Vehicle cooperative scheduling method and system for right-of-way conflict area

Abstract

The application discloses a kind of vehicle coordination scheduling method and system of traffic right conflict area, comprising: judging whether first traffic unit exists with second traffic unit simultaneously reaches the physical possibility of the entry boundary of conflict area, first traffic unit and second traffic unit are respectively closer and more distant traffic unit of conflict area;If no, determine a reachability conflict by the first traffic unit is directed to second traffic unit;According to the first type of relationship containing reachability conflict and the second type of relationship indicating traffic order exchangeable conflict, a conflict relationship graph is constructed with traffic unit as node, the first type of relationship and the second type of relationship are represented as different types of edges in conflict relationship graph;According to conflict relationship graph, generate traffic scheduling scheme so that each traffic unit safely passes through conflict area.The application can better reflect the physical limit under real mixed traffic environment, and the generated scheme is more feasible and safe.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation systems, and in particular to a method and system for coordinated vehicle scheduling in areas with conflicting right-of-way. Background Technology

[0002] With the development of intelligent transportation systems, connected automated vehicles (CAVs) are considered a key technology for solving urban traffic congestion and improving road safety. In areas with conflicting right-of-way conditions, such as unsignaled intersections, how to efficiently and safely coordinate the passage of multiple vehicles is a research hotspot in this field. Vehicles share their own state information through vehicle-to-infrastructure (V2I) communication, enabling a central coordinator to uniformly plan vehicle movements and determine the optimal passage order.

[0003] Early collaborative scheduling strategies often employed First-Come, First-Served (FCFS) or reservation-based resource allocation methods, which involved dividing the intersection into multiple spatiotemporal resource grids and allocating them sequentially to vehicles requesting passage. However, these strategies struggled to achieve optimal passage sequences in complex traffic scenarios, resulting in limited scheduling efficiency and flexibility.

[0004] To overcome the limitations of the aforementioned methods, subsequent research introduced graph theory models to describe the conflict relationships between vehicles. For example, by constructing a conflict-oriented directed graph, the vehicle scheduling problem is transformed into a graph search problem, such as solving for the optimal spanning tree to determine the passage order. However, existing vehicle cooperative scheduling methods based on graph theory models fail to fully consider the conflict relationships between vehicles, resulting in vehicle cooperative scheduling schemes that are not close enough to actual working conditions and have low practical feasibility. Summary of the Invention

[0005] This invention provides a vehicle collaborative scheduling method and system for right-of-way conflict areas, which addresses the problem that vehicle collaborative scheduling methods based on graph theory models fail to fully consider the conflict relationships between vehicles, resulting in vehicle collaborative scheduling schemes that are not close enough to actual working conditions and have low practical feasibility.

[0006] This invention provides a method for coordinated vehicle scheduling in areas with conflicting right-of-way, comprising: For any two access units in each access unit, determine whether there is a physical possibility that the first access unit and the second access unit can reach the entry boundary of the conflict area at the same time. The first access unit and the second access unit are the access units closer to and farther from the conflict area, respectively. If not, determine an accessibility conflict from the first access unit to the second access unit. Based on the first type of relation containing the reachability conflict and the second type of relation representing the commutative conflict of the passage order, a conflict relation graph with passage units as nodes is constructed. The first type of relation and the second type of relation are represented as edges of different types in the conflict relation graph. A traffic scheduling scheme is generated based on the conflict relationship diagram to enable each of the traffic units to safely pass through the conflict area.

[0007] The present invention also provides a vehicle cooperative scheduling system for right-of-way conflict areas, comprising: The accessibility constraint determination module is used to determine, for any two access units in each access unit, whether there is a physical possibility that the first access unit and the second access unit can simultaneously reach the entry boundary of the conflict area, where the first access unit and the second access unit are access units closer to and farther from the conflict area, respectively; if not, then it is determined that there is an accessibility conflict from the access unit closer to the conflict area to the access unit farther from the conflict area. The conflict relationship graph construction module is used to construct a conflict relationship graph with access units as nodes based on a first type of relationship that includes the reachability conflict and a second type of relationship that represents the exchangeable conflict of access order. The first type of relationship and the second type of relationship are represented as edges of different types in the conflict relationship graph. The traffic scheduling scheme generation module is used to generate a traffic scheduling scheme based on the conflict relationship diagram, which enables each of the traffic units to safely pass through the conflict area.

[0008] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle cooperative scheduling method for right-of-way conflict areas as described above.

[0009] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle cooperative scheduling method for right-of-way conflict areas as described above.

[0010] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the vehicle cooperative scheduling method for right-of-way conflict areas as described above.

[0011] Compared with the prior art, the vehicle cooperative scheduling method and system for right-of-way conflict areas provided by the present invention have the following beneficial effects: By introducing accessibility conflicts, determined by vehicle physical performance and serving as an irreversible traffic order constraint, we can prevent two physically impossible traffic units from being scheduled to enter the conflict zone simultaneously during scheduling. This avoids situations where one traffic unit waits for another, improving traffic efficiency and preventing rear-end collisions caused by waiting. Therefore, the scheduling model better reflects the physical constraints of real-world mixed traffic environments, resulting in more feasible and safer solutions. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating the vehicle collaborative scheduling method for right-of-way conflict areas provided by the present invention.

[0014] Figure 2 This is a schematic diagram of a conflict relationship diagram in one embodiment of the present invention.

[0015] Figure 3 This is a schematic diagram of intersection vehicle conflict analysis in one embodiment of the present invention.

[0016] Figure 4 This is a schematic diagram of a generation tree in one embodiment of the present invention.

[0017] Figure 5 This is a schematic diagram of a mixed formation in one embodiment of the present invention.

[0018] Figure 6 This is a schematic diagram of the intersection cooperation and control area in one embodiment of the present invention.

[0019] Figure 7 This is a schematic diagram of a coexisting undirected graph in one embodiment of the present invention.

[0020] Figure 8 This is a schematic diagram of a conflict sub-region in one embodiment of the present invention. Detailed Implementation

[0021] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0022] In the description of this invention, it should be noted that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0023] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0024] Reference Figure 1 The vehicle collaborative scheduling method for right-of-way conflict areas provided by this invention specifically includes: Step S110: For any two access units in each access unit, determine whether there is a physical possibility that the first access unit and the second access unit can reach the entry boundary of the conflict area at the same time. The first access unit and the second access unit are access units that are closer to and farther from the conflict area, respectively. If not, determine an accessibility conflict from the first access unit to the second access unit.

[0025] Step S120: Based on the first type of relationship containing reachability conflicts and the second type of relationship representing commutative conflicts of travel order, construct a conflict relationship graph with travel units as nodes. The first type of relationship and the second type of relationship are represented as edges of different types in the conflict relationship graph.

[0026] Step S130: Generate a traffic scheduling scheme based on the conflict relationship diagram to ensure that each traffic unit can safely pass through the conflict area.

[0027] In the above technical solution, the first step is to determine, for any two passing units, whether there is a physical possibility that the first passing unit and the second passing unit can simultaneously reach the entry boundary of the conflict area. Here, the first and second passing units are relative concepts, referring to the one closer to the conflict area and the other farther away, respectively. This determination aims to identify an inherent passing order determined by the vehicle's kinematic performance limitations. If the determination result is negative, meaning that the second passing unit cannot arrive before or simultaneously with the first passing unit under any circumstances, then an reachability conflict from the first passing unit to the second passing unit is identified. This step incorporates the vehicle's physical limits into the scheduling considerations, eliminating unrealistic scheduling possibilities from the outset and providing strict constraints that conform to physical reality for subsequent graph construction. By pre-determining this irreversible passing order, the search space of subsequent optimization algorithms can be significantly reduced, improving the speed and feasibility of generating scheduling schemes.

[0028] After identifying reachability conflicts, a conflict relationship graph with traffic units as nodes is further constructed. This graph includes not only the aforementioned reachability conflicts but also other types of conflict relationships. This invention categorizes these relationships into two types: Type I and Type II. Type I relationships represent conflicts where traffic order cannot be exchanged, typically including "separation conflicts" where preceding and following vehicles in the same lane must adhere to the rules, in addition to the aforementioned reachability conflicts. Type II relationships represent conflicts where traffic order can be negotiated and exchanged, such as "crossing conflicts" formed by the intersection of paths of vehicles in different lanes or "merging conflicts" formed by vehicles merging into the same lane. In the constructed conflict relationship graph, these two types of relationships are represented by different types of edges; for example, Type I relationships are represented by unidirectional edges, and Type II relationships are represented by bidirectional edges. This step transforms the complex, multi-dimensional inter-vehicle interaction problem into a structured, analyzable graph theory problem. In this way, conflicts of different natures are clearly distinguished and identified, laying the foundation for subsequent hierarchical and targeted optimization scheduling.

[0029] It should be noted that existing technologies typically only consider separation conflicts, merging conflicts, and cross-conflicts. This invention creatively introduces reachability conflicts into the conflict relationship graph, thereby more comprehensively modeling the conflict relationships between passage units. Based on this conflict relationship graph, a vehicle cooperative scheduling scheme that is more in line with the actual physical scenario can naturally be given.

[0030] Finally, based on the constructed conflict graph, a traffic scheduling scheme is generated that allows each traffic unit to safely pass through the conflict area. The core of this step is to use graph theory algorithms to solve the conflict graph to find one or a set of optimal traffic sequences. The generated scheduling scheme can be specifically represented by instructions such as the expected arrival time of each traffic unit, the number of traffic batches, and the speed trajectory within the conflict area. The principle is that any valid solution in the conflict graph (e.g., a loop-free traffic sequence) corresponds to a collision-free traffic scheme. By optimizing the graph structure, optimal solutions that satisfy specific performance indicators (such as highest traffic efficiency and lowest delay) can be systematically found.

[0031] In summary, this invention incorporates the kinematic parameters of traffic units by introducing accessibility conflict assessment. This avoids scheduling two traffic units that are physically impossible to reach the conflict zone entrance simultaneously, thus preventing one traffic unit from waiting for another. This not only improves traffic efficiency but also avoids rear-end collisions caused by stopping. Therefore, the scheduling model better reflects the physical constraints of real-world mixed traffic environments, resulting in more feasible and safer solutions. Furthermore, by constructing a conflict relationship graph that includes first-type relationships (such as non-commutable accessibility conflicts and separation conflicts) and second-type relationships (such as commutable intersection conflicts and merging conflicts), the complex constraints between different traffic units can be more accurately characterized, providing a more refined model foundation for subsequent optimization and making scheduling more flexible.

[0032] In some embodiments, determining whether there is a physical possibility that the first passage unit and the second passage unit arrive at the entry boundary of the conflict area simultaneously includes: based on the kinematic parameters of the first passage unit and the second passage unit, determining whether the second passage unit arrives at the entry boundary of the conflict area at a later time than the first passage unit after traveling at maximum acceleration and maximum speed; if so, determining that there is no physical possibility that the first passage unit and the second passage unit arrive at the entry boundary of the conflict area simultaneously.

[0033] Specifically, the system first obtains the current position, speed, and performance parameters of the second access unit (distant vehicle), such as maximum acceleration and maximum speed. Then, it calculates the shortest time required for the second access unit to accelerate to its maximum speed at maximum acceleration and travel at maximum speed to reach the boundary of the conflict zone. This shortest time is compared with the time it takes for the first access unit (nearby vehicle) to reach the same boundary at its normal or expected speed. If the calculation shows that even under extreme performance conditions, the arrival time of the second access unit is still later than that of the first access unit, it is determined that there is no physical possibility for the first access unit to arrive simultaneously with the second access unit; that is, there is an accessibility conflict between them, meaning that they cannot enter the conflict zone in the same batch in the scheduling scheme. Through this kinematic limit-based judgment, this method ensures that the determination of accessibility conflicts is based on physical reality, thereby avoiding the generation of any scheduling scheme that requires vehicles to make maneuvers beyond their physical performance, enhancing the practicality and safety of the scheduling scheme.

[0034] In some embodiments, the conflict graph is specifically a hybrid conflict directed graph (MCDG). For example... Figure 2 As shown, in a mixed-conflict directed graph, the first type of relationship is represented by unidirectional edges, which can include separation conflicts and the aforementioned reachability conflicts. Separation conflicts refer to the situation where two vehicles traveling in the same lane must pass before the vehicle behind; this is a natural and irreversible order relationship. The second type of relationship is represented by bidirectional edges, which can include intersection conflicts and merging conflicts. For example... Figure 3 As shown, the paths of traffic units VP2 and VP3 from different directions intersect at the intersection, forming a cross-collision; while the paths of traffic units VP2 and VP4 eventually merge into the same lane, forming a merging collision. Theoretically, the passage order of these two types of collisions is interchangeable; that is, VP2 can be scheduled to pass first, or VP3 can be scheduled to pass first, depending on which option brings better overall efficiency. By using unidirectional and bidirectional edges to distinguish between these two types of relationships, this hybrid collision directed graph can more accurately characterize the nature of the collisions, providing clear guidance for subsequent optimization algorithms: for nodes connected by unidirectional edges, their order is fixed; for nodes connected by bidirectional edges, their order is a variable to be optimized. This refined modeling approach creates conditions for implementing more flexible and efficient scheduling strategies.

[0035] In some embodiments, the process of generating a traffic scheduling scheme based on a conflict diagram can be a phased optimization process. Specifically, generating a traffic scheduling scheme that allows each traffic unit to safely pass through a conflict area based on the conflict diagram includes: performing a first-stage optimization based on the conflict diagram to determine the minimum number of traffic batches required for all traffic units to pass through the conflict area; performing a second-stage optimization under the constraint of the minimum number of traffic batches to determine the minimum average delay incurred when all traffic units pass through the conflict area; and performing a third-stage optimization under the constraints of the minimum number of traffic batches and the minimum average delay to determine the optimal traffic order when two traffic units with interchangeable traffic order conflicts pass through the conflict area, thus obtaining the traffic scheduling scheme.

[0036] The principle behind this three-stage optimization strategy is to decompose a complex multi-objective optimization problem into a series of sequential, more easily solvable subproblems. It first ensures the highest macroscopic throughput efficiency (fewest batches), then focuses on the individual user experience (minimum latency) while maintaining that, and finally, without affecting the first two, fine-tunes local conflicts to further explore energy-saving or security potential. Through this hierarchical optimization approach, this method can find a scheduling scheme that balances multiple performance dimensions while ensuring computational efficiency.

[0037] Furthermore, the first phase of optimization includes: finding the spanning tree with the minimum depth for the conflict graph; the depth of the spanning tree with the minimum depth is the minimum number of passing batches.

[0038] like Figure 4 As shown, it illustrates a spanning tree. A spanning tree is a graph structure that represents the passage order of all passing units, where the root node (e.g., VP0) can be considered a virtual guide, and the depth of the tree directly corresponds to the number of batches required for passage. Nodes at the same depth represent passing units that can be arranged in the same batch and pass through the conflict area in parallel. Therefore, the optimization objective of minimizing the number of passing batches is equivalent in graph theory to finding a spanning tree with the minimum depth that covers all nodes.

[0039] Furthermore, the optimization objective of the second stage can be specifically set as maximizing the number of vehicles that can travel side-by-side within each batch. This is inherently consistent with the objective of minimizing average delay, because with a fixed total number of batches, the more vehicles traveling together in each batch, the more compact the traffic flow becomes, and the shorter the average waiting time for vehicles. In graph theory models, this corresponds to accommodating as many non-conflicting nodes as possible at each level of the spanning tree. In addition, the optimization objective of the third stage can be specifically set as minimizing conflict duration. Conflict duration is the time required to clear the conflict, calculated based on parameters such as the length, speed, and distance from the conflict area of ​​the two vehicles involved. For commutative conflicts that can be represented by bidirectional edges, different travel orders will result in different conflict durations. By calculating and selecting the scheme with the shortest total duration, traffic efficiency and safety can be further improved at the micro level, reducing the interaction time of vehicles near the conflict point.

[0040] In some embodiments, the passage unit is a hybrid formation, each hybrid formation consisting of a lead connected autonomous vehicle and at least one follower connected human-driven vehicle.

[0041] Reference Figure 5 Specifically, the passage unit is a hybrid formation in a "1+n" pattern. VP Each mixed formation VP It consists of a lead connected autonomous vehicle (CAV) and at least one (n≥1) following connected human-driven vehicles (CHVs). The CAV, acting as the "brain" of the formation, is responsible for communicating with the scheduling system and executing driving decisions, while the CHVs automatically follow the CAV using a car-following model. By integrating heterogeneous CHVs with uncertain driving behavior into a predictable traffic unit led by the CAV, the entire mixed traffic flow becomes controllable and schedulable. This facilitates handling real-world mixed traffic scenarios and provides an application foundation for the cooperative scheduling method of this invention.

[0042] Furthermore, refer to Figure 6 The vehicle cooperative scheduling method is executed after the mixed formation enters the control area, which includes the conflict zone and is larger than the conflict zone. The mixed formation is formed by the organized operation of individual vehicles in the cooperation zone, which is the upstream area of ​​the control zone. Figure 6 In the scenario shown, the control area has a radius of [missing information]. The circular area, the cooperation zone is a ring with a width of The ring-shaped region.

[0043] Specifically, the vehicle cooperative scheduling method provided by this invention is executed after the mixed platoon enters the control zone. Control of the passing units entering the control zone is transferred to the cooperative scheduling system. Further upstream of the control zone, a cooperation zone (COOP) is established. In the cooperation zone, the mixed platoon is formed by individual vehicles; for example, CAVs and CHVs from different lanes communicate and negotiate within this area, and based on the destination and initial guidance from the scheduling system, complete lane changes and regrouping to form a stable platoon with the same direction. By dividing the cooperation zone and the control zone, this method achieves an orderly and smooth transition from free flow to controlled flow.

[0044] In one application scenario, the conflict zone is an unsignalized intersection, and the boundary of the conflict zone is the stop line for vehicles before the unsignalized intersection.

[0045] Specifically, the conflict zone can be a typical unsignaled intersection, and the entry boundary of the conflict zone is correspondingly the stop lines for vehicles entering from each direction of the unsignaled intersection. This is a typical application scenario of the method of this invention. Using the stop lines as entry boundaries provides a unified and clear benchmark for all calculations (such as arrival time, remaining distance, etc.), simplifies the complexity of the model, and makes it easy to deploy on existing road infrastructure.

[0046] It should be noted that all vehicles passing through an intersection may clash within the intersection area, thus defining the intersection as a general conflict zone. For any two specific vehicles, if the area where they clash falls within the intersection, then the area where the two specific vehicles clash can be defined as a conflict sub-region.

[0047] The following describes a specific embodiment of the present invention in a specific scenario.

[0048] In a specific application scenario, refer to Figure 6 The vehicle cooperative scheduling method for right-of-way conflict zones of the present invention can be applied to an unsignalized intersection containing a right-of-way conflict zone. This zone is divided into a cooperative zone and a control zone. When a vehicle enters a length of... When in a collaborative zone, information can be exchanged with a central coordinator. Within this zone, vehicles with the same driving intent can be organized into traffic units and guided to the correct lanes before entering the controlled zone. The controlled zone is the core area containing the actual right-of-way conflict points, and its length is [length missing]. The passage units entering the control area will be entirely controlled by the central coordinator according to the collaborative scheduling method of the present invention, in order to form a safe and efficient passage sequence. This system architecture, through regional division and centralized coordination, lays the foundation for subsequent refined scheduling.

[0049] The passage unit can be a mixed formation. (See reference...) Figure 5 This hybrid convoy consists of a lead connected autonomous vehicle (CAV) and at least one following connected human-driven vehicle (CHV). This structure can adapt to mixed traffic scenarios with varying penetration rates of connected autonomous vehicles. The lead CAV can communicate bidirectionally with the central coordinator, receiving dispatch instructions and reporting its own status, while the following CHVs only need to transmit their position, speed, and other information unidirectionally to the central coordinator. By scheduling this hybrid convoy as a single traffic unit, the scale of the scheduling problem and the complexity of communication are significantly reduced, enabling the algorithm to handle larger vehicle groups and thus improving the practical applicability of the solution.

[0050] To ensure the stability of this mixed formation during scheduling, i.e., to guarantee that it can be considered a rigidly connected passage unit, the dynamics of the vehicles within the formation need to be modeled. For the leading connected autonomous vehicle (CAV), a second-order linear system model can be used to describe its motion state, as shown below: ; ; ; ; in, It is the state vector of the connected autonomous vehicle i at time t, including its remaining distance to the stop line. and speed ; A represents the control input (including acceleration and steering angle, etc.) of the connected autonomous vehicle i at time t; A and B are state matrices. This represents the dynamic delay of connected autonomous vehicle i. This represents the acceleration of connected autonomous vehicle i.

[0051] Meanwhile, the movement of connected autonomous vehicles is subject to physical constraints; their speed and acceleration must be within preset ranges, as shown below: ; ; in, For maximum speed limit, and These are the maximum deceleration and maximum acceleration limits, respectively. This model provides the mathematical basis for precisely controlling the trajectory of the navigator.

[0052] For connected human-driven vehicles (CHVs) following within a platoon, their behavior can be described by an improved Helly car-following model, as follows: ; in, It is the acceleration of the connected, human-driven vehicle i. and These parameters are determined based on the driver response-stimulus model. It is the driver's reaction time. It is the expected following distance between the connected, human-driven vehicle i and the preceding vehicle i-1. It is the distance between connected, manually driven vehicle i and the preceding vehicle i-1. It is the relative speed between the connected, manually driven vehicle i and the preceding vehicle i-1.

[0053] To analyze formation stability, the position error of the connected human-driven vehicle i relative to the lead CAV can be defined. and speed error : ; in, and These are the position and speed of the lead CAV, respectively. and These are the position and speed of the connected, manually driven vehicle i, respectively. It is the expected distance between the connected human-driven vehicle i and the pilot CAV.

[0054] Based on this, the car-following model can be reconstructed into the following error system equations: ; in, The adjacency matrix of CHV Element, definition , , Then the error system equation can be transformed into the following: ; in, , and They are represented as follows: ; ; ; in, .

[0055] The position and velocity difference between the CHV in the middle of the vehicle and the CAV at the front of the vehicle must satisfy the boundedness condition: ; ; When the vehicle is running, the system When boundedness is satisfied, then a 1+n mixed formation is a stable and controllable vehicle formation.

[0056] After organizing vehicles into stable traffic units, the collaborative scheduling method provided by this invention begins to execute.

[0057] The first step of this method is to determine, for any two access units in each access unit, whether there is a physical possibility that the first access unit and the second access unit can simultaneously reach the entry boundary of the conflict area. The first access unit and the second access unit are the access units closer to and farther from the conflict area, respectively. If not, then an reachability conflict from the first access unit to the second access unit is determined. Traditional conflict analysis refers to... Figure 3 Typically, only geometrical path conflicts are considered, such as the intersection conflict between traffic units VP2 and VP3, the merging conflict between VP2 and VP4, and the separation conflict between VP6 and VP7. However, these analyses neglect an implicit constraint caused by limitations in vehicle physical motion performance. For example, in Figure 3 In the scenario where traffic unit VP5 is about to reach the stop line, another traffic unit VP7, which is still some distance away, also enters the control zone. At this point, even with maximum acceleration, traffic unit VP7 cannot arrive before traffic unit VP5 crosses the intersection; that is, the second traffic unit (VP7) cannot physically arrive at the conflict area before the first traffic unit (VP5). Therefore, a fixed and irreversible traffic order is formed between them, with the first traffic unit (VP5) leading to the second traffic unit (VP7). Introducing this constraint allows the model to fully consider the physical limits of vehicle movement, avoiding the generation of unrealistic scheduling instructions and enhancing the feasibility and safety of the solution.

[0058] Specifically, determining whether the irreversible passage order constraint exists can be done by calculating the shortest time required for passage unit j to reach the stop line at maximum capacity. : ; in, It is the preset expected speed. and These are the maximum acceleration and velocity. It is the length of the control area. It is the length difference between two passage units i and j. This is the distance from the stop line to the center of the intersection. When traffic unit i reaches the boundary of the control zone, if the current state of traffic unit j satisfies: ; That is, the shortest theoretically reachable distance of passage unit j. If the position is still greater than the current position of passage unit i, then it is determined that passage unit i constitutes an irreversible passage order constraint on passage unit j.

[0059] By introducing and quantifying this irreversible passage order constraint, this embodiment ensures that the generated scheduling scheme is physically feasible, avoiding scheduling results that violate vehicle kinematics that may occur in the prior art.

[0060] After identifying the various conflict relationships between travel units, the next step of the method is to treat irreversible travel order constraints as a second type of relationship where travel order is non-commutative, and combine this with a first type of relationship representing commutative conflicts, to construct a conflict relationship graph with travel units as nodes. In this graph, the first and second types of relationships are represented as edges of different types. (Refer to...) Figure 2 This conflict graph is a graph theory model that unifies complex constraints. Specifically, the edges in the conflict graph are divided into two types: the first type represents conflicts where the passage order is commutable, such as intersection conflicts and merging conflicts. The passage order can be adjusted according to the optimization objective, and this type can be represented by a specific identifier (e.g., a bidirectional edge) in the conflict graph. The second type represents conflicts where the passage order is not commutable; the passage order is fixed and irreversible. This includes traditional separation conflicts and the irreversible passage order constraints (i.e., reachability conflicts) introduced in this embodiment, and this type can be represented by another specific identifier (e.g., a unidirectional edge) in the conflict graph. This modeling approach, which distinguishes between conflicts of different natures, provides a structured foundation for subsequent phased optimization, ensuring that the scheduling problem satisfies hard constraints while preserving optimization space.

[0061] Based on the conflict relationship diagram constructed above, this embodiment proposes a three-stage cooperative scheduling optimization method. This method decomposes the complex scheduling problem into three sequential sub-objectives for optimization, generating the final traffic scheduling scheme in sequence. Vehicles first form traffic units during the lane-changing and formation stage, then the following three-stage optimization algorithm is executed during the optimization stage, and finally, control is implemented based on the optimization results during the execution stage.

[0062] The first step of the three-stage optimization is to perform a first-stage optimization based on the conflict graph to determine the minimum number of travel batches required for all travel units to pass through the conflict area, thereby generating a first set of candidate scheduling schemes. In graph theory, this objective is equivalent to finding a spanning tree with the minimum depth of the conflict graph. According to graph theory principles, travel units corresponding to nodes of the same depth in the spanning tree do not conflict and can pass in parallel. Therefore, minimizing the depth of the spanning tree is equivalent to minimizing the number of travel batches. To achieve this objective, this embodiment introduces a coexisting undirected graph CUG (such as...) that is complementary to the conflict graph. Figure 7 As shown in the diagram, if there is no conflict between two traveling units, an edge is connected between the nodes corresponding to these two traveling units. Therefore, the first stage of optimization is specifically implemented by solving the Minimum Clique Covering (MCC) problem of the coexisting undirected graph CUG. A clique is a complete subgraph in the CUG, representing a group of traveling units that can travel in parallel. The minimum clique cover problem is to find the minimum number of cliques to cover all nodes in the graph. This minimum number is the minimum number of travel batches. By solving the minimum clique cover problem, one or more candidate scheduling schemes that all satisfy the minimum number of travel batches requirement can be obtained. These schemes together constitute the first set of candidate scheduling schemes.

[0063] Next, under the constraint of the minimum number of traffic batches determined by the first-stage optimization, the method performs a second-stage optimization on the first set of candidate scheduling schemes. This second-stage optimization minimizes the average delay of all traffic units by maximizing the number of traffic units that can travel in parallel within each batch, thus generating a second set of candidate scheduling schemes. Average delay is directly related to the waiting time of traffic units in the intersection area, and the key to reducing waiting time lies in maximizing parallelism. The first-stage optimization may yield multiple solutions with the same minimum number of traffic batches (i.e., the first set of candidate scheduling schemes), but the number of nodes (traffic units) contained in each cluster (batch) of these solutions may differ. Therefore, the second-stage optimization selects the solution with the largest average number of nodes within a cluster from the first set of candidate scheduling schemes. A larger average number of nodes within a cluster means that within a fixed number of batches, the total number of traffic units passing in parallel is greater, resulting in higher overall system efficiency and effectively reducing the average delay of all traffic units. After this stage of optimization, the selected schemes constitute the second set of candidate scheduling schemes.

[0064] Finally, the method performs a third-stage optimization on the second group of candidate scheduling schemes, including: calculating the passage cost based on a preset passage cost model for conflict relationships where the order of passage can be exchanged between passage units; and minimizing the total passage cost of the scheduling scheme by determining the optimal passage order for these conflict relationships, thereby generating the final passage scheduling scheme. This stage involves fine-tuning at the micro level based on the already determined macro-scheduling structure (number of batches and batch division). The passage cost here mainly targets the first type of relationship where the passage order can be exchanged (i.e., cross-conflict and merging conflict). For these conflicts, although passage units are assigned to different batches, the specific order still has room for adjustment, and different orders will produce different passage costs. In this embodiment, this passage cost is quantified as the conflict duration.

[0065] For example, in a scenario where the conflict area is an intersection, the calculation method is as follows: ; in, This represents the distance from the stop line to the point where traffic unit i exits the conflict sub-region. This represents the distance from the stop line to the point where traffic unit i enters the conflict sub-region. This represents the distance from the stop line to the exit of the conflict sub-region for passage unit j. This represents the distance from the stop line to the point where traffic unit j enters the conflict sub-region. (See reference...) Figure 8 Here, the conflict sub-region refers to the local region where passage units i and j specifically generate a conflict within the conflict region. It is the passage cost between passage units i and j. and These are the lengths of passage units i and j, respectively. and These are the distance differences between the current positions of passage units i and j and the conflict sub-region, respectively. and These are the speeds of passage units i and j, respectively. It is a safe time interval.

[0066] The third optimization stage involves finding a scheme that minimizes the total travel cost (i.e., the sum of the weights of all conflicting edges) by adjusting the passage order of all exchangeable conflicting pairs from the second set of candidate scheduling schemes. This scheme is the final travel scheduling scheme. Through these three progressively layered optimizations, this invention achieves a comprehensive optimization of scheduling efficiency and travel cost while ensuring safety and physical feasibility.

[0067] In summary, the present invention has the following technical effects: First, by introducing a three-stage optimization strategy, this invention can systematically solve the collaborative scheduling problem: the first stage determines the minimum number of passing batches to ensure macro-level efficiency; the second stage minimizes the average delay while considering individual interests; and the third stage minimizes the total passage cost to achieve micro-level fine-tuning. This progressive optimization approach enables the scheduling scheme to achieve a superior level at both the macro and micro levels. Second, the method proposed in this invention has stronger real-world adaptability. By defining the passing unit as a mixed formation and introducing irreversible passage order constraints determined by vehicle physical performance, the scheduling model can better reflect the physical constraints in real mixed traffic environments, resulting in more feasible and secure schemes. Third, this invention transforms the complex scheduling problem into a graph theory optimization problem, such as solving for the minimum clique cover and minimizing the edge weight sum. Compared to traditional mixed integer programming methods, this significantly reduces computational complexity, improves solution efficiency, and is more suitable for real-time traffic control scenarios. Finally, by introducing passage cost as an optimization metric for exchangeable conflicts, this invention enables more precise adjustments to the passage order, effectively reducing additional delays caused by conflict avoidance without affecting the minimum number of passage batches, and improving the overall operational quality of the system.

[0068] The present invention also provides a vehicle cooperative scheduling system for areas with right-of-way conflicts. The system may be a central coordinator deployed in a roadside unit or a cloud server. Its internal structure may include a processor and a memory. The memory stores a computer program. When the processor executes the program, it implements the above-mentioned vehicle cooperative scheduling method.

[0069] Specifically, the system may include: The accessibility constraint determination module is used to determine, for any two access units in each access unit, whether there is a physical possibility that the first access unit and the second access unit can reach the entry boundary of the conflict area at the same time. The first access unit and the second access unit are access units that are closer to the conflict area and those that are farther away from the conflict area, respectively. If not, it is determined that there is an accessibility conflict from the access unit that is closer to the conflict area to the access unit that is farther away from the conflict area. The conflict graph construction module is used to construct a conflict graph with access units as nodes based on a first type of relationship containing reachability conflicts and a second type of relationship representing commutable conflicts of access order. The first and second types of relationships are represented as different types of edges in the conflict graph. The traffic scheduling scheme generation module is used to generate a traffic scheduling scheme based on the conflict relationship diagram, which enables each traffic unit to safely pass through the conflict area.

[0070] This system incorporates accessibility conflict assessment, taking into account the kinematic parameters of traffic units. This prevents two physically impossible traffic units from being scheduled to enter the conflict zone simultaneously during scheduling. This avoids situations where one traffic unit waits for another, improving traffic efficiency and preventing rear-end collisions caused by waiting. Therefore, the scheduling model better reflects the physical constraints of real-world mixed traffic environments, resulting in more feasible and safer solutions.

[0071] It should be noted that the vehicle collaborative scheduling system for right-of-way conflict areas provided by this invention is used to implement the vehicle collaborative scheduling method for right-of-way conflict areas provided by this invention. Therefore, the specific functions of each model in this system can be found in the detailed description of the vehicle collaborative scheduling method in this invention.

[0072] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the vehicle cooperative scheduling method for right-of-way conflict areas provided by the above methods.

[0073] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle cooperative scheduling method for right-of-way conflict areas provided by the above methods.

[0074] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0075] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for coordinated vehicle scheduling in areas with conflicting right-of-way, characterized in that, include: For any two access units in each access unit, determine whether there is a physical possibility that the first access unit and the second access unit can reach the entry boundary of the conflict area at the same time. The first access unit and the second access unit are the access units closer to and farther from the conflict area, respectively. If not, determine an accessibility conflict from the first access unit to the second access unit. Based on the first type of relation containing the reachability conflict and the second type of relation representing the commutative conflict of the passage order, a conflict relation graph with passage units as nodes is constructed. The first type of relation and the second type of relation are represented as edges of different types in the conflict relation graph. A traffic scheduling scheme is generated based on the conflict relationship diagram to enable each of the traffic units to safely pass through the conflict area.

2. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 1, characterized in that, A traffic scheduling scheme is generated based on the conflict relationship diagram to ensure that each passage unit can safely pass through the conflict area, specifically including: Based on the conflict relationship diagram, a first-stage optimization is performed to determine the minimum number of passage batches required for all passage units to pass through the conflict area. Under the constraint of the minimum number of passage batches, a second-stage optimization is performed to determine the minimum average delay generated when all passage units pass through the conflict area; Under the constraints of the minimum number of passage batches and the minimum average delay, a third-stage optimization is performed to determine the optimal passage order when two passage units with exchangeable passage order conflicts pass through the conflict area, so as to obtain the passage scheduling scheme.

3. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 1, characterized in that, The passage unit is a mixed formation, each of which consists of a lead connected autonomous vehicle and at least one follower connected human-driven vehicle.

4. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 3, characterized in that, The vehicle cooperative scheduling method is executed after the mixed formation enters the control area, which includes the conflict area and is larger than the conflict area. The mixed formation is formed by the organized vehicles in the cooperation zone, which is the upstream area of ​​the control zone.

5. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 1, characterized in that, The conflict zone is an unsignalized intersection, and the entry boundary of the conflict zone is the vehicle stop line before the unsignalized intersection.

6. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 1, characterized in that, Determining whether there is a physical possibility that the first passage unit and the second passage unit arrive at the entry boundary of the conflict area simultaneously includes: Based on the kinematic parameters of the first passage unit and the second passage unit, it is determined whether the second passage unit, after traveling at maximum acceleration and maximum speed, reaches the entry boundary of the conflict area at a time later than the time the first passage unit reaches the entry boundary of the conflict area. If so, it is determined that there is no physical possibility that the first passage unit and the second passage unit reach the entry boundary of the conflict area at the same time.

7. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 1, characterized in that, The conflict relationship graph is a mixed conflict directed graph. The first type of relationship is represented by a unidirectional edge and includes separation conflict and reachability conflict. The second type of relationship is represented by a bidirectional edge and includes crossing conflict and merging conflict.

8. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 2, characterized in that, The first stage of optimization includes: finding a spanning tree with minimum depth for the conflict graph; The minimum depth of the spanning tree is the minimum number of passing batches.

9. The vehicle collaborative scheduling method for right-of-way conflict areas according to claim 2, characterized in that, The goal of the second phase of optimization is to maximize the number of passage units that can pass side-by-side in each batch; And / or, the optimization objective of the third stage is to minimize the conflict duration, which is the time required to clear the conflict calculated based on the length, speed, and distance from the conflict area of ​​the two passage units associated with the conflict.

10. A vehicle collaborative scheduling system for right-of-way conflict areas, characterized in that, include: The accessibility constraint determination module is used to determine, for any two access units in each access unit, whether there is a physical possibility that the first access unit and the second access unit can simultaneously reach the entry boundary of the conflict area, where the first access unit and the second access unit are access units closer to and farther from the conflict area, respectively; if not, then it is determined that there is an accessibility conflict from the access unit closer to the conflict area to the access unit farther from the conflict area. The conflict relationship graph construction module is used to construct a conflict relationship graph with access units as nodes based on a first type of relationship that includes the reachability conflict and a second type of relationship that represents the exchangeable conflict of access order. The first type of relationship and the second type of relationship are represented as edges of different types in the conflict relationship graph. The traffic scheduling scheme generation module is used to generate a traffic scheduling scheme based on the conflict relationship diagram, which enables each of the traffic units to safely pass through the conflict area.

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