A method, system, device and medium for controlling alternating traffic of autonomous vehicles

Abstract

The present invention provides a method, system, device, and medium for controlling alternating traffic of autonomous vehicles, including: obtaining driving information of all vehicles on the main road and ramps, and assigning sequences to all vehicles based on the driving information to obtain a vehicle merging sequence; for each current vehicle in the vehicle merging sequence, in response to determining that the preceding vehicle in the sequence is in the same lane as the current vehicle based on the vehicle sequence, using a longitudinal control method to determine a first control scheme for the current vehicle; in response to determining that the preceding vehicle in the sequence is not in the same lane as the current vehicle based on the vehicle sequence, giving the current vehicle additional safety time, and using an optimal trajectory method to determine a second control scheme for the current vehicle. The present invention solves the problem in the prior art that traditional traffic management methods often rely on static signal control and fixed time period scheduling, resulting in low efficiency in vehicle coordinated scheduling and road right allocation in dynamic environments, and an inability to meet rapidly changing traffic needs.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and in particular to a method, system, device and medium for controlling alternating traffic of autonomous driving vehicles. Background Art

[0002] With the rapid development of autonomous driving technology and intelligent connected systems, connected autonomous vehicles (CAVs) hold broad promise in modern transportation systems. The coordinated control capabilities of autonomous vehicles are particularly crucial in alternating traffic scenarios. In these high-risk areas, such as ramp merging and construction zones, vehicles must alternate according to prescribed rules to ensure smooth and safe traffic. In these situations, vehicle queuing, allocation, and coordinated scheduling are key to improving road efficiency and mitigating potential traffic conflicts.

[0003] In alternating traffic scenarios, autonomous vehicles have the ability to exchange real-time information through vehicle-to-vehicle and vehicle-to-infrastructure communication networks, and can collaboratively optimize driving routes, adjust vehicle speeds and traffic order. This advantage enables autonomous vehicles to efficiently pass through complex areas while ensuring traffic safety, avoiding traffic delays and safety hazards caused by poor collaboration between vehicles.

[0004] However, traditional traffic management methods often rely on static signal control and fixed time-cycle scheduling. These methods lack sufficient flexibility and real-time adjustment capabilities when faced with alternating traffic scenarios. Especially in the context of the widespread application of autonomous vehicles, existing control methods fail to fully utilize the vehicle-to-vehicle (V2V) and vehicle-to-roadside infrastructure (V2I) communication capabilities between connected autonomous vehicles (CAVs). As a result, the coordinated scheduling and right-of-way allocation of vehicles in dynamic environments are inefficient and cannot meet rapidly changing traffic needs. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides a method for controlling alternating traffic of autonomous driving vehicles, which solves the problem that traditional traffic management methods in the existing technology often rely on static signal control and fixed time cycle scheduling, resulting in low efficiency in vehicle coordinated scheduling and road right allocation in dynamic environments, and cannot meet rapidly changing traffic needs.

[0006] According to an embodiment of the present invention, a method for controlling alternating traffic of an autonomous driving vehicle includes:

[0007] Obtain the driving information of all vehicles on the main road and ramps, and assign all vehicles to a sequence based on the driving information to obtain the vehicle merging sequence;

[0008] For each current vehicle in the vehicle merging sequence, in response to determining, based on the vehicle sequence, that the preceding vehicle in the sequence is in the same lane as the current vehicle, determining, based on the driving information of the current vehicle, a first control scheme for the current vehicle using a longitudinal control method, and accelerating / decelerating the current vehicle according to the first control scheme;

[0009] In response to determining, based on the vehicle sequence, that the preceding vehicle is not in the same lane as the current vehicle, additional safety time is assigned to the current vehicle. Then, based on the current vehicle's driving information and the safety time, an optimal trajectory method is used to determine a second control scheme for the current vehicle, and the current vehicle accelerates / decelerates according to the second control scheme.

[0010] Preferably, the control area is divided on the main road and the ramp with the merging point of the main road and the ramp as the starting point, and then the distribution area is divided on the main road and the ramp with the end points of the control areas of the main road and the ramp as the starting point respectively. The lengths of the control areas or distribution areas on different roads are equal.

[0011] Preferably, the method for assigning a sequence to the current vehicle and all other vehicles based on the driving information to obtain a vehicle merging sequence includes:

[0012] Obtain driving information of vehicles on the main road and ramps within the assigned area, and calculate the TTM time of each vehicle based on the driving information;

[0013] Sort the vehicles by TTM time from small to large to obtain the vehicle merging sequence.

[0014] Preferably, the calculation formula of the TTM time is as follows:

[0015]

[0016] Where T is the interval time, ( ) is the speed of vehicle k at time t; ( ) is the acceleration of vehicle k at time t; ( ) is the vehicle k in the speed of the moment; ( ) is the preceding vehicle k-1 of vehicle k the speed of the moment; ( ) is the preceding vehicle k-1 of vehicle k The speed of time, is the distance between vehicle k and the merging point of the main road and the ramp at time T+t, is the distance between vehicle k and the merging point of the main road and the ramp at time t, and S is the length of the control area.

[0017] Preferably, the method for calculating the first control scheme of the current vehicle using the longitudinal control method is as follows:

[0018] Build a longitudinal dynamic model of the vehicle and calculate the expected speed based on the distance between the current vehicle and the preceding vehicle;

[0019] An IDM model including all vehicles in the control area is constructed, and then the desired speed is imported into the IDM model to obtain the acceleration change function of the current vehicle, and then the first control scheme is determined according to the acceleration change function.

[0020] Preferably, constraints need to be set before using the optimal trajectory method, wherein the constraints include maximum acceleration, maximum deceleration, and maximum speed of the vehicle when it reaches the merging point;

[0021] The method for determining the second control scheme of the current vehicle using the optimal trajectory method is as follows:

[0022] Calculate the first distance traveled by the current vehicle after the vehicle has traveled at a constant speed at the initial speed for a safe period of time;

[0023] respectively calculating the second travel distance and the third travel distance required for accelerating from the initial speed to the optimal speed at the maximum acceleration and decelerating from the optimal speed to the maximum speed when the vehicle reaches the merging point at the minimum deceleration;

[0024] The length of the control area is subtracted from the first, second and third strokes to obtain the fourth stroke;

[0025] Then, the speed changes during the constant speed driving of the first and fourth strokes, the accelerated driving of the second stroke, and the decelerated driving of the third stroke are used as the second control scheme.

[0026] Preferably, the constraint condition also includes a minimum safety distance. If the distance between the current vehicle and the preceding vehicle is less than the minimum safety distance during acceleration, the vehicle will immediately stop accelerating and maintain a constant speed.

[0027] If the sum of the first stroke, the second stroke and the third stroke is greater than the length of the control zone, the optimal speed is reduced until the sum of the first stroke, the second stroke and the third stroke is equal to the length of the control zone.

[0028] On the other hand, an embodiment of the present invention further provides an autonomous driving vehicle alternating traffic control system, which uses the above-mentioned autonomous driving vehicle alternating traffic control method, including:

[0029] A vehicle information collection module, which is used to collect driving information of all vehicles on the main road and ramps;

[0030] A sequence allocation module is used to allocate a sequence to all vehicles based on driving information to obtain a vehicle merging sequence;

[0031] A scheme planning module, wherein the scheme planning module is used to determine a first control scheme or a second control scheme using a longitudinal control method or an optimal trajectory method, respectively, according to whether the preceding vehicle in the sequence is in the same lane as the current vehicle;

[0032] A collaborative control module is used to control the acceleration / deceleration of the current vehicle according to the first control scheme or the second control scheme.

[0033] On the other hand, an embodiment of the present invention also provides a computer, comprising at least one processor and a memory, wherein the memory stores a computer program, and the computer program is configured to be executed by the processor to implement the above-mentioned method for controlling alternating traffic of autonomous driving vehicles.

[0034] On the other hand, an embodiment of the present invention further provides a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and the computer program can be executed by one or more processors to implement the above-mentioned method for controlling alternating traffic of autonomous driving vehicles.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The present invention allocates a merging sequence for vehicles by calculating the TTM times of all vehicles in the allocation area on the main road and the ramp, and generates a vehicle merging sequence. The allocation no longer depends on the order in which the vehicles enter the allocation area. Then, according to whether each vehicle in the merging sequence is in the same lane as the preceding vehicle in the sequence, different methods are used to generate different control schemes to dynamically accelerate and decelerate each vehicle. Static signal control is no longer relied upon. Moreover, when accelerating and decelerating the vehicles, since the relationship between each vehicle and the preceding vehicle is different, the control scheme for each vehicle is different. Therefore, fixed time periods are no longer used for scheduling, thereby improving the efficiency of coordinated scheduling of vehicles and road right allocation in a dynamic environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Schematic diagram of an alternating traffic control method according to an embodiment of the present invention.

[0038] Figure 2 Schematic diagram of a traffic scene according to an embodiment of the present invention.

[0039] Figure 3 Schematic diagram of sequence allocation results according to an embodiment of the present invention.

[0040] Figure 4 Schematic diagram of vehicle control when the preceding vehicle and the current vehicle are in the same lane according to an embodiment of the present invention.

[0041] Figure 5 Schematic diagram of vehicle control when the preceding vehicle and the current vehicle are not in the same lane according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0043] like Figure 1 As shown, an embodiment of the present invention proposes a method for controlling alternating traffic of an autonomous driving vehicle, comprising:

[0044] S1: Obtain driving information of all vehicles on the main road and ramps;

[0045] The present invention will be described using a traffic scenario where two lanes are merged into one lane. Figure 2 As shown. The scenario involved in this invention uses the basic road section of two one-way lanes merging into one one-way lane. The horizontal lane is the main road, the diagonal lane is the ramp, the connection point between the main road and the ramp is the merging point, the lane lines are all solid lines, the vehicle is a connected autonomous vehicle (ICV), and the roadside is a roadside collaborative control unit (RCCU). The roadside control unit collects real-time driving information (such as position, speed, acceleration, etc.) of all vehicles in the control area, and collaboratively calculates and uniformly schedules the estimated arrival time of the vehicles at the merging point, thereby optimizing traffic flow.

[0046] Based on the influence of the control range of the roadside collaborative control unit, the control area is divided on the main road and the ramp with the merging point of the main road and the ramp as the starting point. Then, the distribution area is divided on the main road and the ramp with the end points of the control areas of the main road and the ramp as the starting point respectively. The length of the control area or distribution area on different roads is equal. The control area is 400m, which is enough distance to control and adjust the vehicle speed so that vehicles on the two lanes can merge in an orderly, safe and efficient manner. The distribution area is 100m, which allows the RCCU to obtain more information to reasonably allocate the sequence.

[0047] FCFS pre-assigns any vehicle upon entering the assigned zone. Although FCFS, one of AIM's earliest vehicle scheduling strategies, has been proven to reduce vehicle delays compared to traditional signal timing in certain traffic environments, it has several drawbacks: it lacks consideration of future merging point traffic flow and is somewhat blind in its vehicle right-of-way allocation.

[0048] S2: To better combine space and time and eliminate the above-mentioned shortcomings, the present invention allocates a merging sequence by calculating the time (TTM) for all vehicles in the distribution area on the main road and the ramp to reach the merging point;

[0049] So first create a collection that contains all vehicles in the allocation area on the main road and ramp: .

[0050] Vehicles entering the allocation area are initially assigned a sequence in the order they enter. That is, the later a vehicle enters the allocation area, the later it is in the sequence. The sequence of the vehicles in the allocation area is then reallocated based on the TTM calculated based on the frequency at which the RCCU collects vehicle data. The smaller the TTM, the smaller the sequence. Reallocation stops until the vehicle enters the control area.

[0051] When the vehicles entering the assigned area and their preceding vehicles enter the control area, it means that the driving information of the vehicles in the control area is known. At this time, the preceding vehicle in the control area is regarded as a virtual preceding vehicle. The calculation is as follows:

[0052]

[0053] Because the default vehicle masses are the same, the acceleration a of the virtual following vehicle is The calculation is as follows:

[0054]

[0055] The distance between the virtual vehicle and the preceding vehicle is calculated based on the distance to the last vehicle.

[0056] When calculating TTM, the future driving behavior of the vehicle is predicted first, and a following model is established by following the virtual vehicle in front. The model adopts an iterative idea. The positions and speeds of the two vehicles are known at this moment. After that, iterate The speed of the following vehicle at the moment and the distance between vehicles at the moment are calculated, and then the time required for each vehicle to travel at the current speed to cross this distance is calculated and accumulated to obtain the TTM time, that is:

[0057]

[0058] in Indicates the TTM time; ( ) is the speed of vehicle k at time t; ( ) is the acceleration of vehicle k at time t; ( ) is the vehicle k in the speed of the moment; ( ) is the preceding vehicle k-1 of vehicle k the speed of the moment; ( ) is the preceding vehicle k-1 of vehicle k The speed of time, is the distance between vehicle k and the merging point of the main road and the ramp at time T+t, is the distance between vehicle k and the merging point of the main road and the ramp at time t, and S is the length of the control area.

[0059] S3: Sort each vehicle by its TTM time from small to large to obtain the vehicle merging sequence, such as Figure 3 shown.

[0060] S4: When the current vehicle enters the control area, determine whether the preceding vehicle in the sequence is in the same lane as the current vehicle;

[0061] After the current vehicle enters the control area, when it is in the same lane as the preceding vehicle, the current vehicle will only be subject to the movement restrictions of the preceding vehicle, so it only needs to receive the one-way communication driving information of the preceding vehicle in the same lane, such as Figure 4 When the vehicle in front of the sequence is in a different lane, the current vehicle must not only have a time difference with the vehicle in front of the sequence at the merging point (i.e., the conflict point), but also maintain a safe distance from the vehicle in front of the sequence in the optimal driving process. Therefore, it will not only receive the one-way communication driving information of the vehicle in front of the sequence, but also receive the one-way communication driving information of the vehicle in front of the sequence in the same lane, such as Figure 5 , so there will be two situations at this time.

[0062] (1) Determine based on the vehicle sequence whether the preceding vehicle is in the same lane as the current vehicle

[0063] S5: Determine a first control scheme for the current vehicle using a longitudinal control method;

[0064] like Figure 4 As shown in the figure, in this case, only the current vehicle and the preceding vehicle in the same lane need to be considered. The driver or ADS has already warned them of the required distance and speed to maintain from the preceding vehicle in order to navigate within the area. The system coordinates the driving behavior of all vehicles in the area to reach a consensus, thereby reducing conflicts between vehicles and improving driving comfort. Therefore, only the recommended speed needs to be sent to the current vehicle to maintain a safe distance from the preceding vehicle. The required speed is derived as follows:

[0065]

[0066] Where, is the expected speed ( ), and are the length of the preceding vehicle and the length of the current vehicle, respectively. Since the proposed guidance and positioning algorithm uses the vehicle GPS signal, which is a mass point in the coordinate system and can be regarded as the center point of the vehicle, it is necessary to consider the length of the vehicle in the actual distance and speed calculation model to reduce the error.

[0067] After receiving the recommended speed information from the RCCU, the vehicle needs to respond promptly while ensuring driving comfort and following stability. The vehicle's longitudinal dynamics model is established in the following equation:

[0068]

[0069] Where: are the current position, velocity and acceleration of the vehicle respectively.

[0070] Using the IDM model, driving decisions regarding following distance and speed mainly correspond to the choice of acceleration, and the acceleration change function is as follows:

[0071]

[0072] Where: It's speed, is the acceleration, is the expected speed, It is an exponential coefficient that reflects the change in speed, usually 4, and is used to control the shape of the acceleration curve. The minimum safe distance between the current vehicle and the vehicle in front is calculated based on the driving information of the vehicle in front. , and the actual vehicle distance Make a comparison.

[0073] S6: Acceleration or deceleration is performed according to the above acceleration formula to determine the first control scheme of the current vehicle. Then, the RCCU controls the acceleration / deceleration of the current vehicle according to the first control scheme.

[0074] S7: When the current vehicle reaches the merging point, the control of the current vehicle ends.

[0075] (2) According to the vehicle sequence, the preceding vehicle is not in the same lane as the current vehicle.

[0076] S5: Determine a second control scheme for the current vehicle using the optimal trajectory method;

[0077] like Figure 5 As shown, when the vehicle and the preceding vehicle are not in the same lane, the TTM of the preceding vehicle is obtained, and the current vehicle is given additional safety time. , so that the TTM time of the current vehicle is greater than the TTM time and safety time of the preceding vehicle The sum of the safety time is generally set to 2s. When arriving at the merging port, the vehicle maintains a sufficient safety distance from the vehicle in front of it in the same lane, and the optimal trajectory method is used to determine the second control plan for the current vehicle.

[0078] Taking into account the upper limit of each actuator's capabilities, safety, ride comfort and other issues, the vehicle constraints include: input constraints (maximum acceleration and deceleration) 2. Maximum speed at the merging point 3. Maximum speed limit in the control area 4. Minimum safety interval.

[0079] 1) Input constraints (maximum acceleration and deceleration)

[0080] On the one hand, excessive acceleration and deceleration can negatively impact the comfort of passengers and the driver. On the other hand, the extreme acceleration and deceleration values ​​must consider the upper limit of the actuator's capabilities. Therefore, we define the vehicle input constraints as follows:

[0081]

[0082] Where, are the minimum deceleration and maximum acceleration of all vehicles respectively. Under the premise of ensuring safety clearance, in order to consider driving comfort, large speed changes should be avoided. Therefore, the vehicle acceleration range is set to .

[0083] 2) Maximum speed at the merging point

[0084] On the one hand, excessive longitudinal speed may cause the vehicle to lose control, especially when turning at a small radius at a merging point. On the other hand, the optimization algorithm based on the minimum principle cannot consider continuous state constraints. However, due to the limited spatial range of the control area, setting a speed constraint at the end of the control area can also limit the vehicle speed within the control area to a certain extent. The specific speed constraint can be set as:

[0085]

[0086] 3) Maximum speed limit in the control area

[0087] For the same reasons as above, the maximum speed of vehicles in this lane area also needs to be limited:

[0088]

[0089] If there is a speed limit on the road section when the vehicle is actually driving, if the speed limit is higher than the maximum speed limit, the maximum speed limit shall prevail; if the speed limit is lower than the maximum speed limit, the speed limit shall be used as the maximum speed limit.

[0090] 4) Minimum safety interval

[0091] During the entire driving process, although the goal is to reduce excess gaps, the minimum safe gap between vehicles must still be calculated. The formula for the safe following distance is as follows:

[0092]

[0093] Where: is the vehicle braking reaction time (s), is the speed of the following vehicle ( ), is the speed of the preceding vehicle ( ).

[0094] Taking into account the comfort of passengers and drivers, the vehicle should reduce the number of accelerations and decelerations to make the time of uniform speed the longest in the entire driving time, which is equivalent to minimizing the non-uniform speed time (acceleration / deceleration time):

[0095]

[0096] Define the state variable displacement ,speed :

[0097]

[0098] Define the Hamiltonian function and comorphic variables , :

[0099]

[0100] in is the Lagrange multiplier of the objective function.

[0101] The corresponding co-state equation is as follows:

[0102]

[0103] The solution is:

[0104]

[0105] Minimum principle requirements minimize :

[0106]

[0107] Physical meaning:

[0108] when When the vehicle is running, it should accelerate to the maximum speed as quickly as possible; when When the speed is less than 0.05, the maximum deceleration should be achieved to meet the terminal speed constraint.

[0109] Therefore, the optimal trajectory consists of three segments: ① with maximum acceleration ( ) Accelerate from the initial speed v0 to the optimal speed , the corresponding time allocation is ,②Move at a uniform speed with the optimal speed limit ( ), the corresponding time allocation is ,③ with maximum deceleration ( ) decelerates from the optimal speed to the maximum speed at the merging point , the corresponding time allocation is .

[0110] Route constraints:

[0111] Since the TTM time of the current vehicle is required to be greater than the TTM time and safety time of the preceding vehicle, Therefore, before accelerating, it is necessary to drive at a constant speed of the initial speed v0 for a safe time to obtain the first trip. In addition, the distance traveled in the acceleration segment is defined as the second trip, the constant speed segment is defined as the third trip, and the deceleration segment is defined as the fourth trip. Therefore, the total distance needs to satisfy:

[0112] First stroke + second stroke + third stroke + fourth stroke.

[0113] The specific formula is as follows:

[0114]

[0115] In addition, if the distance between the current vehicle and the vehicle in front is less than the minimum safe distance during acceleration, the vehicle will stop accelerating immediately and maintain a constant speed. During the constant speed process, if the distance between the current vehicle and the vehicle in front is less than the minimum safe distance, RUCC will set a target speed for the current vehicle based on the current speed of the vehicle in front (generally lower than the speed of the vehicle in front), and the current vehicle will immediately decelerate to the target speed.

[0116] In the above cases, planning is based on the premise that the current vehicle must go through the third trip. At this time, the optimal speed is Equal to the maximum speed limit of the control area, but if the sum of the first trip, the second trip and the third trip is greater than the length of the control area, the optimal speed is reduced until the sum of the first trip, the second trip and the third trip is equal to the length of the control area.

[0117] S6: In summary, the speed changes during the uniform speed driving of the first and fourth strokes, the accelerated driving of the second stroke, and the decelerated driving of the third stroke are taken as the second control scheme, and then the RCCU controls the acceleration / deceleration of the current vehicle according to the first control scheme.

[0118] S7: When the current vehicle reaches the merging point, the control of the current vehicle ends.

[0119] Depending on whether each vehicle in the merging sequence is in the same lane as the preceding vehicle in the sequence, different methods are used to generate different control schemes to dynamically control the acceleration and deceleration of each vehicle, eliminating reliance on static signal control. Furthermore, when accelerating and decelerating vehicles, the control schemes for each vehicle are different because the relationship between each vehicle and the preceding vehicle is different. This eliminates the need for fixed time periods for scheduling, improving the efficiency of coordinated vehicle scheduling and right-of-way allocation in a dynamic environment.

[0120] On the other hand, an embodiment of the present invention further provides an autonomous driving vehicle alternating traffic control system, which uses the above-mentioned autonomous driving vehicle alternating traffic control method, including:

[0121] A vehicle information collection module, which is used to collect driving information of all vehicles on the main road and ramps;

[0122] A sequence allocation module is used to allocate a sequence to all vehicles based on driving information to obtain a vehicle merging sequence;

[0123] A scheme planning module, wherein the scheme planning module is used to determine a first control scheme or a second control scheme using a longitudinal control method or an optimal trajectory method, respectively, according to whether the preceding vehicle in the sequence is in the same lane as the current vehicle;

[0124] A collaborative control module is used to control the acceleration / deceleration of the current vehicle according to the first control scheme or the second control scheme.

[0125] On the other hand, an embodiment of the present invention also provides a computer, comprising at least one processor and a memory, wherein the memory stores a computer program, and the computer program is configured to be executed by the processor to implement the above-mentioned method for controlling alternating traffic of autonomous driving vehicles.

[0126] On the other hand, an embodiment of the present invention further provides a storage medium, which is a computer-readable storage medium. A computer program is stored on the storage medium, and the computer program can be executed by one or more processors to implement the above-mentioned method for controlling alternating traffic of autonomous driving vehicles.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for controlling alternating traffic flow of autonomous vehicles, characterized by: include: Obtain the driving information of all vehicles on the main road and ramps, and assign all vehicles to a sequence based on the driving information to obtain the vehicle merging sequence; Starting from the merging point of the main road and the ramp, a control area is divided on the main road and the ramp. Then, starting from the end of the control area of ​​the main road and the ramp, the distribution area is divided on the main road and the ramp respectively. The length of the control area or distribution area on different roads is equal. For each current vehicle in the vehicle merging sequence, in response to determining, based on the vehicle sequence, that the preceding vehicle in the sequence is in the same lane as the current vehicle, determining, based on the driving information of the current vehicle, a first control scheme for the current vehicle using a longitudinal control method, and accelerating / decelerating the current vehicle according to the first control scheme; In response to determining, based on the vehicle sequence, that the preceding vehicle in the sequence is not in the same lane as the current vehicle, allocating additional safety time to the current vehicle, then determining a second control scheme for the current vehicle using an optimal trajectory method based on the current vehicle's driving information and the safety time, and accelerating / decelerating the current vehicle according to the second control scheme; The method for calculating the first control scheme of the current vehicle using the longitudinal control method is as follows: Build a longitudinal dynamic model of the vehicle and calculate the expected speed based on the distance between the current vehicle and the preceding vehicle; Construct an IDM model that includes all vehicles in the control area, then import the desired speed into the IDM model to obtain the acceleration change function of the current vehicle, and then determine the first control scheme based on the acceleration change function; Before using the optimal trajectory method, constraints need to be set, including the maximum acceleration, the maximum deceleration, and the maximum speed of the vehicle when it reaches the merging point; The method for determining the second control scheme of the current vehicle using the optimal trajectory method is as follows: Calculate the first distance traveled by the current vehicle after the vehicle has traveled at a constant speed at the initial speed for a safe period of time; respectively calculating a second stroke and a third stroke required for accelerating from the initial speed to the optimal speed at the maximum acceleration and decelerating from the optimal speed to the maximum speed when the vehicle reaches the merging point at the maximum deceleration; The length of the control area is subtracted from the first, second and third strokes to obtain the fourth stroke; Then, the speed changes during the constant speed driving of the first and fourth strokes, the accelerated driving of the second stroke, and the decelerated driving of the third stroke are used as the second control scheme.

2. The method for controlling alternating traffic flow of an autonomous driving vehicle according to claim 1, wherein: Methods for assigning sequences to the current vehicle and all other vehicles based on driving information to obtain a vehicle merging sequence include: Obtain the driving information of vehicles in the assigned area on the main road and ramp, and calculate the TTM time of each vehicle based on the driving information; Sort the vehicles by TTM time from small to large to obtain the vehicle merging sequence.

3. The method for controlling alternating traffic flow of an autonomous driving vehicle according to claim 2, wherein: The calculation formula of the TTM time is as follows: Where T is the interval time, ( ) is the speed of vehicle k at time t; ( ) is the acceleration of vehicle k at time t; ( ) is the vehicle k in the speed of the moment; ( ) is the preceding vehicle k-1 of vehicle k the speed of the moment; ( ) is the preceding vehicle k-1 of vehicle k The speed of time, is the distance between vehicle k and the merging point of the main road and the ramp at time T+t, is the distance between vehicle k and the merging point of the main road and the ramp at time t, and S is the length of the control area.

4. The method for controlling alternating traffic flow of an autonomous driving vehicle according to claim 1, wherein: The constraints also include a minimum safe distance. If the distance between the current vehicle and the vehicle ahead is less than the minimum safe distance during acceleration, the vehicle will stop accelerating immediately and maintain a constant speed. If the sum of the first stroke, the second stroke and the third stroke is greater than the length of the control zone, the optimal speed is reduced until the sum of the first stroke, the second stroke and the third stroke is equal to the length of the control zone.

5. An autonomous driving vehicle alternating traffic control system, characterized by: The system uses an autonomous driving vehicle alternating traffic control method according to any one of claims 1 to 4, comprising: A vehicle information collection module, which is used to collect driving information of all vehicles on the main road and ramps; A sequence allocation module is used to allocate a sequence to all vehicles based on driving information to obtain a vehicle merging sequence; A scheme planning module, wherein the scheme planning module is used to determine a first control scheme or a second control scheme using a longitudinal control method or an optimal trajectory method, respectively, according to whether the preceding vehicle in the sequence is in the same lane as the current vehicle; A collaborative control module is used to control the acceleration / deceleration of the current vehicle according to the first control scheme or the second control scheme.

6. A computer, characterized in that: It includes at least one processor and a memory, wherein the memory stores a computer program, and the computer program is configured to be executed by the processor to implement the method for controlling alternating traffic of an autonomous driving vehicle as described in any one of claims 1 to 4.

7. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, on which a computer program is stored. The computer program can be executed by one or more processors to implement an alternating traffic control method for an autonomous driving vehicle as described in any one of claims 1 to 4.

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