Highway ramp merging control method and device based on platoon cooperation

Abstract

This application belongs to the field of computer science, specifically relating to a method and apparatus for highway ramp merging control based on platooning cooperation. The method includes: acquiring real-time driving information of vehicles on the mainline and ramps in a target area, the driving information including current position, speed, acceleration, and lane number of the vehicle; summarizing the vehicle driving information, and based on a platooning cooperation trajectory optimization model, planning the trajectories and merging order of all vehicles in the target area to obtain an optimization scheme, the optimization scheme including platooning decisions, lane-changing decisions, merging order, and vehicle trajectories; and generating control commands based on the optimization scheme, the control commands being used to control the movement of target vehicles. The method of this application improves traffic efficiency and safety in ramp merging areas.

Description

Technical Field

[0001] This application relates to the field of computer technology, specifically to a method and device for highway ramp merging control based on formation coordination. Background Technology

[0002] Highway merging ramps are prone to traffic congestion and safety issues. Traditional methods lack detailed modeling of multi-lane environments when handling lane changes and platooning control, making it difficult to effectively coordinate vehicle trajectories and achieve efficient and safe merging. With the development of vehicle-to-everything (V2X), autonomous driving, and high-precision positioning technologies, closed-loop collaboration between vehicles, roadside, and the cloud has become possible, but the traffic efficiency of merging ramps still needs improvement. Summary of the Invention

[0003] This application provides a method and apparatus for controlling highway ramp merging based on formation coordination, which can improve the traffic efficiency of ramp merging areas.

[0004] In a first aspect, embodiments of this application provide a highway ramp merging control method based on formation coordination, including: Real-time acquisition of vehicle driving information on the main line and ramps of the target area, including current location information, speed, acceleration and the lane number to which the vehicle belongs; By aggregating vehicle driving information and using a platooning cooperative trajectory optimization model, trajectory and merging sequence planning are performed for all vehicles in the target area to obtain an optimization scheme. The optimization scheme includes platooning decision, lane change decision, merging sequence, and vehicle trajectory. Control commands are generated based on the optimization scheme, and these control commands are used to control the movement of the target vehicle.

[0005] Secondly, embodiments of this application provide a highway ramp merging control device based on formation cooperation, comprising: The acquisition module is used to acquire the driving information of vehicles on the main line and ramps in the target area. The driving information includes the current location information, speed, acceleration and the lane number to which the vehicle belongs. The decision module is used to aggregate vehicle driving information and, based on the formation cooperative trajectory optimization model, plan the trajectory and merging order of all vehicles in the target area to obtain an optimization scheme. The optimization scheme includes formation decision, lane change decision, merging order and vehicle trajectory. An execution module is used to generate control commands based on the optimization scheme, the control commands being used to control the movement of the target vehicle.

[0006] Thirdly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any of the above-mentioned embodiments.

[0007] Fourthly, embodiments of this application provide 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 computer program to implement the method described in any of the above-mentioned embodiments. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of this application 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 only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 A flowchart illustrating the highway ramp merging control method based on formation cooperation according to an embodiment of this application is shown. Figure 2 This diagram illustrates a single-lane mainline in an application scenario of the highway ramp merging control method based on formation cooperation, according to an embodiment of this application. Figure 3a and Figure 3b The acceleration and velocity curves of the highway ramp merging control method based on formation cooperation in this application scenario are shown respectively. Figure 4 The image shows a position curve diagram illustrating an application scenario of the highway ramp merging control method based on formation cooperation according to an embodiment of this application. Figure 5 This diagram illustrates a two-lane mainline application scenario two of the highway ramp merging control method based on formation cooperation according to an embodiment of this application. Figure 6a and Figure 6b The diagrams show the position curves of different lanes in application scenario two of the highway ramp merging control method based on formation cooperation according to the embodiments of this application. Figure 7 This diagram illustrates the structure of a highway ramp merging control device based on formation coordination, according to an embodiment of this application. Figure 8 This diagram illustrates the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0010] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0011] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. 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 limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0012] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0013] See Figure 1 This application provides a highway ramp merging control method based on formation cooperation, including: S1. Real-time acquisition of vehicle driving information on the main line and ramps in the target area, including current location, speed, acceleration and the lane number to which the vehicle belongs; S2. Summarize the driving information of vehicles, and based on the formation cooperative trajectory optimization model, plan the trajectory and merging order of all vehicles in the target area to obtain the optimization scheme. The optimization scheme includes formation decision, lane change decision, merging order and vehicle trajectory. S3. Generate control commands based on the optimization scheme. The control commands are used to control the movement of the target vehicle.

[0014] In this embodiment, by collecting real-time traffic status information from the vehicle end and roadside system, information such as the position, speed, acceleration, and lane number of vehicles on the mainline and ramps can be obtained. Based on this information, the adjacency relationship of vehicle queues and the overall traffic status can be constructed in real time. Based on the vehicle platooning cooperative trajectory optimization model for multi-lane and ramp merging scenarios, joint trajectory planning and sequence optimization of vehicles on the mainline and ramps can be performed, thereby generating control commands. When vehicles execute the control commands, safe and efficient trajectory tracking and merging operations can be completed. The method of this embodiment is geared towards intelligent connected vehicle environments, introducing vehicle platooning and multi-lane cooperative lane-changing mechanisms, significantly improving traffic efficiency and safety in ramp merging areas, and is applicable to traffic control in complex highway merging scenarios.

[0015] The steps in the method of this application embodiment can be implemented by the same unit or by different units. For example, each step can be implemented by the vehicle-side system, or by the server, or by the vehicle-side system and the server respectively. The server may include a cloud platform. In specific implementations, the real-time driving information of the vehicle can be collected in real time by the vehicle-side system. Steps such as driving information aggregation, trajectory and merging sequence planning, and generation of control commands can be implemented by the cloud platform. Data aggregation to the cloud platform and processing by the cloud platform can improve the computing speed, reduce the computing load of the vehicle-side system, alleviate the burden on the vehicle-side system, and reduce the hardware requirements of the vehicle-side system. In some embodiments, the target area can be a region within a certain distance near the sluice gate. Specifically, the target area can be the region between a first distance before the sluice gate and the sluice gate itself. Alternatively, the target area can be the region between a first distance before the sluice gate and a second distance after the sluice gate. The values ​​of the first distance and the second distance can be the same or different. In an exemplary embodiment, the value of the first distance can range from 100m to 500m. For example, 100m, 150m, 200m, 300m, 350m, 400m, and 450m. The value of the second distance can range from 50m to 500m. For example, 100m, 150m, 200m, 300m, 350m, 400m, and 450m.

[0016] In some embodiments, real-time acquisition of vehicle driving information on the mainline and ramps of the target area includes: Get the vehicle's current location Current location Let be a continuous variable, representing the first... The car is in the lane At the moment The longitudinal position; Get vehicle speed vehicle speed Let be a continuous variable, representing the first... The car is in the lane At time (TimeStep) speed; Obtain vehicle acceleration Vehicle acceleration Let be a continuous variable, representing the first... The car is in the lane At the moment The acceleration; Get the lane number of the vehicle This is used to identify the lane the vehicle is currently in; Sampling time ,time This represents the discrete time series corresponding to the data acquisition.

[0017] In some embodiments, based on the formation cooperative trajectory optimization model, trajectory and merging sequence planning is performed for all vehicles in the target area, including: Establish a vehicle queue adjacency relationship model and use adjacency determination variables. and lane-changing decision variables Dynamically model and determine the real-time structure of all vehicle queues in a multi-lane environment. , The vehicle number is an integer index that uniquely encodes vehicles entering the target area. , Lane numbering, The sampling time.

[0018] In some embodiments, vehicles on the mainline and ramps can be coded uniformly or separately, while maintaining the uniqueness of vehicle numbers. When the mainline and / or ramps have multiple lanes, vehicles in each lane can also be coded separately. In specific implementations, vehicle codes can be a combination of letters and numbers. Letters are used to distinguish the lane a vehicle is in when entering the target area, and numbers can be incremented according to the order of entry into the target area. For example, if the mainline and ramps each have one lane, vehicles on the mainline can be coded according to the order of entry into the target area, with vehicle numbers M1, M2, M3, etc., sequentially. Vehicles on the ramps can be coded according to the order of entry into the target area, with vehicle numbers R1, R2, R3, etc., sequentially.

[0019] In some embodiments, a vehicle queue adjacency relationship model is established, using adjacency determination variables. and lane-changing decision variables Dynamic modeling and discrimination of the real-time structure of all vehicle queues in a multi-lane environment, including: Define the queue adjacency determination variable It is a 0-1 variable, representing time. ,Lane Get on the vehicle and vehicles Are they in adjacent positions? If so... ,otherwise ; Define lane-changing decision variables It is a 0-1 variable, if at time... vehicle From the lane Change lanes to ,So ,otherwise .

[0020] Queue Adjacency Determination Variable Dynamically updated, based on queue adjacency determination variables The distinction between adjacent and separated queues includes consecutive adjacent, indirect adjacent, lane-changing separation, and interval separation. Consecutive adjacent refers to vehicles... and In the same lane, directly adjacent to each other without changing lanes, at this time... Indirectly adjacent are vehicles and All vehicles in between have changed lanes and left, making it possible for them to pass. New direct adjacencies are formed, at this time Lane separation for vehicles and If any one or two vehicles in the lane change, causing them to no longer be adjacent, then... ; Separation into vehicles and There are other vehicles that have not changed lanes, and the two are not adjacent. .

[0021] In some embodiments, the queue adjacency relationship described above can be implemented using the following constraint logic:

[0022]

[0023]

[0024] Where M is a large positive number, and the value of M is much larger than the value of the maximum distance between vehicles or the upper bound of the maximum state variable. In a specific embodiment, M can be 9999. These are all vehicle numbers, which serve as indices for the vehicle set.

[0025] Formula (1) describes the indirect adjacency determination logic for vehicle queues. At time... If the lane Upper position in vehicle With vehicles any intermediate vehicle between Occurred from the lane To other lanes Lane changing behavior, then vehicles are allowed With vehicles They are considered adjacent. If the vehicle in the middle does not change lanes, then the vehicles... With vehicles They are not allowed to be classified as adjacent.

[0026] Formula (2) is used to describe vehicles. With vehicles Two vehicles can be considered adjacent if neither has changed lanes and all intermediate vehicles have changed lanes and left. or vehicle If it changes lanes, it will do so through large numbers. This invalidates the adjacency relationship.

[0027] Formula (3) is used to guarantee that once the vehicle With vehicles Determined to be adjacent ( When the queue topology is consistent, no lane-switching behavior is allowed between the two queues at that moment.

[0028] Through the above modeling and constraints, it is possible to accurately identify and dynamically maintain the four relationships of continuous adjacency, indirect adjacency, lane-changing separation, and interval separation in complex traffic environments, ensuring the real-time performance and accuracy of the vehicle queue topology.

[0029] In some embodiments, the driving information of vehicles is aggregated, and based on the formation cooperative trajectory optimization model, the trajectories and merging order of all vehicles in the target area are planned to obtain an optimization scheme, including: modeling the vehicle formation relationship and introducing formation intention variables. Formation state variables In addition to dynamic safety distance constraints, automatic coordinated platooning control of vehicles within the queue is achieved. Specifically, this may include the following steps: Formation Intent Variables A 0-1 variable, representing a vehicle. In the lane ,time Does the vehicle intend to form a convoy with the vehicle in front? If so, ,otherwise ; Formation state variables A 0-1 variable, representing a vehicle. In the lane ,time Has the vehicle already formed a convoy with the vehicle in front? If so, then... ,otherwise ; Vehicle platooning relationships include dynamically switchable free-roaming, proposing platooning, and already-platooned phases, with safety distance constraints applied based on each phase. Specifically, during the free-roaming phase... If vehicles are not planned to form a platoon and have not actually formed a platoon, then the distance between the vehicle in front and the vehicle in front must meet the non-platoon safety headway constraint; during the planned platooning phase... When a vehicle intends to form a platoon with the vehicle in front, but has not yet actually entered the platoon, the distance between the two vehicles is allowed to gradually converge towards a platooned state; during the platooning phase... The vehicles have formed a stable formation with the vehicle in front, and the spacing is allowed to be reduced to within the safe distance range for the formation.

[0030] This application defines formation intent variables in its embodiments. and formation state variables By dividing vehicle platooning into three dynamically switchable stages and applying safety distance constraints based on different stages, dynamic formation and disbanding of vehicle platoons can be achieved, effectively supporting safe and efficient collaborative driving of vehicles under different traffic conditions and improving traffic efficiency and stability in merging areas.

[0031] In some embodiments, the distance between a vehicle and the vehicle in front satisfies the following constraints in the three formation states: free-roaming phase, intended formation phase, and already formed formation phase:

[0032]

[0033]

[0034]

[0035] in, This is the minimum headway for non-platoon trains. To minimize the headway of the train in the formation, For vehicle length, The maximum allowable spacing variation for the formation.

[0036] Formula (4) is used to constrain the time at time ,Lane On, when the vehicle Before any formation intention is generated, the vehicles The vehicle in front of it The minimum safe longitudinal spacing between them must be met in the non-formation state. When the formation intention variable... When this constraint takes effect, the vehicle... With vehicles longitudinal distance Not less than the vehicle Current speed Minimum headway in non-formation and vehicle length The safety distance jointly determined; when At that time, through large numbers This invalidates the constraint, thus reserving space for subsequent formation state switching.

[0037] Formula (5) is used to describe the time at time 10:00. ,Lane On, when the vehicle When the intention to form a formation has been expressed but the formation has not yet been entered, the vehicles With vehicles The minimum permissible longitudinal distance constraint between them. When This constraint takes effect at that time, allowing vehicle spacing to be within the minimum headway of the formation. Based on this, and taking into account the vehicle length L, while allowing for deviations not exceeding the maximum allowable value. It gradually converges within the range; when At that time, through large numbers This invalidates the constraint.

[0038] Formula (6) is used to limit the time to time. ,Lane Up, vehicle With vehicles The maximum permissible longitudinal spacing under the condition of being in formation and adjacent. When the formation state variable... And adjacent decision variables This constraint takes effect at that time, and the distance between vehicles must not exceed the distance between the lead vehicles in the platoon. Vehicle length L and maximum permissible deviation A defined upper bound; when not in a formation or not adjacent, this constraint is passed through a large number of cases. Automatically expired.

[0039] Formula (7) is used to constrain the logical consistency between the formation intention variable and the formation state variable, that is, at time t. ,Lane Up, vehicle Only when there is a formation intention Only under certain conditions is it allowed to enter the actual formation state. .

[0040] Through the aforementioned variables and constraints, dynamic formation and disbanding of vehicle platoons are achieved, effectively supporting safe and efficient collaborative driving of vehicles under different traffic conditions and improving traffic efficiency and stability in merging areas.

[0041] In some embodiments, the driving information of vehicles is aggregated, and based on the formation cooperative trajectory optimization model, the trajectories and merging order of all vehicles in the target area are planned to obtain an optimization scheme, including: The following joint constraints are applied to the continuity and scale of vehicle platooning, lane change safety and platooning coordination, and the safe distance between vehicles on the mainline and ramps in the merging area: Formation continuity and size constraints: Ensure that vehicles remain continuous once they enter a formation, and limit the maximum number of vehicles in a continuous formation in any lane, satisfying the following conditions:

[0042]

[0043] Where Q is the maximum formation size. For lane The set of vehicles, where n is the total number of vehicles in the lane; Formula (8) is used to ensure the continuity of the formation state in the time dimension, that is, the vehicles In the lane Once at the moment Once in formation, it will be in a subsequent moment. No one may leave the formation without a valid reason.

[0044] Formula (9) is used to restrict the time to time. ,Lane any continuous Among the vehicles, a maximum of Vehicles are placed in platoons, thus limiting platoon size. This prevents excessively long platoons from negatively impacting traffic stability and merging flexibility. Lane change safety and platooning coordination constraints: When changing lanes, vehicles must maintain a safe distance from vehicles in front and behind in the target lane. Simultaneously, the platooning relationship in the original lane is automatically broken when a lane change occurs, provided the following conditions are met:

[0045]

[0046]

[0047] in, A 0-1 variable, representing time. vehicle In the lane Is it located in the vehicle? In the lane The value behind is 1, and the value in front is 0.

[0048] Formula (10) is used to constrain time. When the vehicle From the lane To the target lane When a lane change occurs, it is in relation to vehicles behind it in the target lane. The minimum safe longitudinal spacing between them must be met in the non-formation state.

[0049] Formula (11) is used to constrain the vehicle When a lane change occurs, it interacts with vehicles in the target lane that are ahead of it. The maximum permissible longitudinal positional relationship between lanes is determined to prevent the risk of rear-end collisions after lane changes.

[0050] Formula (12) is used to guarantee: when the vehicle At any moment When an arbitrary lane change occurs, its platooning status in the original lane. Automatic failure enables coordinated decoupling between lane-changing behavior and formation relationships.

[0051] Merging area safety distance constraints: These are used to ensure the minimum safe distance between vehicles on the mainline and those on the ramp, preventing collisions and rear-end accidents in the merging area. For mainline vehicles... (Lane ) and ramp vehicles (Lane The constraints are as follows:

[0052]

[0053] in, These are the mainline lane number set and the ramp lane number set, respectively.

[0054] Formula (13) is used to constrain traffic within the merging area when mainline vehicles... When it has the right-of-way, it and the ramp vehicles The minimum safe longitudinal spacing between them is determined to prevent merging conflicts.

[0055] Formula (14) is used to constrain traffic within the merging area when ramp vehicles... When priority is given, it should be compared with vehicles on the main line. The minimum safe longitudinal spacing relationship between them.

[0056] In some embodiments, the driving information of vehicles is aggregated, and based on the formation cooperative trajectory optimization model, the trajectories and merging order of all vehicles in the target area are planned to obtain an optimization scheme, including: A global trajectory optimization model is established based on the acquired vehicle driving information. Its objective function minimizes the weighted sum of velocities of all vehicles on the main line and ramps within the optimization period. The expression is as follows:

[0057] in, To optimize the set of discrete moments within the period, in a specific embodiment, the set can be 12, meaning that the optimization period contains 12 discrete moments. This is the optimization weighting coefficient for ramp vehicles, used to adjust the priority of ramp vehicles in the objective function. In a specific embodiment, it can be set to 0.2. The constraints include queue adjacency constraints (e.g., formulas (1)-(3)), vehicle formation modeling and safety distance constraints (e.g., formulas (4)-(7)), formation continuity and scale constraints, lane change safety and formation coordination constraints, merging zone safety distance constraints, and basic vehicle dynamics constraints (e.g., formulas (8)-(14)). Vehicle dynamics includes vehicle speed, acceleration, jerk physical feasibility constraints and discrete update equations.

[0058] The optimization model used in this application embodiment integrates the global vehicle states and control variables to uniformly plan the optimal trajectory, merging order, platooning and lane-changing strategies for vehicles on the main line and ramps.

[0059] In some embodiments, control commands are generated based on the optimization scheme. These control commands are used to control the driving of the target vehicle and include: longitudinal and lateral operation commands, speed and acceleration operation commands, and lane change or merging operation commands for the target vehicle.

[0060] The method described in this application can be used for assisted driving or autonomous driving of vehicles, improving traffic efficiency and safety in merging areas of intelligent connected vehicles. It enables multi-vehicle collaboration based on a vehicle-road-cloud integrated system, achieving goals such as alleviating traffic congestion and improving traffic safety.

[0061] The following describes the highway ramp merging control method based on formation cooperation in specific application scenarios.

[0062] Application Scenario 1 See Figure 2 , construct as Figure 2 The simulation scenario is shown below. The arrows in the diagram indicate the starting points of the merging zone, with 0 representing the coordinates of these starting points. The scenario is set up with two vehicles each participating in the merging from the mainline and the ramp. The mainline is a single lane, and the ramp connects to the mainline at the merging zone. All four vehicles have an initial speed of 11.1 m / s. The initial longitudinal positions of the vehicles on the mainline are -200 m (vehicle M2) and -160 m (vehicle M1), while the initial positions of the vehicles on the ramp are the same as those on the mainline, at -200 m (vehicle R2) and -160 m (vehicle R1).

[0063] In step S1, vehicles M1, M2, R1, and R2 collect real-time status information such as their current position, speed, acceleration, and lane number through their own onboard systems, and upload it to the cloud control platform via vehicle-to-everything (V2X) communication for subsequent unified modeling and scheduling.

[0064] S2, the cloud platform aggregates the status information of all vehicles, constructs a queue adjacency graph between vehicles, and a lane-changing probability determination model. It utilizes adjacency variables. With lane change variables Dynamic modeling of vehicle platoon structure; further introduction of platooning intention variables. State variables The system incorporates dynamic headway constraints to identify potential platooning pairs on the mainline and ramps, and applies platooning safety constraints. Next, combining the relative positions and lane numbers of vehicles on the mainline and ramps, the system sets conflict detection and minimum spacing requirements between vehicles on the merging ramps, constructing a unified global trajectory optimization model. Based on satisfying multiple constraints such as vehicle dynamics, platooning continuity, and lane change coordination, and aiming to minimize overall speed loss, the system optimizes the longitudinal trajectory, merging sequence, and platooning strategy of vehicles, outputting control parameters for each vehicle in the future time domain, including speed-position trajectory, lane change timing, and whether it participates in platooning.

[0065] In step S3, the optimization results are sent to the vehicle system via the cloud control platform in the form of control commands. Vehicles M1–R2 perform longitudinal control and lane change operations according to the commands to achieve tracking of the predetermined trajectory and smooth passage through the merging zone.

[0066] Figure 3a and Figure 3b The displayed velocity and acceleration curves demonstrate the effectiveness and smoothness of the formation control strategy. From the velocity curves... Figure 3b As can be seen, vehicles on the mainline, with their right-of-way, quickly reach and maintain a maximum speed of 20 m / s, passing through the merging zone at a constant speed; while vehicles on the ramps must reduce their speed to approximately 9 m / s to avoid mainline vehicles, and then smoothly accelerate to the target speed under platooning control. (Acceleration curve) Figure 3a This further confirms the effectiveness of the control. Vehicles on the main line experienced gradual acceleration changes, while vehicles on the ramps, although exhibiting a pattern of initial deceleration followed by acceleration, maintained a relatively small range of variation (approximately ±3 m / s²), and the overall curve was smooth without drastic fluctuations. This indicates that the model's formation control strategy successfully achieved unified planning of vehicle acceleration and deceleration processes.

[0067] Application Scenario 2 Figure 4This diagram illustrates the spatiotemporal trajectory relationship between vehicles on the main line and on the ramps. The main plot on the left presents the complete trajectory of the entire merging process, with the orange area representing the merging zone. It can be observed that vehicles on the main line maintain a leading position throughout, while vehicles on the ramps adjust their speeds to form two-vehicle formations. The enlarged plot on the right focuses on the merging zone, showing that both platooned and non-platooned vehicles consistently meet the required safe following distances throughout the merging zone. This demonstrates that the model can effectively plan the merging sequence of vehicles on the main line and on the ramps, ensuring vehicles pass safely and smoothly through the merging zone.

[0068] To further explore the model's performance in more complex traffic environments, this embodiment sets the merging scenario as a two-lane mainline, with 15 vehicles each in the outer lane and on the ramp, and an additional 4 evenly distributed vehicles in the inner lane of the mainline. Figure 5 As shown in the diagram, the arrows indicate the positions where vehicles begin to enter the merging zone, marking the starting point of the merging zone. 0 represents the coordinate value of this starting point. The model incorporates lane-changing strategies for mainline vehicles and vehicle platooning strategies. Vehicles in the outer lanes of the mainline can change lanes to the inner lanes at appropriate times to alleviate coordination pressure with ramp vehicles in the merging zone.

[0069] Figure 6a and Figure 6b The spatiotemporal trajectory diagram of vehicles under a two-lane mainline implementation is shown, revealing the synergistic effect of formation control and lane-changing strategies. Figure 6a The curves showing the positions of vehicles in the outer lanes of the main line (solid blue line) and those in the ramps (dashed red line) are displayed. Figure 6b This displays the trajectory of vehicles in the lanes (blue dashed lines) within the main line.

[0070] from Figure 6a and Figure 6b It can be observed that the vehicles in the outer lanes of the main line and the ramps form an alternating platooning structure in the merging area. The trajectories of each vehicle are evenly spaced and do not intersect, indicating that the model's platooning strategy successfully coordinates the merging order of the two traffic flows, ensuring a safe distance during the merging process. Before entering the merging area, the ramp vehicles adjust their speed (reflected in changes in the curve slope) to successfully insert themselves into the safe gap of the main line traffic flow, achieving a smooth merging. Figure 6b The vehicle trajectories in the inner lanes of the main line are relatively sparse, while some vehicles originate from the outer lanes, indicating that vehicles in the outer lanes have successfully implemented lane-changing strategies. When vehicles in the outer lanes detect a potential conflict with vehicles on the ramp ahead, some choose to switch to the inner lanes. This not only reduces the coordination pressure between vehicles in the outer lanes and those on the ramps but also makes full use of the remaining capacity of the inner lanes.

[0071] Analysis of the two figures shows that the model effectively solves the merging problem in a large-scale two-lane environment by comprehensively applying vehicle platooning and lane-changing strategies. The platooning strategy ensures the orderly insertion of vehicles from the outer lanes and ramps, while the lane-changing strategy optimizes the overall traffic flow distribution through spatial redistribution. The synergistic effect of the two strategies significantly improves the traffic efficiency and safety of the merging area, demonstrating the model's robustness and adaptability in complex traffic environments.

[0072] In summary, the verification results of the two embodiments above demonstrate that the proposed highway ramp merging control method based on platooning cooperation can effectively achieve trajectory planning, merging sequence optimization, and dynamic platooning control for vehicles on the mainline and ramps. In simple scenarios with similar initial vehicle conditions, this method can accurately determine the merging priority order, ensuring vehicles smoothly pass through the merging zone. In complex, large-scale multi-lane scenarios, by combining lane-changing and platooning strategies, the system can effectively alleviate merging conflicts, improve road resource utilization, and maintain good operational stability and safety. The results of the embodiments show that the proposed method has good adaptability, coordination, and optimization capabilities, and can provide theoretical support and application foundation for merging control in practical highway intelligent transportation systems.

[0073] This application provides a highway ramp merging control device based on formation cooperation. The device of this application can implement the method of the above embodiment. The above method embodiment can be used to understand the device of this application, and the description of the device embodiment below can also be used to understand the method of the above embodiment.

[0074] See Figure 7 The highway ramp merging control device based on formation coordination according to this application includes an acquisition module, a decision module, and an execution module.

[0075] The acquisition module is used to acquire the driving information of vehicles on the main line and ramps in the target area. The driving information includes the current location, speed, acceleration and the lane number to which the vehicle belongs.

[0076] The decision-making module is used to aggregate vehicle driving information and, based on the formation cooperative trajectory optimization model, to plan the trajectory and merging order of all vehicles in the target area to obtain an optimization scheme. The optimization scheme includes formation decision, lane change decision, merging order, and vehicle trajectory.

[0077] The execution module is used to generate control commands based on the optimization scheme, and the control commands are used to control the movement of the target vehicle.

[0078] This application 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 computer program to implement any of the methods described above.

[0079] Please see Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 8 As shown, the electronic device 600 may include: at least one processor 601, at least one network interface 604, user interface 603, memory 605, and at least one communication bus 602.

[0080] The communication bus 602 is used to enable communication between these components.

[0081] The user interface 603 may include a display screen and a camera. Optionally, the user interface 603 may also include a standard wired interface and a wireless interface.

[0082] The network interface 604 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0083] The processor 601 may include one or more processing cores. The processor 601 connects to various parts within the electronic device 600 using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 605, and by calling data stored in the memory 605. Optionally, the processor 601 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 601 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 601 and may be implemented as a separate chip.

[0084] The memory 605 may include random access memory (RAM) or read-only memory. Optionally, the memory 605 may include a non-transitory computer-readable storage medium. The memory 605 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 605 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 605 may also be at least one storage device located remotely from the aforementioned processor 601. Figure 8 As shown, the memory 605, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and application programs.

[0085] exist Figure 8 In the electronic device 600 shown, the user interface 603 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 601 can be used to call the application stored in the memory 605 and specifically execute the operations of any of the above method embodiments.

[0086] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0087] This application also provides a computer program product including a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0088] Those skilled in the art will clearly understand that the technical solutions of this application can be implemented using software and / or hardware. In this specification, "unit" and "module" refer to software and / or hardware capable of independently performing or cooperating with other components to perform specific functions. Hardware may include, for example, a Field-Programmable Gate Array (FPGA), an Integrated Circuit (IC), etc.

[0089] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0090] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0091] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0092] 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0094] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0095] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0096] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for controlling merging traffic on highway ramps based on formation coordination, characterized in that, include: Real-time acquisition of vehicle driving information on the main line and ramps of the target area, including current location information, speed, acceleration and the lane number to which the vehicle belongs; By aggregating vehicle driving information and using a platooning cooperative trajectory optimization model, trajectory and merging sequence planning are performed for all vehicles in the target area to obtain an optimization scheme. The optimization scheme includes platooning decision, lane change decision, merging sequence, and vehicle trajectory. Control commands are generated based on the optimization scheme, and these control commands are used to control the movement of the target vehicle.

2. The method according to claim 1, characterized in that, Real-time acquisition of vehicle driving information on the main line and ramps of the target area, including: Get the vehicle's current location Current location Let be a continuous variable, representing the first... The car is in the lane At the moment The longitudinal position; Get vehicle speed vehicle speed Let be a continuous variable, representing the first... The car is in the lane At the moment speed; Obtain vehicle acceleration Vehicle acceleration Let be a continuous variable, representing the first... The car is in the lane At the moment The acceleration; Get the lane number of the vehicle This is used to identify the lane the vehicle is currently in; Sampling time This represents the discrete time series corresponding to the data acquisition.

3. The method according to claim 1, characterized in that, Based on the formation cooperative trajectory optimization model, trajectory and merging sequence planning is performed for all vehicles in the target area, including: Establish a vehicle queue adjacency relationship model and use adjacency determination variables. and lane-changing decision variables Dynamically model and determine the real-time structure of all vehicle queues in a multi-lane environment. , Assign vehicle number, , Lane numbering, The sampling time.

4. The method according to claim 3, characterized in that, Establish a vehicle queue adjacency model, including: Define the queue adjacency determination variable It is a 0-1 variable, representing time. ,Lane Get on the vehicle and vehicles Are they in adjacent positions? If so... ,otherwise ; Define lane-changing decision variables It is a 0-1 variable, if at time... vehicle From the lane Change lanes to ,So ,otherwise ; The queue adjacency determination variable Dynamically updated based on the queue adjacency determination variable The distinction between adjacent and separated queues includes consecutive adjacent, indirect adjacent, lane-changing separation, and interval separation. Consecutive adjacent refers to vehicles... and In the same lane, directly adjacent to each other without changing lanes, at this time... Indirectly adjacent are vehicles and All vehicles in between have changed lanes and left, making it possible for them to pass. New direct adjacencies are formed, at this time Lane separation for vehicles and If any one or two vehicles in the lane change, causing them to no longer be adjacent, then... ; Separation into vehicles and There are other vehicles that have not changed lanes, and the two are not adjacent. ; The adjacency relationship between queues is implemented through the following constraint logic: in For larger positive numbers, Number the vehicle.

5. The method according to claim 1, characterized in that, By aggregating vehicle driving information and using a platooning cooperative trajectory optimization model, the trajectory and merging sequence of all vehicles in the target area are planned to obtain an optimization scheme, including: modeling vehicle platooning relationships and introducing platooning intention variables. Formation state variables And dynamic safety distance constraints enable automatic coordinated platooning control of vehicles within the queue, among which, Formation Intent Variables A 0-1 variable, representing a vehicle. In the lane ,time Does the vehicle intend to form a convoy with the vehicle in front? If so, ,otherwise ; Formation state variables A 0-1 variable, representing a vehicle. In the lane ,time Has the vehicle already formed a convoy with the vehicle in front? If so, then... ,otherwise ; Vehicle platooning relationships include dynamically switchable free-roaming, proposing platooning, and already-platooned phases, with safety distance constraints applied based on each phase. Specifically, during the free-roaming phase... If vehicles are not planned to form a platoon and have not actually formed a platoon, then the distance between the vehicle in front and the vehicle in front must meet the non-platoon safety headway constraint; during the planned platooning phase... When a vehicle intends to form a platoon with the vehicle in front, but has not yet actually entered the platoon, the distance between the two vehicles is allowed to gradually converge towards a platooned state; during the platooning phase... The vehicles have formed a stable formation with the vehicle in front, and the spacing is allowed to be reduced to within the safe distance range for the formation.

6. The method according to claim 5, characterized in that, In the three formation states—free-roaming phase, intended formation phase, and already formed formation phase—the distance between vehicles and the vehicle in front must meet the following constraints: in, This is the minimum headway for non-platoon trains. To minimize the headway of the train in the formation, For vehicle length, The maximum allowable spacing variation for the formation.

7. The method according to claim 6, characterized in that, By aggregating vehicle driving information and using a platooning cooperative trajectory optimization model, trajectory and merging sequence planning is performed for all vehicles in the target area to obtain an optimization scheme, including: The following joint constraints are applied to the continuity and scale of vehicle platooning, lane change safety and platooning coordination, and the safe distance between vehicles on the mainline and ramps in the merging area: Formation continuity and size constraints: Ensure that vehicles remain continuous once they enter a formation, and limit the maximum number of vehicles in a continuous formation in any lane, satisfying the following conditions: in, For the maximum formation size, For lane The vehicle assembly, The total number of vehicles in the lane; Lane change safety and platooning coordination constraints: When changing lanes, vehicles must maintain a safe distance from vehicles in front and behind in the target lane. Simultaneously, the platooning relationship in the original lane is automatically broken when a lane change occurs, provided the following conditions are met: in, A 0-1 variable, representing time. vehicle In the lane Is it located in the vehicle? In the lane The value behind is 1, and the value in front is 0; Merging area safety distance constraints: These are used to ensure the minimum safe distance between vehicles on the mainline and those on the ramp, preventing collisions and rear-end accidents in the merging area. For mainline vehicles... Its lane and ramp vehicles Its lane The constraints are as follows: in, These are the mainline lane number set and the ramp lane number set, respectively.

8. The method according to claim 7, characterized in that, By aggregating vehicle driving information and using a platooning cooperative trajectory optimization model, trajectory and merging sequence planning is performed for all vehicles in the target area to obtain an optimization scheme, including: A global trajectory optimization model is established based on the acquired vehicle driving information. Its objective function minimizes the weighted sum of velocities of all vehicles on the main line and ramps within the optimization period. The expression is as follows: in, To optimize the set of discrete moments within the period; The optimized weighting coefficients for vehicles on the ramp; The constraints include queue adjacency constraints, vehicle platooning modeling and safety distance constraints, platooning continuity and scale constraints, lane change safety and platooning coordination constraints, merging zone safety distance constraints, and basic vehicle dynamics constraints. Vehicle dynamics includes physical feasibility constraints on vehicle speed, acceleration, jerk, and discrete update equations.

9. The method according to claim 1, characterized in that, Control commands are generated based on the optimization scheme. These control commands are used to control the movement of the target vehicle and include: longitudinal and lateral operation commands, speed and acceleration operation commands, and lane change or merging operation commands for the target vehicle.

10. A highway ramp merging control device based on formation coordination, characterized in that, include: The acquisition module is used to acquire the driving information of vehicles on the main line and ramps in the target area. The driving information includes the current location information, speed, acceleration and the lane number to which the vehicle belongs. The decision module is used to aggregate vehicle driving information and, based on the formation cooperative trajectory optimization model, plan the trajectory and merging order of all vehicles in the target area to obtain an optimization scheme. The optimization scheme includes formation decision, lane change decision, merging order and vehicle trajectory. An execution module is used to generate control commands based on the optimization scheme, the control commands being used to control the movement of the target vehicle.

Images