Dynamic cooperative merging control method and system applicable to mixed traffic flows

Abstract

This invention discloses a dynamic cooperative merging control method and system applicable to mixed traffic flows. First, the target control state and optimal platooning scheme are determined. Then, the control time of cooperating vehicles and the start and end times of the gaps they form are defined. When the control time arrives, a deceleration command is sent to the cooperating vehicles. The mainline traffic flow forms a segmented platoon and gaps available for ramp vehicles. For each ramp vehicle, based on the planned distribution of cooperating vehicles and control time, a suitable gap for merging into the mainline is determined, and its speed is planned using an optimization model. This technical solution combines macroscopic traffic flow theory with microscopic vehicle control, simultaneously optimizing the behavior of both mainline and ramp vehicles. It can adapt to dynamically changing mixed traffic flow scenarios, ensuring efficient and safe ramp merging, thereby improving traffic performance and safety while reducing exhaust emissions, achieving more efficient, safe, and sustainable traffic operation.

Description

Technical Field

[0001] This invention belongs to the field of intelligent transportation systems and ramp merging control technology, specifically relating to a dynamic cooperative merging control method and system suitable for mixed traffic flows. Background Technology

[0002] With rapid urbanization and industrialization, traffic flow is increasing daily, and traffic congestion is becoming increasingly severe. Particularly on highways and urban expressways, ramp merging areas have become high-risk congestion zones. In these areas, traffic flows from the main road and ramps need to merge within a limited space; however, improper merging can lead to traffic instability, further triggering congestion, traffic accidents, and a series of other problems. Traditional traffic management models, such as simple traffic signal control or variable speed limit control, can no longer meet the growing and more complex demands of highway traffic. Therefore, developing more precise and intelligent control technologies for ramp merging areas has become an urgent task.

[0003] Ramp merging control technology represents a significant breakthrough in traffic informatization and intelligentization in recent years. This technology primarily utilizes real-time data acquisition and advanced data analysis algorithms to achieve accurate diagnosis and prediction of traffic flow on ramps and main roads. It comprehensively analyzes multi-dimensional information such as vehicle speed, traffic volume, and vehicle spacing within the merging area, and then determines appropriate lane change and speed adjustment control strategies through optimization models. Therefore, in-depth research into ramp merging control technology will not only promote the development of highway traffic management towards a higher level of informatization and intelligentization, but will also have a profound impact on alleviating traffic congestion and improving road transport efficiency and safety.

[0004] In intelligent traffic management systems, various optimization models are frequently used for ramp merging control. However, there is currently no method that can address the problem of merging mixed traffic flows with dynamic changes in traffic volume from both macroscopic and microscopic traffic flow perspectives. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic cooperative merging control method and system suitable for mixed traffic flows. It combines macroscopic traffic flow theory with microscopic vehicle control, and optimizes the behavior of vehicles on the main line and ramps. It can adapt to mixed traffic flow scenarios with dynamic changes in traffic flow, ensure efficient and safe ramp merging, thereby improving traffic performance and safety and reducing exhaust emissions, and achieving more efficient, safe and sustainable traffic operation.

[0006] To achieve the above objectives, the solution of the present invention is:

[0007] A dynamic cooperative merging control method suitable for mixed traffic flows includes the following steps:

[0008] Step 1: Using the basic traffic flow diagram theory, determine the target control state based on the traffic flow information of the main line and ramps;

[0009] Based on the number, type, and location distribution of vehicles on the main line to be planned, and combined with the traffic flow parameters of the target state, the intelligent connected vehicles that need to participate in the coordination are identified and referred to as cooperative vehicles, thus forming the optimal platooning scheme.

[0010] Step 2: Based on the target control state and the optimal formation scheme, determine the control time of the cooperating vehicles and the start and end times of the gaps they form, and send a deceleration command to the cooperating vehicles when the control time is reached. The traffic flow on the main line forms a segmented platoon and gaps that can be used by vehicles on the ramps.

[0011] Step 3: For each vehicle on the ramp, based on the planned distribution of cooperating vehicles and control time, determine the appropriate gap for its merging into the main line, and plan its driving speed.

[0012] In step one above, determining the target control state includes,

[0013] Based on the mainline and ramp traffic flow information, determine the ideal headway and clearance headway for the target control state;

[0014] Based on the ideal headway and clearance headway of the target control state, the basic relationships of traffic flow are described using the basic graph derived from the IDM model, and the target control state of traffic flow is determined.

[0015] In step one above, the optimal formation scheme is formed, including:

[0016] Based on the number, type, and location distribution of the main line vehicles to be planned, the detected intelligent connected vehicles are randomly selected as the cooperative vehicles to obtain the initial group of the platooning scheme.

[0017] Based on the initial population of the formation scheme, a formation optimization model is established to calculate the individual fitness, and selection, crossover and mutation operations are performed on all possible formation schemes. After a certain number of iterations, the optimal formation scheme is determined.

[0018] In step two above, the control time of the cooperative vehicles and the start and end times of the resulting gaps are clearly defined, including:

[0019] Assuming the traffic flow is in state A without any control, when the cooperating vehicle decelerates, the following vehicle also decelerates and transitions to state C. The time required to transition from state A to state C is determined according to traffic wave theory, and the specific formula is as follows:

[0020]

[0021]

[0022] roll out:

[0023]

[0024] In the formula: t AC v is the time required for the transition from state A to state C. AC Let t be the wave speed during the transition from state A to state C. CV-arrive s represents the time it takes for the cooperating vehicles to arrive at the merging point. A Let n be the distance between the front ends of the vehicles in state A. P v represents the number of vehicles in the convoy. i q i k i Let A, C, and t be the traffic flow velocity, flow rate, and density in state i, respectively, where i = A, C, and t is the moment when the deceleration command is issued to the cooperating vehicle.

[0025] The period is defined as the time required for the gap formed by cooperating vehicles and the convoy to pass through the merging point in state C. Based on the arrival time of the cooperating vehicles at the merging point, the time for the gap to reach the merging point and the end time of the period are derived, and the specific formula is as follows:

[0026]

[0027]

[0028] In the formula: t G-arrive G is the time it takes for the gap to reach the sink point, and G is the duration of the gap. i Let t be the headway in state i. end C represents the end time of this period. c The period length is denoted as .

[0029] Step three above includes,

[0030] Obtain the gap information of each ramp vehicle before it merges in, including the start and end time of the gap and the number of vehicles merging in the current gap;

[0031] Based on the number of vehicles merging into the current gap, determine whether there are already merging vehicles in the current cycle:

[0032] If there are already merging vehicles in the current cycle, then based on the start and end times of the gap, determine whether the remaining gap in the current cycle can meet the merging needs of the current vehicle. If so, the vehicle is instructed to follow the preceding vehicle to the merging point; otherwise, read the information of the next cycle and continue to determine whether there are already merging vehicles in the current cycle based on the number of vehicles merging in the current gap.

[0033] If there are no merging vehicles in the current cycle, then based on the start and end times of the gap, it is determined whether the vehicle can arrive at the merging point at the same time as the gap. If so, the vehicle is allowed to arrive at the merging point at the same time as the gap; otherwise, the vehicle is allowed to move at maximum speed to reach the merging point as quickly as possible.

[0034] A dynamic cooperative merging control system suitable for mixed traffic flows includes,

[0035] The target control state determination module is configured to determine the target control state based on the traffic flow information of the mainline and ramps using the basic traffic flow graph theory.

[0036] The optimal formation scheme module is configured to determine the intelligent connected vehicles that need to participate in the collaboration and refer to them as cooperative vehicles based on the number, type and location distribution of vehicles on the main line to be planned, combined with the traffic flow parameters of the target state, and form the optimal formation scheme.

[0037] The deceleration command sending module is configured to, based on the target control state determined by the target control state determination module and the optimal formation scheme formed by the optimal formation scheme forming module, determine the control time of cooperating vehicles and the start and end times of the gaps they form, and send a deceleration command to the cooperating vehicles when the control time arrives, thereby creating a separated platoon and gaps available for ramp vehicles in the mainline traffic flow; and,

[0038] The speed planning module is configured to determine the appropriate gap for each ramp vehicle to merge into the main line based on the pre-planned distribution of cooperative vehicles and control time, and to plan the speed for it.

[0039] The aforementioned target control state determination module is configured to determine the target control state, including,

[0040] Based on the mainline and ramp traffic flow information, determine the ideal headway and clearance headway for the target control state;

[0041] Based on the ideal headway and clearance headway of the target control state, the basic relationships of traffic flow are described using the basic graph derived from the IDM model, and the target control state of traffic flow is determined.

[0042] The aforementioned optimal formation scheme generation module is configured to generate an optimal formation scheme, including,

[0043] Based on the number, type, and location distribution of the main line vehicles to be planned, the detected intelligent connected vehicles are randomly selected as the cooperative vehicles to obtain the initial group of the platooning scheme.

[0044] Based on the initial population of the formation scheme, a formation optimization model is established to calculate the individual fitness, and selection, crossover and mutation operations are performed on all possible formation schemes. After a certain number of iterations, the optimal formation scheme is determined.

[0045] The aforementioned deceleration command sending module specifies the control time of the cooperating vehicles and the start and end times of the resulting gaps, including:

[0046] Assuming the traffic flow is in state A without any control, when the cooperating vehicle decelerates, the following vehicle also decelerates and transitions to state C. The time required to transition from state A to state C is determined according to traffic wave theory, and the specific formula is as follows:

[0047]

[0048]

[0049] roll out:

[0050]

[0051] In the formula: t AC v is the time required for the transition from state A to state C. AC Let t be the wave speed during the transition from state A to state C. CV-arrive s represents the time it takes for the cooperating vehicles to arrive at the merging point. A Let n be the distance between the front ends of the vehicles in state A. P v represents the number of vehicles in the convoy. i q i k i Let A, C, and t be the traffic flow velocity, flow rate, and density in state i, respectively, where i = A, C, and t is the moment when the deceleration command is issued to the cooperating vehicle.

[0052] The period is defined as the time required for the gap formed by cooperating vehicles and the convoy to pass through the merging point in state C. Based on the arrival time of the cooperating vehicles at the merging point, the time for the gap to reach the merging point and the end time of the period are derived, and the specific formula is as follows:

[0053]

[0054]

[0055] In the formula: t G-arrive G is the time it takes for the gap to reach the sink point, and G is the duration of the gap. i Let t be the headway in state i. end C represents the end time of this period. c The period length is denoted as .

[0056] The aforementioned speed planning module is configured to determine the appropriate merging interval for each ramp vehicle onto the main line based on the pre-planned distribution and control time of the cooperating vehicles, and to plan its travel speed, including...

[0057] Obtain the gap information of each ramp vehicle before it merges in, including the start and end time of the gap and the number of vehicles merging in the current gap;

[0058] Based on the number of vehicles merging into the current gap, determine whether there are already merging vehicles in the current cycle:

[0059] If there are already merging vehicles in the current cycle, then based on the start and end times of the gap, determine whether the remaining gap in the current cycle can meet the merging needs of the current vehicle. If so, the vehicle is instructed to follow the preceding vehicle to the merging point; otherwise, read the information of the next cycle and continue to determine whether there are already merging vehicles in the current cycle based on the number of vehicles merging in the current gap.

[0060] If there are no merging vehicles in the current cycle, then based on the start and end times of the gap, it is determined whether the vehicle can arrive at the merging point at the same time as the gap. If so, the vehicle is allowed to arrive at the merging point at the same time as the gap; otherwise, the vehicle is allowed to move at maximum speed to reach the merging point as quickly as possible.

[0061] By adopting the above solution, the present invention has the following beneficial effects compared with the prior art:

[0062] First, the dynamic cooperative merging control method and system of the present invention, applicable to mixed traffic flows, comprehensively considers the global behavior of vehicles on the mainline and ramps, and optimizes the merging control scheme with the help of macroscopic traffic flow theory to ensure smooth traffic flow. Simultaneously, the present invention combines upper-level sequence determination with lower-level control. Upper-level sequence determination includes overall traffic flow planning and control state determination, while lower-level control involves the specific actions and speed control of each vehicle. Through this efficient coordination between macroscopic and microscopic levels, and between the mainline and ramps, the present invention not only achieves smooth traffic merging but also significantly improves the operational efficiency of the entire traffic system.

[0063] Secondly, the dynamic cooperative merging control method and system of the present invention, applicable to mixed traffic flows, possesses the ability to dynamically adjust the control scheme, flexibly adjusting the control scheme based on real-time or near-real-time traffic flow data. Specifically, when traffic flow is low, the present invention can reduce unnecessary merging gaps. When traffic flow increases, especially during peak hours, the present invention can promptly create sufficient merging gaps for ramp vehicles to ensure the efficiency and safety of the merging process. This dynamic adjustment capability not only greatly improves the adaptability and practicality of merging strategies but also enables more refined and humanized traffic management under different traffic scenarios and conditions. Attached Figure Description

[0064] Figure 1 This is a flowchart of an embodiment of the present invention;

[0065] Figure 2 This is a schematic diagram of information collection according to an embodiment of the present invention;

[0066] Figure 3 This is a schematic diagram illustrating the determination of the target control state according to an embodiment of the present invention;

[0067] Figure 4 This is a schematic diagram of the main spatiotemporal information of an embodiment of the present invention;

[0068] Figure 5 This is a schematic diagram illustrating the process of determining the appropriate gap for vehicles merging into the main line according to an embodiment of the present invention. Detailed Implementation

[0069] The technical solution and beneficial effects of the present invention will be described in detail below with reference to the accompanying drawings.

[0070] like Figure 1 As shown, this embodiment of the invention provides a dynamic cooperative merging control method suitable for mixed traffic flows, including the following steps:

[0071] S1, using the basic traffic flow diagram theory, determines the target control state based on the traffic flow information of the main line and ramps;

[0072] S2, based on the number, type and location distribution of vehicles on the main line to be planned, combined with the traffic flow parameters of the target state, determines the intelligent connected vehicles (CAVs) that need to participate in the coordination and refers to them as cooperative vehicles, forming the optimal formation scheme;

[0073] S3, based on the target control state and the optimal formation scheme, further clarify the control time of the cooperating vehicles and the start and end times of the gaps they form, and send a deceleration command to the cooperating vehicles when the control time arrives, so that the traffic flow on the main line forms a separated platoon and gaps that can be used by ramp vehicles.

[0074] S4 determines the appropriate merging interval for each ramp vehicle based on the pre-planned distribution of cooperating vehicles and control time, and further plans its driving speed to achieve non-stop merging.

[0075] In step S1, the process of determining the target control state includes the following steps:

[0076] S11, Based on the mainline and ramp traffic flow information, determine the ideal headway and clearance headway for the target control state;

[0077] S12, based on the ideal headway and clearance headway of the target control state, the basic relationship of traffic flow is described using the basic graph derived from the IDM model, and the target control traffic flow state is determined.

[0078] In step S2, the process of forming the optimal formation scheme includes the following steps:

[0079] S21, based on the number, type and location distribution of the main line vehicles to be planned, randomly select the detected intelligent connected vehicles as the cooperative vehicles to obtain the initial group of the platooning scheme;

[0080] S22, Based on the initial population of the formation scheme, establish a formation optimization model to calculate the individual fitness, and perform selection, crossover and mutation operations on all possible formation schemes. After iterating a certain number of times, determine the optimal formation scheme.

[0081] In step S3, the process of determining the control time of the cooperative vehicles and the start and end times of the gaps they form includes the following steps:

[0082] S31, assuming the traffic flow is in state A without control, when the cooperating vehicle decelerates, the following vehicle also decelerates and transitions to state C. The time required to transition from state A to state C is determined according to traffic wave theory, and the specific formula is as follows:

[0083]

[0084]

[0085] roll out:

[0086]

[0087] In the formula: t AC v is the time required for the transition from state A to state C. AC Let t be the wave speed during the transition from state A to state C. CV-arrive s represents the time it takes for the cooperating vehicles to arrive at the merging point. A Let n be the distance between the front ends of the vehicles in state A. P v represents the number of vehicles in the convoy. i q i k i Let A, C, and t be the traffic flow velocity, flow rate, and density in state i, respectively, where i = A, C, and t is the moment when the deceleration command is issued to the cooperating vehicle.

[0088] S32, the period is defined as the time required for the gap formed by the cooperating vehicles and the convoy to pass through the merging point in state C. Based on the arrival time of the cooperating vehicles at the merging point, the time for the gap to reach the merging point and the end time of the period can be derived, and the specific formula is as follows:

[0089]

[0090]

[0091] In the formula: t G-arrive G is the time it takes for the gap to reach the sink point, and G is the duration of the gap. iLet t be the headway in state i. end C represents the end time of this period. c The period length is denoted as .

[0092] like Figure 5 As shown, step S4 specifically includes the following sub-steps S41 to S44:

[0093] S41, obtain the gap information of the vehicle in front of the vehicle merging into the ramp, such as the start and end time of the gap and the number of vehicles merging into the current gap;

[0094] S42, based on the number of vehicles merging into the current gap, determine whether there are already merging vehicles in the current cycle. If so, proceed to step S43; otherwise, proceed to step S44.

[0095] S43, based on the start and end times of the gap, determine whether the remaining gap of the current cycle can meet the merging requirements of the current vehicle. If so, allow the vehicle to follow the preceding vehicle to the merging point; otherwise, read the information of the next cycle and return to sub-step S42.

[0096] S44. Based on the start and end times of the gap, determine whether the vehicle can arrive at the merging point at the same time as the gap. If so, allow the vehicle to arrive at the gap at the same time; otherwise, allow the vehicle to move at maximum speed to reach the merging point as quickly as possible.

[0097] This invention also provides a dynamic cooperative merging control system suitable for mixed traffic flows, comprising:

[0098] The target control state determination module is configured to determine the target control state based on the traffic flow information of the mainline and ramps using the basic traffic flow graph theory.

[0099] The optimal formation scheme module is configured to determine the intelligent connected vehicles that need to participate in the collaboration and refer to them as cooperative vehicles based on the number, type and location distribution of vehicles on the main line to be planned, combined with the traffic flow parameters of the target state, and form the optimal formation scheme.

[0100] The deceleration command sending module is configured to, based on the target control state determined by the target control state determination module and the optimal formation scheme formed by the optimal formation scheme forming module, determine the control time of cooperating vehicles and the start and end times of the gaps they form, and send a deceleration command to the cooperating vehicles when the control time arrives, thereby creating a separated platoon and gaps available for ramp vehicles in the mainline traffic flow; and,

[0101] The speed planning module is configured to determine the appropriate gap for each ramp vehicle to merge into the main line based on the pre-planned distribution of cooperative vehicles and control time, and to plan the speed for it.

[0102] In an optional embodiment of the present invention, such as Figure 2 As shown, this invention uses detectors placed on the road to detect traffic flow status information of the mainline and ramps. Specifically, ramp detector A is used to monitor traffic flow at the entrance ramps, and two detectors are installed on the mainline: detector B1 is used to measure the mainline traffic flow and record the corresponding macroscopic status A, and detector B2 is used to identify the type and location of vehicles to be planned.

[0103] In an optional embodiment of the present invention, such as Figure 3 As shown, step S1 utilizes the basic traffic flow graph theory to determine the target control state based on the traffic flow information of the main line and ramps. Each point on the density-flow curve in the generalized basic traffic flow graph describes a traffic state, and the slope of the line connecting the point and the origin describes the total speed of vehicles in the current traffic state. Assume that the traffic flow state is in state A without control. When a cooperating vehicle decelerates, the vehicles behind it also decelerate, thus transitioning from state A to state C. In state C, vehicles move at a higher density k. C Driving with a smaller headway h C The vehicles are compacted, creating a gap, defined as state O. This gap begins to form between the cooperating vehicle and the vehicle in front when the cooperating vehicle receives the instruction to decelerate, and continues to lengthen as it moves downstream. Simultaneously, due to the influence of the slow-moving cooperating vehicles, upstream vehicles are compacted and compressed into traffic flow state C. This process is repeated, cyclically controlling the deceleration of other cooperating vehicles to periodically create gaps available for use by ramp vehicles.

[0104] In an optional embodiment of the present invention, such as Figure 4 As shown, step S3, based on the target control state and the optimal platooning scheme, further clarifies the control time of the cooperating vehicles and the start and end times of the gaps they form. When the control time arrives, a deceleration command is sent to the cooperating vehicles, resulting in a segmented platoon and gaps available for use by vehicles on the ramps. When a cooperating vehicle decelerates, a platoon forms within the gap-forming area on the main line. This process is iteratively applied to control the deceleration of other cooperating vehicles, cyclically generating gaps for use by vehicles on the entrance ramps. Therefore, the spatiotemporal information on the main line is divided into two categories: occupied spatiotemporal areas (i.e., areas occupied by platoons) and unoccupied spatiotemporal areas (i.e., areas occupied by gaps). This information can be analogized to traffic light phases, with occupied areas representing the red phase and unoccupied areas representing the green phase. Next, the control center captures these two types of information and encodes them into a time series, then transmits it to all vehicles on the entrance ramps.

[0105] The present invention provides a dynamic cooperative merging control method and system for mixed traffic flows. This method combines macroscopic traffic flow theory with microscopic control to simultaneously optimize the behavior of vehicles on the mainline and ramps to achieve efficient merging, adapting to dynamically changing traffic flow. It exhibits superior performance in ramp merging control, significantly improving the traffic efficiency of both the mainline and ramps while reducing accident risks and exhaust emissions, thus promoting the development of highway traffic management towards a higher level of informatization and intelligence.

[0106] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0107] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0108] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0109] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0110] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0111] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A dynamic cooperative merging control method suitable for mixed traffic flows, characterized in that... Includes the following steps: Step 1: Using the basic traffic flow diagram theory, determine the target control state based on the traffic flow information of the main line and ramps; Based on the number, type, and location distribution of vehicles on the main line to be planned, and combined with the traffic flow parameters of the target state, the intelligent connected vehicles that need to participate in the coordination are identified and referred to as cooperative vehicles, thus forming the optimal platooning scheme. Step 2: Based on the target control state and the optimal formation scheme, determine the control time of the cooperating vehicles and the start and end times of the gaps they form, and send a deceleration command to the cooperating vehicles when the control time is reached. The traffic flow on the main line forms a segmented platoon and gaps that can be used by vehicles on the ramps. In step two, the control time of the cooperative vehicles and the start and end times of the resulting gaps are defined, including: Assuming the traffic flow is in state A without any control, when the cooperating vehicle decelerates, the following vehicle also decelerates and transitions to state C. The time required to transition from state A to state C is determined according to traffic wave theory, and the specific formula is as follows: ， ， roll out: ， In the formula: The time required to transition from state A to state C. The wave speed at which the state transitions from A to C. The time when the cooperating vehicles arrive at the merging point. This refers to the distance between the front ends of the vehicle in state A. The number of vehicles in the convoy. They are respectively Traffic flow speed, volume, and density under certain conditions , The moment when a deceleration command is issued to the cooperating vehicle; The period is defined as the time required for the gap formed by cooperating vehicles and the convoy to pass through the merging point in state C. Based on the arrival time of the cooperating vehicles at the merging point, the time for the gap to reach the merging point and the end time of the period are derived, and the specific formula is as follows: ， ， In the formula: The time it takes for the gap to reach the sink point. The duration of the gap. for The headway in this state represents the end time of that cycle. The period length; Step 3: For each vehicle on the ramp, based on the planned distribution of cooperating vehicles and control time, determine the appropriate gap for its merging into the main line, and plan its driving speed.

2. The dynamic cooperative merging control method for mixed traffic flow as described in claim 1, characterized in that: In step one, determining the target control state includes, Based on the mainline and ramp traffic flow information, determine the ideal headway and clearance headway for the target control state; Based on the ideal headway and clearance headway of the target control state, the basic relationships of traffic flow are described using the basic graph derived from the IDM model, and the target control state of traffic flow is determined.

3. The dynamic cooperative merging control method for mixed traffic flow as described in claim 1, characterized in that: In step one, forming the optimal formation scheme includes, Based on the number, type, and location distribution of the main line vehicles to be planned, the detected intelligent connected vehicles are randomly selected as the cooperative vehicles to obtain the initial group of the platooning scheme. Based on the initial population of the formation scheme, a formation optimization model is established to calculate the individual fitness, and selection, crossover and mutation operations are performed on all possible formation schemes. After a certain number of iterations, the optimal formation scheme is determined.

4. The dynamic cooperative merging control method for mixed traffic flow as described in claim 1, characterized in that: Step three includes, Obtain the gap information of each ramp vehicle before it merges in, including the start and end time of the gap and the number of vehicles merging in the current gap; Based on the number of vehicles merging into the current gap, determine whether there are already merging vehicles in the current cycle: If there are already merging vehicles in the current cycle, then based on the start and end times of the gap, determine whether the remaining gap in the current cycle can meet the merging needs of the current vehicle. If so, the vehicle is instructed to follow the preceding vehicle to the merging point; otherwise, read the information of the next cycle and continue to determine whether there are already merging vehicles in the current cycle based on the number of vehicles merging in the current gap. If there are no merging vehicles in the current cycle, then based on the start and end times of the gap, it is determined whether the vehicle can arrive at the merging point at the same time as the gap. If so, the vehicle is allowed to arrive at the merging point at the same time as the gap; otherwise, the vehicle is allowed to move at maximum speed to reach the merging point as quickly as possible.

5. A dynamic cooperative merging control system suitable for mixed traffic flows, characterized in that: include, The target control state determination module is configured to determine the target control state based on the traffic flow information of the mainline and ramps using the basic traffic flow graph theory. The optimal formation scheme module is configured to determine the intelligent connected vehicles that need to participate in the collaboration and refer to them as cooperative vehicles based on the number, type and location distribution of vehicles on the main line to be planned, combined with the traffic flow parameters of the target state, and form the optimal formation scheme. The deceleration command sending module is configured to determine the control time of the cooperating vehicles and the start and end times of the gaps formed by the target control state determined by the target control state determination module and the optimal formation scheme formed by the optimal formation scheme forming module, and send a deceleration command to the cooperating vehicles when the control time arrives, so that the traffic flow on the main line forms a segmented platoon and gaps that can be used by ramp vehicles. as well as, The speed planning module is configured to determine the appropriate gap for each ramp vehicle to merge into the main line based on the pre-planned distribution of cooperative vehicles and control time, and to plan the speed for it. The deceleration command sending module specifies the control time of the cooperating vehicles and the start and end times of the resulting gaps, including... Assuming the traffic flow is in state A without any control, when the cooperating vehicle decelerates, the following vehicle also decelerates and transitions to state C. The time required to transition from state A to state C is determined according to traffic wave theory, and the specific formula is as follows: ， ， roll out: ， In the formula: The time required to transition from state A to state C. The wave speed at which the state transitions from A to C. The time when the cooperating vehicles arrive at the merging point. This refers to the distance between the front ends of the vehicle in state A. The number of vehicles in the convoy. They are respectively Traffic flow speed, volume, and density under certain conditions , The moment when a deceleration command is issued to the cooperating vehicle; The period is defined as the time required for the gap formed by cooperating vehicles and the convoy to pass through the merging point in state C. Based on the arrival time of the cooperating vehicles at the merging point, the time for the gap to reach the merging point and the end time of the period are derived, and the specific formula is as follows: ， ， In the formula: The time it takes for the gap to reach the sink point. The duration of the gap. for Headway at the front of the vehicle in this state This is the end time of the cycle. The period length is denoted as .

6. The dynamic cooperative merging control system for mixed traffic flow as described in claim 5, characterized in that: The target control state determination module is configured to determine the target control state, including: Based on the mainline and ramp traffic flow information, determine the ideal headway and clearance headway for the target control state; Based on the ideal headway and clearance headway of the target control state, the basic relationships of traffic flow are described using the basic graph derived from the IDM model, and the target control state of traffic flow is determined.

7. The dynamic cooperative merging control system for mixed traffic flow as described in claim 5, characterized in that: The optimal formation scheme forming module is configured to form an optimal formation scheme, including, Based on the number, type, and location distribution of the main line vehicles to be planned, the detected intelligent connected vehicles are randomly selected as the cooperative vehicles to obtain the initial group of the platooning scheme. Based on the initial population of the formation scheme, a formation optimization model is established to calculate the individual fitness, and selection, crossover and mutation operations are performed on all possible formation schemes. After a certain number of iterations, the optimal formation scheme is determined.

8. The dynamic cooperative merging control system for mixed traffic flow as described in claim 5, characterized in that: The speed planning module is configured to determine the appropriate gap for each ramp vehicle merging into the main line based on the pre-planned distribution and control time of cooperating vehicles, and to plan its travel speed, including... Obtain the gap information of each ramp vehicle before it merges in, including the start and end time of the gap and the number of vehicles merging in the current gap; Based on the number of vehicles merging into the current gap, determine whether there are already merging vehicles in the current cycle: If there are already merging vehicles in the current cycle, then based on the start and end times of the gap, determine whether the remaining gap in the current cycle can meet the merging needs of the current vehicle. If so, the vehicle is instructed to follow the preceding vehicle to the merging point; otherwise, read the information of the next cycle and continue to determine whether there are already merging vehicles in the current cycle based on the number of vehicles merging in the current gap. If there are no merging vehicles in the current cycle, then based on the start and end times of the gap, it is determined whether the vehicle can arrive at the merging point at the same time as the gap. If so, the vehicle is allowed to arrive at the merging point at the same time as the gap; otherwise, the vehicle is allowed to move at maximum speed to reach the merging point as quickly as possible.

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