Vehicle control method and device, electronic equipment and medium

Abstract

The embodiment of the invention provides a vehicle control method and device, electronic equipment and a medium, and relates to the technical field of vehicles, and the method comprises the steps: obtaining the passing efficiency cost of an own lane according to the passing efficiency cost of an obstacle located in front of the own vehicle on the own lane, obtaining the passing efficiency cost of a first adjacent lane according to the passing efficiency cost of an obstacle located in front of the vehicle on the first adjacent lane of the vehicle; the passing efficiency cost of the obstacle is obtained according to the movement information of the obstacle and first information, the first information is used for indicating the prediction probability that the obstacle is located in the current lane in the future moment, and the passing efficiency cost is a parameter representing the driving congestion degree of the vehicle; and according to the passing efficiency cost of the own lane and the passing efficiency cost of the first adjacent lane, determining whether a first triggering condition for changing the lane from the own vehicle to the first adjacent lane is established, and if yes, executing an operation of controlling the own vehicle to change the lane. According to the embodiment of the invention, accurate control of lane changing of the vehicle can be realized.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control method, device, electronic equipment and medium. Background Art

[0002] With the rapid development of intelligent driving technology, the control of vehicle driving process is becoming more and more refined. During the driving process, there may be a need for the vehicle to change lanes, so it is necessary to provide a vehicle control method that supports the vehicle to change lanes. Summary of the invention

[0003] The embodiments of the present application provide a vehicle control method, device, electronic device and medium, which can achieve precise control of the lane change of the vehicle.

[0004] In a first aspect, an embodiment of the present application provides a vehicle control method, comprising: obtaining a traffic efficiency cost of a own lane based on a traffic efficiency cost of an obstacle located in front of the own vehicle on the own lane, and obtaining a traffic efficiency cost of a first adjacent lane based on an traffic efficiency cost of an obstacle located in front of the own vehicle on the first adjacent lane of the own lane; wherein the traffic efficiency cost of the obstacle is obtained based on motion information of the obstacle and first information, the first information is used to indicate a predicted probability that the obstacle will be located in the current lane at a future moment, and the traffic efficiency cost is a parameter characterizing a degree of obstruction to the travel of the own vehicle; determining whether a first trigger condition for the own vehicle to change lanes to the first adjacent lane is met based on the traffic efficiency cost of the own lane and the traffic efficiency cost of the first adjacent lane; and executing an operation of controlling the own vehicle to change lanes when the first trigger condition is met.

[0005] In the embodiment of the present application, in addition to the movement information of the obstacle (such as a vehicle), the obstacle cost (i.e., the cost of traffic efficiency) is obtained in combination with the lane change intention of the obstacle. In this way, the obtained obstacle cost takes into account whether there is a lane change intention and the different effects of different degrees of lane change intention on the blocking degree of the vehicle's driving. The obtained obstacle cost can more accurately reflect the blocking situation of the obstacle to the vehicle's driving. In this way, the lane cost obtained based on the cost of the obstacle on the lane can more accurately reflect the lane's unobstructed situation. Furthermore, based on the cost of the lane and the cost of the adjacent lane, precise control of the vehicle's lane change can be achieved.

[0006] Optionally, the traffic efficiency cost of the obstacle is the product of the initial traffic efficiency cost of the obstacle and a correction parameter; the initial traffic efficiency cost is obtained according to the motion information of the obstacle, and the correction parameter is obtained according to the first information of the obstacle.

[0007] By adopting the product method, the correction parameters obtained according to the lane change intention of the obstacle are used to correct the initial cost obtained according to the movement information of the obstacle, so that the correction parameters adjust the initial cost by a corresponding multiple, so that the obstacle cost can be accurately obtained.

[0008] Optionally, the movement information of the obstacle includes the speed of the obstacle; the step of obtaining the first information of the obstacle includes: predicting the driving trajectory of the obstacle in a future period of time based on the 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.

[0009] By predicting the driving trajectory of the obstacle in the future time period and based on the proportion of the predicted driving trajectory in the original lane, the obstacle's lane change intention can be accurately predicted, supporting the accurate acquisition of the obstacle cost.

[0010] Optionally, the traffic efficiency cost is not less than zero; the vehicle control method also includes: obtaining a first difference between the traffic efficiency cost of the lane and the traffic efficiency cost of the first adjacent lane; wherein the first trigger condition is met in the following situations: the first difference is not less than a set threshold; the set threshold is greater than zero.

[0011] By setting cost ≥ 0 and limiting the difference between the cost of the own lane and the cost of the adjacent lane to be less than a threshold, the vehicle is controlled to change lanes. If the limitation is met, it means that the vehicle needs to change lanes and can change lanes. That is, it can have the effect of changing lanes to the adjacent lane when the own lane is congested and the adjacent lane is unobstructed. The control process is simple and meets the actual lane change control of the user's driving.

[0012] Optionally, the vehicle control method also includes: obtaining the traffic efficiency cost of the second adjacent lane based on the traffic efficiency cost of the obstacle located in front of the self-vehicle on the second adjacent lane of the self-vehicle lane; obtaining a second difference between the traffic efficiency cost of the self-vehicle lane and the efficiency cost of the second adjacent lane; wherein, the situation where the second trigger condition for the self-vehicle to change lanes to the second adjacent lane is met includes: the second difference is not less than a set threshold value; when the first trigger condition is met, executing the operation of controlling the self-vehicle to change lanes, including: when both the first trigger condition and the second trigger condition are met, controlling the self-vehicle to change lanes to the adjacent lane located on the left side of the self-vehicle.

[0013] When there are two adjacent lanes and both adjacent lanes are unobstructed to support the vehicle's lane change, it is preferred to change lanes to the left. This implementation method meets the actual needs of users.

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

[0015] Since the blocking effect of the obstacle closest to the vehicle on the current driving of the vehicle is usually significantly higher than the blocking effect of the obstacle farther away from the vehicle, the decision on whether to change lanes of the vehicle can be made based on the blocking effect of the nearest obstacle on the current driving of the vehicle. This can achieve accurate control of the lane change of the vehicle and simplify the lane change control logic.

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

[0017] Since the blocking effect of the obstacle ahead with the maximum cost on the driving of the ego vehicle in the current and future time periods is usually significantly higher than the blocking effect of the obstacle ahead with the smaller cost on the driving of the ego vehicle in the current and future time periods, whether to execute the lane change of the ego vehicle can be determined based on the blocking effect of the obstacle ahead with the maximum cost on the driving of the ego vehicle in the current and future time periods. In this way, accurate control of the lane change of the ego vehicle can be achieved, and it can be forward-looking.

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

[0019] By comprehensively considering the blocking effects of the nearest obstacle and the maximum cost obstacle on the driving of the ego vehicle, accurate control of the ego vehicle's lane change can be achieved with foresight.

[0020] In a second aspect, an embodiment of the present application provides a vehicle control device, comprising: an acquisition module, used to acquire the traffic efficiency cost of the own lane according to the traffic efficiency cost of the obstacle located in front of the own vehicle on the own lane, and to acquire the traffic efficiency cost of the first adjacent lane according to the traffic efficiency cost of the obstacle located in front of the own vehicle on the first adjacent lane of the own lane; wherein the traffic efficiency cost of the obstacle is obtained based on the motion information of the obstacle and the first information, the first information is used to indicate the predicted probability that the obstacle will be located in the current lane at a future moment, and the traffic efficiency cost is a parameter characterizing the degree of obstruction to the driving of the own vehicle; a determination module, used to determine whether a first trigger condition for the own vehicle to change lanes to the first adjacent lane is met based on the traffic efficiency cost of the own lane and the traffic efficiency cost of the first adjacent lane; and a control module, used to execute the operation of controlling the own vehicle to change lanes when the first trigger condition is met.

[0021] In a third aspect, an embodiment of the present application provides an electronic chip, comprising: a processor, which is used to execute 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 any method as in the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising at least one processor, wherein the processor and a memory are coupled, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute a method as described in any one of the first aspects.

[0023] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer executes any method in the first aspect.

[0024] In a sixth aspect, an embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is run on a computer, the computer executes any method in the first aspect.

[0025] The technical effects of the aforementioned aspects can be referenced to each other and will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1A schematic flow chart of a vehicle control method provided by an embodiment of the present application;

[0028] Figure 2 A block diagram of a vehicle control device provided by one embodiment of the present application;

[0029] Figure 3 A schematic diagram of the structure of a computer device provided for one embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0031] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0032] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0033] It should be understood that the term "at least one" used in this article refers to one or more, and "plurality" refers to two or more. The term "and / or" used in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. Among them, A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after 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 be represented by: a, b, c, ab, ac, bc, or abc, wherein a, b, 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 the present 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 the present 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, an embodiment of the present application provides a vehicle control method, which may include steps 101 to 103.

[0036] In one embodiment, Figure 1 The execution subject of the embodiment shown may be the vehicle itself. The vehicle itself may be any vehicle with an automatic driving function. In another embodiment, the execution subject may also be a server device that maintains a communication connection with the vehicle itself.

[0037] In one embodiment, Figure 1 The applicable scenario of the embodiment shown may be a multi-lane driving scenario, such as a high-speed multi-lane driving scenario. The multi-lane is at least two lanes, including at least a self-lane and adjacent lanes on one side or both sides of the self-lane.

[0038] Step 101, according to the traffic efficiency cost (for example, expressed as cost) of the obstacle on the own lane located in front of the own vehicle, the traffic efficiency cost of the own lane is obtained, and according to the traffic efficiency cost of the obstacle on the first adjacent lane of the own lane located in front of the own vehicle, the traffic efficiency cost of the first adjacent lane is obtained; wherein the traffic efficiency cost of the obstacle is obtained according to the motion information of the obstacle and the first information, the first information is used to indicate the predicted probability that the obstacle is located in the current lane at a future time, and the traffic efficiency cost is a parameter representing the blocking degree of the own vehicle.

[0039] The first information is information reflecting the predicted probability that the obstacle will be located in the current lane at a future moment, which can be used to indicate the strength of the obstacle's intention to change lanes, and can reflect the probability that the obstacle will change lanes to an adjacent lane (i.e., leave its own lane) at a future moment.

[0040] For the ego lane or the adjacent lane, when there is an obstacle in front of the ego vehicle on the lane, the motion information of the obstacle and the information reflecting the vehicle's lane change intention can be obtained, so as to obtain the cost of the obstacle.

[0041] In one embodiment, the vehicle's sensors can be used to sense whether there is an obstacle ahead of the vehicle. For example, in one feasible implementation, the image of the road ahead captured by the vehicle's image capture device can be analyzed to determine whether there is an obstacle ahead of the vehicle.

[0042] The obstacle in front of the vehicle can usually be a moving obstacle, such as a moving vehicle, or a stationary obstacle, such as an obstacle avoidance sign.

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

[0044] In one embodiment, the motion information may include the vehicle speed and the distance from the vehicle itself. The distance may be a longitudinal distance along the direction in which the road extends.

[0045] The cost of an obstacle can represent the degree of obstruction of the obstacle to the driving of the vehicle. The larger the cost of the obstacle, the higher the degree of obstruction of the obstacle to the driving of the vehicle, and vice versa.

[0046] The cost of the lane can be obtained based on the cost of the obstacle. The larger the cost of the lane, the more congested the lane is, and the higher the degree of obstruction of the lane to the driving of the vehicle. On the contrary, the smoother the lane is, the lower the degree of obstruction of the lane to the driving of the vehicle.

[0047] In one embodiment of the present application, the traffic efficiency cost of the obstacle is the product of the initial traffic efficiency cost of the obstacle and the correction parameter; the initial traffic efficiency cost is obtained according to the motion information of the obstacle, and the correction parameter is obtained according to the first information of the obstacle.

[0048] In other embodiments of the present application, other methods may be used to correct 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 adopting the multiplication method, the initial cost obtained according to the movement information of the obstacle is corrected using the correction parameters obtained according to the lane change intention of the obstacle, so that the correction parameters adjust the initial cost by a corresponding multiple, so that the obstacle cost (or obstacle cost) can be accurately obtained.

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

[0051] Thus, obstacle cost=initial cost of obstacle×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 may be a speed threshold configured according to the lane change requirement, such as 5m / s; the unit speed difference cost parameter may represent the adjustable situation within the unit speed, such as 3.5; the obstacle impact weight value may be configured based on the steady-state following factor and / or the distance between the vehicle and the obstacle, and the configuration range may be, for example, [0,1].

[0053] The steady-state following factor can be used to characterize the need for the ego vehicle to stably follow the leading vehicle, and can be pre-configured 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 the present application, the movement information of the obstacle includes the speed of the obstacle; the step of obtaining the first information of the obstacle includes: predicting the driving trajectory of the obstacle in a future period of time based on the speed of the obstacle and the 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 can reflect the expected behavior changes of the vehicle in the future and can be used as a prediction of the real behavior of the vehicle. Based on the predicted driving trajectory, the above-mentioned proportion can be obtained, and the size of the obtained proportion can reflect the strength of the obstacle's lane change intention. The larger the proportion, the weaker the lane change intention, and vice versa.

[0056] In one embodiment, the set time length can be determined according to the lane change requirement, for example, it can be set to any time length between 4 and 6 seconds. Taking the set time length of 5 seconds as an example, the driving trajectory of the obstacle in the next 5 seconds can be predicted according to its speed.

[0057] Taking the obstacle as an example, compared with the case where the vehicle has no intention to change lanes or has a small intention to change lanes, if the vehicle has a large intention to change lanes (for example, the vehicle is currently close to the adjacent lane and the vehicle's direction is greatly offset toward the adjacent lane), the predicted driving trajectory will account for a relatively small proportion in the lane where the vehicle is currently located, and a relatively large proportion in the adjacent lane to be changed.

[0058] The proportion of the predicted driving trajectory in the current lane may be the percentage of the predicted driving trajectory (i.e., the entire driving trajectory) in the current lane. In one embodiment, the obtained proportion may be used as the above correction parameter to modify the initial cost of the obstacle.

[0059] In one embodiment, if the vehicle has no intention to change lanes, the proportion of the predicted driving trajectory in the lane where the vehicle is currently located can be 100%; if the vehicle has a small intention to change lanes (such as the early stage of the lane change process), the proportion of the predicted driving trajectory in the lane where the vehicle is currently located can be close to but less than 100%; if the vehicle has a large intention to change lanes (such as the late stage of the lane change process), the proportion of the predicted driving trajectory in the lane where the vehicle is currently located is close to but greater than 0%. In this way, the value range of the obtained proportion can be greater than 0 and not greater than 1.

[0060] The greater the lane change intention of the obstacle in front of the ego lane, the smaller the proportion obtained, the greater the degree of correction of the initial cost of the obstacle, the smaller the corrected obstacle cost, the smaller the obstruction of the obstacle to the ego vehicle's driving, and the less likely it is to cause the ego vehicle to change lanes. Conversely, it is more likely to cause the ego vehicle to change lanes.

[0061] By predicting the driving trajectory of the obstacle in the future time period and based on the proportion of the predicted driving trajectory in the original lane, the obstacle's lane change intention can be accurately predicted, supporting the accurate acquisition of the obstacle cost.

[0062] For example, if there is a vehicle ahead in the ego lane that will change lanes to the adjacent lane in a short time, that is, there is a vehicle ahead with the intention to change lanes, assuming that the speed of the vehicle ahead is slow, if the intention to change lanes is not considered, the cost of the vehicle ahead is large, which will cause the ego vehicle to change lanes. In this way, the ego vehicle follows the slow vehicle ahead and changes lanes to the adjacent lane. After the ego vehicle changes lanes, it still follows the slow vehicle, so that the ego vehicle's driving after changing lanes is still blocked, causing the ego vehicle to perform an unreasonable and unnecessary lane change. If the intention to change lanes is considered, the cost of the vehicle ahead is small, so the ego vehicle will not change lanes, and after the vehicle ahead finishes changing lanes later, the ego vehicle's driving is no longer affected by the blocking effect of the vehicle ahead. This control result of controlling the ego vehicle not to change lanes meets the actual lane change requirements (that is, the ego vehicle does not change lanes when the vehicle ahead changes lanes).

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

[0064] For the nearest obstacle, there is no other obstacle between the nearest obstacle and the vehicle on the corresponding lane.

[0065] For obstacles in front of the vehicle, when obtaining the cost of the lane (or the cost of the lane) based on the cost of the nearest obstacle, it is not necessary to obtain the cost of each obstacle on the lane. If there is only one obstacle on the lane, then the obstacle is the nearest obstacle, and then the cost of the nearest obstacle is obtained. If there is more than one obstacle on the lane, first determine the nearest obstacle based on the distance between the vehicle and each obstacle on the lane, and then obtain the cost of the nearest obstacle.

[0066] Since the blocking effect of the obstacle closest to the vehicle on the current driving of the vehicle is usually significantly higher than the blocking effect of the obstacle farther away from the vehicle, the decision on whether to change lanes of the vehicle can be made based on the blocking effect of the nearest obstacle on the current driving of the vehicle. This can achieve accurate control of the lane change of the vehicle and simplify the lane change control logic.

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

[0068] When other factors are the same or have little impact on the cost, the slowest front obstacle can have the relatively largest cost.

[0069] Since the blocking effect of the obstacle ahead with the maximum cost on the driving of the ego vehicle in the current and future time periods is usually significantly higher than the blocking effect of the obstacle ahead with the smaller cost on the driving of the ego vehicle in the current and future time periods, whether to execute the lane change of the ego vehicle can be determined based on the blocking effect of the obstacle ahead with the maximum cost on the driving of the ego vehicle in the current and future time periods. In this way, accurate control of the lane change of the ego vehicle can be achieved, and it can be forward-looking.

[0070] In one embodiment of the present application, 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 and first information of the obstacle located in front of the vehicle on the lane; obtaining the traffic efficiency cost of each obstacle based on the motion information and first information of each obstacle located in front of the vehicle on the lane; obtaining the traffic efficiency cost of the lane based on the maximum value of 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 maximum cost obstacle may be set respectively. The set weights may be obtained based on empirical values.

[0072] In one embodiment, lane cost=cost of the nearest obstacle on the lane×first weight+maximum value of costs of various obstacles on the lane×second weight.

[0073] By comprehensively considering the blocking effects of the nearest obstacle and the maximum cost obstacle on the driving of the ego vehicle, accurate control of the ego vehicle's lane change can be achieved with foresight.

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

[0075] When the lane cost is high, the demand for lane change is high. Conversely, when the lane cost is low, the demand for lane change is low.

[0076] For example, if the lane cost is not less than the first threshold, it means that the vehicle is blocked in the lane and the road ahead of the vehicle is congested, so the vehicle needs to change lanes. On the contrary, if the lane cost is less than the first threshold, it means that the vehicle is not blocked in the lane and the road ahead of the vehicle is unobstructed, so the vehicle does not need to change lanes.

[0077] In one implementation, whether the adjacent lane supports the lane change of the vehicle can be determined based on the absolute congestion level of the adjacent lane. When the adjacent lane cost is higher, the lane change of the vehicle is less supported, and vice versa, when the adjacent lane cost is lower, the lane change of the vehicle is more supported.

[0078] For example, if the adjacent lane cost is not less than the second threshold, it means that the vehicle is blocked if it is driving in the adjacent lane, and the road ahead of the vehicle in the adjacent lane is congested and not smooth, so the vehicle does not support lane change. On the contrary, if the adjacent lane cost is less than the second threshold, it means that the vehicle is not blocked if it is driving in the adjacent lane, and the road ahead of the vehicle in the adjacent lane is smooth and not congested, so the vehicle supports lane change.

[0079] In another implementation, whether the adjacent lane supports lane change can be determined based on the relative congestion level of the adjacent lane. When the cost of the own lane is greater than the cost of the adjacent lane, and the larger the difference between the two, it means that the smoothness of the adjacent lane is significantly higher than that of the own lane. In this case, even if the adjacent lane is not smooth and congested, the adjacent lane still supports lane change for the own vehicle. On the contrary, when the cost of the own lane and the cost of the adjacent lane are not much different, it means that the smoothness of the adjacent lane is not much different from that of the own lane. In this case, when the adjacent lane is not smooth and congested, the own vehicle does not support lane change.

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

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

[0082] In another embodiment, it is also possible to directly determine whether the difference between the cost of the own lane and the cost of the adjacent lane is not greater than the third threshold value. If so (i.e., the own vehicle needs to change lanes and the adjacent lane supports the own vehicle's lane change), and there are no other factors that do not support the own vehicle's lane change (such as the ramp ahead, etc.), then the operation of controlling the own vehicle's lane change can be executed. Since there is no need to perform two levels of judgment in succession, this helps to simplify the solution implementation process. In addition, this implementation method is also applicable to scenarios where both the own lane and the adjacent lane are congested, but the congestion in the own lane is more serious, and the congestion gap between the two is large, making it necessary to change lanes for the own vehicle, which is in line with the actual lane change control of the user's driving.

[0083] Thus, in one embodiment of the present application, the traffic efficiency cost is not less than zero; the vehicle control method also includes: obtaining a first difference between the traffic efficiency cost of the lane and the traffic efficiency cost of the first adjacent lane; wherein, the situation in which the first trigger condition is met includes: 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 ego lane and the cost of the adjacent lane is not less than the set threshold, it means that the cost of the ego lane is not less than the set threshold (i.e., the ego lane is congested and the ego vehicle needs to change lanes), and it means that the cost of the adjacent lane is small (i.e., the adjacent lane is unobstructed or smoother than the ego lane and supports the ego vehicle to change lanes). In this case, the operation of controlling the ego vehicle to change lanes can be executed.

[0085] If the difference between the cost of the own lane and the cost of the adjacent lane is less than the set threshold, the operation of controlling the lane change of the own vehicle may not be performed. This may be because the own lane is unobstructed and there is no need to change lanes, or both the own lane and the adjacent lane are congested and do not support the lane change of the own vehicle.

[0086] By setting cost ≥ 0 and limiting the difference between the cost of the own lane and the cost of the adjacent lane to be less than a threshold, the vehicle is controlled to change lanes. If the limitation is met, it means that the vehicle needs to change lanes and can change lanes. That is, it can have the effect of changing lanes to the adjacent lane when the own lane is congested and the adjacent lane is unobstructed. The control process is simple and meets the actual lane change control of the user's driving.

[0087] In the scenario where the vehicle ahead of you has the intention to change lanes, if the lane change intention of the vehicle ahead is not considered, the first difference is likely to exceed the set threshold. Compared with not considering the lane change intention of the vehicle ahead, by introducing the impact of the vehicle's lane change intention on the vehicle cost, the cost of the vehicle with the lane change intention is reduced, and the reduction is positively correlated with the intensity of the lane change intention. In this way, the first difference is less likely to exceed the set threshold, and thus it is less likely to cause the vehicle to change lanes, avoiding unreasonable lane changes of the vehicle ahead, and meeting the actual driving lane change requirements.

[0088] In one embodiment of the present application, the first trigger condition may also include: when the vehicle changes lanes to the first adjacent lane, there is no risk of collision with the vehicle 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 rear vehicle, the distance between the rear vehicle and the vehicle, etc.

[0089] In one embodiment of the present application, the situation where the first trigger condition is met may also include: the lane change inhibition condition is not met. In one embodiment, the lane change inhibition condition may include that there is a ramp within a preset distance ahead, the vehicle is in a non-automatic driving state, the vehicle is in the driving lane, the vehicle is not on a highway, and the vehicle has not turned on the overtaking lane change automatic driving function.

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

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

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

[0093] When there is one adjacent lane, if the first trigger condition is not met, the operation of controlling the vehicle to change lanes is not performed.

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

[0095] When there are two adjacent lanes, if the first trigger condition is not met and the trigger condition for the ego vehicle to change lanes to another adjacent lane is also not met, the operation of controlling the ego vehicle to change lanes is not performed.

[0096] When there are two adjacent lanes, if the first trigger condition is not met, but the trigger 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 performed to control the vehicle to change lanes to the other adjacent lane.

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

[0098] In one embodiment of the present application, the vehicle control method also includes: obtaining the traffic efficiency cost of the second adjacent lane based on the traffic efficiency cost of the obstacle located in front of the self-vehicle on the second adjacent lane of the self-vehicle lane; obtaining a second difference between the traffic efficiency cost of the self-vehicle lane and the traffic efficiency cost of the second adjacent lane; wherein, the situation where the second trigger condition for the self-vehicle to change lanes to the second adjacent lane is met includes: the second difference is not less than a set threshold value; when the first trigger condition is met, executing the operation of controlling the self-vehicle to change lanes, including: when both the first trigger condition and the second trigger condition are met, controlling the self-vehicle to change lanes to the adjacent lane located on the left side of the self-vehicle.

[0099] When there are two adjacent lanes and both adjacent lanes are unobstructed to support the vehicle's lane change, it is preferred to change lanes to the left. This implementation method meets the actual needs of users.

[0100] Based on the forward direction of the vehicle, the adjacent lane to the left of the vehicle / lane is the left lane of the vehicle. If the vehicle changes lanes to the left lane, it means the vehicle changes lanes to the left. The adjacent lane to the right of the vehicle / lane is the right lane of the vehicle. If the vehicle changes lanes to the right lane, it means the vehicle changes lanes to the right. To better meet the driving habits and needs of users, if both the left and right lanes support lane changes, the left lane can be preferred.

[0101] In another embodiment, when both the left and right lanes support lane change for the vehicle itself, it may be preferred to change lanes to an adjacent lane with more traffic.

[0102] Figure 1 In the illustrated embodiment, in addition to the movement information of the obstacle, the obstacle cost is also obtained in combination with the obstacle's lane change intention. In this way, the obtained obstacle cost takes into account whether there is a lane change intention and the different effects of different degrees of lane change intention on the driving obstruction of the vehicle. The obtained obstacle cost can more accurately reflect the obstruction of the obstacle to the driving of the vehicle. In this way, the lane cost obtained based on the cost of the obstacle on the lane can more accurately reflect the lane unobstructedness. Furthermore, based on the cost of the lane and the cost of the adjacent lane, precise control of the lane change of the vehicle can be achieved.

[0103] In one embodiment of the present application, 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 front and rear obstacles on the lane to be changed, path planning can be performed through a planning model (such as a path planning decision algorithm, etc.), to obtain a vehicle lane change planning path, and control the vehicle to travel along the obtained vehicle lane change planning path, thereby achieving the purpose of changing lanes to the lane to be changed.

[0104] like Figure 2As shown, an embodiment of the present application provides a vehicle control device 200, including: an acquisition module 201, used to acquire the traffic efficiency cost of the own lane according to the traffic efficiency cost of the obstacle located in front of the own vehicle on the own lane, and to acquire the traffic efficiency cost of the first adjacent lane according to the traffic efficiency cost of the obstacle located in front of the own vehicle on the first adjacent lane of the own lane; wherein the traffic efficiency cost of the obstacle is obtained according to the motion information of the obstacle and the first information, the first information is used to indicate the predicted probability that the obstacle is located in the current lane at a future moment, and the traffic efficiency cost is a parameter characterizing the blocking degree of the own vehicle; a determination module 202, used to determine whether a first trigger condition for the own vehicle to change lanes to the first adjacent lane is met according to the traffic efficiency cost of the own lane and the traffic efficiency cost of the first adjacent lane; a control module 203, used to execute the operation of controlling the own vehicle to change lanes when the first trigger condition is met.

[0105] An embodiment of the present application provides an electronic chip, including: a processor, which is used to execute 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 the present application.

[0106] An embodiment of the present application provides an electronic device, which includes at least one processor, the processor and a memory are coupled, the memory is used to store computer program instructions, and the processor is used to execute the computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute the method described in any embodiment of the present application.

[0107] An embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer executes the method described in any embodiment of the present application.

[0108] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program runs on a computer, the computer executes the method described in any embodiment of the present application.

[0109] Figure 3 A schematic diagram of a computer device provided in one embodiment of the present application. Figure 3 As shown, the computer device 20 of this embodiment includes: a processor 21 and a memory 22, the memory 22 is used to store a computer program 23 that can be run on the processor 21, and the computer program 23 is executed by the processor 21 to implement the steps in the method embodiment of the present application. To avoid repetition, they are not described one by one here. Alternatively, when the computer program 23 is executed by the processor 21, the functions of each model / unit in the device embodiment of the present application are implemented. To avoid repetition, they are not described one by one here.

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

[0111] The processor 21 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor, etc.

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

[0113] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

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

[0115] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0116] The integrated unit implemented in the form of a software functional unit can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (Processor) to perform some steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store program code.

[0117] In the embodiments of the present application, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, method, commodity or device including the element.

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

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

[0120] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the same or similar parts between the various embodiments in this application can be referred to each other. For example, the specific working process of the system, device and unit described in the embodiments of this application can refer to the corresponding process in the method embodiment of this application, and will not be repeated here.

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

Claims

1. A vehicle control method, characterized in that: include: According to the traffic efficiency cost of the obstacle located in front of the vehicle on the own lane, the traffic efficiency cost of the own lane is obtained; and according to the traffic efficiency cost of the obstacle located in front of the vehicle on the first adjacent lane of the own lane, the traffic efficiency cost of the first adjacent lane is obtained; The traffic efficiency cost of the obstacle is obtained according to the movement information of the obstacle and the first information, the first information is used to indicate the predicted probability that the obstacle will be located in the current lane at a future moment, and the traffic efficiency cost is a parameter representing the degree of obstruction to the driving of the ego vehicle; determining whether a first triggering condition for the ego vehicle to change lane to the first adjacent lane is met according to the traffic efficiency cost of the ego lane and the traffic efficiency cost of the first adjacent lane; When the first trigger condition is met, an operation of controlling the vehicle to change lanes is executed.

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

3. The method according to claim 1, characterized in that The obstacle’s motion information includes the obstacle’s speed; The step of obtaining first information of an obstacle includes: According to the speed of the obstacle and the set duration, predict the obstacle's driving trajectory in the future; The proportion of the predicted driving trajectory in the lane where the obstacle is currently located is obtained as the first information of the obstacle.

4. 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 value obtained by subtracting the traffic efficiency cost of the first adjacent lane from the traffic efficiency cost of the own lane; The situations in which the first trigger condition is met include: the first difference is not less than a set threshold; the set threshold is greater than zero.

5. The method according to claim 4, characterized in that The method further comprises: Obtaining a traffic efficiency cost of the second adjacent lane according to a traffic efficiency cost of an obstacle located in front of the vehicle on the second adjacent lane of the vehicle lane; Obtaining a second difference value obtained by subtracting the traffic efficiency cost of the second adjacent lane from the traffic efficiency cost of the own lane; The second trigger condition for the vehicle to change lane to the second adjacent lane is satisfied when: the second difference is not less than the set threshold; When the first trigger condition is met, executing the operation of controlling the vehicle to change lanes includes: When both the first trigger condition and the second trigger condition are satisfied, the vehicle is controlled to change lanes to an adjacent lane located on the left side of the vehicle.

6. The method according to any one of claims 1 to 5, characterized in that: The steps to obtain the lane efficiency cost include: Obtaining a passage efficiency cost of the closest obstacle located in front of the vehicle and closest to the vehicle on the lane according to the motion information of the closest obstacle to the vehicle and the first information; The traffic efficiency cost of the nearest obstacle is used as the traffic efficiency cost of the lane.

7. The method according to any one of claims 1 to 5, characterized in that: The steps to obtain the lane efficiency cost include: Obtaining a traffic efficiency cost of each obstacle on the lane in front of the vehicle according to the motion information and the first information; The maximum value of the traffic efficiency costs of each obstacle is used as the traffic efficiency cost of the lane.

8. The method according to any one of claims 1 to 5, characterized in that: The steps to obtain the lane efficiency cost include: Obtaining a passage efficiency cost of the closest obstacle located in front of the vehicle and closest to the vehicle on the lane according to the motion information of the closest obstacle to the vehicle and the first information; Obtaining a traffic efficiency cost of each obstacle on the lane according to the motion information of each obstacle located in front of the vehicle and the first information; The traffic efficiency cost of the lane is obtained according to the maximum value of the traffic efficiency cost of the nearest obstacle and the traffic efficiency cost of each obstacle.

9. A vehicle control device, characterized in that: include: an acquisition module, configured to acquire the traffic efficiency cost of the own lane according to the traffic efficiency cost of the obstacle located in front of the own vehicle on the own lane, and acquire the traffic efficiency cost of the first adjacent lane according to the traffic efficiency cost of the obstacle located in front of the own vehicle on the first adjacent lane of the own lane; The traffic efficiency cost of the obstacle is obtained according to the movement information of the obstacle and the first information, the first information is used to indicate the predicted probability that the obstacle will be located in the current lane at a future moment, and the traffic efficiency cost is a parameter representing the degree of obstruction to the driving of the ego vehicle; a determination module, configured to determine whether a first triggering condition for the vehicle to change lanes to the first adjacent lane is met according to the traffic efficiency cost of the own lane and the traffic efficiency cost of the first adjacent lane; The control module is used to execute the operation of controlling the vehicle to change lanes when the first trigger condition is met.

10. An electronic device, characterized in that: The electronic device comprises at least one processor, the processor is coupled to a memory, the memory is used to store computer program instructions, and the processor is used to execute computer program instructions, wherein when the computer program instructions are executed by the processor, the electronic device is triggered to execute the method as described in any one of claims 1-8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed on a computer, enables the computer to execute the method according to any one of claims 1 to 8.

Images