Lane changing control method of vehicle, electronic equipment and vehicle

Abstract

The invention relates to a lane changing control method of a vehicle, electronic equipment and the vehicle, and the method comprises the steps: obtaining the types and / or driving data of traffic participants of a plurality of lanes in a vehicle sensing range; calculating the actual traffic efficiency of the plurality of lanes by using the driving data and / or types; and determining a target lane of the vehicle based on the actual traffic efficiency, and controlling the vehicle to change to the target lane under the condition that the target lane is inconsistent with the current driving lane of the vehicle. According to the embodiment of the invention, the actual traffic efficiency of each lane can be calculated according to the dynamic change of the traffic participants of the multiple lanes in the current driving environment of the vehicle, so that the vehicle is controlled to be always kept in the lane with the highest traffic efficiency, the vehicle can efficiently pass through the current road section, and the driving experience of a user is guaranteed.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to a vehicle lane change control method, electronic equipment, and vehicle. Background Technology

[0002] In related technologies, when controlling vehicle lane changes, the focus is mainly on targets in the forward direction, a single lane, or at most adjacent lanes (such as adaptive cruise control and emergency braking). There is a lack of systematic perception and integration of traffic flow conditions in the side, rear, or further lanes, resulting in a narrow decision-making field of view. Furthermore, the lane-changing logic relies on simple, rule-based triggers, such as determining a lane change based on navigation if the vehicle ahead is moving too slowly, or changing lanes based on congestion information ahead. This is typically a passive lane-changing approach, which is not conducive to effectively improving vehicle traffic efficiency and urgently needs improvement. Summary of the Invention

[0003] This application provides a lane change control method, electronic device, and vehicle to solve the technical problems of related technologies being passive lane change control, having a narrow decision-making field of view, and having lane change logic based on simple rule-based condition triggering, which is not conducive to improving vehicle traffic efficiency and thus affects the user's driving experience.

[0004] The first aspect of this application provides a lane-changing control method for a vehicle, comprising the following steps: acquiring the types and / or driving data of traffic participants in multiple lanes within the vehicle's perception range; calculating the actual traffic efficiency of the multiple lanes using the driving data and / or the types; determining the target lane of the vehicle based on the actual traffic efficiency; and controlling the vehicle to change lanes to the target lane when the target lane is inconsistent with the vehicle's current driving lane.

[0005] Based on the above technical content, the embodiments of this application can calculate the real-time traffic efficiency of each lane based on the types of traffic participants and / or the dynamic changes in driving data of multiple lanes in the current driving environment of the vehicle, so as to actively control the vehicle to always stay in the lane with the highest traffic efficiency, so that the vehicle can pass through the current road segment efficiently, thereby ensuring the user's driving experience.

[0006] Optionally, in one embodiment of this application, calculating the actual traffic efficiency of the multiple lanes using the driving data and / or the type includes: obtaining the initial traffic efficiency of the multiple lanes; and correcting the initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency.

[0007] Based on the above technical content, the embodiments of this application can utilize the type of traffic participants and / or driving data to correct the initial traffic efficiency of each lane in order to obtain an actual traffic efficiency that is more in line with the actual driving scenario.

[0008] Optionally, in one embodiment of this application, the step of correcting the initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency includes: determining the total number of traffic participants and longitudinal speed in any lane based on the driving data of traffic participants in any lane; calculating the average driving speed of any lane based on the total number and the longitudinal speed; calculating a first initial traffic efficiency of any lane based on the average driving speed and the speed limit of any lane; and correcting the first initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency.

[0009] Based on the above technical content, the embodiments of this application can calculate the average driving speed of any lane by calculating the driving data of all traffic participants within the perception range of a vehicle. The average driving speed and the maximum driving speed allowed in the lane are then combined to preliminarily determine the first initial traffic efficiency of the lane. This allows for the quantification of the traffic efficiency of each lane for different lane restrictions, facilitating subsequent calculation of the actual traffic efficiency.

[0010] Optionally, in one embodiment of this application, the step of correcting the initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency includes: acquiring road maintenance information for any lane; detecting, based on the driving data of traffic participants in any lane, whether there is at least one abnormal vehicle in any lane that meets preset acceleration abnormality conditions, and obtaining a detection result; obtaining a first traffic efficiency correction parameter for any lane based on the road maintenance information and / or the detection result; obtaining a second initial traffic efficiency based on the first initial traffic efficiency and the first communication efficiency correction parameter; and correcting the second initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency.

[0011] Based on the above technical content, the embodiments of this application can take into account the impact of road maintenance information and abnormal vehicles on traffic efficiency, so that in the event of construction, abnormal vehicle acceleration, abnormal deceleration, etc., traffic efficiency can be corrected in order to find the optimal target lane.

[0012] Optionally, in one embodiment of this application, obtaining the second initial traffic efficiency based on the first initial traffic efficiency and the first traffic efficiency correction parameter includes: verifying the validity of the first initial traffic efficiency and the first traffic efficiency correction parameter respectively, and obtaining a verification result; and generating the second initial traffic efficiency by combining the verification result, the first initial traffic efficiency, and the first traffic efficiency correction parameter.

[0013] Based on the above technical content, the embodiments of this application can avoid deviations in traffic efficiency calculations caused by data errors by verifying validity, thus ensuring data reliability.

[0014] Optionally, in one embodiment of this application, the step of verifying the validity of the first initial traffic efficiency and the first traffic efficiency correction parameter to obtain a verification result includes: simulating the driving trajectory of the traffic participant in any vehicle based on the driving data of the traffic participant in any lane; determining whether the driving trajectory matches the road maintenance information and / or the detection result; if they match, then determining that the verification result is that the first traffic efficiency correction parameter is valid.

[0015] Based on the above technical content, the embodiments of this application can simulate the driving trajectories of other traffic participants based on driving data in the case of road maintenance or the presence of abnormal vehicles, such as avoiding or slowing down in advance, thereby determining whether the avoidance area of ​​the vehicle matches the location of road maintenance or the location of abnormal vehicles through the driving trajectory, and thus determining whether the first traffic efficiency correction parameter is effective, thereby increasing the reliability of the result.

[0016] Optionally, in one embodiment of this application, the step of verifying the validity of the first initial traffic efficiency and the first traffic efficiency correction parameter to obtain a verification result includes: calculating the relative longitudinal speed between the traffic participant in any lane and the vehicle based on the driving data of the traffic participant in any lane and the current longitudinal speed of the vehicle; calculating a first relative distance change value between the traffic participant in any lane and the vehicle within a preset time window using the relative longitudinal speed; obtaining a second relative distance change value between the vehicle and the traffic participant in any lane within the preset time window; and determining that the verification result is valid for the first initial traffic efficiency in response to whether the difference between the first relative distance change value and the second relative distance change value is less than a preset distance difference.

[0017] Based on the above technical content, the embodiments of this application can use the difference between the theoretical distance change value between traffic participants and vehicles calculated by relative vehicle speed and the actual distance change value directly obtained by the vehicle through sensors to verify whether the first initial traffic efficiency is effective.

[0018] Optionally, in one embodiment of this application, the step of calculating the actual traffic efficiency of multiple lanes using the driving data and / or the type includes: obtaining the number of target type vehicles that meet the preset volume conditions in any lane; calculating the proportion of the target type vehicles in any lane based on the number and the total number; obtaining a second traffic efficiency correction parameter using the proportion, and correcting the second initial traffic efficiency using the second traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0019] Based on the above technical content, the embodiments of this application can take into account the impact of large vehicles on traffic efficiency, and determine the correction parameters for traffic efficiency based on the proportion of large vehicles in the lane.

[0020] Optionally, in one embodiment of this application, calculating the actual traffic efficiency of multiple lanes using the driving data and / or the type includes: calculating the lateral speed of a target traffic participant in any lane based on the driving data of traffic participants in any lane, wherein the target traffic participant is a traffic participant entering or leaving the lane where the vehicle is located; calculating the lateral movement speed feature value of the target traffic participant in any lane based on the lateral movement speed feature value; obtaining a third traffic efficiency correction parameter using the lateral movement speed feature value, and correcting the second initial traffic efficiency using the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0021] Based on the above technical content, the embodiments of this application can take into account the impact of traffic participants' lane-changing trends on traffic efficiency, and determine the correction parameters for traffic efficiency based on the changes in the lateral speed of traffic participants.

[0022] Optionally, in one embodiment of this application, the step of calculating the actual traffic efficiency of multiple lanes using the driving data and / or the type includes: correcting the second initial traffic efficiency using the second traffic efficiency correction parameter and the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0023] Based on the above technical content, the embodiments of this application can combine the second traffic efficiency correction parameter and the third traffic efficiency correction parameter to jointly correct the second initial traffic efficiency, so as to obtain a more accurate actual traffic efficiency.

[0024] A second aspect of this application provides a lane-changing control device for a vehicle, comprising: an acquisition module for acquiring the types and / or driving data of traffic participants in multiple lanes within the vehicle's perception range; a calculation module for calculating the actual traffic efficiency of the multiple lanes using the driving data and / or the types; and a control module for determining the vehicle's target lane based on the actual traffic efficiency, and controlling the vehicle to change lanes to the target lane when the target lane is inconsistent with the vehicle's current driving lane.

[0025] Optionally, in one embodiment of this application, the calculation module includes: a first acquisition unit, configured to acquire the initial traffic efficiency of the plurality of lanes; and a first correction unit, configured to correct the initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency.

[0026] Optionally, in one embodiment of this application, the first correction unit includes: a determining subunit, configured to determine the total number of traffic participants and longitudinal speed in the any lane based on the driving data of traffic participants in the any lane; a first calculating subunit, configured to calculate the average driving speed of the any lane based on the total number and the longitudinal speed; a second calculating subunit, configured to calculate a first initial traffic efficiency of the any lane based on the average driving speed and the speed limit value of the any lane; and a first correction subunit, configured to correct the first initial traffic efficiency using the driving data and / or type to obtain the actual traffic efficiency.

[0027] Optionally, in one embodiment of this application, the first correction unit includes: a first acquisition subunit, configured to acquire road maintenance information of any lane; a detection subunit, configured to detect, based on the driving data of traffic participants in any lane, whether there is at least one abnormal vehicle in any lane that meets a preset acceleration abnormality condition, and obtain a detection result; a second acquisition subunit, configured to obtain a first traffic efficiency correction parameter for any lane based on the road maintenance information and / or the detection result; and a second correction subunit, configured to correct the second initial traffic efficiency using the driving data and / or type, to obtain the actual traffic efficiency.

[0028] Optionally, in one embodiment of this application, the second acquisition subunit includes: a verification subunit, used to verify the validity of the first initial traffic efficiency and the first traffic efficiency correction parameter respectively, and obtain a verification result; and a generation subunit, used to combine the verification result, the first initial traffic efficiency and the first traffic efficiency correction parameter to generate a second initial traffic efficiency.

[0029] Optionally, in one embodiment of this application, the verification component includes: a simulation component, used to simulate the driving trajectory of the traffic participant in any vehicle based on the driving data of the traffic participant in any lane; a judgment component, used to determine whether the driving trajectory matches the road maintenance information and / or the detection result; and a first verification component, used to determine that the verification result is valid for the first traffic efficiency correction parameter if a match is found.

[0030] Optionally, in one embodiment of this application, the verification sub-component includes: a first calculation unit, configured to calculate the relative longitudinal speed between the traffic participant in any lane and the vehicle based on the driving data of the traffic participant in any lane and the current longitudinal speed of the vehicle; a second calculation unit, configured to calculate a first relative distance change value between the traffic participant in any lane and the vehicle within a preset time window using the relative longitudinal speed; an acquisition unit, configured to acquire a second relative distance change value between the vehicle and the traffic participant in any lane within the preset time window; and a second verification unit, configured to determine that the verification result is valid for the first initial traffic efficiency in response to whether the difference between the first relative distance change value and the second relative distance change value is less than a preset distance difference.

[0031] Optionally, in one embodiment of this application, the calculation module includes: a second acquisition unit, configured to acquire the number of target type vehicles that meet the preset volume conditions in any lane; a first calculation unit, configured to calculate the proportion of the target type vehicles in any lane based on the number and the total number; and a second correction unit, configured to obtain a second traffic efficiency correction parameter using the proportion, and to correct the second initial traffic efficiency using the second traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0032] Optionally, in one embodiment of this application, the calculation module includes: a second calculation unit, configured to calculate the lateral speed of a target traffic participant in any lane based on the driving data of traffic participants in any lane, wherein the target traffic participant is a traffic participant entering or leaving the lane where the vehicle is located; a third calculation unit, configured to calculate a lateral movement speed characteristic value of the target traffic participant in any lane based on the lateral speed; and a third correction unit, configured to obtain a third traffic efficiency correction parameter using the lateral movement speed characteristic value, and to correct the second initial traffic efficiency using the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0033] Optionally, in one embodiment of this application, the calculation module includes: a fourth correction unit, used to correct the second initial traffic efficiency using the second traffic efficiency correction parameter and the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0034] A third aspect of this application provides an electronic device, including a processor and a memory, wherein the memory is used to store a computer program; and the processor is used to execute the program stored in the memory to implement the vehicle lane change control method as described in the above embodiments.

[0035] A fourth aspect of this application provides a vehicle that includes electronic devices as described in the above embodiments.

[0036] A fifth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle lane change control method described above.

[0037] This application's embodiments can calculate the real-time traffic efficiency of each lane based on the dynamic changes of traffic participants in multiple lanes under the current driving environment. This allows for proactive control, ensuring the vehicle always remains in the lane with the highest traffic efficiency, enabling efficient passage through the current road segment and thus guaranteeing the user's driving experience. This solves the technical problems of related technologies, which are passive lane-change control systems with narrow decision-making perspectives and simple, rule-based triggering logic, which are detrimental to improving vehicle traffic efficiency and consequently impacting the user's driving experience.

[0038] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0039] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a vehicle lane change control method according to an embodiment of this application; Figure 2 This is a schematic diagram illustrating the principle of a vehicle lane change control method according to an embodiment of this application; Figure 3 This is a schematic diagram illustrating the principle of a vehicle lane change control method according to another embodiment of this application; Figure 4 This is a flowchart of a vehicle lane change control method according to an embodiment of this application; Figure 5 This is a schematic diagram illustrating the principle of acquiring sensing data according to an embodiment of this application; Figure 6 This is a schematic diagram of the structure of a vehicle lane change control device according to an embodiment of this application; Figure 7This is a schematic diagram of the structure of an electronic device provided according to an embodiment of this application.

[0040] Among them, 1-Autonomous driving domain controller, 11-Camera sensor, 2-Electric power steering system, 21-Sensor, 3-Body control system, 4-Smart cockpit domain controller, 41-Navigation system, 5-Integrated control module, 6-Head-up display system; 10-Vehicle lane change control device, 100-Acquisition module, 200-Computing module, 300-Control module; 20-Electronic device, 710-Processor, 720-Memory. Detailed Implementation

[0041] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0042] The following description, with reference to the accompanying drawings, illustrates a vehicle lane change control method, electronic device, and vehicle according to embodiments of this application. Addressing the technical problems mentioned in the background art, which employs passive lane change control, resulting in a narrow decision-making field of view and simple rule-based triggering logic for lane changes, thus hindering vehicle traffic efficiency and negatively impacting the user's driving experience, this application provides a vehicle lane change control method. In this method, the real-time traffic efficiency of each lane is calculated based on the dynamic changes of traffic participants in multiple lanes within the vehicle's current driving environment. This allows the vehicle to actively control itself to always remain in the lane with the highest traffic efficiency, enabling the vehicle to efficiently pass through the current road segment and thus ensuring the user's driving experience. Therefore, this method solves the technical problems of passive lane change control, which suffers from a narrow decision-making field of view and simple rule-based triggering logic for lane changes, hindering vehicle traffic efficiency and negatively impacting the user's driving experience.

[0043] Understandably, in related technologies, vehicle lane change control is usually passive. For example, if navigation information confirms the presence of obstacles, construction sites, or congestion ahead, a corresponding lane change plan can be generated to control the vehicle to avoid them, thereby increasing traffic efficiency. Alternatively, the average speed of each lane can be calculated to determine the lane with higher traffic efficiency.

[0044] However, in related technologies, passive lane change triggering decision-making has a narrow field of vision. The lane change target of the vehicle is not necessarily the lane with the highest traffic efficiency. The calculation of average vehicle speed ignores the impact of the actual driving conditions of other traffic participants on traffic efficiency, resulting in poor effectiveness of lane change strategies.

[0045] To address the aforementioned technical issues, the vehicle lane change control method of this application embodiment can calculate lane efficiency based on the kinematic attributes of traffic participants using a perception system. Simultaneously, it integrates the navigation system to calculate traffic efficiency navigation correction parameters based on the operating status of road traffic participants. Furthermore, it calculates traffic efficiency navigation correction parameters by real-time monitoring of the entry and exit states of targets within the lane, thereby obtaining a more accurate traffic efficiency for each lane. This allows the vehicle to select lanes with high traffic efficiency and change lanes in advance when driving, reducing the likelihood of the vehicle slowing down after approaching the vehicle in front and then having to switch lanes back and forth or still encountering obstruction after switching to the newest lane. This improves the smoothness of vehicle operation and ultimately enhances the user experience.

[0046] Specifically, Figure 1 This is a schematic flowchart illustrating a vehicle lane change control method provided in an embodiment of this application.

[0047] like Figure 1 As shown, the lane change control method for this vehicle includes the following steps: In step S101, the types and / or driving data of traffic participants in multiple lanes within the vehicle's perception range are acquired.

[0048] In actual driving, the vehicle's perception system (such as a fusion perception structure including visual sensors, radar sensors, high-precision maps and positioning modules) can be used to obtain the types of traffic participants and driving data of multiple lanes within the perception range.

[0049] The sensing range can be determined based on the basic parameters of the sensing system. For sensors with different sensing ranges, the sensing range of the sensor with the smallest sensing range is used as the benchmark. Multiple lanes refer to the multiple lanes traveling in the same direction within the current road segment, so that lane change control can be performed later based on the calculated traffic efficiency of each lane.

[0050] The types of traffic participants can include various types, such as large vehicles (trucks, buses, etc.) and smaller passenger cars, motorcycles, etc. By using different types, the embodiments of this application can subsequently adjust the traffic efficiency to make the traffic efficiency more in line with actual driving conditions.

[0051] Driving data can include longitudinal speed, lateral speed, heading angle, etc. Based on the driving data and type, this embodiment of the application can determine the attributes of each traffic participant and assign an independent identifier to each participant, allowing for the retrieval of corresponding attributes based on the identifier. These attributes may include deceleration calculated from longitudinal speed, deceleration variance, and the confidence level of the data determined by tracking driving data.

[0052] This application embodiment can calculate the traffic efficiency of each lane by using the attributes of traffic participants, calculate the traffic efficiency of each vehicle by using the driving data of traffic participants, or combine attributes and driving data to comprehensively calculate the traffic efficiency, thereby controlling vehicles to actively change lanes and improving the smoothness of the user's driving.

[0053] In step S102, the actual traffic efficiency of multiple lanes is calculated using driving data and / or type.

[0054] As one possible approach, embodiments of this application can use driving data to calculate information such as the average speed of each lane to determine the initial traffic efficiency. Based on this, the initial traffic efficiency can be corrected by combining the types of traffic participants and / or the changing trends of their driving behavior. For example, if a traffic participant changes lanes in a certain lane, it will affect the traffic efficiency of that lane. Similarly, on highways, the speed limit for large vehicles is different from that for small passenger cars. When a large vehicle is traveling in front, it is very likely to affect the traffic efficiency of the road where the large vehicle is located.

[0055] The embodiments of this application can be flexibly modified to make the actual traffic efficiency more in line with the current driving conditions, so that the final lane-changing decision can effectively improve the traffic efficiency of the vehicle.

[0056] Optionally, in one embodiment of this application, calculating the actual traffic efficiency of multiple lanes using driving data and / or type includes: obtaining the initial traffic efficiency of multiple lanes; and correcting the initial traffic efficiency using driving data and / or type to obtain the actual traffic efficiency.

[0057] In actual implementation, the embodiments of this application can determine the initial traffic efficiency by using driving data, such as calculating the average speed of multiple traffic participants in the lane. After determining the initial traffic efficiency, the embodiments of this application can use the influence of vehicle type on traffic efficiency and / or driving data (such as a traffic participant slowing down due to changing lanes) to correct the initial traffic efficiency, thereby obtaining an actual traffic efficiency that is more in line with the actual driving scenario.

[0058] Optionally, in one embodiment of this application, the initial traffic efficiency is corrected using driving data and / or type to obtain the actual traffic efficiency, including: determining the total number of traffic participants and longitudinal speed in any lane based on the driving data of traffic participants in any lane; calculating the average driving speed of any lane based on the total number and longitudinal speed; calculating the first initial traffic efficiency of any lane based on the average driving speed and the speed limit of any lane; and correcting the first initial traffic efficiency using driving data and / or type to obtain the actual traffic efficiency.

[0059] In some embodiments, the average driving speed VaverageLi for each lane can be calculated based on the attributes of traffic participants in each lane as output from the perceived driving data.

[0060] Where n represents the total number of traffic participants in any lane, i represents the lane number, and Vx * The longitudinal velocity of the target traffic participant is represented by , and m represents the m-th traffic participant in any lane.

[0061] It is understandable that the road speed limit restricts the maximum speed that traffic participants in a lane can travel. Therefore, by using the road speed limit as a factor in calculating traffic efficiency, and combining it with the average lane speed, we can obtain the first initial traffic efficiency, DrvLaneiThroughEfficiency.

[0062]

[0063] in, This indicates the road speed limit.

[0064] Optionally, in one embodiment of this application, the initial traffic efficiency is corrected using driving data and / or type to obtain the actual traffic efficiency, including: acquiring road maintenance information for any lane; detecting whether there is at least one abnormal vehicle in any lane that meets preset acceleration abnormality conditions based on the driving data of traffic participants in any lane, and obtaining a detection result; obtaining a first traffic efficiency correction parameter for any lane based on the road maintenance information and / or detection result; obtaining a second initial traffic efficiency based on the first initial traffic efficiency and the first communication efficiency correction parameter; and correcting the second initial traffic efficiency using driving data and / or type to obtain the actual traffic efficiency.

[0065] In other embodiments, since road maintenance is one of the factors affecting lane traffic efficiency, and abnormal acceleration and deceleration of traffic participants may also affect lane traffic efficiency, this application embodiment can determine the navigation-level first traffic efficiency correction parameter NaviLaneiFitPara based on lane-level road maintenance information and the driving status of traffic participants. Subsequently, this application embodiment can combine the first initial traffic efficiency and the first communication efficiency correction parameter to obtain the second initial traffic efficiency. That is, the first initial traffic efficiency is corrected using the first traffic efficiency correction parameter, and after obtaining the second initial traffic efficiency, it is further corrected based on the actual driving data and / or type of traffic participants in each lane to obtain the actual traffic efficiency.

[0066] The first traffic efficiency correction parameter can be determined by experimental estimation or by experience obtained from big data analysis and summary. For example, it can be shown in Table 1, which is an efficiency comparison table.

[0067] Table 1

[0068] Optionally, in one embodiment of this application, obtaining a second initial traffic efficiency based on a first initial traffic efficiency and a first traffic efficiency correction parameter includes: verifying the validity of the first initial traffic efficiency and the first traffic efficiency correction parameter respectively, and obtaining a verification result; and generating a second initial traffic efficiency by combining the verification result, the first initial traffic efficiency, and the first traffic efficiency correction parameter.

[0069] Furthermore, in this embodiment of the application, the optimal lane navigation parameters can be corrected based on the calculated first initial traffic efficiency DrvLaneiThroughEfficiency and the first traffic efficiency correction parameter NaviLaneiFitPara.

[0070] First, the embodiments of this application can respectively verify the effectiveness of the first initial traffic efficiency DrvLaneiThroughEfficiency and the first traffic efficiency correction parameter NaviLaneiFitPara.

[0071] The effectiveness of the first initial traffic efficiency (DrvLaneiThroughEfficiency) can be verified through methods such as data authenticity assessment and historical data trajectory inference. For example, if a vehicle's current speed is 60 km / h, and traffic participants in adjacent lanes maintain the same speed alongside the vehicle for a period of time, but the calculated average speed deviates significantly from the vehicle's current speed, then the first initial traffic efficiency (DrvLaneiThroughEfficiency) may be invalid.

[0072] When both outputs are valid, the expression for calculating the second initial throughput efficiency, PreLaneiThroughEfficiency, is as follows: PreLaneiThroughEfficiency=DrvLaneiThroughEfficiency+NaviLaneiFitPara; When only one of the output results is valid, PreLaneiThroughEfficiency = the currently valid result. That is, when only the first initial throughput efficiency is valid, the second initial throughput efficiency is the first initial throughput efficiency. Conversely, when only the first throughput efficiency correction parameter is valid, the first throughput efficiency correction parameter is used as the second initial throughput efficiency.

[0073] In addition, the embodiments of this application can also obtain traffic efficiency data provided by the vehicle's navigation system. The navigation system can output the corresponding initial navigation traffic efficiency based on changes in traffic flow on the map, real-time updates of congestion, etc., and then correct the initial navigation traffic efficiency in combination with whether road maintenance or vehicle abnormal events are triggered.

[0074] In this embodiment, the validity of the first initial traffic efficiency and the corrected initial navigation traffic efficiency is further verified. For example, the deviation between the two traffic efficiencies is compared to see if it is greater than a certain threshold. If the deviation is small, it means that both are valid. If the deviation is large, the validity of the first initial traffic efficiency and the corrected initial navigation traffic efficiency are verified respectively, and then the valid data is selected as the second initial traffic efficiency.

[0075] Optionally, in one embodiment of this application, the validity of the first initial traffic efficiency and the first traffic efficiency correction parameter are verified respectively to obtain the verification result, including: simulating the driving trajectory of a traffic participant at any vehicle end based on the driving data of traffic participants in any lane; determining whether the driving trajectory matches the road maintenance information and / or detection results; if they match, then determining that the verification result is that the first traffic efficiency correction parameter is valid.

[0076] Here, the validity verification of the first traffic efficiency correction parameter is explained.

[0077] Understandably, the first traffic efficiency correction parameter is used to correct the first initial traffic efficiency in the event of road maintenance events or abnormal acceleration events of traffic participants.

[0078] This application embodiment can obtain the locations of road maintenance events and abnormal acceleration events of traffic participants through high-precision maps, and acquire and track the driving data of traffic participants before and after the occurrence locations to infer the driving trajectories of traffic participants before and after the occurrence locations. For example, if a traffic participant decelerates in a certain time sequence, or if there are significant changes in lateral speed and heading angle, it can be inferred that the traffic participant's trajectory is to avoid a certain location. If the location matches the occurrence location of the road maintenance event or the abnormal acceleration event of the traffic participant, that is, if the distance between them does not exceed a certain threshold, the data is determined to be valid.

[0079] Optionally, in one embodiment of this application, the validity of the first initial traffic efficiency and the first traffic efficiency correction parameter are verified to obtain a verification result, including: calculating the relative longitudinal speed between the traffic participants in any lane and the vehicle based on the driving data of traffic participants in any lane and the current longitudinal speed of the vehicle; calculating the first relative distance change value between the traffic participants in any lane and the vehicle within a preset time window using the relative longitudinal speed; obtaining the second relative distance change value between the vehicle and the traffic participants in any lane within the preset time window; and determining that the verification result is valid for the first initial traffic efficiency in response to whether the difference between the first relative distance change value and the second relative distance change value is less than a preset distance difference.

[0080] In addition to the verification methods mentioned above, embodiments of this application can also determine whether the first initial traffic efficiency is effective by calculating the change in distance between the traffic participant and any other traffic participant.

[0081] For example, in this embodiment of the application, a time window, such as 3 seconds, can be set to obtain the relative longitudinal speed of traffic participants and the longitudinal speed of vehicles 3 seconds before the acquisition, and the relative longitudinal speed of traffic participants and the longitudinal speed of vehicles 3 seconds after the acquisition. Based on the data before and after 3 seconds, this embodiment of the application can calculate the theoretical change in the longitudinal distance between traffic participants and vehicles.

[0082] This application embodiment can also utilize vehicle sensing devices to directly obtain the relative distance between the vehicle and traffic participants, and similarly obtain the actual change value of the longitudinal distance before and after 3 seconds. By comparing the theoretical change value and the actual change value, it can be determined whether the vehicle speed sensing device is effective, and thus determine whether the first initial traffic efficiency is effective.

[0083] In addition, the embodiments of this application can also adopt a simpler judgment method, such as if the average vehicle speed is greater than the lane speed limit, that is, the first initial traffic efficiency is greater than 1. At this time, it is obviously not in compliance with traffic rules, and the first initial traffic efficiency can be judged to be invalid.

[0084] Optionally, in one embodiment of this application, the actual traffic efficiency of multiple lanes is calculated using driving data and / or type, including: obtaining the number of target type vehicles that meet preset volume conditions in any lane; calculating the proportion of target type vehicles in any lane based on the number and total number; obtaining a second traffic efficiency correction parameter using the proportion, and correcting the second initial traffic efficiency using the second traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0085] Furthermore, since large vehicles can affect visibility and the speed limits for large vehicles differ from those for other types of traffic participants, this application embodiment can obtain the traffic efficiency correction parameter, namely the second traffic efficiency correction parameter LaneiFitTypePara, by the proportion of target types in each lane.

[0086] The relationship between the second traffic efficiency correction parameter and the proportion of large vehicles can be obtained through empirical data or through experiments. For example, it can be shown in Table 2, which is a comparison table of the proportion of large vehicles and the traffic efficiency correction parameter.

[0087] Table 2

[0088] When correcting for traffic efficiency, the calculation expression for the actual traffic efficiency in this embodiment of the application is as follows: ActLaneiThroughEfficiency=PreLaneiThroughEfficiency*LaneiFitTypePara.

[0089] In addition to large vehicles affecting traffic efficiency, other types of road users may also impact traffic flow. However, small passenger cars or motorcycles generally do not obstruct the driver's view, and in manual driving mode, users can change lanes automatically based on their observations. For some special vehicles, it is necessary to actively yield. In this case, there is no need to calculate traffic efficiency. After safely avoiding the obstacle, traffic efficiency can be calculated based on perceived driving data once normal traffic resumes on the current road.

[0090] Optionally, in one embodiment of this application, calculating the actual traffic efficiency of multiple lanes using driving data and / or type includes: calculating the lateral speed of a target traffic participant in any lane based on the driving data of traffic participants in any lane, wherein the target traffic participant is a traffic participant entering or leaving the lane where the vehicle is located; calculating the lateral movement speed characteristic value of the target traffic participant in any lane based on the lateral speed; obtaining a third traffic efficiency correction parameter using the lateral movement speed characteristic value, and correcting the second initial traffic efficiency using the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0091] Furthermore, in this embodiment of the application, the lateral movement speed of the target traffic participant in the lane, the relationship between the target traffic participant and the lane line, the heading angle, and other data can be used to determine the vehicle cutting-in and cutting-out trends in the lane and determine the corresponding target traffic participant identifier. The lateral speed VIDy of the cutting-in and cutting-out targets in the lane is summarized and averaged to determine the target lane-changing trend in the lane and obtain the third traffic efficiency correction parameter.

[0092] Where VIDy represents the lateral movement speed of a target traffic participant within a lane, with a positive value for entering and a negative value for exiting. The characteristic value of the lateral movement speed of a traffic participant in a lane is Viy = The third traffic efficiency correction parameter, LaneiFitChangePara, is obtained based on this value. This third traffic efficiency correction parameter can be obtained through empirical data or through experiments. For example, it can be shown in Table 3, which is a comparison table of lateral velocity movement speed characteristic values ​​and traffic efficiency correction parameters.

[0093] Table 3

[0094] The expression for calculating the actual traffic efficiency in this application embodiment can be: ActLaneiThroughEfficiency=PreLaneiThroughEfficiency*LaneiFitChangePara.

[0095] Optionally, in one embodiment of this application, calculating the actual traffic efficiency of multiple lanes using driving data and / or type includes: correcting the second initial traffic efficiency using a second traffic efficiency correction parameter and a third traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0096] In this embodiment, the second initial traffic efficiency can also be corrected by combining the second traffic efficiency and the third traffic efficiency. The calculation expression for the actual traffic efficiency can be: ActLaneiThroughEfficiency=PreLaneiThroughEfficiency*LaneiFitTypePara* LaneiFitChangePara.

[0097] In step S103, the target lane of the vehicle is determined based on the actual traffic efficiency, and if the target lane is inconsistent with the vehicle's current driving lane, the vehicle is controlled to change lanes to the target lane.

[0098] According to the embodiments of this application, the lane with the highest calculated actual traffic efficiency is determined as the highest traffic efficiency lane (target lane), and it is determined whether the lane the vehicle is currently traveling in is the target lane. If it is the target lane, the vehicle does not change lanes. If it is not the target lane, the vehicle is controlled to change lanes to the target lane, and a certain safe distance is maintained between the vehicle and the vehicle in front during the lane change.

[0099] In particular, lane changes are subject to various constraints during vehicle movement. For example, on a highway, if a vehicle needs to exit at the next exit and the exit is nearby, the vehicle should first move to the right lane. Similarly, if the vehicle's navigation system indicates it needs to turn left at the next intersection, and there are two left-turn lanes, the vehicle can choose the lane with higher actual traffic efficiency as its target lane.

[0100] In summary, the embodiments of this application can comprehensively determine the target lane by combining actual traffic efficiency and lane change constraints.

[0101] The above describes lane change control for vehicles in automatic control mode. When the vehicle is in manual control mode, this embodiment can use an in-vehicle display device to display the target lane, or use voice broadcast or other methods to remind the user of the location of the target lane.

[0102] Combination Figures 2 to 4 As shown, the working principle of the vehicle lane change control method of this application embodiment is explained in detail with reference to one embodiment.

[0103] like Figure 2 As shown, embodiments of this application may include: an autonomous driving domain controller 1, a camera sensor 11, an electric power steering system 2, a sensor 21, a body control system 3, a smart cockpit domain controller 4, a navigation system 41, an integrated control module 5, and a head-up display system 6.

[0104] Furthermore, combined Figure 3 and Figure 4 As shown, embodiments of this application may include the following steps: Step S401: Detect traffic participants in each lane and obtain their attributes. In this embodiment of the application, such as... Figure 5 As shown, the autonomous driving domain controller 1 can use camera sensor 11 and sensor 21 (such as radar sensor, etc.) to obtain the driving parameters and types of traffic participants in each lane, and use navigation system 41 to obtain a high-precision map. The autonomous driving domain controller 1 can combine driving parameters, types and high-precision maps to identify all traffic participants (traffic participants within a certain range with the vehicle as the origin) and assign a corresponding identifier to each traffic participant.

[0105] Step S402: Calculate lane throughput efficiency by receiving lane throughput efficiency transmitted from the navigation system. The autonomous driving domain controller 1 can use the acquired data to calculate the evaluated throughput speed of each lane and, in conjunction with the speed limit values ​​of each lane obtained from the navigation system 41, calculate the first initial throughput efficiency.

[0106] Step S403: The target lane is determined by comprehensively calculating and correcting the traffic efficiency of each lane on the current path. The autonomous driving domain controller 1 obtains a second initial traffic efficiency based on road maintenance information and abnormal vehicle information provided by the navigation system 41. Then, the autonomous driving domain controller 1 further corrects the second initial traffic efficiency based on driving parameters and type to obtain the actual traffic efficiency and determine the target lane.

[0107] For example, the autonomous driving domain controller 1 in this application embodiment can calculate the weighted coefficient of traffic efficiency by the number of target types present in each lane to correct the lane traffic efficiency. Generally, small passenger cars or two-wheeled motorcycles can observe the traffic flow of the lane ahead from a distance and will move to the lane with high traffic efficiency in advance.

[0108] By monitoring the lateral movement speed of objects within each lane and their relationship with lane lines, weighted coefficients are calculated to correct lane traffic efficiency. Generally, vehicles tend to move into lanes with higher traffic efficiency; correction coefficients are obtained by statistically analyzing the lateral speeds of vehicles entering and exiting each lane.

[0109] In some cases, if either the calculated lane efficiency or the factors affecting the efficiency determined by the navigation system 41 (based on the efficiency judged by the navigation system 41) cannot be calculated or there is a verification failure, the two can be selected through the normal calculation channel.

[0110] After obtaining the lane traffic efficiency, the traffic efficiency needs to be corrected by a correction factor before the lane with the highest traffic efficiency is determined as the target lane.

[0111] Step S404: Determine if the current lane is the target lane. The autonomous driving domain controller 1 determines if the vehicle's current driving lane is the target lane. If not, proceed to step S405.

[0112] Step S405: Determine whether the vehicle is being driven manually. If yes, proceed to step S406; otherwise, proceed to step S407.

[0113] Step S406: Send lane change recommendation prompts to the head-up display system 6 for display. In manual driving mode, the automated driving domain controller 1 sends the recommended target lane to the intelligent cockpit domain controller 4. The intelligent cockpit domain controller 4 determines the appropriate recommendation method, such as displaying it on the head-up display 6 or using voice prompts. Simultaneously, the integrated control module 5 can display corresponding icons on the instrument panel according to the instructions of the automated driving domain controller 1 or the intelligent cockpit domain controller 4, so that the user can confirm the current status.

[0114] In step S407, the vehicle automatically changes lanes before approaching the vehicle ahead and the distance is greater than the deceleration safety distance. This avoids the discomfort caused by the vehicle decelerating and then choosing an empty lane next to it after discovering congestion or low traffic efficiency in the current lane. At this time, the autonomous driving domain controller 1 can send lane change commands (including steering wheel angle commands, etc.) to the electronic power steering system 2, which uses the electronic power steering system 2 to drive the steering motor, turning the steering wheel to the target angle so that the vehicle seamlessly enters the target lane. Before and after the lane change, the autonomous driving domain controller 1 may issue acceleration and deceleration commands to integrate into the traffic flow of the target lane. At this time, corresponding commands can be sent to the body control system 3 to utilize the electronic stability program, engine control unit, etc. in the body control system 3 to control the vehicle body and ensure a smooth lane change.

[0115] The lane change control method for vehicles proposed in this application can calculate the real-time traffic efficiency of each lane based on the dynamic changes of traffic participants in multiple lanes under the current driving environment. This allows the vehicle to be actively controlled to always remain in the lane with the highest traffic efficiency, enabling it to efficiently pass through the current road segment and thus ensuring a better driving experience for the user. This solves the technical problems of related technologies, which are passive lane change control methods with narrow decision-making perspectives and simple rule-based triggering logic, which are not conducive to improving vehicle traffic efficiency and thus affect the user's driving experience.

[0116] Next, with reference to the accompanying drawings, a lane change control device for a vehicle according to an embodiment of this application is described.

[0117] Figure 6 This is a block diagram of a vehicle lane change control device according to an embodiment of this application.

[0118] like Figure 6 As shown, the lane change control device 10 of the vehicle includes: an acquisition module 100, a calculation module 200, and a control module 300.

[0119] Specifically, the acquisition module 100 is used to acquire the types and / or driving data of traffic participants in multiple lanes within the vehicle's perception range.

[0120] The calculation module 200 is used to calculate the actual traffic efficiency of multiple lanes using driving data and / or type.

[0121] The control module 300 is used to determine the target lane of the vehicle based on the actual traffic efficiency, and to control the vehicle to change lanes to the target lane if the target lane is inconsistent with the vehicle's current driving lane.

[0122] Optionally, in one embodiment of this application, the calculation module 200 includes: a first acquisition unit and a first correction unit.

[0123] The first acquisition unit is used to acquire the initial traffic efficiency of multiple lanes.

[0124] The first correction unit is used to correct the initial traffic efficiency using driving data and / or type to obtain the actual traffic efficiency.

[0125] Optionally, in one embodiment of this application, the first correction unit includes: a determining subunit, a first calculation subunit, a second calculation subunit, and a first correction subunit.

[0126] The determination sub-unit is used to determine the total number of traffic participants and longitudinal speed in any lane based on the driving data of traffic participants in any lane.

[0127] The first calculation subunit is used to calculate the average driving speed of any lane based on the total number of vehicles and the longitudinal speed.

[0128] The second calculation subunit is used to calculate the first initial traffic efficiency of any lane based on the average driving speed and the speed limit value of any lane.

[0129] The first correction subunit is used to correct the first initial traffic efficiency using driving data and / or type to obtain the actual traffic efficiency.

[0130] Optionally, in one embodiment of this application, the first correction unit includes: a first acquisition subunit, a detection subunit, a second acquisition subunit, and a second correction subunit.

[0131] The first acquisition subunit is used to acquire road maintenance information for any lane.

[0132] The detection subunit is used to detect whether there is at least one abnormal vehicle in any lane that meets the preset acceleration abnormality conditions based on the driving data of traffic participants in any lane, and obtain the detection result.

[0133] The second acquisition subunit is used to obtain the first traffic efficiency correction parameter for any lane based on road maintenance information and / or detection results.

[0134] The second correction subunit is used to correct the second initial traffic efficiency using driving data and / or type to obtain the actual traffic efficiency.

[0135] Optionally, in one embodiment of this application, the second acquisition subunit includes: a verification subunit and a generation subunit.

[0136] The verification sub-component is used to verify the effectiveness of the first initial traffic efficiency and the first traffic efficiency correction parameter, respectively, and obtain the verification results.

[0137] A sub-component is generated to combine the verification results, the first initial traffic efficiency, and the first traffic efficiency correction parameters to generate a second initial traffic efficiency.

[0138] Optionally, in one embodiment of this application, the verification component includes: a simulation component, a judgment component, and a first verification component.

[0139] Among them, the simulation component is used to simulate the driving trajectory of any vehicle-side traffic participant based on the driving data of traffic participants in any lane.

[0140] The judgment component is used to determine whether the driving trajectory matches the road maintenance information and / or detection results.

[0141] The first verification piece is used to determine, in the case of a match, that the verification result is valid for the first traffic efficiency correction parameter.

[0142] Optionally, in one embodiment of this application, the verification component includes: a first calculation component, a second calculation component, an acquisition component, and a second verification component.

[0143] The first calculation unit is used to calculate the relative longitudinal speed between the traffic participants and the vehicle in any lane based on the driving data of the traffic participants in any lane and the current longitudinal speed of the vehicle.

[0144] The second calculation unit is used to calculate the first relative distance change between traffic participants and vehicles in any lane within a preset time window using relative longitudinal vehicle speed.

[0145] The acquisition component is used to acquire the second relative distance change value between the vehicle and any traffic participant in any lane within a preset time window.

[0146] The second verification component is used to determine whether the difference between the first relative distance change value and the second relative distance change value is less than a preset distance difference value, and to determine that the verification result is that the first initial traffic efficiency is effective.

[0147] Optionally, in one embodiment of this application, the calculation module 200 includes: a second acquisition unit, a first calculation unit, and a second correction unit.

[0148] The second acquisition unit is used to acquire the number of target type vehicles that meet the preset volume conditions in any lane.

[0149] The first calculation unit is used to calculate the proportion of target type vehicles in any lane based on the quantity and total number.

[0150] The second correction unit is used to obtain the second traffic efficiency correction parameter using the proportion, and then use the second traffic efficiency correction parameter to correct the second initial traffic efficiency to obtain the actual traffic efficiency.

[0151] Optionally, in one embodiment of this application, the calculation module 200 includes: a second calculation unit, a third calculation unit, and a third correction unit.

[0152] The second calculation unit is used to calculate the lateral speed of a target traffic participant in any lane based on the driving data of traffic participants in any lane. The target traffic participant is the traffic participant that cuts into or out of the lane where the vehicle is located.

[0153] The third calculation unit is used to calculate the lateral movement speed characteristic value of the target traffic participant in any lane based on the lateral velocity.

[0154] The third correction unit is used to obtain the third traffic efficiency correction parameter by utilizing the lateral movement speed characteristic value, and then use the third traffic efficiency correction parameter to correct the second initial traffic efficiency to obtain the actual traffic efficiency.

[0155] Optionally, in one embodiment of this application, the calculation module 200 includes a fourth correction unit.

[0156] The fourth correction unit is used to correct the second initial traffic efficiency using the second traffic efficiency correction parameter and the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

[0157] It should be noted that the foregoing explanation of the vehicle lane change control method embodiment also applies to the vehicle lane change control device of this embodiment, and will not be repeated here.

[0158] The lane change control device for vehicles proposed in this application can calculate the real-time traffic efficiency of each lane based on the dynamic changes of traffic participants in multiple lanes under the current driving environment. This allows the device to actively control the vehicle to always remain in the lane with the highest traffic efficiency, enabling the vehicle to efficiently pass through the current road segment and thus ensuring the user's driving experience. This solves the technical problems of related technologies, which are passive lane change control systems with narrow decision-making perspectives and simple, rule-based triggering logic, which are detrimental to improving vehicle traffic efficiency and consequently affecting the user's driving experience.

[0159] This application also provides an electronic device 20, please refer to... Figure 7 It includes a processor 710 and a memory 720, wherein the memory 710 is used to store computer programs; the processor 720 is used to execute the programs stored in the memory 710 to implement the vehicle lane change control method described in any embodiment of this application.

[0160] This application also provides a vehicle that includes the electronic equipment described in any embodiment of this application.

[0161] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle lane change control method described in any embodiment of this application.

[0162] In this application, "multiple" refers to two or more.

[0163] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0164] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0165] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0166] Unless otherwise specified, all steps in this application may be performed sequentially or randomly. For example, if a method includes steps A and B, it means that the method may include steps A and B performed sequentially, or it may include steps B and A performed sequentially. For example, if the method may also include step C, it means that step C may be added to the method in any order. For example, the method may include steps A, B, and C, or it may include steps A, C, and B, or it may include steps C, A, and B, etc.

[0167] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A lane change control method for a vehicle, characterized in that, Includes the following steps: Acquire the types and / or driving data of traffic participants in multiple lanes within the vehicle's perception range; Calculate the actual traffic efficiency of multiple lanes using the driving data and / or the type; The vehicle's target lane is determined based on the actual traffic efficiency, and if the target lane is inconsistent with the vehicle's current driving lane, the vehicle is controlled to change lanes to the target lane.

2. The method according to claim 1, characterized in that, The calculation of the actual traffic efficiency of multiple lanes using the driving data and / or the type includes: Obtain the initial traffic efficiency of multiple lanes; The initial traffic efficiency is corrected using the driving data and / or the type to obtain the actual traffic efficiency.

3. The method according to claim 2, characterized in that, The step of correcting the initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency includes: Based on the driving data of traffic participants in any lane, determine the total number of traffic participants and the longitudinal speed in that lane. Based on the total number and the longitudinal vehicle speed, calculate the average driving speed of any lane; Based on the average driving speed and the speed limit of any lane, calculate the first initial traffic efficiency of any lane; The first initial traffic efficiency is corrected using the driving data and / or type to obtain the actual traffic efficiency.

4. The method according to claim 3, characterized in that, The step of correcting the initial traffic efficiency using the driving data and / or the type to obtain the actual traffic efficiency includes: Obtain road maintenance information for any of the lanes; Based on the driving data of traffic participants in any lane, detect whether there is at least one abnormal vehicle in any lane that meets the preset abnormal acceleration conditions, and obtain the detection result. Based on the road maintenance information and / or the detection results, a first traffic efficiency correction parameter is obtained for any lane. The second initial passage efficiency is obtained based on the first initial passage efficiency and the first communication efficiency correction parameter; The second initial traffic efficiency is corrected using the driving data and / or type to obtain the actual traffic efficiency.

5. The method according to claim 4, characterized in that, The process of obtaining the second initial traffic efficiency based on the first initial traffic efficiency and the first traffic efficiency correction parameter includes: The effectiveness of the first initial traffic efficiency and the first traffic efficiency correction parameter were verified respectively, and the verification results were obtained. The second initial traffic efficiency is generated by combining the verification results, the first initial traffic efficiency, and the first traffic efficiency correction parameter.

6. The method according to claim 5, characterized in that, The step of verifying the effectiveness of the first initial traffic efficiency and the first traffic efficiency correction parameter, respectively, and obtaining the verification results, includes: The driving trajectory of the traffic participant at any vehicle end is simulated based on the driving data of the traffic participants in any lane. Determine whether the driving trajectory matches the road maintenance information and / or the detection result; If a match is found, the verification result is determined to indicate that the first traffic efficiency correction parameter is valid.

7. The gas-based method according to claim 5, characterized in that the step of verifying the effectiveness of the first initial passage efficiency and the first passage efficiency correction parameter respectively, and obtaining the verification result, includes: Based on the driving data of traffic participants in any lane and the current longitudinal speed of the vehicle, calculate the relative longitudinal speed between the traffic participants in any lane and the vehicle. The relative longitudinal speed is used to calculate the first relative distance change between the traffic participant and the vehicle in any lane within a preset time window; Obtain the second relative distance change value between the vehicle and traffic participants in any lane within the preset time window; In response to whether the difference between the first relative distance change value and the second relative distance change value is less than a preset distance difference, the verification result is determined to be that the first initial traffic efficiency is effective.

8. The method according to claim 5, characterized in that, The calculation of the actual traffic efficiency of multiple lanes using the driving data and / or the type includes: Obtain the number of target type vehicles that meet the preset volume conditions in any lane; Based on the quantity and the total number, calculate the percentage of the target type of vehicles in any lane; The second traffic efficiency correction parameter is obtained using the ratio, and the second initial traffic efficiency is corrected using the second traffic efficiency correction parameter to obtain the actual traffic efficiency.

9. The method according to claim 8, characterized in that, The calculation of the actual traffic efficiency of multiple lanes using the driving data and / or the type includes: Based on the driving data of traffic participants in any lane, calculate the lateral speed of the target traffic participant in any lane, where the target traffic participant is the traffic participant entering or leaving the lane where the vehicle is located. Based on the lateral velocity, calculate the lateral movement speed characteristic value of the target traffic participant in any lane; The third traffic efficiency correction parameter is obtained using the lateral movement speed characteristic value, and the second initial traffic efficiency is corrected using the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

10. The method according to claim 9, characterized in that, The calculation of the actual traffic efficiency of multiple lanes using the driving data and / or the type includes: The second initial traffic efficiency is corrected using the second traffic efficiency correction parameter and the third traffic efficiency correction parameter to obtain the actual traffic efficiency.

11. An electronic device, characterized in that, Including processor and memory, among which, Memory, used to store computer programs; A processor is configured to execute a program stored in a memory to implement the lane change control method for the vehicle as described in any one of claims 1-10.

12. A vehicle, characterized in that, It includes the electronic device as described in claim 11.

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