Vehicle control method and device, electronic equipment and medium

Abstract

This application provides a vehicle control method, device, electronic device, and medium, relating to the field of vehicle technology. The method includes: obtaining a traffic efficiency cost for a vehicle lane based on the traffic efficiency cost of an obstacle located ahead of the vehicle in its own lane; and obtaining a traffic efficiency cost for a first adjacent lane based on the traffic efficiency cost of an obstacle located ahead of the vehicle in a first adjacent lane. The traffic efficiency cost of the obstacle is obtained based on the obstacle's motion information and first information, where the first information indicates the predicted probability that the obstacle will be in its current lane at a future time, and the traffic efficiency cost is a parameter characterizing the degree of obstruction to the vehicle's movement. Based on the traffic efficiency cost of the vehicle lane and the traffic efficiency cost of the first adjacent lane, it determines whether a first triggering condition for the vehicle to change lanes into the first adjacent lane is met; if so, it executes an operation to control the vehicle to change lanes. This application embodiment enables precise control of the vehicle's lane changes.

Description

Technical Field

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

[0002] With the rapid development of intelligent driving technology, the control of vehicle driving processes is becoming increasingly sophisticated. Vehicles may need to change lanes during operation, thus necessitating a vehicle control method that supports lane-changing maneuvers. Summary of the Invention

[0003] This application provides a vehicle control method, device, electronic device, and medium that can achieve precise control of a vehicle changing lanes.

[0004] In a first aspect, embodiments of this application provide a vehicle control method, comprising: obtaining a traffic efficiency cost of a lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in the lane; and obtaining a traffic efficiency cost of a first adjacent lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in a first adjacent lane of the lane; wherein the traffic efficiency cost of the obstacle is obtained based on the obstacle's motion information and first information, the first information being used to indicate the predicted probability that the obstacle will be located in the current lane at a future time, and the traffic efficiency cost being a parameter characterizing the degree of obstruction to the vehicle's travel; determining whether a first triggering condition for the vehicle to change lanes to the first adjacent lane is met based on the traffic efficiency cost of the lane and the traffic efficiency cost of the first adjacent lane; and performing a lane-changing operation for the vehicle if the first triggering condition is met.

[0005] In this embodiment, in addition to the movement information of obstacles (such as vehicles), the lane-changing intention of the obstacles is also considered to obtain the obstacle cost (i.e., traffic efficiency cost). This ensures that the obtained obstacle cost takes into account whether there is a lane-changing intention and the different impacts of varying degrees of lane-changing intention on the vehicle's congestion level. Therefore, the obtained obstacle cost can more accurately reflect the congestion caused by obstacles to the vehicle's movement. Thus, the lane cost obtained based on the cost of obstacles in the lane can more accurately reflect the lane's traffic flow. Furthermore, based on the cost of the vehicle's own lane and the cost of adjacent lanes, precise control of lane changes by the vehicle can be achieved.

[0006] Optionally, the passage efficiency cost of an obstacle is the product of the initial passage efficiency cost of the obstacle and the correction parameter; the initial passage efficiency cost is obtained based on the obstacle's motion information, and the correction parameter is obtained based on the obstacle's first information.

[0007] By employing a product approach, the initial cost obtained from the obstacle's movement information is corrected using correction parameters derived from the obstacle's lane-changing intention. This allows the correction parameters to adjust the initial cost by a corresponding multiple, thus enabling accurate acquisition of the obstacle's cost.

[0008] Optionally, the obstacle's motion information includes the obstacle's speed; the steps for obtaining the obstacle's first information include: predicting the obstacle's trajectory over a future period based on the obstacle's speed and a set duration; and obtaining the proportion of the predicted trajectory in the obstacle's current lane as the obstacle's first information.

[0009] By predicting the trajectory of an obstacle in the future and based on the proportion of the predicted trajectory in the original lane, it is possible to accurately predict the obstacle's lane-changing intention and support the accurate acquisition of obstacle costs.

[0010] Optionally, the traffic efficiency cost is not less than zero; the vehicle control method further includes: obtaining a first difference value obtained by subtracting the traffic efficiency cost of the first adjacent lane from the traffic efficiency cost of the lane; wherein, the first triggering condition is met when: the first difference value is not less than a set threshold value; the set threshold value is greater than zero.

[0011] By setting cost≥0 and limiting the control of lane change to a threshold value when the difference between the cost of the lane and the cost of the adjacent lane is less than a threshold value, the control can be applied to indicate that the vehicle needs to change lanes and can change lanes. This can achieve the effect of changing lanes to the adjacent lane when the lane is congested and the adjacent lane is clear. The control process is simple and conforms to the actual lane change control of the user.

[0012] Optionally, the vehicle control method further includes: obtaining the traffic efficiency cost of the second adjacent lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in the second adjacent lane of the vehicle's own lane; obtaining a second difference obtained by subtracting the traffic efficiency cost of the second adjacent lane from the traffic efficiency cost of the vehicle's own lane; wherein the second triggering condition for the vehicle to change lanes to the second adjacent lane is met when the second difference is not less than a set threshold; and when the first triggering condition is met, performing the operation of controlling the vehicle to change lanes includes: when both the first triggering condition and the second triggering condition are met, controlling the vehicle to change lanes to the adjacent lane located to the left of the vehicle.

[0013] When there are two adjacent lanes, and both adjacent lanes are clear enough to support lane changing, changing lanes to the left is the preferred option, which meets the actual needs of users.

[0014] Optionally, the step of obtaining the traffic efficiency cost of the lane includes: obtaining the traffic efficiency cost of the nearest obstacle based on the motion information of the nearest obstacle in front of the vehicle and the first information; and using the traffic efficiency cost of the nearest obstacle as the traffic efficiency cost of the lane.

[0015] Since the obstruction effect of the nearest obstacle to the vehicle on the vehicle's current driving is usually significantly higher than that of the obstacle farther away from the vehicle, the decision to change lanes can be based on the obstruction effect of the nearest obstacle on the vehicle's current driving. This allows for accurate control of lane changes and simplifies the lane change control logic.

[0016] Optionally, the step of obtaining the traffic efficiency cost of a lane includes: obtaining the traffic efficiency cost of each obstacle based on the motion information of each obstacle located in front of the vehicle in the lane and the first information; and using the maximum value of the traffic efficiency cost of each obstacle as the traffic efficiency cost of the lane.

[0017] Since the obstruction effect of the obstacle with the highest cost on the vehicle's current and future travel time is usually significantly higher than that of the obstacle with the lower cost, it is possible to determine whether to perform a lane change based on the obstruction effect of the obstacle with the highest cost on the vehicle's current and future travel time. This allows for accurate control of the vehicle's lane change and provides foresight.

[0018] Optionally, the step of obtaining the traffic efficiency cost of a lane includes: obtaining the traffic efficiency cost of the nearest obstacle in the lane based on the motion information and first information of the obstacle located in front of the vehicle; obtaining the traffic efficiency cost of each obstacle in the lane based on the motion information and first information of each obstacle located in front of the vehicle; and obtaining the traffic efficiency cost of the lane based on the maximum value between the traffic efficiency cost of the nearest obstacle and the traffic efficiency cost of each obstacle.

[0019] By comprehensively considering the obstructive impact of the nearest and most costly obstacles on the vehicle's movement, accurate control of lane changes can be achieved, and it can also be forward-looking.

[0020] Secondly, embodiments of this application provide a vehicle control device, comprising: an acquisition module, configured to acquire a traffic efficiency cost of a lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in the lane, and to acquire a traffic efficiency cost of a first adjacent lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in the first adjacent lane; wherein the traffic efficiency cost of the obstacle is obtained based on the obstacle's motion information and first information, the first information being used to indicate the predicted probability that the obstacle will be located in the current lane at a future time, and the traffic efficiency cost being a parameter characterizing the degree of obstruction to the vehicle's travel; a determination module, configured to determine whether a first triggering condition for the vehicle to change lanes to the first adjacent lane is met based on the traffic efficiency cost of the lane and the traffic efficiency cost of the first adjacent lane; and a control module, configured to execute an operation to control the vehicle to change lanes if the first triggering condition is met.

[0021] Thirdly, embodiments of this application provide an electronic chip, including: a processor for executing computer program instructions stored in a memory, wherein when the computer program instructions are executed by the processor, the electronic chip is triggered to perform the method as described in any of the first aspects.

[0022] Fourthly, embodiments of this application provide an electronic device including at least one processor and a memory coupled together. The memory is used to store computer program instructions, and the processor is used to execute the computer program instructions. When the computer program instructions are executed by the processor, the electronic device is triggered to perform a method as described in any of the first aspects.

[0023] Fifthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when run on a computer, causes the computer to perform the method as described in any of the first aspects.

[0024] In a sixth aspect, embodiments of this application provide a computer program product, which includes a computer program that, when run on a computer, causes the computer to perform the method as described in any of the first aspects.

[0025] The technical effects of the aforementioned aspects can be referenced from each other, and will not be elaborated further here. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1A schematic flowchart illustrating a vehicle control method according to one embodiment of this application;

[0028] Figure 2 A block diagram of a vehicle control device provided in one embodiment of this application;

[0029] Figure 3 This is a schematic diagram of the structure of a computer device provided in one embodiment of this application. Detailed Implementation

[0030] To better understand the technical solution of this application, the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0031] It should be understood that the described embodiments are merely some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0032] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0033] It should be understood that the term "at least one" as used in this document refers to one or more, and "more than one" refers to two or more. The term "and / or" as used in this document 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 alone, A and B simultaneously, and B alone. A and B can be singular or plural. Additionally, the character " / " in this document generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0034] It should be understood that although the terms "first," "second," etc., may be used to describe the set thresholds in the embodiments of this application, these set thresholds should not be limited to these terms. These terms are only used to distinguish the set thresholds from each other. For example, without departing from the scope of the embodiments of this application, the first set threshold may also be referred to as the second set threshold, and similarly, the second set threshold may also be referred to as the first set threshold.

[0035] like Figure 1As shown, one embodiment of this application provides a vehicle control method, which may include steps 101 to 103.

[0036] In one embodiment, Figure 1 In the illustrated embodiment, the executing entity can be a vehicle. The vehicle can be any type of vehicle with autonomous driving capabilities. In another embodiment, the executing entity can also be a server device that maintains a communication connection with the vehicle.

[0037] In one embodiment, Figure 1 The illustrated embodiment is applicable to multi-lane driving scenarios, such as highway multi-lane driving scenarios. The multi-lane configuration includes at least two lanes, comprising at least the primary lane and one or both adjacent lanes on one or both sides of the primary lane.

[0038] Step 101: Obtain the traffic efficiency cost of the self-lane based on the traffic efficiency cost (e.g., represented by cost) of the obstacle located in front of the self-lane, and obtain the traffic efficiency cost of the first adjacent lane based on the traffic efficiency cost of the obstacle located in front of the self-lane in the first adjacent lane; wherein, the traffic efficiency cost of the obstacle is obtained based on the obstacle's motion information and first information, the first information being used to indicate the predicted probability that the obstacle will be located in the current lane at a future time, and the traffic efficiency cost is a parameter characterizing the degree of obstruction to the self-lane.

[0039] The first piece of information reflects the predicted probability that the obstacle will be in the current lane at a future time. It can be used to indicate the strength of the obstacle's lane-changing intention and can reflect the probability that the obstacle will change lanes to an adjacent lane (i.e., leave its own lane) at a future time.

[0040] When there is an obstacle in front of the vehicle in the lane or adjacent lane, the vehicle can obtain information about the obstacle's movement and information reflecting the vehicle's intention to change lanes, so as to obtain the obstacle's cost.

[0041] In one embodiment, the vehicle's sensors can be used to detect whether there are obstacles in front of the vehicle. For example, in one feasible implementation, the presence of obstacles in front of the vehicle can be determined by analyzing and processing images of the road conditions ahead captured by the vehicle's image acquisition device.

[0042] Among them, obstacles in front of the vehicle can be moving obstacles, such as vehicles in motion, or stationary obstacles, such as obstacle avoidance signs.

[0043] In one embodiment, the first adjacent lane can be any lane in the same direction adjacent to the lane itself.

[0044] In one embodiment, motion information may include vehicle speed and distance from the vehicle. This distance may be a longitudinal distance along the direction of road extension.

[0045] The cost of an obstacle can characterize the degree to which an obstacle obstructs the movement of a vehicle. The higher the cost of an obstacle, the greater the degree of obstruction to the movement of a vehicle, and vice versa.

[0046] The cost of an obstacle can be used to determine the cost of the lane it occupies. The higher the lane cost, the more congested the lane is, and the greater the obstruction to the travel of your vehicle. Conversely, the lower the lane cost, the more unobstructed the lane is, and the less obstruction to the travel of your vehicle is.

[0047] In one embodiment of this application, the passage efficiency cost of an obstacle is the product of the initial passage efficiency cost of the obstacle and the correction parameter; the initial passage efficiency cost is obtained based on the motion information of the obstacle, and the correction parameter is obtained based on the first information of the obstacle.

[0048] In other embodiments of this application, other methods may be used to modify the initial traffic efficiency cost according to the lane-changing intention of the obstacle, such as adding a correction value corresponding to the lane-changing intention of the obstacle to the initial traffic efficiency cost.

[0049] By employing a product approach, the initial cost obtained from the obstacle's movement information is corrected using correction parameters derived from the obstacle's lane-changing intention. This allows the correction parameters to adjust the initial cost by a corresponding multiple, thus enabling accurate acquisition of the obstacle cost.

[0050] In one embodiment, the initial cost of the obstacle is calculated as max(the speed difference between the obstacle speed and the preset speed, 0) × unit speed difference cost parameter × obstacle influence weight value.

[0051] Thus, obstacle cost = initial obstacle cost × correction parameter, that is: obstacle cost = max(speed difference between obstacle speed and preset speed, 0) × unit speed difference cost parameter × obstacle influence weight value × correction parameter.

[0052] Taking the obstacle as a moving vehicle in front as an example, in one embodiment, the obstacle speed represents the speed of the vehicle in front; the preset speed can be a speed threshold configured according to lane change requirements, such as 5 m / s; the unit speed difference cost parameter can represent the adjustable situation within a unit speed, such as 3.5; the obstacle influence weight value can be configured based on the steady-state following factor and / or the distance between the vehicle and the obstacle, and the configuration range can be, for example, [0,1].

[0053] The steady-state following factor can be used to characterize the need for a vehicle to stably follow the vehicle in front. It can be configured in advance according to the vehicle's autonomous driving following requirements. For example, in one embodiment, the steady-state following factor can be set to 0.9.

[0054] In one embodiment of this application, the motion information of the obstacle includes the vehicle speed of the obstacle; the step of obtaining the first information of the obstacle includes: predicting the driving trajectory of the obstacle in the future period of time based on the vehicle speed of the obstacle and a set duration; obtaining the proportion of the predicted driving trajectory in the lane where the obstacle is currently located as the first information of the obstacle.

[0055] The predicted driving trajectory reflects the expected changes in a vehicle's behavior over a future period and can serve as a prediction of the vehicle's actual behavior. Based on the predicted driving trajectory, the aforementioned percentage can be obtained, and the magnitude of the obtained percentage reflects the strength of the lane-changing intention from the obstacle. The higher the percentage, the weaker the lane-changing intention, and vice versa.

[0056] In one embodiment, the set duration can be determined according to the lane change requirement, for example, it can be set to any duration between 4 and 6 seconds. Taking a set duration of 5 seconds as an example, the trajectory of the obstacle within the next 5 seconds can be predicted based on the obstacle's speed.

[0057] Taking the obstacle as a vehicle as an example, compared with the vehicle having no or a small intention to change lanes, if the vehicle has a large intention to change lanes (such as the vehicle being close to the adjacent lane or the vehicle's orientation deviating significantly towards the adjacent lane), the predicted driving trajectory will have a relatively small proportion in the vehicle's current lane and a relatively large proportion in the adjacent lane where the vehicle is about to change lanes.

[0058] The percentage of the predicted driving trajectory within the current lane can be defined as the portion of the predicted driving trajectory within the current lane relative to the total predicted driving trajectory (i.e., the entire driving trajectory). In one embodiment, this percentage can be used as the aforementioned correction parameter to modify the initial cost of the obstacle.

[0059] In one embodiment, if the vehicle does not intend to change lanes, the predicted trajectory may have 100% of its current lane. If the vehicle has a minor intention to change lanes (e.g., in the early stages of a lane change), the predicted trajectory may have a percentage of its current lane that is close to but less than 100%. If the vehicle has a major intention to change lanes (e.g., in the later stages of a lane change), the predicted trajectory may have a percentage of its current lane that is close to but greater than 0%. Thus, the obtained percentage can range from greater than 0 to no greater than 1.

[0060] The greater the lane-changing intention of the obstacle ahead in the lane, and the smaller the percentage obtained, the greater the degree of correction to the obstacle's initial cost. The smaller the corrected obstacle cost, the less obstruction the obstacle poses to the vehicle's movement, and the less likely the vehicle is to change lanes. Conversely, the smaller the obstacle's intention, the more likely the vehicle is to change lanes.

[0061] By predicting the trajectory of an obstacle in the future and based on the proportion of the predicted trajectory in the original lane, it is possible to accurately predict the obstacle's lane-changing intention and support the accurate acquisition of obstacle costs.

[0062] For example, if there is a vehicle in your lane that intends to change lanes to the adjacent lane in a short time, and assuming the vehicle in front is traveling at a slow speed, if we disregard the intention to change lanes, the cost of the vehicle in front is high, thus triggering your own lane change. This could result in your own car following the slower vehicle into the adjacent lane, continuing to follow it after the lane change, causing continued congestion and making the lane change unnecessary. However, if we consider the intention to change lanes, the cost of the vehicle in front is lower, preventing your own lane change. Furthermore, once the vehicle in front finishes its lane change, the congestion caused by that vehicle disappears. This control result, preventing your own car from changing lanes, aligns with actual lane change requirements (i.e., your own car does not change lanes when the vehicle in front changes lanes).

[0063] In one embodiment of this application, the step of obtaining the traffic efficiency cost of a lane includes: obtaining the traffic efficiency cost of the nearest obstacle based on the motion information of the nearest obstacle located in front of the vehicle on the lane and first information; and using the traffic efficiency cost of the nearest obstacle as the traffic efficiency cost of the lane.

[0064] For the nearest obstacle, there are no other obstacles in the corresponding lane between the nearest obstacle and the obstacle itself.

[0065] When dealing with obstacles in front of the vehicle, to obtain the cost of its lane (or lane cost) based on the cost of the nearest obstacle, it is not necessary to obtain the cost of every obstacle in that lane. Instead, if there is only one obstacle in the lane, that obstacle is the nearest obstacle, and its cost is then obtained. If there is more than one obstacle in the lane, the nearest obstacle is first determined based on the distance between the vehicle and each obstacle in the lane, and then its cost is obtained.

[0066] Since the obstruction effect of the nearest obstacle to the vehicle on the vehicle's current driving is usually significantly higher than that of the obstacle farther away from the vehicle, the decision to change lanes can be based on the obstruction effect of the nearest obstacle on the vehicle's current driving. This allows for accurate control of lane changes and simplifies the lane change control logic.

[0067] In one embodiment of this application, the step of obtaining the traffic efficiency cost of a lane includes: obtaining the traffic efficiency cost of each obstacle based on the motion information of each obstacle located in front of the vehicle on the lane and first information; and using the maximum value of the traffic efficiency cost of each obstacle as the traffic efficiency cost of the lane.

[0068] All other things being equal or having little impact on cost, the slowest obstacle ahead can have the highest relative cost.

[0069] Since the obstruction effect of the obstacle with the highest cost on the vehicle's current and future travel time is usually significantly higher than that of the obstacle with the lower cost, it is possible to determine whether to perform a lane change based on the obstruction effect of the obstacle with the highest cost on the vehicle's current and future travel time. This allows for accurate control of the vehicle's lane change and provides foresight.

[0070] In one embodiment of this application, the step of obtaining the traffic efficiency cost of a lane includes: obtaining the traffic efficiency cost of the nearest obstacle in the lane based on the motion information of the nearest obstacle in front of the vehicle and first information; obtaining the traffic efficiency cost of each obstacle in the lane based on the motion information of each obstacle in front of the vehicle and first information; and obtaining the traffic efficiency cost of the lane based on the maximum value between the traffic efficiency cost of the nearest obstacle and the traffic efficiency cost of each obstacle.

[0071] In one embodiment, a first weight corresponding to the nearest obstacle and a second weight corresponding to the obstacle with the highest cost can be set separately. The weights can be determined empirically.

[0072] In one embodiment, lane cost = cost of the nearest obstacle in the lane × first weight + maximum cost of all obstacles in the lane × second weight.

[0073] By comprehensively considering the obstructive impact of the nearest and most costly obstacles on the vehicle's movement, accurate control of lane changes can be achieved, and it can also be forward-looking.

[0074] Step 102: Determine whether the first triggering condition for the vehicle to change lanes to the first adjacent lane is met based on the traffic efficiency cost of the vehicle's own lane and the traffic efficiency cost of the first adjacent lane.

[0075] When the cost of a lane is high, the demand for lane changing is high; conversely, when the cost of a lane is low, the demand for lane changing is low.

[0076] For example, if the cost of the self-lane is not less than the first threshold, it means that the self-lane is blocked and the road ahead of the self-lane is congested, so the self-lane needs to change lanes. Conversely, if the cost of the self-lane is less than the first threshold, it means that the self-lane is not blocked and the road ahead of the self-lane is clear and not congested, so the self-lane does not need to change lanes.

[0077] In one implementation, the ability of an adjacent lane to allow lane changing can be determined based on the absolute congestion level of that lane. A higher cost for an adjacent lane generally means less support for lane changing, while a lower cost for an adjacent lane generally means more support for lane changing.

[0078] For example, if the cost of the adjacent lane is not less than the second threshold, it means that if the vehicle is blocked in the adjacent lane, the road ahead of the vehicle in the adjacent lane is congested and not smooth, so lane changing is not supported. Conversely, if the cost of the adjacent lane is less than the second threshold, it means that if the vehicle is not blocked in the adjacent lane, the road ahead of the vehicle in the adjacent lane is smooth and not congested, so lane changing is supported.

[0079] In another implementation, the decision to allow a vehicle to change lanes can be determined based on the relative congestion level of the adjacent lane. If the cost of the vehicle's lane is greater than the cost of the adjacent lane, and the larger the difference, the more congested the adjacent lane is, indicating that the traffic flow in the adjacent lane is significantly higher than that of the vehicle's lane. In this case, even if the adjacent lane is congested, lane changing is still supported. Conversely, if the cost of the vehicle's lane and the cost of the adjacent lane are similar, it indicates that the traffic flow in both lanes is similar. In this case, lane changing is not supported if the adjacent lane is congested.

[0080] In this way, based on the cost of the vehicle's own lane and the cost of the adjacent lane, it can be determined whether the vehicle needs to change lanes and whether it can change lanes to the adjacent lane. If so, the vehicle can be controlled to change lanes to the adjacent lane.

[0081] In one embodiment, it can be first determined whether the cost of the vehicle's own lane is not less than a first threshold. If so (i.e., the vehicle needs to change lanes), then it can be determined whether the cost of the adjacent lane is not greater than a second threshold. If so (i.e., the adjacent lane supports the vehicle changing lanes), and there are no other factors that do not support the vehicle changing lanes (such as an upcoming ramp), then the operation of controlling the vehicle to change lanes can be executed. This implementation can achieve accurate control of the vehicle's lane changes, supporting the control of the vehicle to change lanes to the adjacent lane when the own lane is congested and the adjacent lane is clear.

[0082] In another embodiment, it can be directly determined whether the difference between the cost of the primary lane and the cost of the adjacent lane is not greater than a third threshold. If so (i.e., the vehicle needs to change lanes and the adjacent lane supports the vehicle's lane change), and there are no other factors that do not support the vehicle's lane change (such as an upcoming ramp), then the operation to control the vehicle's lane change can be executed. Since there is no need to perform two levels of judgment sequentially, this helps to simplify the implementation process. In addition, this implementation method is also applicable to scenarios where both the primary lane and the adjacent lane are congested, but the primary lane is more congested, and the congestion difference between the two is large enough to make it necessary for the vehicle to change lanes, which is consistent with the actual lane change control of the user's driving.

[0083] Thus, in one embodiment of this application, the traffic efficiency cost is not less than zero; the vehicle control method further includes: obtaining a first difference obtained by subtracting the traffic efficiency cost of the first adjacent lane from the traffic efficiency cost of the lane; wherein, the first triggering condition is met when: the first difference is not less than a set threshold; the set threshold is greater than zero.

[0084] Since cost≥0, if the difference between the cost of the vehicle lane and the cost of the adjacent lane is not less than the set threshold, it means that the cost of the vehicle lane is not less than the set threshold (i.e., the vehicle lane is congested and the vehicle needs to change lanes), and it also means that the cost of the adjacent lane is smaller (i.e., the adjacent lane is smooth or more smooth than the vehicle lane and supports the vehicle changing lanes). In this case, the operation of controlling the vehicle to change lanes can be performed.

[0085] If the difference between the cost of the primary lane and the cost of the adjacent lane is less than a set threshold, the operation to control the primary lane change may not be executed. This may be because the primary lane is clear and does not require lane change, or because both the primary lane and the adjacent lane are congested and do not support lane change.

[0086] By setting cost≥0 and limiting the control of lane change to a threshold value when the difference between the cost of the lane and the cost of the adjacent lane is less than a threshold value, the control can be applied to indicate that the vehicle needs to change lanes and can change lanes. This can achieve the effect of changing lanes to the adjacent lane when the lane is congested and the adjacent lane is clear. The control process is simple and conforms to the actual lane change control of the user.

[0087] In a scenario where a vehicle ahead in the driver's lane intends to change lanes, if this intention is ignored, the first difference (or inaccuracy) is likely to exceed a set threshold. However, by incorporating the impact of lane-changing intentions on vehicle cost, the cost of vehicles with such intentions is reduced. The reduction is directly proportional to the intensity of the intention. This makes it less likely for the first difference to exceed the set threshold, thus reducing the likelihood of the driver changing lanes and preventing unreasonable lane changes, thus aligning with actual driving lane-changing needs.

[0088] In one embodiment of this application, the first triggering condition may further include: when the vehicle changes lanes to the first adjacent lane, there is no risk of collision with a vehicle located behind the vehicle in the first adjacent lane. In one embodiment, whether there is a risk of collision may depend on the speed difference between the vehicle and the vehicle behind, the distance between the vehicle behind and the vehicle, etc.

[0089] In one embodiment of this application, the first triggering condition may be met if the lane change suppression condition is not met. In one embodiment, the lane change suppression condition may include a ramp within a preset distance ahead, the vehicle being in a non-automatic driving state, the vehicle being in the driving lane, the vehicle not being on a highway, or the vehicle not activating the automatic overtaking and lane-changing function.

[0090] Step 103: If the first triggering condition is met, execute the operation of controlling the vehicle to change lanes.

[0091] In one embodiment, the lane has an adjacent lane, namely the first adjacent lane.

[0092] When there is an adjacent lane, if the first triggering condition is met, the operation of controlling the vehicle to change lanes can be executed to control the vehicle to change lanes to the first adjacent lane.

[0093] If there is an adjacent lane, and the first triggering condition is not met, the operation to control the vehicle to change lanes will not be executed.

[0094] In another embodiment, the lane has two adjacent lanes, one of which is the first adjacent lane.

[0095] When there are two adjacent lanes, if the first triggering condition is not met, and the triggering condition for the vehicle to change lanes to the other adjacent lane is also not met, then the operation to control the vehicle to change lanes will not be executed.

[0096] When there are two adjacent lanes, if the first triggering condition is not met, but the triggering condition for the vehicle to change lanes to the other adjacent lane is met, the operation of controlling the vehicle to change lanes can be executed to control the vehicle to change lanes to the other adjacent lane.

[0097] When there are two adjacent lanes, if the first triggering condition is met, and the triggering condition for the vehicle to change lanes to the other adjacent lane is also met, then the operation of controlling the vehicle to change lanes can be executed to control the vehicle to change lanes to one of the adjacent lanes.

[0098] In one embodiment of this application, the vehicle control method further includes: obtaining the traffic efficiency cost of the second adjacent lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in the second adjacent lane of the vehicle lane; obtaining a second difference obtained by subtracting the traffic efficiency cost of the second adjacent lane from the traffic efficiency cost of the vehicle lane; wherein the second triggering condition for the vehicle to change lanes to the second adjacent lane is met when the second difference is not less than a set threshold; and when the first triggering condition is met, performing the operation of controlling the vehicle to change lanes includes: when both the first triggering condition and the second triggering condition are met, controlling the vehicle to change lanes to the adjacent lane located to the left of the vehicle.

[0099] When there are two adjacent lanes, and both adjacent lanes are clear enough to support lane changing, changing lanes to the left is the preferred option, which meets the actual needs of users.

[0100] Based on the vehicle's direction of travel, the lane adjacent to the left of the vehicle / lane is the vehicle's left lane; changing lanes to the left means changing lanes to the left. Conversely, the lane adjacent to the right of the vehicle / lane is the vehicle's right lane; changing lanes to the right means changing lanes to the right. To better suit user driving habits and needs, when both left and right lanes support lane changing, changing lanes to the left is preferred.

[0101] In another embodiment, when both left and right lanes support lane changing, it is preferable to change lanes to the adjacent lane where there is more free traffic.

[0102] Figure 1 In the illustrated embodiment, in addition to considering the obstacle's movement information, the obstacle's lane-changing intention is also taken into account to obtain the obstacle cost. This ensures that the obtained obstacle cost takes into account whether a lane-changing intention exists and the different impacts of varying degrees of lane-changing intention on the vehicle's congestion level. Therefore, the obtained obstacle cost can more accurately reflect the congestion level of the vehicle due to obstacles. Consequently, the lane cost obtained based on the cost of obstacles in the lane can more accurately reflect the lane's traffic flow. Furthermore, based on the cost of the vehicle's own lane and the cost of adjacent lanes, precise control of the vehicle's lane changes can be achieved.

[0103] In one embodiment of this application, a path planning model (such as a path planning decision algorithm) can be used to plan the vehicle lane change based on the preset lane speed and lane width of the lane to be changed, as well as the speed difference and distance between the vehicle and the obstacles in front and behind on the lane to be changed. The vehicle lane change planning path is obtained, and the vehicle is controlled to drive along the obtained vehicle lane change planning path, thereby achieving the purpose of changing the vehicle lane to the lane to be changed.

[0104] like Figure 2As shown, one embodiment of this application provides a vehicle control device 200, including: an acquisition module 201, configured to acquire a traffic efficiency cost of a lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in the lane, and to acquire a traffic efficiency cost of a first adjacent lane based on the traffic efficiency cost of an obstacle located in front of the vehicle in the first adjacent lane; wherein, the traffic efficiency cost of the obstacle is obtained based on the obstacle's motion information and first information, the first information being used to indicate the predicted probability that the obstacle will be located in the current lane at a future time, and the traffic efficiency cost is a parameter characterizing the degree of obstruction to the vehicle's travel; a determination module 202, configured to determine whether a first triggering condition for the vehicle to change lanes to the first adjacent lane is met based on the traffic efficiency cost of the lane and the traffic efficiency cost of the first adjacent lane; and a control module 203, configured to execute an operation to control the vehicle to change lanes if the first triggering condition is met.

[0105] One embodiment of this application provides an electronic chip, including: a processor for executing computer program instructions stored in a memory, wherein when the computer program instructions are executed by the processor, the electronic chip is triggered to execute the method described in any embodiment of this application.

[0106] One embodiment of this application provides an electronic device including at least one processor and a memory coupled together. The memory is used to store computer program instructions, and the processor is used to execute the computer program instructions. When the computer program instructions are executed by the processor, the electronic device is triggered to execute the method described in any embodiment of this application.

[0107] One embodiment of this application provides a computer-readable storage medium storing a computer program that, when run on a computer, causes the computer to perform the methods described in any embodiment of this application.

[0108] One embodiment of this application provides a computer program product, which includes a computer program that, when run on a computer, causes the computer to perform the methods described in any embodiment of this application.

[0109] Figure 3 This is a schematic diagram of a computer device provided according to one embodiment of this application. Figure 3 As shown, the computer device 20 in this embodiment includes a processor 21 and a memory 22. The memory 22 stores a computer program 23 that can run on the processor 21. When the computer program 23 is executed by the processor 21, it implements the steps in the method embodiments of this application. To avoid repetition, these steps are not described in detail here. Alternatively, when the computer program 23 is executed by the processor 21, it implements the functions of each model / unit in the device embodiments of this application. To avoid repetition, these functions are not described in detail here.

[0110] Computer device 20 includes, but is not limited to, processor 21 and memory 22. Those skilled in the art will understand that... Figure 3 This is merely an example of computer device 20 and does not constitute a limitation on computer device 20. It may include more or fewer components than shown, or combine certain components, or different components. For example, computer device may also include input / output devices, network access devices, buses, etc.

[0111] The processor 21 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor, or it can be any conventional processor.

[0112] The memory 22 can be an internal storage unit of the computer device 20, such as a hard disk or RAM of the computer device 20. The memory 22 can also be an external storage device of the computer device 20, such as a plug-in hard disk, Smart Media (SM) card, Secure Digital (SD) card, or FlashCard equipped on the computer device 20. Furthermore, the memory 22 can include both internal and external storage units of the computer device 20. The memory 22 is used to store the computer program 23 and other programs and data required by the computer device. The memory 22 can also be used to temporarily store data that has been output or will be output.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, apparatuses, or units, and may be electrical, mechanical, or other forms.

[0114] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0115] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in a combination of hardware and software functional units.

[0116] An integrated unit implemented as a software functional unit can be stored in a computer-readable storage medium. This software functional unit, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0117] In this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0118] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0119] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments of this application can be implemented using electronic hardware, computer software, or a combination of electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0120] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the same or similar parts between the various embodiments of this application can be referred to mutually. For example, the specific working processes of the systems, devices, and units described in the embodiments of this application can be referred to the corresponding processes in the method embodiments of this application, and will not be repeated here.

[0121] The above description is merely a specific embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A vehicle control method, characterized in that, include: The traffic efficiency cost of the self-lane is obtained based on the traffic efficiency cost of the obstacle located in front of the self-lane, and the traffic efficiency cost of the first adjacent lane is obtained based on the traffic efficiency cost of the obstacle located in front of the self-lane in the first adjacent lane. The obstacle's traffic efficiency cost is obtained based on the obstacle's motion information and the first information. The first information is used to indicate the predicted probability that the obstacle will be in the current lane at a future time. The traffic efficiency cost is a parameter that characterizes the degree of obstruction to the vehicle's driving. Based on the traffic efficiency cost of the vehicle lane and the traffic efficiency cost of the first adjacent lane, determine whether the first triggering condition for the vehicle to change lanes to the first adjacent lane is met. If the first triggering condition is met, the operation of controlling the vehicle to change lanes will be executed; The motion information of the obstacle includes the obstacle's speed; The steps to obtain initial information about obstacles include: Based on the obstacle's speed and the set duration, predict the obstacle's trajectory over a future period of time; The percentage of the predicted driving trajectory that is in the lane where the obstacle is currently located is obtained as the first information about the obstacle; the percentage is the proportion of the predicted driving trajectory that is in the lane where the obstacle is currently located to the predicted driving trajectory.

2. The method according to claim 1, characterized in that, The passage efficiency cost of an obstacle is the product of the initial passage efficiency cost of the obstacle and the correction parameter; The initial traffic efficiency cost is obtained based on the motion information of the obstacle, and the correction parameter is obtained based on the first information of the obstacle.

3. The method according to claim 1, characterized in that, The traffic efficiency cost is not less than zero; The method further includes: obtaining a first difference between the traffic efficiency cost of the self-lane and the traffic efficiency cost of the first adjacent lane; The first triggering condition is met when: the first difference is not less than a set threshold; or the set threshold is greater than zero.

4. The method according to claim 3, characterized in that, The method further includes: The traffic efficiency cost of the second adjacent lane is obtained based on the traffic efficiency cost of the obstacle located in front of the vehicle in the second adjacent lane of the vehicle lane. Obtain the second difference obtained by subtracting the traffic efficiency cost of the second adjacent lane from the traffic efficiency cost of the lane itself; Among them, the second triggering condition for the vehicle to change lanes to the second adjacent lane is met when the second difference is not less than the set threshold. The step of controlling the vehicle to change lanes when the first triggering condition is met includes: If both the first and second triggering conditions are met, the vehicle is controlled to change lanes to the adjacent lane to the left of the vehicle.

5. The method according to any one of claims 1-4, characterized in that, The steps to obtain the traffic efficiency cost of a lane include: Based on the motion information of the nearest obstacle in the lane that is located in front of the vehicle and the first information, the passage efficiency cost of the nearest obstacle is obtained. The traffic efficiency cost of the nearest obstacle is used as the traffic efficiency cost of the lane in which it is located.

6. The method according to any one of claims 1-4, characterized in that, The steps to obtain the traffic efficiency cost of a lane include: Based on the motion information and first information of each obstacle located in front of the vehicle in the lane, obtain the traffic efficiency cost of each obstacle; The maximum value of the traffic efficiency cost of each obstacle is taken as the traffic efficiency cost of the lane.

7. The method according to any one of claims 1-4, characterized in that, The steps to obtain the traffic efficiency cost of a lane include: Based on the motion information of the nearest obstacle in the lane that is located in front of the vehicle and the first information, the passage efficiency cost of the nearest obstacle is obtained. Based on the motion information and first information of each obstacle located in front of the vehicle in the lane, obtain the traffic efficiency cost of each obstacle; The traffic efficiency cost of the lane is obtained by taking the maximum value of the traffic efficiency cost of the nearest obstacle and the traffic efficiency cost of each obstacle.

8. A vehicle control device, characterized in that, include: The acquisition module is used to acquire the traffic efficiency cost of the self-lane based on the traffic efficiency cost of the obstacle located in front of the self-lane, and to acquire the traffic efficiency cost of the first adjacent lane based on the traffic efficiency cost of the obstacle located in front of the self-lane in the first adjacent lane. The obstacle's traffic efficiency cost is obtained based on the obstacle's motion information and the first information. The first information is used to indicate the predicted probability that the obstacle will be in the current lane at a future time. The traffic efficiency cost is a parameter that characterizes the degree of obstruction to the vehicle's driving. The determination module is used to determine whether the first triggering condition for the vehicle to change lanes to the first adjacent lane is met based on the traffic efficiency cost of the vehicle lane and the traffic efficiency cost of the first adjacent lane. The control module is used to perform the operation of controlling the vehicle to change lanes when the first triggering condition is met; The motion information of the obstacle includes the obstacle's speed; The steps to obtain initial information about obstacles include: Based on the obstacle's speed and the set duration, predict the obstacle's trajectory over a future period of time; The percentage of the predicted driving trajectory that is in the lane where the obstacle is currently located is obtained as the first information about the obstacle; the percentage is the proportion of the predicted driving trajectory that is in the lane where the obstacle is currently located to the predicted driving trajectory.

9. An electronic device, characterized in that, The electronic device includes at least one processor coupled to a memory for storing computer program instructions and for executing the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when run on a computer, causes the computer to perform the method as described in any one of claims 1-7.

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