage information of the traffic meeting scheduling area. Optionally, the area usage information may include the total area capacity information, available area capacity information, and vehicle occupancy status information of the traffic meeting scheduling area. The total area capacity information can be used to represent the total number of vehicles that the traffic meeting scheduling area can accommodate. The total area capacity information can be represented by the total number of parking spaces in the traffic meeting scheduling area. The available area capacity information can be used to represent the number of vehicles that the traffic meeting scheduling area can currently accommodate. The vehicle occupancy status information can be understood as whether each parking space in the traffic meeting scheduling area is occupied. Correspondingly, the node attribute information includes at least the node identifier, total node capacity information, available node capacity information, and node vehicle occupancy status information. The node identifier is used to uniquely identify the node. The total node capacity information corresponds to the total area capacity information, that is, it represents the total number of vehicles that the traffic meeting scheduling area corresponding to the node can accommodate. The available node capacity information corresponds to the available area capacity information, that is, it represents the number of vehicles that the traffic meeting scheduling area corresponding to the node can currently accommodate. The vehicle occupancy status information of a node corresponds to the vehicle occupancy status information of the area, that is, it indicates whether each parking space in the traffic dispatch area corresponding to the node is occupied. It should be noted that since the vehicles in the target area change in real time, the area usage information of the traffic dispatch area is also updated in real time. In order to ensure that the target network flow model can be consistent with the actual real-time road network status, the node attribute information in the target network flow model is updated in real time as the area usage information changes.

[0038] The edge attribute information changes with the road usage information of the two-way single-lane road. Optionally, the road usage information can be used to characterize the current vehicle usage status of the two-way single-lane road. This can include the associated vehicle dispatching area information, the road capacity information corresponding to the two-way single-lane road, the current number of vehicles in each direction of travel, and the traffic status information. The associated vehicle dispatching area information can be understood as the vehicle dispatching area associated with that two-way single-lane road. For example, taking an underground area as the target area, the associated vehicle dispatching area information for the two-way single-lane road could be: the two-way single-lane road corresponds to two intersections and one chamber. The road capacity information can be understood as the number of vehicles that the two-way single-lane road can normally pass through. The current number of vehicles in each direction of travel can be understood as the number of vehicles currently traveling in the two-way single-lane road in each of the two directions of travel. The traffic status information is used to characterize whether other vehicles are still allowed to enter and pass through the two-way single-lane road.

[0039] Accordingly, the edge attribute information includes at least the edge identifier corresponding to each edge in the reverse directed edge pair, the identifier of at least one associated node, edge capacity information, current vehicle quantity information, and traffic status information. The node identifier can be the identifier of the node associated with the edge corresponding to the edge identifier. The edge capacity information can be determined based on the road capacity information.

[0040] Optionally, road capacity information includes two scenarios. The first scenario is when all vehicles in a two-way single-lane road are traveling in the same direction. In this case, the road capacity information for that two-way single-lane road can be determined based on the road length, vehicle length, and safe following distance, as shown in the formula below.

[0041] ;

[0042] in, Indicates road capacity information. Indicates road length information. Indicates the length of the vehicle. This indicates the safe following distance between vehicles. For example, , If the two-way single lane allows only 15 vehicles to travel simultaneously in the same direction, then the remaining number of vehicles in the two-way single lane can be determined based on the road capacity information and the current number of vehicles. For example, if the two-way single lane allows 15 vehicles to travel simultaneously in the same direction, and the current number of vehicles is 13, then the two-way single lane can still allow 2 more vehicles to travel in the same direction.

[0043] Another scenario is where vehicles in the two-way single lane are traveling in opposite directions. In this case, the road capacity information of the two-way single lane is consistent with the available capacity information of its associated meeting point scheduling area, ensuring that vehicles have available spaces for scheduling after entering the node. That is, .in, This refers to the available capacity information for the area (node ​​available capacity information). For example, if one of the edges corresponding to this two-way single lane... The associated nodes of ,but That is, the edge The corresponding edge capacity information is 2.

[0044] The current vehicle count information in the edge attribute information corresponds to the current vehicle count information in each driving direction. It should be noted that a reverse directed edge pair consists of two edges, each with corresponding edge attribute information. For these two edges, the current vehicle count information corresponding to each edge is consistent with the current vehicle count in the corresponding driving direction of the two-way single-lane road. For example, if there are 3 vehicles traveling in the first driving direction and 2 vehicles traveling in the second driving direction on a two-way single-lane road, the current vehicle count information in the edge attribute information corresponding to the first driving direction will be 3.

[0045] For a pair of opposite directed edges, the passage status information in the edge attribute information of one edge can be determined based on the current vehicle quantity information in the edge attribute information of the other edge. For example, if the current vehicle quantity information corresponding to the opposite edge of the current edge is greater than or equal to 1, the passage status information in the edge attribute information of the current edge can be set to the locked state, that is, vehicles are not allowed to enter. In other words, if there are vehicles traveling in one direction in a two-way single lane, the passage status of the edge corresponding to the other direction is locked.

[0046] The passage status information in the edge attribute information is also related to the current number of vehicles and the edge capacity information. Optionally, if the current number of vehicles matches the edge capacity information, the passage status is locked, meaning other vehicles are not allowed to enter. If the current number of vehicles is less than the edge capacity information, the passage status is open, meaning other vehicles are allowed to enter.

[0047] It should be noted that the edge attribute information corresponding to each edge of the reverse directed edge pair is updated in real time as the road usage information of the two-way single lane changes.

[0048] Specifically, when a vehicle passing scheduling request is received for overall vehicle passing scheduling in the target area, the target network flow model corresponding to the target area is determined based on the road usage information of multiple two-way single lanes in the target area and the area usage information of at least one passing scheduling area associated with each two-way single lane.

[0049] In this embodiment of the invention, the method for determining the target network flow model corresponding to the target area may be as follows: when a traffic dispatch request for the target area is received, if a historical network flow model corresponding to the target area is detected, the historical network flow model is updated in real time based on the road usage information corresponding to each two-way single lane in the target area and the area usage information of the traffic dispatch area associated with the two-way single lane to obtain the target network flow model; if no historical network flow model corresponding to the target area exists, an initial network flow model is constructed based on the area map corresponding to the target area; and the initial network flow model is updated in real time based on the road usage information corresponding to each two-way single lane in the target area and the area usage information of the traffic dispatch area associated with the two-way single lane to obtain the target network flow model.

[0050] The edge attribute information of the target network flow model includes at least the edge identifier corresponding to each edge in the reverse directed edge pair, the identifier of at least one associated node, edge capacity information, current vehicle quantity information, and traffic status information. The node attribute information of the target network flow model includes at least the node identifier, total node capacity information, available node capacity information, and node vehicle occupancy status information.

[0051] The historical network flow model can be a network flow model corresponding to the target area, determined based on historical traffic meeting scheduling request events. The area map can be a map corresponding to the target area. The initial network flow model can be determined based on multiple two-way single lanes and traffic meeting scheduling areas corresponding to the area map.

[0052] Specifically, upon receiving a traffic dispatch request for a target area, if a historical network flow model corresponding to the target area is detected, the historical network flow model can be updated in real time based on the road usage information corresponding to each two-way single lane in the target area and the area usage information of the traffic dispatch area associated with the two-way single lane, thereby determining the target network flow model. This improves the modeling efficiency of the target network flow model.

[0053] Correspondingly, if no historical network flow model exists for the target area, multiple bidirectional single-lane roads corresponding to the target area and at least one passing dispatch area associated with each bidirectional single-lane road can be determined based on the regional map of the target area. The bidirectional single-lane roads are abstracted as reverse directed edge pairs, and the passing dispatch areas are abstracted as nodes to obtain the initial network flow model corresponding to the target area. The initial network flow model is then updated in real time based on the road usage information corresponding to each bidirectional single-lane road in the target area and the regional usage information of the passing dispatch areas associated with each bidirectional single-lane road to obtain the target network flow model. By determining a target network flow model consistent with the actual road network conditions, it is easier to accurately predict global chain conflicts in future time periods, overcoming the scheduling limitations caused by local conflicts.

[0054] For example, taking the underground area as the target area, the area map as a road network CAD drawing, and the passing and dispatching area as the avoidance chamber and / or intersection as an example, this will be explained.

[0055] Based on the road network CAD drawings corresponding to the target area, determine the bypass chambers and / or intersections corresponding to each two-way single lane in the target area, and abstract the bypass chambers and / or intersections as nodes to obtain a node set. .

[0056] Among them, node set Corresponding to all avoidance chambers and / or intersections, each node Node attribute information may include: ,in, Indicates the node identifier. This indicates the total capacity information of the nodes. This indicates the vehicle occupancy status information at the node. This indicates the available capacity information for the node.

[0057] Regarding the vehicle occupancy status information at a node, when a vehicle enters the meeting dispatch area (node), for example, when a vehicle is detected... Entering the node Parking spaces in the corresponding meeting and dispatching area back, Updated to , Reduce by 1 simultaneously:

[0058] , ; after the vehicle was detected Exit node After the corresponding train dispatch area, Updated to 0. Add 1 synchronously:

[0059] , .

[0060] Based on the road network CAD drawings corresponding to the target area, determine the multiple two-way single lanes corresponding to the target area, and abstract the two-way single lanes as reverse directed edge pairs to obtain the edge set. Among them, a pair of reverse directed edges can be represented as ,in, express The direction of travel, express The direction of travel. Among them, the side set Including all pairs of reverse directed edges, each edge The edge attribute information is ;in, Indicates the edge identifier. and It is the identifier of at least one node associated with the edge. This indicates the side length (corresponding to the road length information mentioned above). Represents edge capacity information; express Current vehicle quantity information at any given moment. Indicates the passage status.

[0061] It should be noted that since the edge attribute information is the edge attribute information of one edge in a reverse directed edge pair, to ensure the accuracy of subsequent correspondences, a reverse edge mapping relationship can be established based on the edge attribute information of the two edges belonging to the same reverse directed edge pair. That is, for any The reverse edges of the same reverse directed edge pair are ,remember, .

[0062] The accessibility information in the edge attribute information can be determined as follows, wherein the accessibility information... This indicates that the passage status information is open. This indicates that the passage status information is in a locked state.

[0063] If the edge The corresponding current number of vehicles information Then the edge Corresponding passage status information ,vice versa.

[0064] If the edge The corresponding current number of vehicles information Then the edge Corresponding passage status information until hour, .in, Representing an edge The edge capacity information.

[0065] The target network flow model is determined based on the aforementioned edge set, node set, and reverse edge mapping relationship. The target network flow model is updated in real time based on road usage information and area usage information to ensure the target network flow model is optimized. It perfectly matches the actual road network conditions, providing accurate data support for subsequent scheduling. At the same time, it can avoid the waste or conflict of static resources such as parking spaces in the meeting and dispatching area.

[0066] S120. Based on the target network flow model, analyze the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area to determine at least one scheduling information to be processed.

[0067] Specifically, vehicles within the target area can be designated as vehicles to be processed; that is, there can be at least one vehicle to be processed within the target area. The preset driving path can be a pre-planned route corresponding to the vehicle to be processed. Vehicle driving information can be understood as the driving information of the vehicle to be processed within the target area. Optionally, the vehicle driving information can be determined by collecting information from the vehicle to be processed using at least one of Ultra Wide Band (UWB) technology, a satellite positioning system, and / or a vehicle speed sensor.

[0068] Optionally, the vehicle driving information includes at least: the vehicle's location, speed, direction, and driving sequence within its respective bidirectional single-lane. Each type of scheduling information includes at least one scheduling sub-information corresponding to the vehicle. The location information can be understood as the real-time location of the vehicle in the target area, indicating which bidirectional single-lane the vehicle is currently in. The speed information can be the vehicle's speed. The direction information is the direction the vehicle is traveling. The driving sequence within its respective bidirectional single-lane can be understood as: which vehicle in the same direction is the vehicle being processed within the bidirectional single-lane.

[0069] The pending scheduling information can be information regarding the scheduling of at least one vehicle in the target area. It should be noted that each type of pending scheduling information includes scheduling information for at least one vehicle in the target area. For example, if there are three vehicles in the target area—vehicle a, vehicle b, and vehicle c—then the pending scheduling information includes scheduling for these three vehicles. For instance, one possible pending scheduling information would be: vehicle a yields, vehicle b proceeds normally, and vehicle c yields.

[0070] Specifically, based on the preset driving path information of at least one vehicle to be processed in the target area, the initial trajectory information corresponding to the vehicle to be processed in the target network flow model is determined. Based on the initial trajectory information, vehicle driving information, and the real-time updated target network flow model, at least one type of scheduling information to be processed is determined, so as to perform simulated scheduling processing on at least one vehicle to be processed based on each type of scheduling information to be processed.

[0071] In this embodiment of the invention, the method for determining at least one type of scheduling information to be processed may be as follows: based on the preset driving path of at least one vehicle to be processed, determine the initial trajectory information corresponding to the vehicle to be processed in the target network flow model; wherein, the initial trajectory information includes at least: at least one target edge, at least one target node, edge attribute information corresponding to the target edge, and node attribute information corresponding to the target node; based on the edge attribute information corresponding to the target edge, the node attribute information corresponding to the target node, and the vehicle driving information in the initial trajectory information, determine the initial driving conflict information; based on the initial driving conflict information, determine at least one type of scheduling information to be processed related to meeting vehicle scheduling.

[0072] The initial trajectory information can be understood as the trajectory information of the vehicle to be processed within the target network flow model. Initial trajectory information can be determined for each vehicle to be processed. Optionally, the initial trajectory information includes at least: at least one target edge, at least one target node, edge attribute information corresponding to the target edge, and node attribute information corresponding to the target node. The target edge can be used to represent the bidirectional single lane and the corresponding driving direction within the preset driving path of the vehicle to be processed. The target node can be used to represent the meeting point scheduling area within the preset driving path of the vehicle to be processed.

[0073] Initial driving conflict information can be used to characterize situations where at least two vehicles cannot proceed straight, requiring at least one vehicle to yield so that other vehicles can proceed normally. Initial driving conflict information includes at least the target edge requiring oncoming traffic scheduling, the target node, the corresponding vehicle, and the corresponding edge and node attribute information. For example, if it is detected that vehicle a and vehicle b are both traveling in the same two-way single lane at the same time, and in opposite directions, then vehicle a, vehicle b, the target edge corresponding to vehicle a, the corresponding edge corresponding to vehicle b (which belongs to the same reverse directed edge pair as the target edge corresponding to vehicle a), and the schedulable target node can be considered as a set of initial driving conflict sub-information. Correspondingly, multiple sets of initial driving conflict sub-information may exist in the target area; that is, multiple sets of initial driving conflict sub-information can be considered as initial driving conflict information.

[0074] Specifically, for at least one vehicle to be processed, based on the preset driving path of each vehicle to be processed, the next target edge to be driven by the vehicle to be processed and the target edge expected to be driven in the preset future time period are analyzed according to the network flow model, and the target node associated with each target edge, the edge attribute information corresponding to the target edge and the node attribute information corresponding to the target node are determined, so as to obtain the initial trajectory information corresponding to each vehicle to be processed.

[0075] Based on the edge attribute information of the target edge, the node attribute information of the target node, and the vehicle driving information of the vehicle to be processed in the initial trajectory information corresponding to each vehicle to be processed, the initial driving conflict information is determined according to the target network flow model. Based on the initial driving conflict information, at least one type of scheduling information related to meeting scheduling is determined.

[0076] For example, in conjunction with the above example, based on the target network flow model, a preset driving path is assigned to each vehicle to be processed. Analysis is performed to determine the path edge sequence and corresponding target node corresponding to the preset driving path. The path edge sequence includes at least one target edge. Based on the target network flow model, the next target edge to be traveled for each vehicle is determined. And at least one target edge that is expected to be traveled within a preset future time period. Based on the next target edge to be traveled for each vehicle to be processed. Given at least one target edge that is expected to be traveled within a preset future time period, as well as the target node associated with the target edge, the edge attribute information of the target edge, and the node attribute information of the target node, determine the corresponding global conflict pair (i.e., the initial travel conflict information mentioned above). ,in, , Indicates the vehicles involved in the current driving conflict that are yet to be processed. , Indicates the vehicles involved in the current driving conflict that are yet to be processed. , This represents the reverse directed edge pair corresponding to the target edge that conflicts with the current driving direction.

[0077] Regarding the current global conflict Each conflict There are two scheduling scenarios, such as The corresponding dispatch status could be vehicles pending processing. Give way to vehicles awaiting processing. Go straight. Or, vehicles awaiting processing. Straight ahead, vehicles awaiting processing Avoidance. Since there are at least two scheduling scenarios for each conflict pair, there are one or more scheduling options to be processed for the global conflict pair corresponding to the target area.

[0078] Optionally, the method for determining at least one type of scheduling information to be processed related to meeting scheduling based on the initial driving conflict information can be as follows: based on the initial driving conflict information, determine at least one type of sub-scheduling information corresponding to each vehicle to be processed; based on the at least one type of sub-scheduling information corresponding to each vehicle to be processed, determine at least one type of scheduling information to be adjusted; for at least one type of scheduling information to be adjusted, if there is a type of scheduling information to be adjusted that meets the preset pruning conditions, then the type of scheduling information to be adjusted is pruned to obtain at least one type of scheduling information to be processed.

[0079] The sub-scheduling information can be used to represent the meeting scheduling information corresponding to each vehicle to be processed. Optionally, for each vehicle to be processed, the sub-scheduling information may include two types of scheduling information: vehicle to avoid or vehicle to proceed straight.

[0080] The scheduling information to be adjusted can be the overall scheduling information corresponding to all vehicles to be processed, determined comprehensively based on at least one vehicle to be processed and at least one type of sub-scheduling information corresponding to each vehicle to be processed. For example, if there is an initial driving conflict between three vehicles to be processed in the target area, and each vehicle to be processed corresponds to two types of scheduling sub-information, then six types of scheduling information to be adjusted can be determined accordingly.

[0081] The default pruning condition is that the number of vehicles to be avoided corresponding to the same target node is higher than the node's available capacity. A target node can be a node associated with a target edge that has a driving conflict. The number of vehicles to be avoided corresponding to a target node can be understood as the number of vehicles among the multiple vehicles to be processed corresponding to the target edge with the driving conflict that need to travel to the target node for avoidance processing.

[0082] Specifically, based on the initial driving conflict information, at least one sub-scheduling information corresponding to each vehicle to be processed is determined. Based on at least one vehicle to be processed and at least one sub-scheduling information corresponding to each vehicle to be processed, at least one scheduling information to be adjusted corresponding to the target area is determined. For at least one scheduling information to be adjusted, if the number of vehicles to be avoided at the same target node corresponding to the scheduling information to be adjusted is higher than the node's available capacity information, then the scheduling information to be adjusted is pruned to obtain at least one scheduling information to be processed.

[0083] For example, in conjunction with the above example, if the number of vehicles to be avoided corresponding to a target edge with a driving conflict in the scheduling information to be adjusted (the vehicles need to be avoided to the corresponding target node) (Number of vehicles) Exceeding the target node Available capacity information of nodes If the desired result is not found, the scheduling information to be adjusted is deleted, and no more than a preset threshold number of scheduling information to be processed is retained. For example, the preset threshold number can be 10, meaning that no more than 10 types of scheduling information to be processed are retained.

[0084] S130. For at least one type of scheduling information to be processed, simulate scheduling processing is performed on at least one vehicle to be processed according to the target network flow model to determine the vehicle prediction trajectory information and the total waiting time of the vehicle corresponding to the vehicle prediction trajectory information under each type of scheduling information to be processed.

[0085] The vehicle predicted trajectory information can be the trajectory information of the actual driving path of the vehicle to be processed in the target network flow model after the simulated scheduling of the vehicle to be processed based on the scheduling information to be processed. There is corresponding vehicle predicted trajectory information for each vehicle to be processed. The total vehicle waiting time can be the total waiting time required for all vehicles to be processed due to global vehicle meeting scheduling when at least one vehicle to be processed is simulated based on the scheduling information to be processed.

[0086] Specifically, for at least one type of scheduling information to be processed, simulated scheduling processing is performed on at least one vehicle to be processed based on the target network flow model to determine the initial trajectory information to be updated for each vehicle under each type of scheduling information to obtain the predicted trajectory information of each vehicle. Based on the predicted trajectory information of at least one vehicle to be processed under each type of scheduling information, the total waiting time for the vehicle corresponding to at least one vehicle to be processed is determined.

[0087] S140. Based on the vehicle prediction trajectory information corresponding to each type of pending scheduling information and the total waiting time of the vehicles corresponding to the vehicle prediction trajectory information, determine the target scheduling information, so as to perform meeting scheduling processing on at least one pending vehicle based on the target scheduling information.

[0088] The target scheduling information can be scheduling information determined based on at least one type of scheduling information to be processed.

[0089] Specifically, based on the predicted vehicle trajectory information and total vehicle waiting time corresponding to each type of pending scheduling information, target scheduling information is determined for at least one pending vehicle in the target area. Meeting point scheduling control is then performed on at least one pending vehicle in the target area using this target scheduling information.

[0090] In this embodiment of the invention, when performing meeting scheduling processing on at least one vehicle to be processed based on target scheduling information, if new driving conflict information is detected, the target scheduling information is updated based on the new driving conflict information, so as to perform global meeting scheduling based on the updated target scheduling information.

[0091] Among them, newly added driving conflicts can be sudden driving conflicts that may occur due to other special circumstances when scheduling at least one vehicle to be processed through target scheduling information. The newly added driving conflict information can be the driving conflict information corresponding to the newly added driving conflict.

[0092] Specifically, when performing meeting scheduling for at least one vehicle based on target scheduling information, if a new driving conflict is detected in the target area, the corresponding new driving conflict information is determined. The target scheduling information is then updated based on the new driving conflict information, and the updated target scheduling information is used for global meeting scheduling.

[0093] For example, if a meeting scheduling process is performed on at least one vehicle to be processed based on the target scheduling information, and an unpredictable sudden conflict is detected, the newly added driving conflict information corresponding to the sudden conflict is obtained, and the corresponding vehicle to be processed is controlled to stop, so as to adjust the corresponding target scheduling information in the next scheduling cycle based on the newly added driving conflict information and update the target network flow model G.

[0094] Optionally, traffic scheduling is performed on at least one vehicle to be processed based on target scheduling information, including: sending target scheduling information to the corresponding at least one vehicle to be processed so that the at least one vehicle to be processed can drive and / or avoid obstacles according to the target scheduling information; controlling the traffic light status in the target area based on the target scheduling information to indicate that at least one vehicle to be processed can enter or exit the traffic scheduling area and the two-way single lane; and determining the available capacity information of the corresponding node when a vehicle to be processed is detected entering or exiting the parking space of the corresponding traffic scheduling area to update the target network flow model.

[0095] The vehicle status of the vehicles to be processed is collected in real time to determine their status information. This vehicle status information includes: awaiting avoidance, entering, avoiding, exiting, and already exited. The target network flow model is then updated in real time based on this vehicle status information.

[0096] The technical solution of this embodiment, in response to a meeting dispatch request event, determines the target network flow model corresponding to the target area, ensuring that the target network flow model is completely consistent with the actual road network state of the target area, providing accurate data support for subsequent dispatch decisions. Based on the target network flow model, the preset driving paths and vehicle driving information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of dispatch information to be processed. For each type of dispatch information to be processed, a dispatch simulation is performed on the at least one vehicle to be processed according to the target network flow model to determine the predicted vehicle trajectory information and the total waiting time corresponding to the predicted vehicle trajectory information for each type of dispatch information in the target area. Based on the predicted vehicle trajectory information and the total waiting time corresponding to each type of dispatch information to be processed, the target dispatch information is determined, and meeting dispatch processing is performed on the at least one vehicle to be processed according to the target dispatch information. This invention solves the problems of judgment errors, low dispatch efficiency, and inability to meet the global meeting dispatch requirements of the area caused by relying on driver experience for meeting dispatch in the prior art. It achieves global meeting dispatch processing for all vehicles in the target area, ensuring the overall traffic efficiency of the target area.

[0097] Example 2

[0098] Figure 2 This is a flowchart of a meeting scheduling method applied to a two-way single-vehicle road network according to Embodiment 2 of the present invention. This embodiment is a preferred embodiment of the above embodiments. For specific implementation details, please refer to the technical solution of this embodiment. Technical terms that are the same as or corresponding to those in the above embodiments will not be repeated here. Figure 2 As shown, the method includes:

[0099] S210. In response to the meeting scheduling request event, determine the target network flow model corresponding to the target area.

[0100] The target network flow model includes: multiple nodes, reverse directed edge pairs associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the reverse directed edge pairs. The nodes correspond to the meeting scheduling area of ​​the target region, and the reverse directed edge pairs correspond to the two-way single lanes of the target region. The node attribute information changes with the area usage information of the meeting scheduling area, and the edge attribute information changes with the road usage information of the two-way single lanes.

[0101] S220. Based on the target network flow model, analyze the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area to determine at least one scheduling information to be processed.

[0102] The vehicle driving information includes at least the following: the driving position information, driving speed information, driving direction information, and driving sequence information of the vehicle to be processed in its respective two-way single lane. Each type of scheduling information to be processed includes at least one scheduling sub-information corresponding to the vehicle to be processed.

[0103] S230. Based on the scheduling information to be processed and the target network flow model, simulate scheduling processing is performed on at least one vehicle to be processed to update the initial trajectory information corresponding to the target network flow model and determine the first trajectory information.

[0104] The initial trajectory information is related to the preset driving path of the vehicle to be processed. The first trajectory information can be the updated trajectory information after the initial trajectory information is updated based on the scheduling information to be processed when the vehicle to be processed is scheduled to meet another vehicle.

[0105] Specifically, for at least one type of scheduling information to be processed, at least one vehicle to be processed is simulated and scheduled based on the scheduling information to be processed and the target network flow model, so as to update the initial trajectory information of each vehicle to be processed and determine the first trajectory information corresponding to each vehicle to be processed under each type of scheduling information to be processed.

[0106] S240. Based on the first trajectory information, determine the chain driving conflict information.

[0107] Among them, chain driving conflict information can be other conflict information caused by updating the initial driving trajectory information, so that the vehicle to be processed drives according to the first trajectory information.

[0108] Specifically, based on the first trajectory information corresponding to each vehicle under each type of pending scheduling information, and according to the target network flow model, the chain driving conflict information corresponding to the first trajectory information is determined.

[0109] S250, adjust the scheduling information to be processed based on the chain driving conflict information, and update the first trajectory information based on the adjusted scheduling information to be processed, so as to obtain the second trajectory information.

[0110] The second trajectory information can be the trajectory information updated from the first trajectory information.

[0111] Specifically, the scheduling information to be processed is adjusted based on the chain-driven conflict information to obtain the adjusted scheduling information to be processed. Based on the adjusted scheduling information to be processed, at least one vehicle to be processed is simulated and scheduled again according to the target network flow model to update the first trajectory information and obtain the second trajectory information.

[0112] S260. The second trajectory information is used as the first trajectory information, and the process of determining the chain driving conflict information based on the first trajectory information and updating the first trajectory information based on the chain driving conflict information is repeated, so that when the vehicle driving time corresponding to the trajectory information reaches the preset driving time, there is no new chain driving conflict information, and the vehicle predicted trajectory information is obtained.

[0113] The preset travel time can be a pre-set standard value corresponding to the vehicle travel time during simulated scheduling.

[0114] Specifically, the second trajectory information is used as the first trajectory information, and the process of determining the chain driving conflict information based on the first trajectory information and updating the first trajectory information based on the chain driving conflict information is repeated. When the vehicle driving time corresponding to the trajectory information reaches the preset driving time and there is no new chain driving conflict information, the trajectory information at this time is determined as the vehicle predicted trajectory information.

[0115] Optionally, for each type of scheduling information to be processed, cascading driving conflicts within future time periods are recursively inferred based on the target network flow model G. That is, the initial trajectory information in the target network flow model G is updated based on the scheduling information to be processed to obtain first trajectory information, and the time information corresponding to the first trajectory information is determined. This is illustrated in the following equation:

[0116] ;

[0117] ;

[0118] in, Indicates vehicles awaiting processing Drive into the corresponding target edge The initial start time, Indicates vehicles awaiting processing Drive out of the corresponding target area The initial and final times, and It is related to the initial trajectory information. Indicates vehicles awaiting processing Drive into the corresponding target edge The first starting moment, Indicates vehicles awaiting processing Drive out of the corresponding target area The first ending moment, and It is related to the information of the first trajectory. This indicates the conflict pairs in the initial driving conflict information. Vehicles awaiting processing The avoidance delay time is the vehicle waiting time.

[0119] Based on the first trajectory information and the reverse edge mapping relationship in the target network flow model, the chain of driving conflicts caused by the delay of the vehicle to be processed due to the first trajectory information are determined. Information. Based on the chain driving conflict information, the scheduling information to be processed is adjusted, and the first trajectory information is updated based on the adjusted scheduling information to obtain the second trajectory information. The chain conflict detection and trajectory information update process is repeated until no new chain driving conflict information is added when the preset driving time is reached. Then, the predicted trajectory information of each vehicle to be processed corresponding to the scheduling information to be processed is determined.

[0120] S270. Determine the total waiting time of vehicles corresponding to the predicted vehicle trajectory information.

[0121] In this embodiment of the invention, the total vehicle waiting time can be determined as follows: based on the vehicle predicted trajectory information and the adjusted pending scheduling information corresponding to the vehicle predicted trajectory information, at least one vehicle to be avoided and a first vehicle waiting time corresponding to each vehicle to be avoided are determined; wherein, the vehicle to be avoided is one of the at least one pending vehicles; based on the at least one vehicle to be avoided and the adjusted pending scheduling information corresponding to the vehicle predicted trajectory information, at least one associated vehicle and a second vehicle waiting time corresponding to each associated vehicle are determined; wherein, the meeting scheduling of the associated vehicle and the vehicle to be avoided is related; the first weight information and the first vehicle waiting time of the at least one vehicle to be avoided, the second weight information and the second vehicle waiting time of the at least one associated vehicle are input into the total waiting time determination model to determine the total vehicle waiting time; wherein, the weight information is related to the vehicle type.

[0122] Here, a vehicle to be avoided can be understood as at least one vehicle among those awaiting processing that needs to enter the meeting point dispatch area for dispatching and avoidance processing in the event of a driving conflict. The first vehicle waiting time can be the waiting time of the vehicle to be avoided due to dispatching processing. It is related to the meeting point dispatching of associated vehicles and the vehicle to be avoided. It is related to cascading driving conflict information. When the vehicle to be avoided is being dispatched, it may cause other vehicles to avoid or wait. Other vehicles can be considered as associated vehicles. The second vehicle waiting time can be the waiting time required for associated vehicles due to dispatching processing.

[0123] The first weighting information relates to the vehicle type of the vehicle to be avoided. The second weighting information relates to the vehicle type of the associated vehicle. Optionally, vehicle types can be categorized as inspection vehicles, transport vehicles, repair vehicles, and emergency response vehicles. The priority of vehicle types, from highest to lowest, is: emergency response vehicles, repair vehicles, transport vehicles, and inspection vehicles. Correspondingly, the higher the priority of a vehicle type, the greater its weighting information. Optionally, the priority of vehicle types can be adjusted according to actual needs.

[0124] The total waiting time determination model can be a mathematical model used to determine the total waiting time for all vehicles. Optionally, the total waiting time determination model can be represented by the following function:

[0125] ;

[0126] in, This indicates initial driving conflict information. This indicates the adjusted pending scheduling information. The corresponding chain driving conflict information, This indicates the vehicle to be avoided in the adjusted pending scheduling information. The vehicle to be avoided can be either the vehicle to be avoided in the initial driving conflict information or the vehicle to be avoided in the chain driving conflict information. This represents the first weight information. Indicates the waiting time of the first vehicle. Indicates associated vehicles, This represents the second weighting information. This indicates the second waiting time.

[0127] Specifically, based on the predicted vehicle trajectory information and the adjusted scheduling information corresponding to the predicted vehicle trajectory information, at least one vehicle to be avoided and a first vehicle waiting time corresponding to each vehicle to be avoided are determined. Based on the at least one vehicle to be avoided and the adjusted pending scheduling information corresponding to the predicted vehicle trajectory information, at least one associated vehicle and a second vehicle waiting time corresponding to each associated vehicle are determined. Based on the vehicle type corresponding to each vehicle to be avoided, first weight information corresponding to each vehicle to be avoided is determined, and based on the vehicle type of each associated vehicle, second weight information corresponding to each associated vehicle is determined. The first weight information and first vehicle waiting time of at least one vehicle to be avoided, the second weight information and second vehicle waiting time of at least one associated vehicle are input into the function corresponding to the total waiting time determination model to obtain the total vehicle waiting time. Based on the total vehicle waiting time of each adjusted pending scheduling information, the target scheduling information is determined. By synchronously simulating and determining all adjusted pending scheduling information corresponding to all current driving conflicts, and combining the target network flow model to recursively deduce vehicle trajectory information, the total vehicle waiting time corresponding to each adjusted pending scheduling information can be determined. This facilitates the subsequent determination of target scheduling information based on the total vehicle waiting time. Compared with local scheduling, this can effectively reduce the total vehicle waiting time of two-way single-vehicle road networks.

[0128] S280. Determine the target scheduling information based on the vehicle prediction trajectory information corresponding to each type of scheduling information to be processed and the total waiting time of the vehicles corresponding to the vehicle prediction trajectory information.

[0129] Optionally, the target scheduling information can be determined by: determining the number of chain driving conflicts corresponding to each adjusted pending scheduling information; and determining the adjusted pending scheduling information corresponding to the minimum number of chain driving conflicts and / or the shortest total vehicle waiting time as the target scheduling information.

[0130] The number of chain driving conflicts can be the total number of chain driving conflicts that occur, based on the adjusted pending scheduling information.

[0131] Specifically, for at least one adjusted pending scheduling information, the number of cascading driving conflicts corresponding to each adjusted pending scheduling information is determined. The adjusted pending scheduling information corresponding to the minimum number of cascading driving conflicts and / or the shortest total vehicle waiting time is taken as the target scheduling information.

[0132] Optionally, for at least one adjusted pending scheduling information, the total vehicle waiting time is... The smallest adjusted pending scheduling information is used as the target scheduling information. If two adjusted pending scheduling information have the same total vehicle waiting time and both are small, then the adjusted pending scheduling information with the fewest chain driving conflicts can be used as the target scheduling information.

[0133] The technical solution of this embodiment, in response to a meeting dispatch request event, determines the target network flow model corresponding to the target area, ensuring that the target network flow model is completely consistent with the actual road network state of the target area, providing accurate data support for subsequent dispatch decisions. Based on the target network flow model, the preset travel paths and vehicle travel information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of dispatch information to be processed. Based on the dispatch information to be processed and the target network flow model, simulated dispatch processing is performed on at least one vehicle to be processed to update the initial trajectory information corresponding to the target network flow model, determining first trajectory information. Based on the first trajectory information, chain driving conflict information is determined. The dispatch information to be processed is adjusted based on the chain driving conflict information, and the first trajectory information is updated based on the adjusted dispatch information to obtain second trajectory information. The second trajectory information is used as the first trajectory information, and the process of determining chain driving conflict information based on the first trajectory information and updating the first trajectory information based on the chain driving conflict information is repeated until no new chain driving conflict information is added when the vehicle travel time corresponding to the trajectory information reaches the preset travel time, thus obtaining predicted vehicle trajectory information. The total waiting time of the vehicle corresponding to the predicted vehicle trajectory information is determined. Based on the predicted vehicle trajectory information and total vehicle waiting time corresponding to each type of pending scheduling information, target scheduling information is determined, and at least one pending vehicle is scheduled for passing according to the target scheduling information. This invention solves the problems of judgment errors, low scheduling efficiency, and inability to meet the global passing scheduling needs of a region caused by prior art relying on driver experience for passing scheduling. It realizes automated global passing scheduling of all vehicles in the target area, reduces manual intervention, and ensures the overall traffic efficiency of the target area.

[0134] Example 3

[0135] Figure 3 This is a schematic diagram of a vehicle passing scheduling device applied to a two-way single-vehicle road network, provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a network flow model determination module 310, a scheduling information determination module 320, a vehicle simulation scheduling module 330, and a meeting scheduling module 340.

[0136] A network flow model determination module 310 is used to determine a target network flow model corresponding to a target area in response to a vehicle meeting scheduling request event. The target network flow model includes: multiple nodes, pairs of reverse directed edges associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the pairs of reverse directed edges. The nodes correspond to the vehicle meeting scheduling area of ​​the target area, the pairs of reverse directed edges correspond to the two-way single lanes of the target area, the node attribute information changes with the area usage information of the vehicle meeting scheduling area, and the edge attribute information changes with the road usage information of the two-way single lanes. A scheduling information determination module 320 is used to analyze the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area based on the target network flow model to determine at least one scheduling information to be processed. The vehicle driving information includes at least: the driving position information, driving speed information, driving direction information, and driving sequence information of the vehicle to be processed in its respective two-way single lane. Each type of scheduling information to be processed includes scheduling sub-information corresponding to at least one vehicle to be processed. The vehicle simulation scheduling module 330 is used to perform simulated scheduling processing on the at least one vehicle to be processed according to the target network flow model for the at least one type of scheduling information to be processed, so as to determine the vehicle predicted trajectory information and the total vehicle waiting time corresponding to the vehicle predicted trajectory information under each type of scheduling information. The meeting scheduling module 340 is used to determine the target scheduling information based on the vehicle predicted trajectory information and the total vehicle waiting time corresponding to the vehicle predicted trajectory information, so as to perform meeting scheduling processing on the at least one vehicle to be processed based on the target scheduling information.

[0137] The technical solution of this embodiment, in response to a meeting dispatch request event, determines the target network flow model corresponding to the target area, ensuring that the target network flow model is completely consistent with the actual road network state of the target area, providing accurate data support for subsequent dispatch decisions. Based on the target network flow model, the preset driving paths and vehicle driving information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of dispatch information to be processed. For each type of dispatch information to be processed, a dispatch simulation is performed on the at least one vehicle to be processed according to the target network flow model to determine the predicted vehicle trajectory information and the total waiting time corresponding to the predicted vehicle trajectory information for each type of dispatch information in the target area. Based on the predicted vehicle trajectory information and the total waiting time corresponding to each type of dispatch information to be processed, the target dispatch information is determined, and meeting dispatch processing is performed on the at least one vehicle to be processed according to the target dispatch information. This invention solves the problems of judgment errors, low dispatch efficiency, and inability to meet the global meeting dispatch requirements of the area caused by relying on driver experience for meeting dispatch in the prior art. It achieves global meeting dispatch processing for all vehicles in the target area, ensuring the overall traffic efficiency of the target area.

[0138] Based on the above embodiments, optionally, a network flow model determination module is used to, upon receiving a traffic dispatch request for a target area, if a historical network flow model corresponding to the target area is detected, update the historical network flow model in real time based on the road usage information corresponding to each bidirectional single lane in the target area and the area usage information of the traffic dispatch area associated with the bidirectional single lane to obtain a target network flow model; if no historical network flow model corresponding to the target area exists, construct an initial network flow model based on the area map corresponding to the target area; and update the initial network flow model in real time based on the road usage information corresponding to each bidirectional single lane in the target area and the area usage information of the traffic dispatch area associated with the bidirectional single lane to obtain a target network flow model; wherein, the edge attribute information of the target network flow model includes at least the edge identifier corresponding to each edge in the reverse directed edge pair, at least one associated node identifier, edge capacity information, current vehicle quantity information, and traffic status information, and the node attribute information of the target network flow model includes at least the node identifier, node total capacity information, node available capacity information, and node vehicle occupancy status information.

[0139] Optionally, the scheduling information determination module includes: an initial trajectory information determination unit, used to determine the initial trajectory information corresponding to the vehicle to be processed in the target network flow model based on the preset driving path of the at least one vehicle to be processed; wherein the initial trajectory information includes at least: at least one target edge, at least one target node, edge attribute information corresponding to the target edge, and node attribute information corresponding to the target node; an initial driving conflict information determination unit, used to determine initial driving conflict information based on the edge attribute information corresponding to the target edge, the node attribute information corresponding to the target node, and the vehicle driving information in the initial trajectory information; and a pending scheduling information determination unit, used to determine at least one pending scheduling information related to meeting vehicle scheduling based on the initial driving conflict information.

[0140] Optionally, the pending scheduling information determination unit is used to determine at least one sub-scheduling information corresponding to each pending vehicle based on the initial driving conflict information; determine at least one scheduling information to be adjusted based on the at least one sub-scheduling information corresponding to each pending vehicle; for the at least one scheduling information to be adjusted, if there is a scheduling information to be adjusted that meets a preset pruning condition, then the scheduling information to be adjusted is pruned to obtain at least one scheduling information to be processed; wherein, the preset pruning condition is that the number of vehicles to be avoided corresponding to the same target node is higher than the node's available capacity information.

[0141] Optionally, the vehicle simulation scheduling module includes: a trajectory information determination unit, used to perform simulated scheduling processing on at least one vehicle to be processed based on the scheduling information to be processed and the target network flow model, to update the initial trajectory information corresponding to the target network flow model and determine first trajectory information; wherein the initial trajectory information is related to the preset driving path of the vehicle to be processed; based on the first trajectory information, determine chain driving conflict information; adjust the scheduling information to be processed based on the chain driving conflict information, and update the first trajectory information based on the adjusted scheduling information to obtain second trajectory information; use the second trajectory information as the first trajectory information, and repeat the process of determining chain driving conflict information based on the first trajectory information and updating the first trajectory information based on the chain driving conflict information, so that when the driving time of the vehicle corresponding to the trajectory information reaches the preset driving time, there is no new chain driving conflict information, and vehicle predicted trajectory information is obtained.

[0142] Optionally, the vehicle simulation scheduling module includes: a total waiting time determination unit, configured to determine at least one vehicle to be avoided and a first vehicle waiting time corresponding to each vehicle to be avoided, based on the vehicle predicted trajectory information and the adjusted pending scheduling information corresponding to the vehicle predicted trajectory information; wherein, the vehicle to be avoided is one of the at least one pending vehicles; based on the at least one vehicle to be avoided and the adjusted pending scheduling information corresponding to the vehicle predicted trajectory information, determine at least one associated vehicle and a second vehicle waiting time corresponding to each associated vehicle; wherein, the associated vehicle is related to the meeting scheduling of the vehicle to be avoided; input the first weight information and the first vehicle waiting time of the at least one vehicle to be avoided, the second weight information and the second vehicle waiting time of the at least one associated vehicle into the total waiting time determination model to determine the total vehicle waiting time; wherein, the weight information is related to the vehicle type.

[0143] Optionally, the vehicle meeting scheduling module includes: a target scheduling information determination unit, used to determine the number of chain driving conflicts corresponding to each adjusted pending scheduling information; and to determine the adjusted pending scheduling information corresponding to the minimum number of chain driving conflicts and / or the shortest total vehicle waiting time as the target scheduling information.

[0144] Optionally, the device further includes: a scheduling information update module, used to update the target scheduling information based on the newly detected driving conflict information when the at least one vehicle to be processed is being scheduled based on the target scheduling information, so as to perform global vehicle scheduling based on the updated target scheduling information.

[0145] The vehicle passing scheduling device for two-way single-vehicle road networks provided in this embodiment of the invention can execute the vehicle passing scheduling method for two-way single-vehicle road networks provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0146] Example 4

[0147] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0148] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0149] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0150] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a vehicle passing scheduling method applied to a two-way single-vehicle road network.

[0151] In some embodiments, the vehicle passing scheduling method applied to a two-way single-vehicle road network can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the vehicle passing scheduling method for a two-way single-vehicle road network described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the vehicle passing scheduling method for a two-way single-vehicle road network by any other suitable means (e.g., by means of firmware).

[0152] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0153] Computer programs for implementing the meeting scheduling method of the present invention for bidirectional single-vehicle road networks can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0154] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0155] Example 5

[0156] Embodiment 5 of the present invention also provides a computer-readable storage medium storing computer instructions for causing a processor to execute a meeting scheduling method applied to a two-way single-vehicle road network, the method comprising:

[0157] In response to a vehicle meeting scheduling request event, a target network flow model corresponding to a target area is determined; wherein, the target network flow model includes: multiple nodes, reverse directed edge pairs associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the reverse directed edge pairs, the nodes correspond to the vehicle meeting scheduling area of ​​the target area, the reverse directed edge pairs correspond to the two-way single lanes of the target area, the node attribute information changes with the area usage information of the vehicle meeting scheduling area, and the edge attribute information changes with the road usage information of the two-way single lanes;

[0158] Based on the target network flow model, the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of scheduling information to be processed; wherein, the vehicle driving information includes at least: the driving position information, driving speed information, driving direction information and driving sequence information of the vehicle to be processed in the two-way single lane, and each type of scheduling information to be processed includes scheduling sub-information corresponding to the at least one vehicle to be processed.

[0159] For the at least one pending scheduling information, simulated scheduling processing is performed on the at least one pending vehicle according to the target network flow model to determine the vehicle prediction trajectory information and the total vehicle waiting time corresponding to the at least one pending vehicle under each pending scheduling information.

[0160] Based on the vehicle prediction trajectory information corresponding to each type of pending scheduling information and the total waiting time of the vehicles corresponding to the vehicle prediction trajectory information, target scheduling information is determined, so as to perform meeting scheduling processing on the at least one pending vehicle based on the target scheduling information.

[0161] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0162] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0163] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0164] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0165] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0166] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for scheduling passing traffic in a two-way single-vehicle road network, characterized in that, include: In response to a vehicle meeting scheduling request event, a target network flow model corresponding to a target area is determined; wherein, the target network flow model includes: multiple nodes, reverse directed edge pairs associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the reverse directed edge pairs, the nodes correspond to the vehicle meeting scheduling area of ​​the target area, the reverse directed edge pairs correspond to the two-way single lanes of the target area, the node attribute information changes with the area usage information of the vehicle meeting scheduling area, and the edge attribute information changes with the road usage information of the two-way single lanes; Based on the target network flow model, the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of scheduling information to be processed; wherein, the vehicle driving information includes at least: the driving position information, driving speed information, driving direction information and driving sequence information of the vehicle to be processed in the two-way single lane, and each type of scheduling information to be processed includes scheduling sub-information corresponding to the at least one vehicle to be processed. For the at least one pending scheduling information, simulated scheduling processing is performed on the at least one pending vehicle according to the target network flow model to determine the vehicle prediction trajectory information and the total vehicle waiting time corresponding to the at least one pending vehicle under each pending scheduling information. Based on the vehicle prediction trajectory information corresponding to each type of pending scheduling information and the total waiting time of the vehicles corresponding to the vehicle prediction trajectory information, target scheduling information is determined, so as to perform meeting scheduling processing on the at least one pending vehicle based on the target scheduling information.

2. The method according to claim 1, characterized in that, The step of determining the target network flow model corresponding to the target area in response to the vehicle meeting scheduling request event includes: When a vehicle passing scheduling request for a target area is received, if a historical network flow model corresponding to the target area is detected, the historical network flow model is updated in real time based on the road usage information corresponding to each two-way single lane in the target area and the area usage information of the vehicle passing scheduling area associated with the two-way single lane, so as to obtain the target network flow model. If no historical network flow model exists for the target region, then an initial network flow model is constructed based on the region map corresponding to the target region; and, Based on the road usage information corresponding to each bidirectional single lane in the target area and the area usage information of the meeting scheduling area associated with the bidirectional single lane, the initial network flow model is updated in real time to obtain the target network flow model. The edge attribute information of the target network flow model includes at least the edge identifier corresponding to each edge in the reverse directed edge pair, the identifier of at least one associated node, edge capacity information, current vehicle quantity information, and traffic status information. The node attribute information of the target network flow model includes at least the node identifier, node total capacity information, node available capacity information, and node vehicle occupancy status information.

3. The method according to claim 1, characterized in that, Based on the target network flow model, the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area are analyzed to determine at least one type of scheduling information to be processed, including: Based on the preset driving path of the at least one vehicle to be processed, the initial trajectory information corresponding to the vehicle to be processed in the target network flow model is determined; wherein, the initial trajectory information includes at least: at least one target edge, at least one target node, edge attribute information corresponding to the target edge, and node attribute information corresponding to the target node; Based on the edge attribute information corresponding to the target edge, the node attribute information corresponding to the target node, and the vehicle driving information in the initial trajectory information, the initial driving conflict information is determined. Based on the initial driving conflict information, at least one type of scheduling information to be processed related to meeting vehicle scheduling is determined.

4. The method according to claim 3, characterized in that, The step of determining at least one type of scheduling information to be processed related to meeting point scheduling based on the initial driving conflict information includes: Based on the initial driving conflict information, at least one sub-scheduling information corresponding to each vehicle to be processed is determined; Based on at least one sub-scheduling information corresponding to each vehicle to be processed, determine at least one scheduling information to be adjusted; For the at least one type of scheduling information to be adjusted, if there is a type of scheduling information to be adjusted that meets a preset pruning condition, then the type of scheduling information to be adjusted is pruned to obtain at least one type of scheduling information to be processed; wherein, the preset pruning condition is that the number of vehicles to be avoided corresponding to the same target node is higher than the node's available capacity information.

5. The method according to claim 1, characterized in that, The step of performing simulated scheduling processing on the at least one vehicle to be processed based on the target network flow model to determine the predicted trajectory information of the at least one vehicle to be processed under each type of scheduling information includes: Based on the scheduling information to be processed and the target network flow model, simulated scheduling processing is performed on the at least one vehicle to be processed to update the initial trajectory information corresponding to the target network flow model and determine the first trajectory information; wherein, the initial trajectory information is related to the preset driving path of the vehicle to be processed; Based on the first trajectory information, determine the chain driving conflict information; The scheduling information to be processed is adjusted based on the chain driving conflict information, and the first trajectory information is updated based on the adjusted scheduling information to be processed, so as to obtain the second trajectory information. The second trajectory information is used as the first trajectory information, and the process of determining the chain driving conflict information based on the first trajectory information and updating the first trajectory information based on the chain driving conflict information is repeated, so that when the vehicle driving time corresponding to the trajectory information reaches the preset driving time, there is no new chain driving conflict information, and the vehicle predicted trajectory information is obtained.

6. The method according to claim 5, characterized in that, Determining the total vehicle waiting time corresponding to the predicted vehicle trajectory information includes: Based on the vehicle predicted trajectory information and the adjusted pending scheduling information corresponding to the vehicle predicted trajectory information, at least one vehicle to be avoided and a first vehicle waiting time corresponding to each vehicle to be avoided are determined; wherein, the vehicle to be avoided is one of the at least one pending vehicles. Based on the at least one vehicle to be avoided and the adjusted scheduling information to be processed corresponding to the predicted trajectory information of the vehicle, at least one associated vehicle and the waiting time of a second vehicle corresponding to each associated vehicle are determined; wherein, the associated vehicle is related to the meeting scheduling of the vehicle to be avoided; The first weight information and first vehicle waiting time of the at least one vehicle to be avoided, the second weight information and second vehicle waiting time of the at least one associated vehicle are input into the total waiting time determination model to determine the total vehicle waiting time; wherein, the weight information is related to the vehicle type.

7. The method according to claim 6, characterized in that, Based on the vehicle prediction trajectory information corresponding to each type of pending scheduling information and the total vehicle waiting time corresponding to the vehicle prediction trajectory information, the target scheduling information is determined, including: Determine the number of chain driving conflicts corresponding to each adjusted pending scheduling information; The adjusted pending scheduling information corresponding to the minimum number of chain driving conflicts and / or the shortest total vehicle waiting time is determined as the target scheduling information.

8. The method according to claim 1, characterized in that, When performing meeting scheduling processing on the at least one vehicle to be processed based on the target scheduling information, the method further includes: If new driving conflict information is detected, the target scheduling information is updated based on the new driving conflict information, so as to perform global vehicle meeting scheduling based on the updated target scheduling information.

9. A vehicle passing scheduling device applied to a two-way single-vehicle road network, characterized in that, include: A network flow model determination module is used to determine a target network flow model corresponding to a target area in response to a vehicle meeting scheduling request event. The target network flow model includes: multiple nodes, pairs of reverse directed edges associated with the nodes, node attribute information corresponding to the nodes, and edge attribute information corresponding to each edge of the pairs of reverse directed edges. The nodes correspond to the vehicle meeting scheduling area of ​​the target area, the pairs of reverse directed edges correspond to the two-way single lanes of the target area, the node attribute information changes with the area usage information of the vehicle meeting scheduling area, and the edge attribute information changes with the road usage information of the two-way single lanes. The scheduling information determination module is used to analyze the preset driving path and vehicle driving information of at least one vehicle to be processed in the target area based on the target network flow model, and determine at least one scheduling information to be processed; wherein, the vehicle driving information includes at least: the driving position information, driving speed information, driving direction information and driving sequence information of the vehicle to be processed in the two-way single lane, and each type of scheduling information to be processed includes scheduling sub-information corresponding to the at least one vehicle to be processed. The vehicle simulation scheduling module is used to simulate scheduling the at least one vehicle to be processed according to the target network flow model for the at least one scheduling information to be processed, so as to determine the vehicle prediction trajectory information and the total vehicle waiting time corresponding to the at least one vehicle to be processed under each scheduling information to be processed. The vehicle meeting scheduling module is used to determine target scheduling information based on the vehicle prediction trajectory information corresponding to each type of scheduling information to be processed and the total waiting time of the vehicles corresponding to the vehicle prediction trajectory information, so as to perform vehicle meeting scheduling processing on the at least one vehicle to be processed based on the target scheduling information.

10. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the meeting scheduling method for a two-way single-vehicle road network as described in any one of claims 1-8.

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