Method and device for generating vehicle lane change instruction, and vehicle

Abstract

The application discloses a vehicle lane change instruction generation method and device and a vehicle, and relates to the technical field of intelligent driving. The method comprises the following steps: acquiring at least one lane passing efficiency of a target vehicle to be changed, and selecting a target lane according to the lane passing efficiency, wherein the lane passing efficiency is used to represent the expected passing smoothness of the target vehicle when driving in the lane to be changed; acquiring driving state information of the target vehicle under the condition that the vehicle collision time in the target lane matches the reference collision time; generating a lane change instruction of the target lane under the condition that the driving state information does not match the lane change inhibition strategy of the target lane, so as to trigger vehicle lane change driving planning based on the lane change instruction. The application can significantly improve the recognition accuracy of lane change intention, meet the stability and safety requirements of lane change instruction generation, and improve the accuracy of vehicle lane change instruction generation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent driving, in particular to a vehicle lane change instruction generation method and device and vehicle. BACKGROUND

[0002] With the rapid development of intelligent driving technology, the control of the vehicle driving process is becoming more and more refined. Among them, there is usually a vehicle lane change situation in the vehicle driving process, so as to meet different driving planning needs.

[0003] At present, the generation of the existing vehicle lane change instruction is usually based on machine learning algorithm for intelligent prediction, so as to determine the vehicle lane change instruction and then perform the vehicle lane change driving planning. However, the vehicle lane change instruction determined based on the machine learning algorithm will cause long-time driving with slow vehicles, and there are unreasonable lane changing situations, such as collision risk in the vehicle lane changing process, etc., which leads to instability of lane changing, greatly increases the safety risk of vehicle driving, and cannot meet the stability and safety requirements of vehicle lane change instruction generation, thereby reducing the accuracy of vehicle lane change instruction generation. SUMMARY

[0004] Therefore, the present application provides a vehicle lane change instruction generation method and device and vehicle, which mainly aims to solve the problem of poor accuracy of existing vehicle lane change instruction generation.

[0005] According to one aspect of the present application, a vehicle lane change instruction generation method is provided, comprising:

[0006] Obtaining at least one lane change lane traffic efficiency of a target vehicle, and selecting a target lane according to the lane traffic efficiency, the lane traffic efficiency being used to represent the expected traffic smoothness when the target vehicle drives into the lane to be changed;

[0007] Obtaining the driving state information of the target vehicle under the condition that the vehicle collision time in the target lane matches the reference collision time;

[0008] Generating a lane change instruction of the target lane under the condition that the driving state information and the lane change inhibition strategy of the target lane do not match, so as to trigger vehicle lane change driving planning based on the lane change instruction.

[0009] The embodiment of the application selects a target lane according to a lane traffic efficiency of at least one lane to be changed of a target vehicle, the lane traffic efficiency is used to represent an expected traffic smoothness when the target vehicle drives into the lane to be changed; obtains driving state information of the target vehicle under a condition that a collision time of a vehicle in the target lane matches a reference collision time; generates a lane change instruction of the target lane under a condition that the driving state information does not match a lane change inhibition strategy of the target lane, and triggers vehicle lane change driving planning based on the lane change instruction, so as to select the lane to be changed in a screening mode based on the lane traffic efficiency, greatly reduce the occurrence of unreasonable lane change, increase the stability of vehicle lane change, ensure the safety of vehicle lane change in the automatic driving process, meet the stability and safety requirements of the lane change instruction generation, and thus improve the accuracy of the vehicle lane change instruction generation.

[0010] Further, the lane traffic efficiency of at least one lane to be changed of the target vehicle includes:

[0011] At least one front obstacle in the lane to be changed corresponding to the target vehicle is determined within a first preset distance range, and a single-body traffic efficiency cost of the front obstacle is determined based on a front obstacle speed, the single-body traffic efficiency cost being used to represent a situation that the front obstacle is expected to block the target vehicle;

[0012] The lane traffic efficiency of the lane to be changed where the front obstacle is located is selected based on the single-body traffic efficiency cost.

[0013] Further, the single-body traffic efficiency cost of the front obstacle determined based on the front obstacle speed includes:

[0014] A speed difference value of the front obstacle speed and a preset speed is determined, and the single-body traffic efficiency cost of the front obstacle is calculated based on the speed difference value, an obstacle influence weight value and a unit speed difference cost parameter, the obstacle influence weight value being configured based on a steady-state following factor.

[0015] Further, after the lane traffic efficiency of the lane to be changed where the front obstacle is located is selected based on the single-body traffic efficiency cost, the method further includes:

[0016] The lane traffic efficiency is filtered according to a preset filtering time interval;

[0017] The target lane is selected according to the lane traffic efficiency includes:

[0018] The lane corresponding to the maximum value of the filtered lane traffic efficiency is determined as the target lane; or,

[0019] In a case where the difference between the filtered lane traffic efficiency and the efficiency of the lane where the target vehicle is located meets a preset difference threshold, a lane with the lane traffic efficiency meeting the preset difference threshold is determined as the target lane.

[0020] Further, before the obtaining of the driving state information of the target vehicle, the method further comprises:

[0021] determining at least one rear obstacle in the target lane with the target vehicle within a second preset distance range, and determining a vehicle collision time of the rear obstacle based on a preset following distance, a vehicle driving speed and a rear obstacle speed, to compare the vehicle collision time with the reference collision time;

[0022] The reference collision time is determined based on the steady-state following factor and the preset following distance.

[0023] Further, before the generating of the lane change instruction for the target lane, the method further comprises:

[0024] parsing an inhibition target in the lane change inhibition strategy, the inhibition target being used to represent an object blocking the target vehicle from performing lane change driving, the lane change inhibition strategy including at least one sub-rule blocking the target vehicle from performing lane change;

[0025] obtaining a driving parameter corresponding to the inhibition target in the driving state information, and matching the driving parameter with the lane change inhibition strategy to determine whether to generate the lane change instruction for the target lane.

[0026] Further, the method further comprises:

[0027] in a case where the lane change instruction includes a left lane change instruction and a right lane change instruction, the left lane change instruction is determined as the target lane change instruction; or,

[0028] in a case where the lane change instruction is a left lane change instruction or a right lane change instruction, the left lane change instruction or the right lane change instruction is determined as the target lane change instruction;

[0029] lane change driving planning of the vehicle is performed based on the target lane change instruction to obtain a vehicle lane change planning path;

[0030] in a case where the vehicle lane change of the target vehicle is completed based on the vehicle lane change driving planning path, a lane to be changed of the target vehicle is updated.

[0031] Further, the method further comprises:

[0032] determining that the target lane changing instruction generation fails under a condition that a vehicle collision time in the target lane does not match a reference collision time, or the driving state information matches a lane changing inhibition strategy of the target lane, and re-executing the step of acquiring the lane passing efficiency of at least one lane to be changed of the target vehicle under a condition that a preset cooling time interval is reached; or

[0033] re-executing the step of acquiring the lane passing efficiency of at least one lane to be changed of the target vehicle under a condition that the lane to be changed of the target vehicle is updated and a preset cooling time interval is reached.

[0034] According to another aspect of the present application, a vehicle lane changing instruction generation device is provided, comprising:

[0035] a first acquiring module configured to acquire a lane passing efficiency of at least one lane to be changed of a target vehicle, and select a target lane according to the lane passing efficiency, the lane passing efficiency being used to represent an expected passing situation of the target vehicle when driving in the lane to be changed;

[0036] a second acquiring module configured to acquire driving state information of the target vehicle under a condition that a vehicle collision time in the target lane matches a reference collision time;

[0037] a generating module configured to generate a lane changing instruction of the target lane under a condition that the driving state information does not match a lane changing inhibition strategy of the target lane, so as to trigger a vehicle lane changing driving plan based on the lane changing instruction.

[0038] Further, the first acquiring module comprises:

[0039] a determining unit configured to determine at least one front obstacle in the lane to be changed corresponding to the target vehicle within a first preset distance range, and determine a single-body passing efficiency cost of the front obstacle based on a front obstacle speed, the single-body passing efficiency cost being used to represent a situation that the front obstacle is expected to block the target vehicle;

[0040] a selecting unit configured to select a lane passing efficiency of the lane to be changed where the front obstacle is located based on the single-body passing efficiency cost.

[0041] Further, the determining unit is specifically configured to determine a speed difference value between the front obstacle speed and a preset speed, and calculate the single-body passing efficiency cost of the front obstacle based on the speed difference value, an obstacle influence weight value and a unit speed difference cost parameter, the obstacle influence weight value being configured based on a steady-state following factor.

[0042] Further, the first acquiring module further comprises:

[0043] a filtering unit configured to filter the lane traffic efficiency according to a preset filtering time interval;

[0044] The selection unit is specifically configured to determine a lane corresponding to a maximum value in the filtered lane traffic efficiency as a target lane; or, under a condition that a difference between the filtered lane traffic efficiency and an efficiency of a lane where the target vehicle is located matches a preset difference threshold, determine a lane corresponding to the lane traffic efficiency that matches the preset difference threshold as the target lane.

[0045] Further, the device further comprises:

[0046] The determination module is configured to determine at least one rear obstacle in the target lane with the target vehicle within a second preset distance range, and determine a vehicle collision time of the rear obstacle based on a preset following distance, a vehicle driving speed, and a rear obstacle speed, to compare the vehicle collision time with the reference collision time; wherein the reference collision time is determined based on the steady-state following factor and the preset following distance.

[0047] Further, the device further comprises:

[0048] The analysis module is configured to analyze an inhibition target in the lane change inhibition strategy, the inhibition target being used to represent an object that blocks the target vehicle from driving in a lane change, and the lane change inhibition strategy comprising at least one sub-rule that blocks the target vehicle from driving in a lane change;

[0049] The matching module is configured to obtain a driving parameter corresponding to the inhibition target in the driving state information, and match the driving parameter with the lane change inhibition strategy to determine whether to generate a lane change instruction for the target lane.

[0050] Further, the device further comprises: a planning module, an updating module,

[0051] The determination module is further configured to, under a condition that the lane change instruction comprises a left lane change instruction and a right lane change instruction, determine the left lane change instruction as a target lane change instruction; or, under a condition that the lane change instruction is a left lane change instruction or a right lane change instruction, determine the left lane change instruction or the right lane change instruction as the target lane change instruction.

[0052] The planning module is configured to perform vehicle lane change driving planning based on the target lane change instruction to obtain a vehicle lane change planning path.

[0053] The updating module is configured to update a lane to be changed of the target vehicle under a condition that the target vehicle completes vehicle lane change based on the vehicle lane change driving planning path.

[0054] Further, the determining module is further configured to determine that the target lane changing instruction generation fails under a condition that a collision time of a vehicle in the target lane does not match a reference collision time, or the driving state information matches a lane changing inhibition strategy of the target lane, and re-perform the step of acquiring the lane passing efficiency of at least one lane to be changed of the target vehicle under a condition that a preset cooling time interval is reached; or, re-perform the step of acquiring the lane passing efficiency of at least one lane to be changed of the target vehicle under a condition that the lane to be changed of the target vehicle is updated and a preset cooling time interval is reached.

[0055] According to an aspect of the present application, a vehicle is provided, which comprises the above-mentioned vehicle lane changing instruction generation apparatus.

[0056] According to another aspect of the present application, a readable storage medium is provided, which stores a program or instruction, and the program or instruction is executed by a processor to implement the steps of the above-mentioned vehicle lane changing instruction generation method.

[0057] According to still another aspect of the present application, a computer device is provided, which comprises at least one processor, the processor is coupled with a memory, and the memory stores a program or instruction which is run on the processor, and the program or instruction is executed by the processor to implement the steps of the above-mentioned vehicle lane changing instruction generation method.

[0058] The above description is only a summary of the technical solutions of the present application. In order to enable one of ordinary skill in the art to better understand the technical means of the present application and implement it according to the contents of the description, and in order to enable the above and other purposes, characteristics and advantages of the present application to be more apparent, the following specific embodiments of the present application are described in detail. BRIEF DESCRIPTION OF DRAWINGS

[0059] Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The accompanying drawings are included to provide a description of the preferred embodiments and are not meant to limit the present application. Furthermore, the same reference numerals are used throughout the several views that follow. In the drawings:

[0060] Figure 1 A flow chart of a vehicle lane changing instruction generation method provided by an embodiment of the present application is shown;

[0061] Figure 2 A flow chart of another vehicle lane changing instruction generation method provided by an embodiment of the present application is shown;

[0062] Figure 3 A schematic diagram of a target vehicle lane to be changed provided by an embodiment of the present application is shown;

[0063] Figure 4 Fig. 1 shows a flow chart of another method for generating a vehicle lane change instruction according to an embodiment of the present application;

[0064] Figure 5 Fig. 2 shows a block diagram of a device for generating a vehicle lane change instruction according to an embodiment of the present application;

[0065] Figure 6 Fig. 3 shows a structure of a terminal according to an embodiment of the present application. DETAILED DESCRIPTION

[0066] Exemplary embodiments of the present disclosure will be described herein below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art.

[0067] An embodiment of the present application provides a method for generating a vehicle lane change instruction, as shown in Fig. 1, the method comprises: Figure 1

[0068] 101, obtaining at least one lane passing efficiency of a target vehicle to be changed, and selecting a target lane according to the lane passing efficiency.

[0069] In an embodiment of the present application, during the trajectory planning process of an unmanned intelligent vehicle, the automatic driving processor as the current execution subject can be a processor configured at the vehicle end, or a cloud server matched with the vehicle, etc. At this time, the current execution subject can scan the road where the vehicle is located through an intelligent perception system, so as to determine whether to generate a vehicle lane change instruction. Specifically, the current execution subject can determine the vehicle passing efficiency of the target vehicle expected to change lanes in real time, and the lane passing efficiency is used to represent the expected passing smoothness when the target vehicle enters the lane to be changed. At this time, since the lane to be changed can be multiple, for example, the left lane of the target vehicle or the right lane of the target vehicle, the current execution subject can determine the lane passing efficiency by determining the expected blocking situation of each lane to be changed by obstacles, i.e., by determining the lane passing efficiency representing the expected blocking situation of the target vehicle in the lane by obstacles, so as to select the target vehicle according to the lane passing efficiency. In a specific implementation scenario, the current execution subject can select the lane corresponding to the maximum lane passing efficiency as the target lane, or select multiple target vehicles meeting the preset lane change condition, which is not limited in the present application. In addition, the obstacle in the present application can be other moving vehicles in the lane to be changed, or non-moving objects, such as obstacle avoidance signs, etc., which is not limited in the present application. ​

[0070] It should be noted that the vehicle is a vehicle with an automatic control system in an automatic driving scene, including passenger cars and commercial vehicles, common models of passenger cars include but are not limited to cars, sport utility vehicles, multi-person business cars, etc., common models of commercial vehicles include but are not limited to pick-up trucks, micro-vans, self-loading vehicles, trucks, tractors, trailers and mining vehicles, etc., at this time, the vehicle can realize automatic driving based on the automatic control system.

[0071] 102, obtain the driving state information of the target vehicle under the condition that the vehicle collision time in the target lane matches the reference collision time.

[0072] In the embodiment of the application, after the current execution subject selects the target lane, in order to avoid the vehicle from colliding with the obstacle after entering the target road to be changed, the vehicle collision time in the target lane is matched with the reference collision time in advance, which is used as a judgment basis for entering the target lane. The reference collision time is determined based on a steady-state following factor and a preset following distance. The steady-state following factor is used to represent the demand of the target vehicle to follow the preceding vehicle stably. The current execution subject configures it in advance according to the automatic driving following demand of the target vehicle, such as a steady-state following factor factor = 0.9. The preset following distance is used to represent the minimum distance of the target vehicle to follow the preceding vehicle stably. The current execution subject configures it in advance according to the automatic driving following demand of the target vehicle. The embodiment of the application does not make specific limitation. Further, in order to ensure that the target vehicle will not collide with other obstacles in the target lane after changing lanes, the reference collision time is directly determined based on the steady-state following factor and the preset following distance. For example, it can be directly configured by a person or calculated through a linear relationship. The embodiment of the application does not make specific limitation.

[0073] It should be noted that the vehicle collision time is the time when the target vehicle is expected to collide with other obstacles after changing to the target lane. It can be calculated by the speed of the target vehicle and the distance of the perceived obstacle. The embodiment of the application does not make specific limitation. At this time, the current execution subject obtains the driving state information of the target vehicle, which includes but is not limited to driving speed, driving scene information, lane changing function state, lane changing duration, automatic driving state, etc., so as to match the driving state information with the lane changing inhibition strategy. The driving state information can be scanned and obtained based on a perception system, obtained based on data recorded in the current execution subject, or obtained based on a vehicle navigation system. The embodiment of the application does not make specific limitation.

[0074] 103, generate a lane changing instruction of the target lane under the condition that the driving state information does not match the lane changing inhibition strategy of the target lane.

[0075] In the embodiment of the present application, the current execution subject is pre-configured with a lane change inhibition strategy of the target vehicle, so as to determine whether the lane change condition is met according to the driving state information of the target vehicle, so that the target vehicle generates a lane change instruction under the condition that the lane change condition is met, and triggers the vehicle lane change driving planning based on the lane change instruction. Wherein, the lane change inhibition strategy includes at least one sub-rule of blocking the target vehicle from changing lanes, for example, if the driving scene information in the driving state information is that the target vehicle is in a non-ramp, the sub-rule is that lane change is prohibited in the ramp, and it is indicated that the lane change inhibition strategy of the target vehicle and the target lane does not match, and the current execution subject generates the lane change instruction of the target lane, and the embodiment of the present application is not limited.

[0076] It should be noted that different lane change inhibition sub-strategies can be pre-configured in the current execution subject to meet the real-time changing lane change requirements, for example, the lane change inhibition strategy can include but is not limited to any one or more of the following sub-rules: lane change is prohibited when the overtaking lane change automatic driving function is not started, lane change is prohibited on non-highway, lane change is prohibited in a solid line lane, lane change is prohibited when there is a dangerous vehicle behind, lane change is prohibited when the lane change cooling time is less than the preset time, lane change is prohibited in a non-automatic driving state, lane change is prohibited in a ramp within a preset distance in front, lane change is prohibited when the target vehicle speed is less than the preset speed, lane change is prohibited when the curvature speed limit of the target vehicle is less than the preset speed, lane change is prohibited when there is a fixed obstacle in front of the target lane, etc. The embodiment of the present application is not limited. In addition, after the current execution subject generates the lane change instruction of the target lane, the driving route of the target vehicle changing lanes into the target lane can be planned based on the path planning of the automatic driving, so as to automatically drive into the target lane according to the planned path, and the embodiment of the present application is not limited.

[0077] In another embodiment of the present application, in order to further illustrate and limit, as shown in Figure 2 The step of obtaining at least one lane passing efficiency of the target vehicle to be changed lanes includes:

[0078] 201. Determine at least one front obstacle in the target vehicle corresponding to the lane to be changed within a first preset distance range, and determine the single-body passing efficiency cost of the front obstacle based on the front obstacle speed;

[0079] 202. Select the lane passing efficiency of the lane to be changed where the front obstacle is located based on the single-body passing efficiency cost.

[0080] In order to accurately select a target lane based on vehicle passing efficiency, when obtaining the lane passing efficiency of the lane to be changed, specifically, the single passing efficiency cost of each vehicle in the lane to be changed as an obstacle is first calculated to accurately calculate the lane passing efficiency of each lane to be changed. Wherein, the single passing efficiency cost of each vehicle in the lane to be changed is used to represent the situation that the front obstacle is expected to block the target vehicle. At this time, the front obstacle can be a front obstacle vehicle or a front roadblock in the lane to be changed, and the embodiments of the present application do not make specific limitations. The first preset distance range is determined by the intelligent sensing system according to the first preset distance range, and the front obstacle is determined, such as scanning to find that there are two front vehicles in the lane to be changed, and the embodiments of the present application do not make specific limitations, so as to determine the single passing efficiency cost based on the front obstacle speed of the front obstacle.

[0081] It should be noted that, since there can be multiple front obstacles in a lane to be changed, in order to make the target vehicle change lanes in the safest way, the single passing efficiency cost of each front obstacle is selected, and in a specific implementation scenario, the maximum value of the multiple single passing efficiency cost is directly determined as the lane passing efficiency cost cost of the lane to be changed, i.e. the single passing efficiency cost of the slowest vehicle in a lane, i.e. the single passing efficiency cost of the slowest vehicle in a lane, is used as the lane passing efficiency cost of the lane, and further, the single passing efficiency cost and the lane passing efficiency are negatively correlated, i.e. the greater the single passing efficiency cost of the front obstacle, the more serious the situation that the target vehicle is expected to be blocked, resulting in lower lane passing efficiency of the lane. In an optional embodiment of the present application, the single with the maximum passing efficiency cost in the lane is selected as a reference to determine the lane passing efficiency of the lane. Specifically, in an embodiment, the lane passing efficiency = 1 / single passing efficiency cost. For example, as shown in Figure 3 There are three front obstacles in the lane to be changed 1, and the corresponding single passing efficiency cost cost is 2.3, 3.5 and 2.5, respectively, so 3.5 is directly selected as the lane passing efficiency cost of the lane to be changed 1, so that the lane passing efficiency can be determined based on the inverse proportional relationship between the lane passing efficiency cost and the lane passing efficiency, and the embodiments of the present application do not make specific limitations.

[0082] In another embodiment of the present application, in order to further illustrate and limit, the step of determining the single passing efficiency cost of the front obstacle based on the front obstacle speed includes:

[0083] determining a speed difference value of the front obstacle speed and a preset speed, and calculating a single-body passing efficiency cost of the front obstacle based on the speed difference value, an obstacle influence weight value and a unit speed difference cost parameter.

[0084] In order to achieve the purpose of determining the lane passing efficiency based on the single-body passing efficiency cost, thereby improving the safety of lane changing, and accurately generating a lane changing instruction, when determining the single-body passing efficiency cost based on the obstacle speed, specifically, first, a speed difference value of the obstacle speed and a preset speed is determined. The obstacle speed can be obtained by scanning through a perception system, and the preset speed is a speed threshold configured according to the lane changing requirement, such as 5 m / s. When determining the speed difference value, it can be determined based on comparison with a static state, such as speed difference value = max(v_set-object_v, 0.0), wherein v_set is the preset speed and object_v is the obstacle speed. Then, the single-body passing efficiency cost is calculated based on the speed difference value, the obstacle influence weight value and the unit speed difference cost parameter, and the specific calculation method is: single-body passing efficiency cost = speed difference value × unit speed difference cost parameter × obstacle influence weight value, wherein the obstacle influence weight value is configured based on a steady-state following factor, and the configuration range is preferably [0.0, 0.1], and the unit speed difference cost parameter is the adjustable situation within a unit speed, and is preferably 3.5, which is not limited in the embodiment of the present application.

[0085] It should be noted that the perception system in the embodiment of the present application is a system with the function of image scanning in time frame units, so as to determine the speed, position and other information of the vehicle according to the vehicle position in each frame of image, and also can determine the environmental information and other contents of the vehicle based on the identification of each frame of image data, which is not limited in the embodiment of the present application.

[0086] In another embodiment of the present application, in order to further illustrate and limit, after the step of selecting the lane passing efficiency of the lane where the front obstacle is located based on the single-body passing efficiency cost, the method further comprises:

[0087] filtering the lane passing efficiency according to a preset filtering time interval;

[0088] the selecting the target lane according to the lane passing efficiency comprises:

[0089] determining the lane corresponding to the maximum value of the filtered lane passing efficiency as the target lane; or,

[0090] under the condition that the efficiency difference between the filtered lane passing efficiency and the efficiency of the lane where the target vehicle is located matches a preset difference threshold, determining the lane corresponding to the lane passing efficiency matching the preset difference threshold as the target lane.

[0091] In order to ensure stability in determining the lane traffic efficiency based on the single-vehicle traffic efficiency cost, after determining the lane traffic efficiency, the vehicle traffic efficiency needs to be filtered. The preset filtering time can be configured based on the scanning time of the perception system, for example, the preset filtering time interval can be 2 seconds, and the like, which is not limited in the embodiments of the present application. At this time, since the speed and the like information needs to be obtained by the perception system at the scanning time point when calculating the single-vehicle traffic efficiency cost, and the speed is not uniform during vehicle driving, filtering the lane traffic efficiency according to the preset filtering time interval is to filter the lane traffic efficiency calculated from all time points according to the preset filtering time interval, obtain the lane traffic efficiency corresponding to the preset filtering time interval, and then perform overfitting based on the smooth curve mode at other time points, so that the final vehicle traffic efficiency calculated by the speed obtained at each scanning time is balanced, so as to reduce the excessively high or low vehicle traffic efficiency, and ensure the stability of the final calculation result of the lane traffic efficiency.

[0092] In one specific scenario in the embodiments of the present application, after filtering the lane traffic efficiency, the target lane is selected based on the filtered lane traffic efficiency. Specifically, the lane corresponding to the maximum value of the plurality of lane traffic efficiencies can be directly selected as the target lane of the target vehicle. In another specific scenario in the embodiments of the present application, after filtering the lane traffic efficiency, the target lane is selected based on the filtered lane traffic efficiency. Specifically, when the single-vehicle traffic efficiency cost of each vehicle is calculated by the current execution subject, the single-vehicle traffic efficiency cost of the target vehicle is also calculated by the same method as the single-vehicle traffic efficiency cost of the target vehicle in the lane of the ego vehicle. When the lane traffic efficiency is determined, the single-vehicle traffic efficiency cost of the lane of the ego vehicle is calculated by the ratio of each lane traffic efficiency, and the efficiency difference is obtained, so as to be compared with the preset difference threshold. At this time, the preset difference threshold is pre-configured, so that when the efficiency difference matches the preset difference threshold, the lane with the lane traffic efficiency matching the preset difference threshold is determined as the target lane.

[0093] In another embodiment of the present application, in order to further illustrate and limit, before the step of obtaining the driving state information of the target vehicle, the method further comprises:

[0094] At least one rear obstacle in the target lane with the target vehicle is determined within the second preset distance range, and the vehicle collision time of the rear obstacle is determined based on the preset following distance, the vehicle driving speed and the speed of the rear obstacle, so as to compare the vehicle collision time with the reference collision time.

[0095] In order to ensure the safety of the target vehicle in the expected lane changing process, and avoid vehicle collision caused by lane changing, before obtaining the driving state information of the target vehicle, it is necessary to determine the rear obstacle generated by the target vehicle in the target lane, so as to judge whether the collision between the target vehicle and the rear obstacle occurs. Among them, the second preset distance range can be the same as the first preset distance range, or different, and based on the perception system, the rear obstacle of the target vehicle in the second preset distance range is scanned to obtain at least one rear obstacle. At this time, the rear obstacle is usually a rear vehicle, such as Figure 3 As shown in the figure, the right lane is the target lane, and the vehicle collision time based on the rear obstacle is compared with the reference collision time, which is not limited in the embodiment of the application. After determining the rear obstacle, the rear obstacle speed of the rear obstacle is obtained by scanning the perception system, so as to calculate the vehicle collision time in combination with the preset following distance and the vehicle driving speed. Specifically, the vehicle collision time ttc=distance / (v_set-object_v), wherein distance is the preset following distance, v_set is the vehicle driving speed, and object_v is the rear obstacle speed. At this time, since the target vehicle is in automatic driving mode, the vehicle driving speed can be a preset speed, which is not limited in the embodiment of the application.

[0096] It should be noted that the reference collision time TTC in the embodiment of the application is determined based on the steady following factor and the preset following distance, that is, the steady following factor is used to represent the demand of the target vehicle to follow the front vehicle stably, and the current executor is configured in advance according to the automatic driving following demand of the target vehicle, such as the steady following factor factor=0.9, and the preset following distance is used to represent the minimum distance of the target vehicle to follow the front vehicle stably, and the current executor is configured in advance according to the automatic driving following demand of the target vehicle, which is not limited in the embodiment of the application. In the high-speed scene, the reference collision time TTC can be associated only based on the steady following factor factor, that is, when the steady following factor is adjusted, the reference collision time TTC is also adjusted. In addition, in the embodiment of the application, since the obstacle influence weight value is configured based on the steady following factor, when the steady following factor factor is adjusted, the obstacle influence weight value is also associated and adjusted, so as to improve the calculation of the single body passing efficiency cost of the front obstacle, affect the lane passing efficiency of the target lane, and improve the effectiveness of the intention judgment of triggering lane changing, so as to realize the judgment of lane changing in different scenes by adjusting the steady following factor.

[0097] In another embodiment of the application, in order to further illustrate and limit, as shown in Figure 4 Before the step of generating the lane changing instruction of the target lane, the method further comprises:

[0098] 301、analyzing the inhibition target in the lane-changing inhibition strategy;

[0099] 302、obtaining a driving parameter corresponding to the inhibition target in the driving state information, and matching the driving parameter with the lane-changing inhibition strategy to determine whether to generate a lane-changing instruction of the target lane.

[0100] To improve the accuracy of lane-changing instruction generation, before generating a lane-changing instruction of the target lane, the current execution subject analyzes the inhibition target in the lane-changing inhibition strategy to match the driving parameter in the driving state information based on the inhibition target. Since the lane-changing inhibition strategy includes at least one sub-rule that blocks the target vehicle from lane-changing, when the driving state information is matched with the lane-changing inhibition strategy, the inhibition target is determined, which is used to represent the object that blocks the target vehicle from lane-changing. For example, if the sub-rule is that the target vehicle speed is lower than the preset vehicle speed to prohibit lane-changing, the inhibition target to be analyzed is the target vehicle speed. In the embodiment of the present application, since the lane-changing inhibition strategy can be stored in the form of text content or compiled based on the code form, when the inhibition target is analyzed, it can be analyzed and recognized based on natural language technology, or it can be analyzed and recognized based on code identification and other compilation methods, which are not limited in the embodiment of the present application. When the inhibition target is analyzed, the driving parameter in the driving state information is obtained according to the inhibition target, and the corresponding sub-rule in the lane-changing inhibition strategy is matched according to the driving parameter. For example, the sub-rule in the lane-changing inhibition strategy is that the overtake lane-changing automatic driving function is not started to prohibit lane-changing, and the inhibition target is the overtake lane-changing function. The current execution subject obtains the lane-changing function state information corresponding to the overtake lane-changing function in the driving state information as the driving parameter, so as to determine whether the lane-changing function state information is in the starting state. If it is started, the lane-changing instruction can be generated, and if it is not started, the lane-changing instruction is not generated.

[0101] It should be noted that after the current execution subject matches the driving parameter with the lane-changing inhibition strategy, if the lane-changing instruction is generated, the lane-changing inhibition strategy is no longer further determined according to the real-time driving state information of the vehicle, and the target vehicle only needs to complete the lane-changing according to the lane-changing instruction.

[0102] In another embodiment of the present application, to further illustrate and limit, the step further comprises:

[0103] Under the condition that the lane-changing instruction includes a left lane-changing instruction and a right lane-changing instruction, the left lane-changing instruction is determined as the target lane-changing instruction; or,

[0104] Under the condition that the lane-changing instruction is a left lane-changing instruction or a right lane-changing instruction, the left lane-changing instruction or the right lane-changing instruction is determined as the target lane-changing instruction.

[0105] planning a vehicle lane-changing travel based on the target lane-changing instruction to obtain a vehicle lane-changing planning path;

[0106] updating the target vehicle's to-be-changed lane when the target vehicle's vehicle lane-changing condition is met based on the vehicle lane-changing planning path.

[0107] To achieve the lane-changing execution purpose of the target vehicle based on the lane-changing instruction, since the target lane can be the left lane of the target vehicle or the right lane of the target vehicle, that is, the lane-changing instruction includes the left lane-changing instruction and / or the right lane-changing instruction, further judgment is needed. Specifically, when the multiple target lanes do not match the lane-changing inhibition strategy, and the multiple target lanes include the left lane and the right lane, the generated lane-changing instruction includes the left lane-changing instruction and the right lane-changing instruction. At this time, in order to select the optimal and most suitable target lane and improve the lane-changing safety, the left lane-changing instruction is directly selected as the target lane-changing instruction to control the vehicle to plan travel based on the left lane-changing instruction. When one target lane does not match the lane-changing inhibition strategy, and this target lane is the left lane or the right lane, the left lane-changing instruction or the right lane-changing instruction is directly determined as the target lane-changing instruction.

[0108] It should be noted that after the target lane-changing instruction is determined, the current execution subject needs to plan a vehicle lane-changing travel according to the target lane-changing instruction, that is, plan a path from the current lane of the target vehicle to the target lane to obtain a vehicle lane-changing planning path, in order to control the target vehicle according to the target lane-changing instruction to complete the lane-changing. At this time, the path planning can be performed based on the preset lane speed, lane width, and speed and distance between the front obstacle and the rear obstacle of the target lane through a planning model (such as a path planning decision algorithm), to obtain the vehicle lane-changing planning path, which is not limited in the embodiment of the present application. After the vehicle lane-changing planning path is obtained, the current execution subject controls the target vehicle to travel according to the vehicle lane-changing planning path to enter the target lane until the lane-changing is completed. When the target vehicle completes the lane-changing of the target lane, the target lane where the target vehicle is located has become the ego lane of the target vehicle, and therefore the lane information of the target vehicle can be updated, that is, the to-be-changed lane of the target vehicle is updated, so as to perform the lane-changing next time.

[0109] In another embodiment of the present application, for further illustration and limitation, the step further includes:

[0110] determining that the target lane change instruction generation fails under a condition that a vehicle collision time in the target lane does not match a reference collision time or the driving state information matches a lane change inhibition strategy of the target lane, and re-executing the step of acquiring the lane traffic efficiency of at least one lane to be changed of the target vehicle under a condition that a preset cooling time interval is reached; or

[0111] re-executing the step of acquiring the lane traffic efficiency of at least one lane to be changed of the target vehicle under a condition that the target lane to be changed of the target vehicle is updated and a preset cooling time interval is reached.

[0112] To meet the safety and effectiveness requirements of vehicle lane changing, in one specific scenario in the embodiment, when the vehicle collision time in the target lane does not match the reference collision time or the driving state information matches the lane change inhibition strategy, it indicates that the target vehicle is not suitable for lane changing at this time. Therefore, the current execution subject determines that the target lane change instruction generation fails, starts cooling time calculation, and re-executes the step of acquiring the lane traffic efficiency of the target vehicle and the subsequent steps after the preset cooling time is reached to perform the next lane change instruction generation judgment. In another specific scenario in the embodiment, the current execution subject updates the target lane to be changed of the target vehicle, and reaches the preset cooling time interval. It indicates that the target vehicle reaches the preset cooling time interval after changing to the target lane, and the next lane change instruction generation judgment can be performed. Therefore, the current execution subject executes the step of acquiring the lane traffic efficiency of at least one lane to be changed of the target vehicle to enter the next lane change instruction generation judgment. The preset cooling time can be 2 seconds, 5 seconds, etc., which is configured according to the lane change requirement, and the embodiment is not limited in particular.

[0113] The embodiment provides a vehicle lane change instruction generation method. Compared with the prior art, the embodiment acquires the lane traffic efficiency of at least one lane to be changed of a target vehicle, and selects a target lane according to the lane traffic efficiency. The lane traffic efficiency is used to represent an expected traffic smoothness when the target vehicle drives in the lane to be changed. Under a condition that a vehicle collision time in the target lane matches a reference collision time, driving state information of the target vehicle is acquired. Under a condition that the driving state information does not match a lane change inhibition strategy of the target lane, a lane change instruction of the target lane is generated to trigger vehicle lane change driving planning based on the lane change instruction. The lane to be changed is selected in a screening mode based on the lane traffic efficiency, the occurrence of unreasonable lane changing is greatly reduced, the stability of vehicle lane changing is increased, the safety of vehicle lane changing in the automatic driving process is ensured, the stability and safety requirements of the lane change instruction generation are met, and therefore the accuracy of the vehicle lane change instruction generation is improved.

[0114] Further, as to the aboveFigure 1 To achieve the method, the embodiment of the present application provides a vehicle lane change instruction generation device. Figure 5 The device comprises:

[0115] A first acquisition module 41 is configured to acquire lane traffic efficiency of at least one lane to be changed of a target vehicle, and select a target lane according to the lane traffic efficiency, wherein the lane traffic efficiency is used to represent expected traffic conditions when the target vehicle drives into the lane to be changed.

[0116] A second acquisition module 42 is configured to acquire driving state information of the target vehicle under a condition that a vehicle collision time in the target lane matches a reference collision time.

[0117] A generation module 43 is configured to generate a lane change instruction of the target lane under a condition that the driving state information does not match a lane change inhibition strategy of the target lane, so as to trigger vehicle lane change driving planning based on the lane change instruction.

[0118] Further, the first acquisition module comprises:

[0119] A determination unit is configured to determine at least one front obstacle in the lane to be changed corresponding to the target vehicle within a first preset distance range, and determine a single-body traffic efficiency cost of the front obstacle based on a front obstacle speed, wherein the single-body traffic efficiency cost is used to represent a situation that the front obstacle is expected to block the target vehicle.

[0120] A selection unit is configured to select lane traffic efficiency of the lane to be changed where the front obstacle is located based on the single-body traffic efficiency cost.

[0121] Further, the determination unit is specifically configured to determine a speed difference value between the front obstacle speed and a preset speed, and calculate the single-body traffic efficiency cost of the front obstacle based on the speed difference value, an obstacle influence weight value and a unit speed difference cost parameter, wherein the obstacle influence weight value is configured based on a steady-state following factor.

[0122] Further, the first acquisition module further comprises:

[0123] A filtering unit is configured to filter the lane traffic efficiency according to a preset filtering time interval.

[0124] The selection unit is specifically configured to determine a lane corresponding to a maximum value of the filtered lane traffic efficiency as the target lane, or, under a condition that an efficiency difference between the filtered lane traffic efficiency and a self lane where the target vehicle is located matches a preset difference threshold, determine a lane corresponding to the lane traffic efficiency matching the preset difference threshold as the target lane.

[0125] Further, the device further comprises:

[0126] The determination module is configured to determine at least one rear obstacle in the target lane with the target vehicle within a second preset distance range, and determine a vehicle collision time of the rear obstacle based on a preset following distance, a vehicle driving speed and a rear obstacle speed, so as to compare the vehicle collision time with the reference collision time; wherein the reference collision time is determined based on the steady-state following factor and the preset following distance.

[0127] Further, the device further comprises:

[0128] The analysis module is configured to analyze an inhibition target in the lane-changing inhibition strategy, the inhibition target being used to represent an object blocking the target vehicle from performing lane-changing driving, and the lane-changing inhibition strategy comprising at least one sub-rule blocking the target vehicle from performing lane-changing.

[0129] The matching module is configured to acquire a driving parameter corresponding to the inhibition target in the driving state information, and match the driving parameter with the lane-changing inhibition strategy, so as to determine whether to generate a lane-changing instruction of the target lane.

[0130] Further, the device further comprises: a planning module, an updating module,

[0131] The determination module is further configured to, in a condition that the lane-changing instruction comprises a left lane-changing instruction and a right lane-changing instruction, determine the left lane-changing instruction as a target lane-changing instruction; or, in a condition that the lane-changing instruction is a left lane-changing instruction or a right lane-changing instruction, determine the left lane-changing instruction or the right lane-changing instruction as the target lane-changing instruction.

[0132] The planning module is configured to perform vehicle lane-changing driving planning based on the target lane-changing instruction, to obtain a vehicle lane-changing planning path.

[0133] The updating module is configured to, in a condition that vehicle lane-changing of the target vehicle is completed based on the vehicle lane-changing driving planning path, update a to-be-changed lane of the target vehicle.

[0134] Further, the determining module is further configured to determine that the target lane change instruction generation fails under a condition that a vehicle collision time in the target lane does not match a reference collision time, or the driving state information matches a lane change inhibition strategy of the target lane, and re-perform the step of acquiring the lane traffic efficiency of at least one lane to be changed of the target vehicle under a condition that a preset cooling time interval is reached; or, re-perform the step of acquiring the lane traffic efficiency of at least one lane to be changed of the target vehicle under a condition that the lane to be changed of the target vehicle is updated and a preset cooling time interval is reached.

[0135] The embodiment of the present application provides a vehicle lane change instruction generation device, compared with the prior art, the embodiment of the present application acquires the lane traffic efficiency of at least one lane to be changed of a target vehicle, and selects a target lane according to the lane traffic efficiency, the lane traffic efficiency is used for representing an expected traffic smoothness when the target vehicle drives into the lane to be changed; acquires driving state information of the target vehicle under a condition that a vehicle collision time in the target lane matches a reference collision time; generates a lane change instruction of the target lane under a condition that the driving state information does not match a lane change inhibition strategy of the target lane, so as to trigger a vehicle lane change driving plan based on the lane change instruction, realize a selection of the lane to be changed based on the lane traffic efficiency screening mode, greatly reduce the occurrence of unreasonable lane change, increase the stability of vehicle lane change, ensure the safety of vehicle lane change in the automatic driving process, meet the stability and safety requirements of the lane change instruction generation, and thus improve the accuracy of the vehicle lane change instruction generation.

[0136] According to an embodiment of the present application, a vehicle is provided, which comprises the above-mentioned vehicle lane change instruction generation device.

[0137] According to an embodiment of the present application, a readable storage medium is provided, the readable storage medium has a program or instruction stored thereon, and the program or instruction is executed by a processor to realize the steps of the above-mentioned vehicle lane change instruction generation method.

[0138] Figure 6 A structural schematic diagram of a computer device according to an embodiment of the present application is shown, which comprises at least one processor, the processor and a memory are coupled, the memory stores a program or instruction running on the processor, and the program or instruction is executed by the processor to realize the steps of the above-mentioned vehicle lane change instruction generation method. The embodiment of the present application does not limit the specific implementation of the computer device.

[0139] As Figure 6As shown, the computer device can include a processor 502, a communications interface 504, a memory 506, and a communications bus 508.

[0140] The processor 502, the communications interface 504, and the memory 506 can communicate with each other through the communications bus 508.

[0141] The communications interface 504 is configured to communicate with network elements such as clients or other servers.

[0142] The processor 502 is configured to execute the program 510, and in particular, can execute the related steps in the above-described method for generating a vehicle lane change instruction.

[0143] In particular, the program 510 can include program code including computer operation instructions.

[0144] The processor 502 can be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present application. The one or more processors included in the terminal can be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0145] The memory 506 is configured to store the program 510. The memory 506 can include a high-speed RAM memory, and can also include a non-volatile memory such as at least one disk memory.

[0146] The program 510 can be specifically configured to cause the processor 502 to perform the following operations:

[0147] Obtain at least one lane passage efficiency of a target vehicle to be changed to a target lane, and select the target lane according to the lane passage efficiency, the lane passage efficiency being used to represent an expected passage smoothness of the target vehicle when driving in the target lane;

[0148] Obtain driving state information of the target vehicle under a condition that a collision time of a vehicle in the target lane matches a reference collision time;

[0149] Generate a lane change instruction of the target lane under a condition that the driving state information does not match a lane change suppression strategy of the target lane, and trigger a vehicle lane change driving plan based on the lane change instruction.

[0150] It should be apparent to those skilled in the art that the modules or steps of the application described above can be implemented with general computing devices, which can be centralized on a single computing device or distributed over a network of multiple computing devices, and optionally implemented with program code executable by a computing device, which can be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described can be performed in a different order than shown, or made into individual integrated circuit modules, or multiple modules or steps made into a single integrated circuit module. Thus, the application is not limited to any particular combination of hardware and software.

[0151] The preferred embodiments of the application described above are intended to be merely illustrative, and not limiting. Having now described a few embodiments of the application, various modifications and changes in the implementations thereof will occur to those skilled in the art to which the present application pertains. It is intended that the application be construed as including all such modifications and changes as fall within the spirit and scope of the application.

Claims

1. A method of generating a vehicle lane change instruction, characterized by, The method comprises: obtaining lane traffic efficiency of at least one lane to be changed of a target vehicle, and selecting a target lane according to the lane traffic efficiency, the lane traffic efficiency being used to represent expected traffic conditions when the target vehicle drives into the lane to be changed; obtaining driving state information of the target vehicle under a condition that vehicle collision time in the target lane matches a reference collision time; generating a lane change instruction of the target lane under a condition that the driving state information does not match a lane change inhibition strategy of the target lane, so as to trigger vehicle lane change driving planning based on the lane change instruction; wherein the obtaining of the lane traffic efficiency of the at least one lane to be changed of the target vehicle comprises: determining at least one front obstacle in the lane to be changed corresponding to the target vehicle within a first preset distance range, and determining a single obstacle traffic efficiency cost of the front obstacle based on a front obstacle speed, the single obstacle traffic efficiency cost being used to represent a situation that the front obstacle is expected to block the target vehicle; selecting lane traffic efficiency of the lane to be changed where the front obstacle is located based on the single obstacle traffic efficiency cost.

2. The method of claim 1, wherein, The determination of the single obstacle traffic efficiency cost of the front obstacle based on the front obstacle speed comprises: determining a speed difference value between the front obstacle speed and a preset speed, and calculating the single obstacle traffic efficiency cost of the front obstacle based on the speed difference value, an obstacle influence weight value and a unit speed difference cost parameter, the obstacle influence weight value being configured based on a steady-state following factor.

3. The method of claim 1, wherein, After the selection of the lane traffic efficiency of the lane to be changed where the front obstacle is located based on the single obstacle traffic efficiency cost, the method further comprises: filtering the lane traffic efficiency according to a preset filtering time interval; the selection of the target lane according to the lane traffic efficiency comprises: determining a lane corresponding to a maximum value in the filtered lane traffic efficiency as the target lane; or under a condition that a difference between the filtered lane traffic efficiency and lane traffic efficiency of a lane where the target vehicle is located matches a preset difference threshold, determining a lane corresponding to the lane traffic efficiency matching the preset difference threshold as the target lane.

4. The method of claim 2, wherein, Before the obtaining of the driving state information of the target vehicle, the method further comprises: determining at least one rear obstacle in the target lane corresponding to the target vehicle within a second preset distance range, and determining vehicle collision time of the rear obstacle based on a preset following distance, a vehicle driving speed and a rear obstacle speed, so as to compare the vehicle collision time with the reference collision time; wherein the reference collision time is determined based on the steady-state following factor and the preset following distance.

5. The method of claim 1, wherein, Before the generation of the lane change instruction of the target lane, the method further comprises: analyzing an inhibition target in the lane change inhibition strategy, the inhibition target being used to represent an object blocking the target vehicle from changing lanes, the lane change inhibition strategy comprising at least one sub-rule blocking the target vehicle from changing lanes; The driving parameter corresponding to the inhibition target in the driving state information is acquired, and the driving parameter is matched with the lane change inhibition strategy to determine whether to generate the lane change instruction of the target lane.

6. The method of claim 1, wherein, The method further comprises: In the case that the lane change instruction comprises a left lane change instruction and a right lane change instruction, the left lane change instruction is determined as a target lane change instruction; or, In the case that the lane change instruction is a left lane change instruction or a right lane change instruction, the left lane change instruction or the right lane change instruction is determined as a target lane change instruction; Vehicle lane change driving planning is performed based on the target lane change instruction to obtain a vehicle lane change planning path; In the case that vehicle lane change of the target vehicle is completed based on the vehicle lane change driving planning path, the lane to be changed of the target vehicle is updated.

7. The method according to any one of claims 1 to 6, characterized in that, The method further comprises: In the case that the vehicle collision time in the target lane does not match the reference collision time, or the driving state information matches the lane change inhibition strategy of the target lane, it is determined that the generation of the target lane change instruction fails, and the step of acquiring the lane passing efficiency of at least one lane to be changed of the target vehicle is re-executed when a preset cooling time interval is reached; or, In the case that the lane to be changed of the target vehicle is updated and a preset cooling time interval is reached, the step of acquiring the lane passing efficiency of at least one lane to be changed of the target vehicle is re-executed.

8. A device for generating a lane change instruction for a vehicle, characterized in that Comprise: The first acquisition module is configured to acquire the lane passing efficiency of at least one lane to be changed of a target vehicle, and select a target lane according to the lane passing efficiency, wherein the lane passing efficiency is used to represent an expected passing condition of the target vehicle when driving into the lane to be changed; The second acquisition module is configured to acquire driving state information of the target vehicle in the case that the vehicle collision time in the target lane matches the reference collision time; The generation module is configured to generate a lane change instruction of the target lane in the case that the driving state information does not match the lane change inhibition strategy of the target lane, so as to trigger vehicle lane change driving planning based on the lane change instruction. The first acquisition module comprises: The determination unit is configured to determine at least one front obstacle in the lane to be changed corresponding to the target vehicle within a first preset distance range, and determine a single passing efficiency cost of the front obstacle based on a front obstacle speed, wherein the single passing efficiency cost is used to represent an expected situation in which the front obstacle blocks the target vehicle; The selection unit is configured to select the lane passing efficiency of the lane to be changed in which the front obstacle is located based on the single passing efficiency cost.

9. A vehicle characterized by comprising: The vehicle lane change instruction generation device of claim 8 is comprised.

10. A computer device, comprising: The program or instruction is executed by the processor to implement the steps of the vehicle lane change instruction generation method of any one of claims 1 to 7.

11. A readable storage medium, on which a program or instructions are stored, characterized in that, The program or instruction is executed by the processor to implement the steps of the vehicle lane change instruction generation method of any one of claims 1 to 7.

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