Method and device for identifying intelligent network connection vehicle cooperation party in ramp confluence area

Abstract

The invention belongs to the technical field of intelligent traffic, and provides a method and a device for identifying an intelligent network connection vehicle cooperation party in a ramp confluence area. According to the invention, the cooperative vehicles of the intelligent network connection vehicles are dynamically screened and confirmed through the communication between the intelligent network connection vehicles and the road side unit in combination with the real-time data collected by the road side unit, so that the intelligent network connection vehicles on the ramp can be ensured to safely and efficiently converge into the main lane. Through a step-by-step screening process, the intelligent network connection vehicle firstly finds the key vehicle in the main lane range through the overall traffic information of the road side unit RSU, and then finds the cooperative vehicle through the expected movement track of the key vehicle, so that cooperative party identification of the intelligent network connection vehicle is realized. According to the invention, the identification accuracy and efficiency of the cooperation party are improved, so that the intelligent network connection vehicle can better adapt to the mixed traffic environment.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and in particular to a method and device for identifying cooperative parties of intelligent connected vehicles in a ramp merging area. Background Art

[0002] The ramp merging area is a typical bottleneck area in the highway. The influx of ramp vehicles often causes serious interference to the traffic flow of the main road, significantly affecting traffic efficiency and safety. When ramp vehicles enter the main lane, the stability of the traffic flow on the main road is disrupted, which in turn causes traffic congestion, increased accident risks and other problems.

[0003] With the rapid development of intelligent network technology, connected-automated vehicles (CAVs) have shown great potential in solving these problems. CAVs have high-precision motion control capabilities and efficient information communication capabilities. They can effectively optimize the ramp merging process through enhanced collaborative strategies and improve the overall efficiency and safety of traffic flow. Therefore, the application of CAVs in ramp merging operations has become a hot topic in current traffic research, showing a wide range of application prospects in alleviating traffic interference.

[0004] In the ramp merging area, the selection of collaborators for intelligent connected vehicles is particularly critical. The collaborators in this article refer to other vehicles that can ensure the safe merging of HVs by appropriately adjusting their own driving behaviors (such as acceleration and deceleration, lane changing, etc.). In the ramp merging scenario, vehicles need to coordinate with other vehicles or infrastructure on the main road to ensure smooth and safe merging into the main road. However, the simple rule-based screening strategies commonly used in the existing technology are difficult to fully consider the dynamics and diversity of traffic, especially in mixed traffic environments (such as the coexistence of autonomous driving vehicles and manually driven vehicles). It is difficult for traditional methods to achieve accurate selection of collaborators.

[0005] In the existing technologies selected by intelligent connected vehicle-road collaboration parties, there are the following main technical problems:

[0006] 1) Insufficient real-time performance in partner selection: Most existing solutions rely on preset rules or static thresholds (such as distance or speed difference), which makes it difficult for vehicles to select the best partner in real time and accurately in a high-speed, dynamically changing traffic environment. Especially in complex ramp merging areas, partner selection that is not real-time may lead to an unsmooth merging process or increase the risk of collision.

[0007] 2) Incomplete information: In the traditional ramp collaborative selection method, the vehicle status information of the ramp and the main line mainly depends on the data collected by fixed detectors. The data of fixed detectors is not accurate and the information is relatively lagging, which makes it difficult to meet the real-time requirements of merging vehicle flow control. This may lead to a decrease in the accuracy of the collaborative party selection, especially when the environmental information is more complex.

[0008] 3) Poor adaptability to mixed traffic environments: In a mixed traffic environment where autonomous vehicles and traditional manually driven vehicles coexist, the existing collaborative selection scheme is difficult to take into account the behavioral characteristics and driving modes of different types of vehicles, resulting in low efficiency of collaborative cooperation and possible merging failures or congestion. Summary of the invention

[0009] In view of the defects in the prior art, the present invention provides a method and device for identifying the cooperating party of an intelligent networked vehicle in a ramp merging area, so as to improve the accuracy and efficiency of identifying the cooperating party and reduce the merging failure or congestion of intelligent networked vehicles.

[0010] A method for identifying cooperative parties of intelligent connected vehicles in a ramp merging area, comprising:

[0011] According to the real-time position of the main vehicle and the ideal merging point, determine the critical moment for the main vehicle to merge from the ramp into the adjacent main lane of the ramp;

[0012] The position of the main vehicle at the critical moment is determined as the critical position, and the speed of the main vehicle at the critical moment is determined as the critical speed;

[0013] A coordinate system is established with the key position as the origin, and vehicles within a preset lateral range on the left and right sides of the origin are selected as the key vehicle set;

[0014] The expected time is calculated based on the critical speed, critical position and the position of the ideal confluence point;

[0015] Determine the expected position of each key vehicle in the key vehicle set according to the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the critical moment;

[0016] The cooperative vehicle that merges with the main vehicle is determined based on the expected positions of each key vehicle in the key vehicle set and the position of the ideal merging point.

[0017] Furthermore, it also includes:

[0018] The intersection of the lane centerline of the ramp entrance and the lane edgeline of the main lane adjacent to the ramp is determined as the ideal merging point.

[0019] Furthermore, according to the real-time position of the main vehicle and the ideal merging point, the key moment for the main vehicle to merge from the ramp into the main lane adjacent to the ramp is determined, including:

[0020] The moment when the straight-line distance between the real-time position of the main vehicle and the ideal merging point is equal to 40m is determined as the key moment for the main vehicle to merge from the ramp into the main lane adjacent to the ramp.

[0021] Furthermore, the expected time is calculated based on the distance between the critical speed, the critical position and the ideal confluence point, including:

[0022] The expected time is calculated based on the critical speed, critical position and the position of the ideal confluence point using the method shown in the following formula:

[0023]

[0024] Among them, T1 represents the expected time, represents the location of the ideal entry point, x HV (t) represents the key position, v HV (t) represents the critical speed.

[0025] Furthermore, according to the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the key moment, the expected position of each key vehicle in the key vehicle set is calculated, including:

[0026] The expected position of each key vehicle in the key vehicle set is calculated based on the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the critical moment using the method shown in the following formula:

[0027]

[0028] in, represents the expected position of the key vehicle j, v j (t) represents the speed of key vehicle j at the key moment t, a j (t) represents the acceleration of key vehicle j at the key moment t, x j (t) represents the position of key vehicle j at key time t, and Key_car represents the key vehicle set.

[0029] Furthermore, according to the expected positions of each key vehicle in the key vehicle set and the position of the ideal merging point, the cooperative vehicle for merging with the main vehicle is determined, including:

[0030] According to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point, the expected distance between the expected position of each key vehicle in the key vehicle set and the ideal merging point is calculated to obtain an expected distance set;

[0031] Based on the expected spacing set, the cooperative vehicle that merges with the main vehicle is determined.

[0032] A device for identifying cooperative vehicles of intelligent connected vehicles in a ramp merging area includes a first determination unit, a second determination unit, a selection unit, a calculation unit, a third determination unit, and a fourth determination unit, wherein:

[0033] The first determination unit is used to determine the critical moment when the main vehicle merges from the ramp into the main lane adjacent to the ramp according to the real-time position of the main vehicle and the ideal merging point;

[0034] A second determining unit is used to determine the position of the host vehicle at the critical moment as the critical position, and determine the speed of the host vehicle at the critical moment as the critical speed;

[0035] A selection unit is used to establish a coordinate system with the key position as the origin, and select vehicles within a preset lateral range on the left and right sides of the origin as a key vehicle set;

[0036] A calculation unit, used for calculating the expected time according to the key speed, the key position and the position of the ideal merging point;

[0037] A third determining unit is used to determine the expected position of each key vehicle in the key vehicle set according to the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the key moment;

[0038] The fourth determining unit is used to determine the cooperative vehicle that merges with the main vehicle according to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point.

[0039] Beneficial effects of the present invention: The present invention dynamically screens and confirms the cooperative vehicles of the intelligent connected vehicles through the communication between the intelligent connected vehicles and the roadside units, combined with the real-time data collected by the roadside units, to ensure that the intelligent connected vehicles on the ramp merge into the main lane safely and efficiently. The present invention uses a step-by-step screening process to enable the intelligent connected vehicles to first find the key vehicles within the main lane through the overall traffic information of the roadside unit RSU, and then find the cooperative vehicles through the expected motion trajectory of the key vehicles, thereby realizing the identification of the cooperative parties of the intelligent connected vehicles. The present invention improves the accuracy and efficiency of cooperative party identification, allowing intelligent connected vehicles to better adapt to mixed traffic environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific embodiments of the present invention, the following will briefly introduce the drawings required for the specific embodiments or the prior art description. In all the drawings, each element or part is not necessarily drawn according to the actual scale.

[0041] Figure 1 A flowchart of a method for identifying cooperative vehicles of intelligent connected vehicles in a ramp merging area provided by one embodiment of the present invention;

[0042] Figure 2A diagram of a coordinated merging scenario of intelligent connected vehicles on a ramp provided by an embodiment of the present invention;

[0043] Figure 3 A key vehicle identification scene diagram provided by an embodiment of the present invention;

[0044] Figure 4 A scene diagram of cooperative vehicle identification at an ideal merging point provided by an embodiment of the present invention;

[0045] Figure 5 A collaborative vehicle identification flow chart provided by one embodiment of the present invention;

[0046] Figure 6 A scene diagram of a main vehicle that cannot merge at an ideal merging point provided by an embodiment of the present invention;

[0047] Figure 7 A scene diagram of a host vehicle being able to cooperatively merge into an acceleration lane provided by an embodiment of the present invention;

[0048] Figure 8 A scene diagram of cooperative vehicle identification of a host vehicle in an acceleration lane provided by an embodiment of the present invention;

[0049] Fig. 9 A scene diagram of a cooperative vehicle changing lanes in a transition zone provided by an embodiment of the present invention;

[0050] Fig.10 A flowchart of a cooperative vehicle lane-changing behavior analysis provided by an embodiment of the present invention;

[0051] In the attached figure, HV represents the host vehicle; CAV represents other autonomous driving vehicles; HDV represents other manually driven vehicles. DETAILED DESCRIPTION

[0052] The following embodiments of the technical solution of the present invention are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and cannot be used to limit the protection scope of the present invention.

[0053] It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the invention belongs.

[0054] In one embodiment, a method for identifying a cooperating party of an intelligent connected vehicle in a ramp merging area is provided, comprising:

[0055] 1. Determine the critical moment for the main vehicle to merge from the ramp into the adjacent main lane of the ramp based on the real-time position of the main vehicle and the ideal merging point;

[0056] The main lane adjacent to the ramp is called the ramp-adjacent main lane.

[0057] The research scenario of the present invention is mainly to study the scenario of vehicles merging into the main lane from the ramp of the highway. The research scenarios include: 3 main lanes (one of which is a ramp-adjacent main lane) and 1 ramp, or 2 main lanes (one of which is a ramp-adjacent main lane) and 1 ramp, or 1 main lane (a ramp-adjacent main lane) and 1 ramp, etc.

[0058] The research object is the traffic flow where connected autonomous vehicles and manually driven vehicles are mixed. CAV can detect the surrounding vehicle information by itself and has the ability to communicate with the roadside unit RSU. The host vehicle (HV) specifically refers to the autonomous driving vehicle that sends intention information or intention requests, and manually driven vehicles are considered uncontrollable.

[0059] like Figure 2 As shown, a research scenario of 2 main lanes (including 1 ramp adjacent to the main lane) and 1 ramp is displayed.

[0060] The research scenarios shown in the diagrams of the present invention are all 2 main lanes (including 1 ramp adjacent main lane) and 1 ramp, but other research scenarios can also be applied to the collaborative vehicle identification method of 2 main lanes and 1 ramp. Because this series of research scenarios all include the same merging scenario, that is, 1 ramp + 1 ramp adjacent main lane, the present invention is based on the collaborative vehicle identification of the merging scenario.

[0061] The merge scene is divided into three main areas: merge area, transition area, and ramp area (ramp). White vehicles represent autonomous vehicles, while black vehicles represent traditional manually driven vehicles.

[0062] The main vehicle of the present invention is an autonomous driving vehicle, which is represented by HV. Vehicles other than the main vehicle are other vehicles, which include autonomous driving vehicles and manually driven vehicles. Other autonomous driving vehicles traveling on the main lane adjacent to the ramp are represented by CAV, and other manually driven vehicles traveling on the main lane adjacent to the ramp are represented by HDV.

[0063] When an HV needs to merge while driving in the ramp area, it should select an appropriate cooperative vehicle based on the current position of the HV and the conditions of vehicles in the merging area and transition area.

[0064] HV generally performs merging action at the ideal merging point in the merging area until the HV completely enters the Figure 2 The center position of lane 2 is shown.

[0065] Preferably, in order to achieve HV in such a Figure 2 Safe and efficient merging into lane 2 as shown requires pre-setting of the ideal merging point for the HV.

[0066] Preferably, the intersection of the lane centerline of the ramp entrance and the lane edgeline of the main lane adjacent to the ramp is determined as the ideal merging point.

[0067] Preferably, the moment when the straight-line distance between the real-time position of the host vehicle and the ideal merging point is equal to 40 m is determined as the key moment when the host vehicle merges from the ramp into the main lane adjacent to the ramp.

[0068] 2. The position of the main vehicle at the critical moment is determined as the critical position, and the speed of the main vehicle at the critical moment is determined as the critical speed;

[0069] 3. Establish a coordinate system with the key position as the origin, and select vehicles within the preset lateral range on the left and right sides of the origin as the key vehicle set;

[0070] A coordinate system is established with the key position as the origin, and vehicles within a preset lateral range on both sides of the origin are selected as the key vehicle set. That is, the coordinate system only considers the horizontal coordinate values ​​of each key vehicle position in the key vehicle set, and does not consider the vertical coordinate values.

[0071] The preset lateral range is vehicles on the left and right sides of the origin with a certain lateral range length from the origin.

[0072] After the coordinate system is established with the key position as the origin, each vehicle on the main lane adjacent to the ramp will have a horizontal coordinate value. Vehicles on the left and right sides of the origin and within a certain horizontal range from the origin and traveling on the main lane adjacent to the ramp are selected as key vehicles to form a key vehicle set.

[0073] Specifically, the key vehicle set is determined using the following formula:

[0074]

[0075] Among them, x HV (t) represents the horizontal coordinate of HV at the critical moment t, x j (t) represents the horizontal coordinate of the key vehicle j at the key time t, L cr represents a certain lateral range length, Key_car represents the key vehicle set, and all key vehicles in Key_car are within the range L of this HV cr Inside.

[0076] like Figure 3 As shown, the key vehicles at the critical moment are G1, G2, ..., Gn from right to left.

[0077] Preferably, L cr =50m.

[0078] 4. Calculate the expected time based on the key speed, key position and the position of the ideal entry point;

[0079] Preferably, the expected time is calculated according to the key speed, key position and the position of the ideal confluence point using the method shown in the following formula:

[0080]

[0081] Among them, T1 represents the expected time, represents the location of the ideal entry point, x HV (t) represents the key position, v HV (t) represents the critical speed. By default, the main vehicle travels at a constant speed in a straight line from the critical position to the ideal merging point at the critical speed.

[0082] 5. Determine the expected position of each key vehicle in the key vehicle set based on the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the critical moment.

[0083] The expected position of each key vehicle in the key vehicle set is calculated based on the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the critical moment using the method shown in the following formula:

[0084]

[0085] in, represents the expected position of the key vehicle j, v j (t) represents the speed of key vehicle j at the key moment t, a j (t) represents the acceleration of key vehicle j at the key moment t, x j (t) represents the position of key vehicle j at the key time t.

[0086] 6. Determine the cooperative vehicle that merges with the main vehicle based on the expected positions of each key vehicle in the key vehicle set and the position of the ideal merging point.

[0087] According to the expected positions of each key vehicle in the key vehicle set and the position of the ideal merging point, the cooperative vehicles that merge with the main vehicle are determined, including:

[0088] Determine the expected distance between the expected position of each key vehicle in the key vehicle set and the ideal merging point according to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point;

[0089] Preferably, the method shown in the following formula is used to calculate the expected distance between the expected position of each key vehicle in the key vehicle set and the ideal merging point according to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point, so as to obtain the expected distance set:

[0090]

[0091] Among them, D HV (t) represents the expected spacing set, represents the expected distance between the expected position of each key vehicle in the key vehicle set and the ideal merging point, L j is the length of the key vehicle j.

[0092] Based on the expected spacing set, the cooperative vehicle that merges with the main vehicle is determined.

[0093] like Figure 4-Figure 5 As shown, when satisfied When , the candidate cooperative vehicles Gj, Gj+1 are output (Gj, Gj+1 are adjacent key vehicles).

[0094] Determine whether the candidate cooperative vehicle Gj+1 is an autonomous driving vehicle CAV, if so, it is a cooperative vehicle RV merging with the main vehicle;

[0095] Determine whether Gj is an autonomous driving vehicle CAV, if so, it is a cooperative vehicle RV merging with the main vehicle.

[0096] Only when Gj and Gj+1 are both autonomous driving vehicles or when Gj+1 is an autonomous driving vehicle, after receiving the merging intention request from the HV, will they perform corresponding operations according to the coordination instructions of the RSU to assist the main vehicle to merge from the ramp into the adjacent main lane of the ramp.

[0097] If Gj and Gj+1 are both autonomous vehicles, then Gj and Gj+1 are both cooperative vehicles of the main vehicle;

[0098] If Gj+1 is an autonomous driving vehicle and Gj is a manually driven vehicle, then there is only a cooperative vehicle with Gj+1 as the main vehicle.

[0099] If Gj+1 is not an autonomous driving vehicle CAV but an HDV, the main vehicle HV will not be able to merge from the ramp into the adjacent main lane of the ramp at the ideal merging point.

[0100] like Figure 6 As shown in FIG. 1 , the main vehicle HV cannot merge from the ramp into the adjacent main lane of the ramp at the ideal merging point, which includes the following two types:

[0101] Type 1: HDV-HV-CAVType 2: HDV-HV-HDV

[0102] When type 1 or type 2 occurs, the host vehicle cannot find a cooperative vehicle at the ideal merging point to merge into the main lane. At this time, the host vehicle needs to continue driving in the acceleration lane to find a cooperative vehicle to change lanes and merge into the main lane until the following situation occurs: Figure 7 The main vehicle can merge into the main lane only when the type 3 is shown. Figure 8 At this time, it is determined that the following vehicle (autonomous driving vehicle CAV) is a cooperative vehicle RV merging with the main vehicle.

[0103] Type 3: CAV-HV-HDV.

[0104] Preferably, it also includes performing lane change analysis on the cooperative vehicle, such as Figure 9-10 As shown:

[0105] When the main road has multiple main lanes, such as two main lanes, the RV has two options to match the HV:

[0106] Choice 1: Switch from 2 lanes to 1 lane

[0107] Choice 2: Continue driving in lane 2

[0108] It is assumed that in the process of collaborative selection, RV must not only consider its own safety, but also the impact of each choice on upstream vehicles, as well as the acceleration and comfort benefits that can be obtained through the choice.

[0109] Therefore, RV will make choices that provide better overall system benefits.

[0110]

[0111] Where U1(t) and U2(t) represent the utilities of the two choices at time t RV respectively.

[0112] The acceleration of RV at time t is express.

[0113] It represents the deceleration that vehicle f needs to take relative to vehicle l to avoid collision at time t, as a safety measure indicator. l∈{RV,TLV,LV}and f∈{RV,TFV,FV}. The smaller, the safer.

[0114] α, β, γ and ζ are weight coefficients, where α<0, β>0, γ>0 and ζ<0.

[0115] The first item represents the safety consideration of the RV and the front and rear vehicles, and the larger the value, the higher the safety.

[0116] The second item reflects the degree of impact on the following vehicles, with smaller values ​​indicating greater impact.

[0117] The third term represents the speed-up benefit that RV can obtain from its choice, with larger values ​​indicating higher potential speed.

[0118] The fourth item represents the difference between the current and new RV accelerations, characterizing driving comfort, the smaller the more comfortable.

[0119] Assume M RVrepresents the choice of RV, then the cooperation decision of RV can be obtained:

[0120]

[0121] The present invention dynamically screens and confirms the cooperative vehicles of intelligent connected vehicles through the communication between intelligent connected vehicles and roadside units, combined with the real-time data collected by the roadside units, to ensure that the intelligent connected vehicles on the ramp merge into the main lane safely and efficiently. The present invention uses a step-by-step screening process to enable the intelligent connected vehicles to first find the key vehicles within the main lane through the overall traffic information of the roadside unit RSU, and then find the cooperative vehicles through the expected motion trajectory of the key vehicles, thereby realizing the identification of the cooperative parties of the intelligent connected vehicles. The present invention improves the accuracy and efficiency of cooperative party identification, allowing intelligent connected vehicles to better adapt to mixed traffic environments.

[0122] In one embodiment, a device for identifying cooperative vehicles of intelligent connected vehicles in a ramp merging area is provided, comprising a first determination unit, a second determination unit, a selection unit, a calculation unit, a third determination unit and a fourth determination unit, wherein:

[0123] The first determination unit is used to determine the critical moment when the main vehicle merges from the ramp into the main lane adjacent to the ramp according to the real-time position of the main vehicle and the ideal merging point;

[0124] A second determining unit is used to determine the position of the host vehicle at the critical moment as the critical position, and determine the speed of the host vehicle at the critical moment as the critical speed;

[0125] A selection unit is used to establish a coordinate system with the key position as the origin, and select vehicles within a preset lateral range on the left and right sides of the origin as a key vehicle set;

[0126] A calculation unit, used for calculating the expected time according to the key speed, the key position and the position of the ideal merging point;

[0127] A third determining unit is used to determine the expected position of each key vehicle in the key vehicle set according to the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the key moment;

[0128] The fourth determining unit is used to determine the cooperative vehicle that merges with the main vehicle according to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point.

[0129] In the description of the present invention, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures and techniques are not shown in detail so as not to obscure the understanding of this description.

[0130] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0131] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for identifying cooperative parties of intelligent connected vehicles in a ramp merging area, characterized in that: include: According to the real-time position of the main vehicle and the ideal merging point, determine the critical moment for the main vehicle to merge from the ramp into the adjacent main lane of the ramp; The position of the main vehicle at the critical moment is determined as the critical position, and the speed of the main vehicle at the critical moment is determined as the critical speed; A coordinate system is established with the key position as the origin, and vehicles within a preset lateral range on the left and right sides of the origin are selected as the key vehicle set; The expected time is calculated based on the critical speed, critical position and the position of the ideal confluence point; Determine the expected position of each key vehicle in the key vehicle set according to the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the critical moment; The cooperative vehicle that merges with the main vehicle is determined based on the expected positions of each key vehicle in the key vehicle set and the position of the ideal merging point.

2. A method for identifying cooperative parties of intelligent connected vehicles in a ramp merging area according to claim 1, characterized in that: Also includes: The intersection of the lane centerline of the ramp entrance and the lane edgeline of the main lane adjacent to the ramp is determined as the ideal merging point.

3. A method for identifying cooperative parties of intelligent connected vehicles in a ramp merging area according to any one of claims 1 or 2, characterized in that: According to the real-time position of the main vehicle and the ideal merging point, determine the key moment for the main vehicle to merge from the ramp into the adjacent main lane of the ramp, including: The moment when the straight-line distance between the real-time position of the main vehicle and the ideal merging point is equal to 40m is determined as the key moment for the main vehicle to merge from the ramp into the main lane adjacent to the ramp.

4. A method for identifying cooperative parties of intelligent connected vehicles in a ramp merging area according to claim 3, characterized in that: The expected time is calculated based on the distance between the key speed, the key position and the ideal merging point, including: The expected time is calculated based on the critical speed, critical position and the position of the ideal confluence point using the method shown in the following formula: Among them, T1 represents the expected time, represents the location of the ideal entry point, x HV (t) represents the key position, v HV (t) represents the critical speed.

5. The method for identifying cooperative parties of intelligent connected vehicles in a ramp merging area according to claim 4, characterized in that: According to the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the critical moment, the expected position of each key vehicle in the key vehicle set is calculated, including: The expected position of each key vehicle in the key vehicle set is calculated based on the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the critical moment using the method shown in the following formula: in, represents the expected position of the key vehicle j, v j (t) represents the speed of key vehicle j at the key moment t, a j (t) represents the acceleration of key vehicle j at the key moment t, x j (t) represents the position of key vehicle j at key time t, and Key_car represents the key vehicle set.

6. A method for identifying cooperative parties of intelligent connected vehicles in a ramp merging area according to claim 5, characterized in that: The step of determining the cooperative vehicle for merging with the main vehicle according to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point includes: According to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point, the expected distance between the expected position of each key vehicle in the key vehicle set and the ideal merging point is calculated to obtain an expected distance set; Based on the expected spacing set, the cooperative vehicle that merges with the main vehicle is determined.

7. A vehicle identification device for intelligent connected vehicles in a ramp merging area, characterized in that: The method comprises a first determining unit, a second determining unit, a selecting unit, a calculating unit, a third determining unit and a fourth determining unit, wherein: The first determination unit is used to determine the critical moment when the main vehicle merges from the ramp into the main lane adjacent to the ramp according to the real-time position of the main vehicle and the ideal merging point; The second determination unit is used to determine the position of the host vehicle at the critical moment as the critical position, and determine the speed of the host vehicle at the critical moment as the critical speed; The selection unit is used to establish a coordinate system with the key position as the origin, and select vehicles within a preset lateral range on the left and right sides of the origin as the key vehicle set; The calculation unit is used to calculate the expected time according to the key speed, the key position and the position of the ideal merging point; The third determining unit is used to determine the expected position of each key vehicle in the key vehicle set according to the expected time, the position, speed and acceleration of each key vehicle in the key vehicle set at the key moment; The fourth determining unit is used to determine the cooperative vehicle that merges with the main vehicle according to the expected position of each key vehicle in the key vehicle set and the position of the ideal merging point.

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