A method for event-triggered cooperative control of mixed-traffic group handover under communication interruption conditions

Abstract

This invention relates to an event-triggered cooperative control method for mixed-traffic vehicle group handover under communication interruption conditions, belonging to the field of intelligent vehicles and smart transportation. The method first designs a mixed traffic scenario including connected autonomous vehicles, autonomous vehicles, and traditional human-driven vehicles, and formulates four sub-vehicle group division rules. Next, it establishes a longitudinal dynamics model of heterogeneous vehicles within the mixed-traffic vehicle group considering communication interruption, including dynamics models for connected autonomous vehicles, autonomous vehicles, and traditional human-driven vehicles. When the leading connected autonomous vehicle in a sub-vehicle group experiences a communication interruption, that vehicle degenerates into an autonomous vehicle and merges with the previous sub-vehicle group to form a new sub-vehicle group. To ensure the stability of the handover process, this invention establishes an event-triggered cooperative control strategy. This method controls vehicle states through event-triggered functions, ensuring the consistency and stability of cooperative driving within the mixed-traffic vehicle group, and resolving the impact of communication interruption on the cooperative control of mixed-traffic vehicle groups.

Description

Technical Field

[0001] This invention belongs to the field of intelligent vehicles and intelligent transportation, and relates to a method for coordinated control of mixed traffic group handover based on event triggering under communication interruption conditions. Background Technology

[0002] In intelligent transportation systems, cooperative control of mixed-traffic vehicle groups is of great significance for improving road traffic efficiency, reducing traffic congestion, and lowering energy consumption and emissions. Through cooperative control, vehicles can maintain appropriate distances and speeds, thereby optimizing traffic flow and improving road utilization efficiency.

[0003] In the cooperative control of mixed-traffic vehicle groups, communication between vehicles is crucial. However, in real-world traffic environments, communication often interrupts due to various reasons (such as signal interference and equipment failure), preventing vehicles from obtaining timely status information from other vehicles and thus affecting the effectiveness of cooperative control. Furthermore, communication interruptions often disrupt the continuous switching of mixed-traffic groups (e.g., switching from a small group of vehicles to a large group of vehicles), making it even more difficult to guarantee the stability of cooperative driving in such situations.

[0004] To address the impact of communication interruptions on the cooperative control of mixed-traffic vehicle groups, this invention proposes an event-triggered cooperative control method for handover in mixed-traffic vehicle groups. This method triggers control actions based on state information such as relative distance and speed between vehicles to adjust the position, speed, and acceleration of heterogeneous vehicles, ensuring the consistency of cooperative driving in mixed-traffic vehicle groups under communication interruption conditions. A review of relevant literature reveals few studies on event-triggered cooperative control of mixed-traffic vehicle groups under communication interruption conditions. Therefore, how to more effectively improve the stability of cooperative driving in mixed-traffic vehicle groups under communication interruption conditions remains an unresolved research issue. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method for coordinated control of mixed traffic group handover based on event triggering under communication interruption conditions. This method can effectively ensure the consistency and stability of coordinated driving during the handover of mixed traffic group under communication interruption conditions, thereby helping to improve road traffic efficiency.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A method for event-triggered handover coordination control of mixed-traffic groups under communication interruption conditions, the method comprising the following steps:

[0008] S1: Design a hybrid traffic scenario that includes connected autonomous vehicles (CAV), autonomous vehicles (AV), and traditional human-driven vehicles (HV);

[0009] S2: Based on vehicle type characteristics, formulate sub-vehicle group division rules and describe the changes in sub-vehicle groups caused by communication interruption;

[0010] S3: Establish a longitudinal dynamics model of heterogeneous vehicles in a mixed traffic group that takes into account communication interruptions, including dynamics models of connected autonomous vehicles, autonomous vehicles, and traditional human-driven vehicles;

[0011] S4: Establish an event-triggered collaborative control strategy to control vehicle status and ensure the consistency and stability of collaborative driving of mixed vehicle groups.

[0012] Furthermore, in S1, a single lane contains M connected autonomous vehicles, K autonomous driving vehicles, and Q traditional human-driven vehicles, where M+K+Q=N, and N represents the total number of vehicles. The autonomous vehicles are equipped with sensors, including LiDAR, millimeter-wave radar, and high-definition cameras; they acquire the status information of adjacent vehicles ahead, including position, speed, and acceleration information; based on the acquired status information, the autonomous vehicles make autonomous decisions and precisely control their own driving state; the connected autonomous vehicles perceive the status information of adjacent vehicles ahead through sensors and acquire the status information of other connected autonomous vehicles, including position, speed, and acceleration information, through vehicle-to-vehicle communication technology; based on this information, the connected autonomous vehicles perform real-time control of their own vehicle status.

[0013] Furthermore, S2 includes:

[0014] S21: Logical sub-vehicle group division rules;

[0015] S22: Changes in the logical sub-vehicle group under communication interruption conditions;

[0016] S23: Kinematic description of mixed-vehicle subgroups;

[0017] In S21, based on the characteristics of connected autonomous vehicles, autonomous vehicles, and traditional human-driven vehicles, there are four scenarios for the sub-vehicle group division rules:

[0018] (1) A subgroup of vehicles consists of a lead connected autonomous vehicle, k autonomous vehicles and q traditional human-driven vehicles;

[0019] (2) A sub-group of vehicles consists of a lead connected autonomous vehicle and k autonomous vehicles;

[0020] (3) A sub-group of vehicles consists of a lead connected autonomous vehicle and q traditional human-driven vehicles;

[0021] (4) A subgroup of vehicles contains only one lead connected autonomous vehicle;

[0022] In S22, when the connected autonomous vehicle is affected by communication failure while driving on the road, it is unable to obtain the status information of other connected autonomous vehicles. At this time, the connected autonomous vehicle degenerates into an autonomous vehicle, and the sub-vehicle group is reorganized with the previous sub-vehicle group to form a new sub-vehicle group.

[0023] In S23, the state of each sub-vehicle group approximates the state of a connected autonomous vehicle, and the longitudinal kinematic model of each sub-vehicle group is defined as:

[0024]

[0025] In the formula, P sub,l V sub,l A sub,l and L sub,l This represents the position, velocity, acceleration, and length of the l-th subgroup of vehicles at time t. Let len ​​represent the position, velocity, acceleration, and length of the leading connected autonomous vehicle in the l-th subgroup at time t; This indicates the position of the last car in the l-th subgroup. * This refers to either an autonomous vehicle or a traditional human-driven vehicle.

[0026] Furthermore, in S3, the l-th sub-group of vehicles... i The longitudinal driving behavior of the vehicle can be represented by a third-order linear model as follows:

[0027]

[0028] In the formula, Where p l,i ,v l,i and a l,i Indicates the l-th subgroup of vehicles. i The vehicle's longitudinal position, velocity, and acceleration; T l,i >0 indicates the time constant of the power transmission system; u l,i (t-Ω l,i ) represents the l-th subgroup of vehicles. i Vehicle control input, Ω l,i This represents the different time delays of heterogeneous vehicles, and

[0029]

[0030] S3 specifically includes the following steps:

[0031] S31: In the absence of communication failure, the lead connected autonomous vehicle in each sub-group obtains the status information of the lead connected autonomous vehicles in other sub-groups through vehicle-to-vehicle communication, and obtains the status information of the driver-driven vehicles at the rear of the adjacent sub-groups through onboard sensors. The control input of the lead connected autonomous vehicle in the l-th sub-group is represented as:

[0032]

[0033] In the formula, and This represents the position, speed, and acceleration of the leading connected autonomous vehicle in the l-th subgroup. and This represents the position, speed, and acceleration of the leading connected autonomous vehicle in the j-th subgroup. This represents the expected distance between the leading connected autonomous vehicle in the l-th sub-group and the last vehicle in the (l-1)-th sub-group. This represents the expected distance between the leading connected automated vehicle in the l-th subgroup and the leading connected automated vehicle in the j-th subgroup; and τ represents the position, speed, and acceleration control gain of the leading connected autonomous vehicle in the l-th sub-vehicle group. l,0 and θ l,0 This represents communication latency and perceived latency;

[0034] In a mixed vehicle group, when one or more connected autonomous vehicles are unable to obtain the status information of other connected autonomous vehicles due to communication interruption, the connected autonomous vehicle relies on onboard sensors to measure the status information of the adjacent vehicles in front to control its own behavior. The connected autonomous vehicle degenerates into an autonomous vehicle, the communication topology of the mixed vehicle group changes, and the dynamics model of the connected autonomous vehicle will be switched to the dynamics model of the autonomous vehicle.

[0035] S32: The autonomous vehicle lacks communication capabilities. The autonomous vehicle in the l-th sub-group obtains the state information of adjacent vehicles ahead based on its onboard sensors and adjusts its own vehicle's state accordingly. The longitudinal dynamics model of the autonomous vehicle in the l-th sub-group is represented as:

[0036]

[0037] In the formula, and Indicates the l-th subgroup. i The position, speed, and acceleration of the autonomous vehicle and This represents the position, speed, and acceleration of the (i-1)th autonomous vehicle in the l-th subgroup. and This represents the position, speed, and acceleration control gain of the autonomous vehicle in the l-th subgroup of vehicles; Indicates the l-th subgroup. i The expected distance between autonomous vehicles;

[0038] When the leading connected autonomous vehicle in the l-th sub-vehicle group experiences a communication interruption, the connected autonomous vehicle degenerates into an autonomous vehicle, and the longitudinal dynamics model of the connected autonomous vehicle that experienced the communication interruption is switched to the longitudinal dynamics model of the autonomous vehicle; at the same time, the l-th sub-vehicle group reorganizes with the preceding sub-vehicle groups to form a new sub-vehicle group.

[0039] S33: An improved IDM model considering driver randomness and reaction time delay is proposed. The dynamic model of the i-th traditional human-driven vehicle in the l-th subgroup is expressed as:

[0040]

[0041] In the formula, Indicates the l-th subgroup of vehicles. i The speed of a conventionally driven vehicle, where a, b, and c represent the maximum acceleration, comfortable deceleration, and acceleration index, respectively; and Let represent the expected and actual vehicle distances between the i-th traditional human-driven vehicle and the vehicle in front in the l-th subgroup of vehicles; v represents the reaction time delay of the i-th traditional human-driven vehicle in the l-th subgroup of vehicles. des Indicates the desired speed of the vehicle; δ a This represents the acceleration noise generated by the driver's random actions, and d0 and T represent the minimum distance and expected time interval between vehicles, respectively. This represents the speed difference between the i-th traditional human-driven vehicle and the adjacent vehicle in front of it in the l-th subgroup.

[0042] Furthermore, in S4, when the communication of the leading connected autonomous vehicle in the sub-vehicle group is interrupted, the connected autonomous vehicle degenerates into an autonomous vehicle, and the current sub-vehicle group merges with the adjacent sub-vehicle group in front to switch into a new sub-vehicle group; an event-triggered mixed vehicle group switching cooperative control strategy is established.

[0043] S4 specifically includes the following steps:

[0044] S41: Set the event trigger time of the i-th vehicle in the l-th subgroup to t. l,i,k Let k = 0, 1, ..., and define the event trigger function for the i-th vehicle in the l-th subgroup as follows:

[0045]

[0046] In the formula, Let x be the state measurement error, and xl,i =[p l,i ,v l,i ,a l,i ] T That is, the i-th car in the l-th subgroup is in t l,i,k The difference between the state at time t and the state at time t, where * represents the vehicle type, including CAV, AV, or HV; Used to quantify the state measurement error of the i-th vehicle in the l-th sub-vehicle group. This represents the upper limit threshold for the state measurement error of the i-th vehicle within the l-th subgroup. Δp represents the positional difference between the i-th vehicle and its preceding adjacent vehicle in the l-th subgroup. l,i Speed ​​difference Δv l,i and acceleration difference Δa l,i The matrix, where λ and δ are κ. ∞ Class function, ρ * ρ is the scaling factor for the heterogeneous vehicle event triggering condition, and 0 < ρ * <1;

[0047] S42: When the i-th vehicle in the l-th subgroup can quickly track the state of the adjacent vehicles in front. Become very small, make When the distance between the i-th car in the l-th subgroup and its preceding neighbor is much greater than the expected distance, It became very large, making This indicates that the state of the i-th vehicle in the l-th subgroup cannot be consistent with the state of the vehicle in front, i.e., the event is triggered. The event trigger time t for the i-th vehicle in the l-th subgroup is... l,i,k pass The solution yields the control input of the i-th vehicle in the l-th subgroup. and the state at the trigger time Update once, The next trigger time is then obtained through the event trigger function, thus obtaining the trigger time t. l,i,k+1 , t l,i,k+2 ...; Between two triggering times, the control input of the i-th vehicle in the l-th subgroup remains constant, that is, for t∈[t... l,i,k+n ,t l,i,k+n+1 ),have

[0048] The beneficial effects of this invention are as follows: This invention utilizes intelligent connected vehicle technology and autonomous driving technology to obtain the status information of heterogeneous vehicles, and designs an event-triggered collaborative control method for mixed traffic group switching under communication interruption conditions. This method can improve the traffic efficiency and safety of roads and provide a new approach to solving new types of mixed traffic congestion.

[0049] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0050] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein:

[0051] Figure 1 This is a schematic diagram of a novel mixed traffic scenario according to the present invention;

[0052] Figure 2 This is a schematic diagram of the logical vehicle group division rules of the present invention:

[0053] Figure 3 This is a schematic diagram of logical vehicle group switching under communication interruption conditions of the present invention. Detailed Implementation

[0054] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0055] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0056] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0057] Please see Figures 1-3 This is a collaborative control method for switching of mixed traffic groups based on event triggering under communication interruption conditions.

[0058] The event-triggered cooperative control method for mixed-traffic group handover under communication interruption conditions of the present invention includes the following steps:

[0059] S1. Design a hybrid traffic scenario that aligns with future roads;

[0060] S2. Give the logical sub-vehicle group division rules and kinematic description considering communication interruption;

[0061] S3. Constructing a longitudinal dynamics model of heterogeneous vehicles in a mixed traffic group under communication interruption conditions;

[0062] S4. Establish a collaborative control strategy for switching between mixed traffic groups based on event triggering.

[0063] Furthermore, in S1, a single lane contains M connected autonomous vehicles, K autonomous vehicles, and Q traditional human-driven vehicles, and M + K + Q = N, where N represents the total number of vehicles. Figure 1 As shown, autonomous vehicles are equipped with advanced sensors (such as LiDAR, millimeter-wave radar, and high-definition cameras) that can accurately acquire the status information (such as position, speed, and acceleration) of adjacent vehicles ahead. Based on this information, autonomous vehicles make autonomous decisions and precisely control their own driving state. Connected autonomous vehicles can not only perceive the status information of adjacent vehicles through sensors, but also acquire the status information (such as position, speed, and acceleration) of other connected autonomous vehicles through vehicle-to-vehicle communication technology. Based on this information, connected autonomous vehicles can control their own vehicle status in real time. In contrast, traditional human drivers rely solely on their eyes to obtain the status information of vehicles ahead and cannot directly control the vehicle. In other words, the driving state of traditional human drivers needs to closely follow the driving state of the vehicles adjacent to them.

[0064] Furthermore, S2 includes the following steps:

[0065] S21, Logical sub-vehicle group division rules;

[0066] S22. Changes in the logical sub-vehicle group under communication interruption conditions;

[0067] S23, Kinematic description of mixed-traffic vehicle subgroups;

[0068] Furthermore, in S21, based on the characteristics of connected autonomous vehicles, autonomous vehicles, and traditional human-driven vehicles, there are four scenarios for the sub-vehicle group division rules, such as... Figure 2 As shown, they are respectively:

[0069] (1) A subgroup of vehicles consists of a lead connected autonomous vehicle, k autonomous vehicles and q traditional human-driven vehicles;

[0070] (2) A sub-group of vehicles consists of a lead connected autonomous vehicle and k autonomous vehicles;

[0071] (3) A sub-group of vehicles consists of a lead connected autonomous vehicle and q traditional human-driven vehicles;

[0072] (4) A subgroup of vehicles contains only one lead connected autonomous vehicle.

[0073] Furthermore, in S22, connected autonomous vehicles are susceptible to communication failures while driving on the road, resulting in their inability to obtain status information from other connected autonomous vehicles. In this case, the connected autonomous vehicle degenerates into a fully autonomous vehicle. Then, the sub-vehicle group will reorganize with the previous sub-vehicle groups to form a new sub-vehicle group; that is, a small sub-vehicle group switches to a large sub-vehicle group, such as... Figure 3 As shown.

[0074] from Figure 2 As can be seen, when a communication interruption occurs in the connected autonomous vehicle group of the second sub-group, the connected autonomous vehicle cannot obtain the status information of other connected autonomous vehicles. Therefore, the second sub-group forms a new sub-group with the first sub-group, such as... Figure 3 As shown in sub-car group 1.

[0075] Furthermore, in S23, to ensure the stability of the mixed vehicle group, the state of each sub-group of vehicles approximates the state of a connected autonomous vehicle. Therefore, the longitudinal kinematic model of each sub-group of vehicles can be defined as:

[0076]

[0077] In the formula, P sub,l V sub,l A sub,l and L sub,l This represents the position, velocity, acceleration, and length of the l-th subgroup of vehicles at time t. Let len ​​represent the position, speed, acceleration, and length of the leading connected autonomous vehicle in the l-th subgroup at time t. This indicates the position of the last car in the l-th subgroup. * This refers to either an autonomous vehicle or a traditional human-driven vehicle.

[0078] Furthermore, in S3, the l-th subgroup of vehicles... i The longitudinal driving behavior of a vehicle can be represented by a third-order linear model as follows:

[0079]

[0080] In the formula, Where p l,i ,v l,i and a l,i Indicates the l-th subgroup of vehicles. i The vehicle's longitudinal position, velocity, and acceleration; T l,i >0 indicates the time constant of the power transmission system; u l,i (t-Ω l,i ) represents the l-th subgroup of vehicles. i Vehicle control input, Ω l,i This represents the different time delays of heterogeneous vehicles, and

[0081]

[0082] Furthermore, S3 specifically includes the following steps:

[0083] S31: In the absence of communication failure, the leading connected autonomous vehicle in each sub-group obtains the status information of the leading connected autonomous vehicles in other sub-groups through vehicle-to-vehicle communication, and obtains the status information of the driver-driven vehicles at the rear of the adjacent sub-groups through onboard sensors. Then, the control input of the leading connected autonomous vehicle in the l-th sub-group can be represented as:

[0084]

[0085] In the formula, and This represents the position, speed, and acceleration of the leading connected autonomous vehicle in the l-th subgroup. and This represents the position, speed, and acceleration of the leading connected autonomous vehicle in the j-th subgroup. This represents the expected distance between the leading connected autonomous vehicle in the l-th sub-group and the last vehicle in the (l-1)-th sub-group. This represents the expected distance between the leading connected automated vehicle in the l-th subgroup and the leading connected automated vehicle in the j-th subgroup. and τ represents the position, speed, and acceleration control gain of the leading connected autonomous vehicle in the l-th sub-vehicle group. l,0 and θ l,0 This represents communication latency and perceived latency.

[0086] In a mixed vehicle group, when one or more connected autonomous vehicles are unable to obtain the status information of other connected autonomous vehicles due to communication interruption, the connected autonomous vehicle can only rely on onboard sensors to measure the status information of the adjacent vehicles in front to control its own behavior. In other words, the connected autonomous vehicle degenerates into an autonomous vehicle, and the communication topology of the mixed vehicle group will also change. Then the dynamics model of the connected autonomous vehicle will be switched to the dynamics model of the autonomous vehicle.

[0087] S32: Since autonomous vehicles lack communication capabilities, the autonomous vehicles in the l-th sub-group can only obtain the state information of adjacent vehicles ahead based on onboard sensors and adjust their own vehicle state accordingly. Therefore, the longitudinal dynamics model of the autonomous vehicles in the l-th sub-group can be represented as:

[0088]

[0089] In the formula, and Indicates the l-th subgroup. i The position, speed, and acceleration of the autonomous vehicle and This represents the position, speed, and acceleration of the (i-1)th autonomous vehicle in the l-th subgroup. and This represents the position, speed, and acceleration control gain of the autonomous vehicle in the l-th subgroup of vehicles; Indicates the l-th subgroup. i The expected distance between autonomous vehicles.

[0090] If the lead connected vehicle in the l-th sub-vehicle group suddenly experiences a communication interruption, then this connected vehicle degenerates into an autonomous vehicle. In other words, the longitudinal dynamics model of the connected vehicle experiencing the communication interruption switches to the longitudinal dynamics model of an autonomous vehicle. Simultaneously, the l-th sub-vehicle group needs to regroup with the preceding sub-vehicle groups to form a new sub-vehicle group.

[0091] S33: To more realistically describe the driving behavior of traditional human drivers, an improved IDM model considering driver randomness and reaction time delay is proposed. Then, in the l-th subgroup of vehicles... i The dynamic model of a traditional human-driven vehicle can be represented as:

[0092]

[0093] In the formula, Indicates the l-th subgroup of vehicles. i The speed of a conventionally driven vehicle, where a, b, and c represent the maximum acceleration, comfortable deceleration, and acceleration index, respectively; and Indicates the l-th subgroup of vehicles. i The expected and actual distance between a traditional human-driven vehicle and the vehicle in front; Indicates the l-th subgroup of vehicles. i Traditional human-driven vehicle reaction time delay, v des Indicates the desired speed of the vehicle; δ a This represents the acceleration noise generated by the driver's random actions, and d0 and T represent the minimum distance and expected time interval between vehicles, respectively. Indicates the l-th subgroup of vehicles. i The speed difference between a traditional human-driven vehicle and the vehicle adjacent to it in front.

[0094] Furthermore, in S4, when the leading connected autonomous vehicle in the sub-group experiences a communication interruption, the connected autonomous vehicle degenerates into an autonomous vehicle, and the current sub-group merges with the adjacent sub-groups to form a new sub-group. To ensure the stability of the mixed-traffic group switching under communication interruption conditions, an event-triggered mixed-traffic group switching cooperative control strategy is established.

[0095] Furthermore, S4 specifically includes the following steps:

[0096] S41: Set the event trigger time of the i-th vehicle in the l-th subgroup to t. l,i,k Let k = 0, 1, ..., and define the event trigger function for the i-th vehicle in the l-th subgroup as follows:

[0097]

[0098] In the formula, Let x be the state measurement error, and x l,i =[p l,i ,v l,i ,a l,i ] T That is, the i-th car in the l-th subgroup is in t l,i,k The difference between the state at time t and the state at time t, where * represents the vehicle type (CAV, AV, or HV); Used to quantify the state measurement error of the i-th vehicle in the l-th sub-vehicle group. This represents the upper limit threshold for the state measurement error of the i-th vehicle within the l-th subgroup. Δp represents the positional difference between the i-th vehicle and its preceding adjacent vehicle in the l-th subgroup. l,i Speed ​​difference Δv l,i and acceleration difference Δal,i The matrix, where λ and δ are κ. ∞ Class function, ρ * ρ is the scaling factor for the heterogeneous vehicle event triggering condition, and 0 < ρ * <1.

[0099] S42: If the i-th vehicle in the l-th subgroup can quickly track the state of its preceding neighboring vehicles, then... It will become very small, making When the distance between the i-th car in the l-th subgroup and its preceding adjacent car is much greater than the expected distance, then... It will become very large, making therefore, This indicates that the state of the i-th vehicle in the l-th subgroup cannot be consistent with the state of the vehicle in front, i.e., the event is triggered. The event trigger time t for the i-th vehicle in the l-th subgroup is... l,i,k It can be done The solution yields the control input of the i-th vehicle in the l-th subgroup. and the state at the trigger time Update once, at this time The next trigger time is then obtained through the event trigger function, thus yielding the trigger time t. l,i,k+1 , t l,i,k+2 ... Between the two triggering times, the control input of the i-th vehicle in the l-th subgroup remains constant, that is, for t∈[t... l,i,k+n ,t l,i,k+n+1 ),have

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for coordinated control of mixed-traffic group handover based on event triggering under communication interruption conditions, characterized in that: The method includes the following steps: S1: Design a hybrid traffic scenario that includes connected autonomous vehicles (CAV), autonomous vehicles (AV), and traditional human-driven vehicles (HV); S2: Based on vehicle type characteristics, formulate sub-vehicle group division rules and describe the changes in sub-vehicle groups caused by communication interruption; S3: Establish a longitudinal dynamics model of heterogeneous vehicles in a mixed traffic group that takes into account communication interruptions, including dynamics models of connected autonomous vehicles, autonomous vehicles, and traditional human-driven vehicles; In S3, the first The first in the group of cars The longitudinal driving behavior of the vehicle can be represented by a third-order linear model as follows: In the formula, ,in , and Indicates the first The first in the group of cars The vehicle's longitudinal position, velocity, and acceleration; Represents the time constant of the power transmission system; Indicates the first The first in the group of cars Vehicle control inputs, This represents the different time delays of heterogeneous vehicles, and , , S3 specifically includes the following steps: S31: In the absence of communication failure, the lead connected autonomous vehicle in each sub-group obtains the status information of the lead connected autonomous vehicles in other sub-groups through vehicle-to-vehicle communication, and obtains the status information of the vehicles driven by drivers in the rear of the adjacent sub-groups through onboard sensors. The control input for the lead connected autonomous vehicle in a group of vehicles is represented as follows: In the formula, , and Indicates the first The position, speed, and acceleration of the lead connected autonomous vehicle in a group of vehicles. , and Indicates the first The position, speed, and acceleration of the lead connected autonomous vehicle in a group of vehicles. Indicates the first The leading connected autonomous vehicle in the group of cars and the first The expected distance between the last car in a group of cars Indicates the first The leading connected autonomous vehicle in the group of cars and the first The expected spacing between the leading connected autonomous vehicles in a group of vehicles; , and Indicates the first The position, speed, and acceleration control gain of the lead connected autonomous vehicle in a group of vehicles. and This represents communication latency and perceived latency; In a mixed vehicle group, when one or more connected autonomous vehicles are unable to obtain the status information of other connected autonomous vehicles due to communication interruption, the connected autonomous vehicle relies on onboard sensors to measure the status information of the adjacent vehicles in front to control its own behavior. The connected autonomous vehicle degenerates into an autonomous vehicle, the communication topology of the mixed vehicle group changes, and the dynamics model of the connected autonomous vehicle will be switched to the dynamics model of the autonomous vehicle. S32: Autonomous vehicles lack communication capabilities. In a convoy of vehicles, autonomous vehicles obtain status information from adjacent vehicles ahead using onboard sensors, and adjust their own vehicle status accordingly. The longitudinal dynamics model of autonomous vehicles in a group of vehicles is represented as follows: In the formula, , and Indicates the first The first group of cars The position, speed, and acceleration of the autonomous vehicle , and Indicates the first The first group of cars The position, speed, and acceleration of the autonomous vehicle , and Indicates the first Position, speed, and acceleration control gains of autonomous vehicles in a group of vehicles; Indicates the first The first group of cars The expected distance between autonomous vehicles; When the If the lead connected autonomous vehicle in a group of vehicles experiences a communication outage, it degenerates into an autonomous vehicle, and its longitudinal dynamics model switches to that of the autonomous vehicle. Simultaneously, the... Each subgroup of vehicles is reorganized with the preceding subgroup of vehicles to form a new subgroup of vehicles; S33: An improved IDM model considering driver randomness and reaction time delay is proposed. The first in the group of cars i The dynamic model of a traditional human-driven car is represented as follows: In the formula, Indicates the first The first in the group of cars The speed of a traditional human-driven vehicle , and These represent maximum acceleration, comfortable deceleration, and acceleration index, respectively. and Indicates the first The first in the group of cars i The expected and actual distance between a traditional human-driven vehicle and the vehicle in front; Indicates the first The first in the group of cars i Traditional human-driven vehicles have a delayed reaction time. Indicates the vehicle's desired speed; This represents the acceleration noise generated by the driver's random actions. and Indicates the minimum distance and expected time interval between vehicles; Indicates the first The first in the group of cars i The speed difference between a traditional human-driven vehicle and the vehicle adjacent to it in front; S4: Establish an event-triggered collaborative control strategy to control vehicle status and ensure the consistency and stability of collaborative driving of mixed vehicle groups.

2. The event-triggered collaborative control method for mixed-traffic group handover under communication interruption conditions as described in claim 1, characterized in that: In S1, the single lane includes Connected autonomous vehicles autonomous vehicles and A traditional human-driven vehicle, and , This indicates the total number of vehicles; autonomous vehicles are equipped with sensors, including LiDAR, millimeter-wave radar, and high-definition cameras; they acquire status information of adjacent vehicles ahead, including position, speed, and acceleration information; based on the acquired status information, autonomous vehicles make autonomous decisions and precisely control their own driving state; connected autonomous vehicles perceive the status information of adjacent vehicles ahead through sensors and acquire the status information of other connected autonomous vehicles through vehicle-to-vehicle communication technology, including position, speed, and acceleration information; based on this information, connected autonomous vehicles perform real-time control of their own vehicle status.

3. The event-triggered collaborative control method for mixed-traffic group handover under communication interruption conditions as described in claim 1, characterized in that: S2 includes: S21: Logical sub-vehicle group division rules; S22: Changes in the logical sub-vehicle group under communication interruption conditions; S23: Kinematic description of mixed-vehicle subgroups; In S21, based on the characteristics of connected autonomous vehicles, autonomous vehicles, and traditional human-driven vehicles, there are four scenarios for the sub-vehicle group division rules: (1) A subgroup of vehicles contains a lead connected autonomous vehicle. autonomous vehicles and A traditional human-driven vehicle; (2) A sub-vehicle group includes a lead connected autonomous vehicle and A self-driving car; (3) A sub-vehicle group consists of a lead connected autonomous vehicle and A traditional human-driven vehicle; (4) A subgroup of vehicles contains only one lead connected autonomous vehicle; In S22, when the connected autonomous vehicle is affected by communication failure while driving on the road, it is unable to obtain the status information of other connected autonomous vehicles. At this time, the connected autonomous vehicle degenerates into an autonomous vehicle, and the sub-vehicle group is reorganized with the previous sub-vehicle group to form a new sub-vehicle group. In S23, the state of each sub-vehicle group approximates the state of a connected autonomous vehicle, and the longitudinal kinematic model of each sub-vehicle group is defined as: In the formula, , , and Indicates in Time of the first The position, speed, acceleration, and length of each vehicle group; , , and Indicates in Time of the first The position, speed, acceleration, and length of the lead connected autonomous vehicle within a group of vehicles; Indicates the first The position of the last car in the group of cars. This refers to either an autonomous vehicle or a traditional human-driven vehicle.

4. The event-triggered collaborative control method for mixed-traffic group handover under communication interruption conditions as described in claim 1, characterized in that: In S4, when the communication of the leading connected autonomous vehicle in the sub-vehicle group is interrupted, the connected autonomous vehicle degenerates into an autonomous vehicle, and the current sub-vehicle group merges with the adjacent sub-vehicle group in front to switch into a new sub-vehicle group; and an event-triggered mixed vehicle group switching cooperative control strategy is established. S4 specifically includes the following steps: S41: Setting the... The first in the group of cars The event trigger time for the vehicle is , At the same time, define the first The first group of cars The event trigger function for the vehicle is: In the formula, For state measurement error, and That is, the first The first in the group of cars The car is Current state and time The difference in state at any given time, where * represents the vehicle type, including CAV, AV, or HV; Used to quantify the The first group of cars Vehicle condition measurement error. Indicates the first The first in the group of cars The upper limit threshold for vehicle condition measurement error. Indicates the first The first in the group of cars Position difference between the vehicle and the adjacent vehicle in front Speed ​​difference and acceleration difference The matrix, , for Class function, This is the scaling factor for the heterogeneous vehicle event triggering condition, and ; S42: When the first The first in the group of cars The vehicle can quickly track the status of the adjacent vehicles in front. Become very small, make When the first The first in the group of cars When the distance between a vehicle and the adjacent vehicle in front is much greater than the expected distance, It became very large, making ; Indicates the first The first in the group of cars The vehicle's state cannot be consistent with the state of the vehicle in front, i.e., the event is triggered, the first... The first in the group of cars Vehicle event trigger time pass The solution yields the result of the first step. The first in the group of cars Vehicle control input and the state at the trigger time Update once, Then, the next trigger time is obtained through the event trigger function, thus obtaining the trigger time. , , Between the two triggering times, the first The first in the group of cars The control inputs of the vehicle remain constant, that is, for ,have .

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