CN115798261A

CN115798261A - Vehicle obstacle avoidance control method, device and equipment

Info

Publication number: CN115798261A
Application number: CN202211468115.4A
Authority: CN
Inventors: 蔡礼松; 李文洋; 蔡庆佳; 张硕; 钱永强
Original assignee: Shanghai Mooe Robot Technology Co ltd
Current assignee: Shanghai Mooe Robot Technology Co ltd
Priority date: 2022-11-22
Filing date: 2022-11-22
Publication date: 2023-03-14
Anticipated expiration: 2042-11-22
Also published as: CN115798261B

Abstract

The invention discloses a vehicle obstacle avoidance control method, device and equipment. The method comprises the following steps: carrying out region division on a driving lane with a preset length in front of a target vehicle; determining an obstacle influence range on the driving lane according to the obstacle information on the driving lane; determining filling values of all the areas according to the coverage information of the influence range of the obstacles in all the areas on the driving lane; determining the road passing efficiency of the driving lane according to the filling value and the road passing influence parameter of each region; and determining an obstacle avoidance control decision of the target vehicle according to the road passing efficiency of the driving lane. According to the technical scheme, the obstacle information is analyzed to determine the obstacle influence range on the driving lane so as to determine the filling value of each area under the influence of the obstacles, the filling value and the road traffic influence parameters are conveniently analyzed to determine the traffic efficiency of the lane, and finally the efficiency of avoiding obstacles by vehicles is improved according to the traffic efficiency.

Description

Vehicle obstacle avoidance control method, device and equipment

Technical Field

The invention relates to the technical field of intelligent vehicle control, in particular to a vehicle obstacle avoidance control method, device and equipment.

Background

The automatic driving vehicle is an intelligent vehicle which automatically plans a driving route and controls the vehicle to reach a preset destination after sensing the road environment through a vehicle-mounted sensing system. In the running process of a vehicle, when obstacles appear on a running road or the running speed of a front vehicle is low due to failure or the like, which influences the normal running of the vehicle, the unmanned vehicle needs to obtain the information of the self vehicle and the information of the external environment through a vehicle-mounted device, and completes the lane changing action under the double constraints of safety and efficiency. If the lane change is not proper, the traffic efficiency of road traffic is affected, and a collision accident may occur.

In the prior art, the problem that control decisions of a vehicle when the vehicle encounters an obstacle are inaccurate exists, for example, factors such as screening of the obstacle and the passable probability of a road are not analyzed, so that the control decisions of the vehicle when the vehicle encounters the obstacle are greatly influenced. Therefore, when an obstacle exists on the road, it is important how to accurately and efficiently control the vehicle so that the vehicle can effectively avoid the obstacle.

Disclosure of Invention

The invention provides a vehicle obstacle avoidance control method, device and equipment, and aims to solve the problem that a road obstacle influences safe running of a vehicle.

According to an aspect of the present invention, there is provided a vehicle obstacle avoidance control method, including:

carrying out region division on a driving lane with a preset length in front of a target vehicle; wherein the driving lanes comprise a candidate driving lane and a current driving lane, and the driving direction of the candidate driving lane is the same as that of the current driving lane;

determining an obstacle influence range on the driving lane according to the obstacle information on the driving lane;

determining filling values of all areas according to the coverage information of the obstacle influence range in all areas on the driving lane;

determining the road passing efficiency of the driving lane according to the filling values of the areas and the road passing influence parameters;

and determining an obstacle avoidance control decision of the target vehicle according to the road passing efficiency of the driving lane.

According to another aspect of the present invention, there is provided a vehicle obstacle avoidance control apparatus, the apparatus including:

the region division module is used for carrying out region division on a driving lane with a preset length in front of the target vehicle; wherein the driving lanes comprise a candidate driving lane and a current driving lane, and the driving direction of the candidate driving lane is the same as that of the current driving lane;

the range determining module is used for determining the influence range of the obstacles on the driving lane according to the information of the obstacles on the driving lane;

the filling value determining module is used for determining the filling value of each area according to the coverage information of the obstacle influence range in each area on the driving lane;

the efficiency determination module is used for determining the road traffic efficiency of the driving lane according to the filling values of the areas and the road traffic influence parameters;

and the decision module is used for determining the obstacle avoidance control decision of the target vehicle according to the road passing efficiency of the driving lane.

According to another aspect of the present invention, there is provided an electronic apparatus including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the vehicle obstacle avoidance control method according to any embodiment of the invention.

According to another aspect of the present invention, a computer-readable storage medium is provided, where computer instructions are stored, and the computer instructions are used for causing a processor to implement the vehicle obstacle avoidance control method according to any embodiment of the present invention when executed.

According to the technical scheme of the embodiment of the invention, the driving lane with the preset length in front of the target vehicle is subjected to region division; determining an obstacle influence range on the driving lane according to the obstacle information on the driving lane; determining filling values of all the areas according to the coverage information of the influence range of the obstacles in all the areas on the driving lane; determining the road passing efficiency of the driving lane according to the filling value and the road passing influence parameter of each region; and determining an obstacle avoidance control decision of the target vehicle according to the road passing efficiency of the driving lane. According to the technical scheme, the obstacle information is analyzed to determine the obstacle influence range on the driving lane so as to determine the filling value of each area under the influence of the obstacles, the filling value and the road traffic influence parameters are conveniently analyzed to determine the traffic efficiency of the lane, and finally the efficiency of avoiding obstacles by vehicles is improved according to the traffic efficiency.

It should be understood that the statements in this section are not intended to identify key or critical features of the embodiments of the present invention, nor are they intended to limit the scope of the invention. Other features of the present invention will become apparent from the following description.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

Fig. 1 is a flowchart of a vehicle obstacle avoidance control method according to an embodiment of the present invention;

fig. 2 is an exemplary diagram for regionalizing a driving lane of a preset length ahead of a target vehicle to which the embodiment of the present invention is applied;

FIG. 3 is an exemplary plot of range of obstruction effects and travelable lane widths for which embodiments of the present invention are applicable;

fig. 4 is an exemplary diagram in which the influence ranges of obstacles to which the embodiment of the present invention is applied are respectively located on both sides of a vehicle travel guide line of a travel lane in which a target area is located;

fig. 5 is a flowchart of a vehicle obstacle avoidance control method according to an embodiment of the present invention;

FIG. 6 is a diagram illustrating the correspondence between weights and lane change triggering distances applied in the embodiment of the present invention;

fig. 7 is a flowchart of a method for determining an obstacle avoidance control decision according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of a vehicle obstacle avoidance control device according to an embodiment of the present invention;

fig. 9 is a schematic structural diagram of an electronic device implementing the vehicle obstacle avoidance control method according to the embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.

It should be noted that the terms "candidate," "target," "first" and "second" etc. in the description and claims of the invention and the above drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example one

Fig. 1 is a flowchart of a vehicle obstacle avoidance control method according to an embodiment of the present invention, where the present embodiment is applicable to a situation where an autonomous vehicle automatically plans a road driving route after knowing a road environment during a road driving process, and the method may be executed by a vehicle obstacle avoidance control device, where the vehicle obstacle avoidance control device may be implemented in a form of hardware and/or software, and the vehicle obstacle avoidance control device may be configured in an electronic device having the vehicle obstacle avoidance control method. As shown in fig. 1, the method includes:

s110, carrying out region division on a driving lane with a preset length in front of the target vehicle; wherein the driving lanes comprise a candidate driving lane and a current driving lane, and the driving direction of the candidate driving lane is the same as that of the current driving lane.

The candidate driving lane may be a lane adjacent to the current driving lane, may be one of the left and right adjacent lanes, or may be two of the left and right adjacent lanes, and the driving direction of the candidate driving lane is the same as the driving direction of the current driving lane, so as to ensure that the vehicle can correctly drive on other lanes when making a decision. The current traveling lane is a lane in which the target vehicle is currently traveling.

Specifically, in the driving process of the current lane, the target vehicle can sense the condition of the road environment through a sensing system on the vehicle, so that the target vehicle can perform corresponding operation in time according to the condition of the road environment. In order to accurately judge the road environment condition, the driving lane with the preset length in front of the target vehicle needs to be subjected to region division so as to analyze the road environment of each region, and then the condition of the road environment can be accurately obtained. The area with the preset length in front of the target is divided, so that the integrity of the road condition analysis is ensured as far as possible, and the influence on the road condition analysis caused by too much useless information obtained due to too long area setting is avoided. For example, referring to fig. 2, if a driving lane ahead of the target vehicle is divided into regions by a preset length L and each region is divided according to the length d, the number of the regions that can be divided is N = L/d.

And S120, determining the influence range of the obstacle on the driving lane according to the information of the obstacle on the driving lane.

The obstacle information may be position information, motion trajectory, speed information, and size information of an obstacle that affects the travel of the target vehicle on the travel lane. The obstacle influence range may be a range in which an obstacle appearing on the target lane may affect the target vehicle, for example, the obstacle occupies an area of a square meter on the travel path, the target vehicle cannot travel on the area, and the area of a square meter is the obstacle influence range.

Specifically, dividing areas of a driving lane with a preset length in front of a target vehicle are obtained, obstacle information in each area is determined, then the obstacle information is analyzed to judge the influence of obstacles in each area on a driving road, and the obstacle influence range of the obstacles on the driving lane is determined according to the influence degree; for example, if the influence degree is greater than or equal to the preset threshold, it indicates that the obstacle may prevent the target vehicle from safely driving on the driving road, and it is necessary to determine the obstacle influence range of the obstacle on the driving lane according to the obstacle information; if the influence degree is smaller than the preset threshold value, the obstacle does not influence the safe driving of the target vehicle on the driving road, and the obstacle can be eliminated, namely the influence range of the obstacle on the driving lane is not calculated. Therefore, the obstacle influencing the safe driving of the target vehicle can be accurately determined according to the obstacle information, and the influence range of the obstacle on the driving lane can be accurately obtained.

In one possible embodiment, optionally, determining the obstacle influence range on the driving lane according to the obstacle information on the driving lane may include steps A1-A2:

step A1, determining a target obstacle of a target driving lane according to obstacle motion information on the target driving lane based on obstacle screening conditions.

And A2, determining an obstacle influence range on the target driving lane according to the motion track of the target obstacle in a preset time period.

Wherein the obstacle screening condition includes at least one of: the method comprises the steps of reserving an obstacle which is located on a target driving lane and has a speed of 0, reserving an obstacle which is located on other driving lanes, changes lanes from the other driving lanes to the target driving lane within a preset time period and has a speed smaller than a preset speed threshold value, and reserving the obstacle which is located on the target driving lane continuously within the preset time period.

The obstacle screening condition can be a condition for screening obstacles on a driving lane, namely the obstacle which can influence the safe driving of a target vehicle can be accurately determined through the condition, namely the obstacle is accurately positioned. The obstacle motion information may be information such as a speed, an acceleration, a position, and a motion trajectory of the obstacle on the driving lane. The target driving lane may be one of the candidate driving lane and the current driving lane.

Specifically, after determining each region of a target driving lane with a preset length in front of the target vehicle, obtaining obstacle information on each region, and screening obstacles according to obstacle screening conditions and obstacle movement information of the obstacles on the target driving lane, so as to accurately determine a target obstacle affecting traffic of the target driving lane, and further accurately determine an obstacle affecting range on the target driving lane according to a movement track of the target obstacle within a preset time period, where a rectangular shadow a in fig. 3 is an obstacle affecting range of the target obstacle in the region.

For example, if the obstacle a stops on the target driving lane and the speed is zero, which indicates that the obstacle a stops on the target driving lane and affects the traffic on the target driving lane, the obstacle a needs to be marked as a target obstacle, and since the obstacle a does not move, the obstacle affecting range of the obstacle a on the target driving lane can be accurately obtained by projecting the position of the obstacle a on the road;

if the obstacle A is continuously located on the target driving lane within the preset time period, the obstacle A is indicated to move on the target driving lane all the time and does not leave the target driving lane, if the speed of the obstacle A is detected to be smaller than a preset speed threshold value, the obstacle A is indicated to influence the traffic on the target driving lane, the obstacle A needs to be marked as a target obstacle, and the relative relation between the position of the obstacle A moving within the preset time period and the target driving lane is projected so as to accurately determine the obstacle influence range of the obstacle A on the target driving lane; if the speed of the obstacle A is detected to be greater than the preset speed threshold value, the obstacle does not influence the traffic of the target driving lane, and therefore the obstacle influence range of the obstacle does not need to be recorded;

if the obstacle A is far away from the target driving lane in the preset time period, the obstacle A shows that the obstacle does not influence the traffic of the target driving lane, and the obstacle influence range of the obstacle does not need to be recorded;

if the obstacle a is on another driving lane, but the lane is changed from the other driving lane to the target driving lane within the preset time period and the speed is less than the preset speed threshold, it is described that the obstacle a does not initially exist on the target driving lane, but can drive to the target driving lane within the preset time period, because the speed is less than the preset speed threshold, the obstacle a does not leave the target driving lane within the preset time period, so that the traffic on the target driving lane is affected, the obstacle a needs to be marked as a target obstacle, and the relative relationship between the position of the obstacle a moving within the preset time period and the target driving lane is projected to accurately determine the obstacle affecting range on the target driving lane.

According to the technical scheme, based on the barrier screening condition, whether the barrier influences the traffic of the target driving lane is accurately judged by analyzing the barrier movement information on the target driving lane, so that the target barrier of the target driving lane is accurately determined, the barrier is accurately screened, and the situation that the barrier without influence or with small influence is calibrated is avoided; and then analyzing the movement track of the target obstacle on the target driving lane in the preset time period to accurately determine the region of the target obstacle influencing the target driving lane, namely the obstacle influence range, so that the obstacle influence range is accurately determined, and the filling value of each region is conveniently determined through the obstacle influence range.

And S130, determining filling values of the areas according to the coverage information of the obstacle influence range in the areas on the driving lane.

The filling value can be used for indicating the congestion condition of each area on the driving lane, and the smaller the filling value is, the more congested the area is, and the more unobstructed the area is.

Specifically, the influence range of the obstacles in each area on the driving lane is obtained, the coverage information of the influence range of the obstacles in each area is analyzed, the influence condition of the obstacles in each area on the target driving lane is accurately obtained, and then each area is accurately filled, namely, each area is assigned with a filling value.

In a possible embodiment, optionally, determining the filling value of each area according to the coverage information of the obstacle influence range in each area on the driving lane may include steps B1 to B4:

and B1, determining the width of the travelable channel in the target area according to the coverage information of the obstacle influence range in the target area.

B2, if the travelable channel width in the target area is smaller than a preset width threshold, determining that the filling value of the target area is 0; wherein the preset width threshold is determined according to the width of the target vehicle.

And B3, if the width of the travelable channel in the target area is greater than or equal to a preset width threshold, the obstacle influence range in the target area and the obstacle influence range in the adjacent area are respectively positioned on two sides of a vehicle driving guide line of a driving lane in which the target area is positioned, and the longitudinal distance between the obstacles in the target area and the adjacent area is smaller than the longitudinal threshold, determining the filling value of the target area and the adjacent area to be 0.

Step B4, otherwise, determining a target filling value in the target area according to the mapping relation between the width of the drivable channel and the candidate filling value; wherein the candidate padding value is greater than 0.

The travelable lane width may be, among other things, the distance of the obstacle from the road boundary, see distance l in 3. The preset width threshold may be a minimum driving lane width that allows the target vehicle to safely pass through, which may be determined according to the width of the target vehicle and the road boundary driving safety distance. The road boundary driving safety distance may be a minimum distance that the vehicle is allowed to be from the road boundary for vehicle driving safety in the road driving regulations. The candidate fill value may be a value determined from experience with historical vehicle travel in the travel lane.

Specifically, coverage information of an obstacle influence range in a target area is obtained, position information of an obstacle is obtained from the coverage information, a road boundary distance between the obstacles is determined according to the position information of the obstacle and the position information of a road boundary, namely the width of a travelable channel, and a preset width threshold is determined by adding the width of a vehicle body of a target vehicle to the road boundary travel safety distance; comparing the travelable lane width to a preset width threshold, there are three situations:

in the first case: and if the width of the drivable lane in the target area is smaller than the preset width threshold, indicating that the area of the drivable lane is blocked, and the target vehicle cannot pass through the area, and assigning the filling value of the target area to be 0.

In the second case: if the width of the travelable channel in the target area is greater than or equal to the preset width threshold, but the obstacle influence range in the target area and the obstacle influence range in the adjacent area are respectively located on two sides of the vehicle travel guideline of the travel lane in which the target area is located (see fig. 4), and the longitudinal distance between the obstacles in the target area and the adjacent area is smaller than the longitudinal threshold, which indicates that the target vehicle cannot pass through the area of the travel lane no matter how the target vehicle makes a detour, the filling value of the target area and the adjacent area is assigned to be 0. For example, the longitudinal threshold value in fig. 4 is 10cm, then when the longitudinal distance between the obstacles in the target area and the adjacent area is less than 10cm, the filling value of the target area and the adjacent area needs to be assigned to 0.

In the third case: in addition to the above two cases, the target filling value in the target area is determined according to the mapping relationship between the travelable channel width and the candidate filling value. The mapping relation can be obtained according to experience information of historical vehicles running in the road, namely the one-to-one correspondence relation between the obtained historical travelable channel width and the historical filling value is analyzed, and then the mapping relation between the travelable channel width and the candidate filling value is accurately obtained. For example, the mapping relationship between the travelable channel width and the candidate filling value may be that the larger the travelable channel width is, the larger the candidate filling value is, the smaller the travelable channel width is, and the smaller the candidate filling value is. According to the technical scheme, the passable degree of the target area under different conditions of the relation between the travelable channel width and the preset width threshold is accurately determined by comparing the travelable channel width in the target area with the preset width threshold, and then the filling value of the target area is accurately determined, so that the accurate assignment of the filling value of the target area is realized, and the following judgment error on the road passing efficiency caused by the error of the filling value is avoided, and further the vehicle control decision is influenced.

S140, determining the road passing efficiency of the driving lane according to the filling values of the regions and the road passing influence parameters.

The road traffic influence parameter may be a factor influencing safe traffic of the target vehicle on the road. Road traffic efficiency may be the probability that a target vehicle can safely and efficiently traverse a road.

Specifically, the filling values and road traffic influence parameters of all the areas on the driving lane are obtained, and the filling values and the road traffic influence parameters of all the areas are analyzed and processed, so that the road traffic efficiency of the driving lane is accurately determined. For example, the influence probability of the filling value and the road traffic influence parameter of each region on the driving lane is analyzed, the influence probability is analyzed to determine the accurate road traffic efficiency, or the filling value and the road traffic influence parameter of each region are calculated through a formula to obtain an accurate calculation value, and the calculation value is analyzed to determine the accurate road traffic efficiency.

In a possible embodiment, optionally, before determining the road traffic efficiency of the driving lane according to the filling values of the areas and the road traffic influence parameters, the method further comprises steps C1-C3:

step C1, determining whether to issue a forced control decision to the target vehicle according to the running task information and the running environment information of the target vehicle; wherein the forced control decision comprises a forced lane change decision and a forced lane change-free decision.

And C2, if the forced lane change decision is made, setting the filling value of the area in the current driving lane to be 0.

And C3, if the decision of not changing the lane is made, setting the filling value of the area in the candidate driving lane as 0.

The driving task information may refer to information that a user issues a task for a target vehicle in advance or temporarily, for example, the target vehicle performs a driving task according to a specified route. The driving environment information may be information of surrounding environment encountered by the target vehicle during driving, such as traffic lights, or special situations such as stops (buses need to stop at the stops) and the like.

Specifically, when the target vehicle encounters some emergency situations during the driving process, at this time, in order to ensure that the target vehicle can normally travel, it is necessary to determine whether to issue a forced control decision for the target vehicle, and if necessary, a rule is set to forcibly change the road traffic efficiency of the driving lane, that is, the minimum range (for example, all areas of the driving lane that need to be filled) in front of the road needs to be filled is virtually filled, so as to ensure that the road traffic efficiency of the driving lane of the vehicle is greater than the road traffic efficiency of other lanes, thereby ensuring that the vehicle can safely travel.

The specific rule is as follows: judging whether the target vehicle is in a forced lane change decision or a forced non-lane change decision; if the lane change is a forced lane change decision, if a task is temporarily assigned to the target vehicle to change the lane, the area in the current driving lane of the target vehicle needs to be virtually filled, and the filling value is set to be 0, so that the road passing efficiency of the current driving lane is ensured to be smaller than the road passing efficiency of the candidate driving lane, and the forced lane change of the target vehicle is further completed; if a decision is made without changing lanes forcibly, if the situation of traffic lights is met in the front, the target vehicle cannot change lanes according to the traffic rules, so that the area in the candidate driving lane needs to be virtually filled, and the filling value is set to be 0, so that the road passing efficiency of the candidate driving lane is ensured to be smaller than that of the current driving lane, and the target vehicle is ensured not to perform lane changing operation.

According to the technical scheme, the running task information and the running environment information of the target vehicle are analyzed to accurately determine whether to issue the forced control decision to the target vehicle, so that the target vehicle can safely run according to the issued forced control decision.

S150, determining an obstacle avoidance control decision of the target vehicle according to the road traffic efficiency of the driving lane.

The obstacle avoidance control decision may be a decision that the target vehicle safely drives in order to avoid an obstacle.

Specifically, the road traffic efficiency of the target vehicle running lane is obtained, the road traffic efficiency is analyzed, and if the road traffic efficiency of the running lane can ensure that the target vehicle can run safely through comparison with historical experience, or a new analysis rule is set for the road traffic efficiency, whether the road traffic efficiency of the running lane can ensure that the target vehicle can run safely is determined through the new analysis rule, and accurate determination of obstacle avoidance control decision of the target vehicle is achieved, so that the target vehicle can run safely on the running lane.

According to the technical scheme of the embodiment of the invention, the driving lane with the preset length in front of the target vehicle is subjected to region division; determining an obstacle influence range on the driving lane according to the obstacle information on the driving lane; determining filling values of all areas according to the coverage information of the obstacle influence range in all areas on the driving lane; determining the road traffic efficiency of a driving lane according to the filling value and the road traffic influence parameter of each area; and determining an obstacle avoidance control decision of the target vehicle according to the road passing efficiency of the driving lane. According to the technical scheme, the driving lane in front of the target vehicle is divided into areas according to the preset length, so that the driving lane in front of the target vehicle can be accurately determined to be divided into a plurality of areas, the obstacles in the areas are subjected to key analysis processing, the target obstacles influencing the driving channel are screened out, the influence range of the obstacles on the driving lane is determined according to the information of the target obstacles on the driving lane, and the influence range of the obstacles in each area on the driving lane is more definite; and then, the coverage information of the influence range of the obstacle in the target area is analyzed to determine the filling value of each area under the influence of the obstacle, so that the filling value and the road traffic influence parameter are analyzed to determine the traffic efficiency of the vehicle, and finally, the vehicle is accurately controlled to avoid the obstacle according to the traffic efficiency, so that the problem that the road obstacle influences the safe running of the vehicle is solved.

Example two

Fig. 5 is a flowchart of a vehicle obstacle avoidance control method according to an embodiment of the present invention, and the embodiment further describes in detail S140 and S150 in the foregoing embodiment. As shown in fig. 5, the method includes:

and S210, carrying out region division on a driving lane with a preset length in front of the target vehicle.

And S220, determining the influence range of the obstacle on the driving lane according to the information of the obstacle on the driving lane.

And S230, determining filling values of the areas according to the coverage information of the obstacle influence range in the areas on the driving lane.

S240, determining the road filling value of the driving lane according to the filling value of each region and the region weight.

The region weight is determined according to the driving style risk factor and the longitudinal distance between the region center and the target vehicle. The driving style risk factor can be determined according to the historical driving condition of the driver, namely the historical driving condition of the driver is evaluated, the more the driving style is accelerated, the shorter the corresponding lane changing distance is, and the larger the corresponding driving style risk factor is.

Specifically, the attention degree of the front driving lane is different in different driving styles, so that the region weight w is accurately determined according to the attention degree in different driving styles _i So that the region weight can be closer to the actual situation, the subsequent road filling value can be more accurately determined, and then the filling values of the regions are combined

Accurately determining road fill values for driving lanes

The determination can be made by the following equation:

optionally, the region weight is determined according to the following formula:

wherein, w _i The area weight of the ith area on the driving lane is represented, C represents the maximum weight value in a preset close range, and L _w Denotes the average lane change trigger distance, σ _w A fluctuation variance representing a lane change trigger distance, gamma representing the driving style risk factor, s _i Indicating the longitudinal distance of the zone center of the i-th zone from the target vehicle.

The maximum weight value in the preset close range can be adjusted according to the summary analysis of historical experience. The average lane change triggering distance can be determined according to a large amount of collected historical vehicle driving data, such as a large amount of data of vehicle running speed, obstacle distribution condition, lane line, vehicle execution task, lane change style and the like, and the data are analyzed to determine a corresponding relation graph (such as fig. 6) between the weight and the lane change triggering distance, so that the average lane change triggering distance can be accurately determined. The fluctuation variance of the lane change trigger distance can be a range of the lane change trigger distance which is allowed to float up and down, and can be set according to actual conditions.

Specifically, for the determination of the regional weight, the longitudinal distance s from the center of the region to the target vehicle may be determined according to _i With average lane change distance gammal combined with driving style risk _w Judging; if the longitudinal distance between the center of the area and the target vehicle is less than or equal to the average lane change distance, the area weight is a first weight threshold value; if the longitudinal distance between the center of the area and the target vehicle is greater than the average lane changing distance, the area weight is a second weight threshold value; wherein the first weight threshold is greater than the second weight threshold.

According to the technical scheme, the driving style risk factors are introduced into the calculation mode of the regional weight, so that the regional weight is more in line with the actual situation, the lane change distances corresponding to different driving styles are different, and the lane change distances excited by the driving styles are small, so that the regional weight can be accurately and reasonably distributed after the average lane change triggering distance is combined, and the situation that the determination error of the regional weight is caused by only considering the average lane change triggering distance is avoided, and the final road traffic efficiency is influenced is avoided.

And S250, determining the road passing efficiency of the driving lane according to the road filling value and the road passing influence parameter.

The road traffic influence parameters comprise regional weight and driving style risk factors.

Specifically, the method comprises the steps of obtaining a road filling value and road traffic influence parameters, analyzing the road filling value and the road traffic influence parameters, for example, combining the road filling value and the road traffic influence parameters together for analysis, determining the influence degree on road traffic, judging the road traffic efficiency of a driving lane according to the influence degree, or calculating the filling value and the road traffic influence parameters through a formula to accurately obtain the road traffic efficiency of the driving lane; so as to make obstacle avoidance control decisions for the target vehicles according to the subsequent road passing efficiency.

Optionally, the road traffic efficiency of the driving lane is determined according to the following formula:

wherein P represents the road passing efficiency of the driving lane,

representing a nominal road mean area fill value, σ _p Representing the fluctuating variance of the road-area filling value,

represents the road filling value, W represents the regional total weight on the driving lane, and γ represents the driving style risk factor.

In particular, the method comprises the following steps of,

training can be carried out according to a large amount of historical driving data; the historical driving data can be data such as real-time running speed of a vehicle, obstacle distribution condition, lane line, task execution of the vehicle or lane change style of the vehicle, and the historical driving data is trained to obtain the historical driving data and a filling value of a calibrated road average area

Then the calibrated road average region filling value can be accurately determined through the mapping relation

The total weight W of the regions on the driving lane is obtained by weighting the region weight W of each region _i Obtained by summing, the formula is as follows:

according to the technical scheme, the road filling value and the road passing influence parameter are combined together through a formula, so that the road passing efficiency is accurately determined; the road traffic efficiency is closer to the actual driving condition due to the introduction of the driving style risk factors, the error in determining the road traffic efficiency caused by too large deviation from the actual condition is avoided so as to influence the driving of vehicles, meanwhile, the error possibly occurring in the actual condition is considered due to the consideration of the calibrated road average area filling value and the fluctuation variance of the road area filling value, so that the determination of the road traffic efficiency is more practical, namely the road traffic efficiency is more representative, and the obstacle avoidance control decision of the target vehicle finally determined according to the road traffic efficiency is more accurate.

And S260, determining an obstacle avoidance control decision of the target vehicle according to the road passing efficiency of the driving lane.

The obstacle avoidance control decision comprises in-lane obstacle avoidance, lane changing obstacle avoidance and lane borrowing obstacle avoidance. The obstacle avoidance in the lane can be realized by only avoiding the obstacle in the current driving lane without changing the lane of the target vehicle. The lane change obstacle avoidance method can be that the current target vehicle cannot continuously run on the lane, needs to be changed to other lanes to run, and can keep running on the lane after the lane change. The obstacle borrowing and avoiding method can be used for temporarily borrowing other lanes to carry out obstacle avoidance driving when a target vehicle cannot drive on a current driving lane, and returning to an original driving lane to continue driving after the obstacle avoidance is successful.

In one possible embodiment, optionally, determining the obstacle avoidance control decision of the target vehicle according to the road traffic efficiency of the driving lane may include steps D1-D3:

step D1, if the road passing efficiency of the current driving lane is smaller than a preset efficiency threshold, the difference value between the road passing efficiency of the candidate driving lane and the road passing efficiency of the current driving lane is larger than a first efficiency difference value, the road passing efficiency of the candidate driving lane is larger than or equal to the preset efficiency threshold, and the rear of the candidate driving lane is safe, determining that the obstacle avoidance control decision of the target vehicle is lane borrowing and obstacle avoidance.

And D2, if the road passing efficiency of the current driving lane is smaller than a preset efficiency threshold value, the difference value between the road passing efficiency of the candidate driving lane and the road passing efficiency of the current driving lane is larger than a second efficiency difference value, the road passing efficiency of the candidate driving lane is larger than or equal to the preset efficiency threshold value, and the rear of the candidate driving lane is safe, determining that the obstacle avoidance control decision of the target vehicle is lane changing obstacle avoidance.

And D3, if not, determining that the obstacle avoidance control decision of the target vehicle is an in-road obstacle avoidance.

Wherein the first efficiency difference is less than the second efficiency difference.

Specifically, fig. 7 is a flowchart of a decision method for determining obstacle avoidance control according to an embodiment of the present invention, where P1 in fig. 7 is road traffic efficiency of a current driving lane, P2 is road traffic efficiency of a candidate driving lane, Q is a preset efficiency threshold, G1 is a first efficiency difference, and G2 is a second efficiency difference. The obstacle avoidance control decision of the target vehicle can be distributed according to the following conditions, specifically:

when P1 is less than Q, which indicates that the current driving lane is blocked or has other special conditions and the target vehicle cannot normally pass, comparing the difference value of P2 and P1 with G1 and G2 respectively, simultaneously determining whether P2 is greater than or equal to Q and whether the rear safety of the candidate driving lane is safe, and further allocating a proper obstacle avoidance control decision for the target vehicle; if P2-P1 is greater than G1, P2 is greater than or equal to Q, and the rear of the candidate driving lane is safe, it is indicated that the candidate driving lane is relatively smooth at the moment, but the road passing efficiency of the candidate driving lane cannot enable the target vehicle to continuously drive on the lane, but the candidate driving lane can be used as a temporary obstacle avoidance channel, namely, the target vehicle issues an instruction of borrowing and avoiding obstacles, and the target vehicle needs to return to the original current driving lane to continue driving after executing the task of borrowing and avoiding obstacles; if P2-P1 is greater than G2, P2 is greater than or equal to Q, and the rear of the candidate driving lane is safe, the candidate driving lane is smooth at the moment, and the road passing efficiency of the candidate driving lane can enable the target vehicle to continuously drive in the lane, so that a lane changing and obstacle avoiding instruction can be given to the target vehicle, and the target vehicle can keep driving in the candidate driving lane after lane changing; except the situation that the target vehicle needs to change the lane to avoid the obstacle or borrow the lane to avoid the obstacle, the current driving lane in other situations can enable the target vehicle to successfully avoid the obstacle so as to carry out normal passing, namely, the target vehicle issues an instruction of avoiding the obstacle in the lane so as to enable the target vehicle to carry out obstacle avoidance driving.

Optionally, in the tasks of lane changing and obstacle avoiding, lane borrowing and obstacle avoiding of the target vehicle, the situations of active or passive removal of lane changing and obstacle avoiding and lane borrowing and obstacle avoiding can occur; the method specifically comprises the following steps:

the lane changing and obstacle avoiding active removing conditions are as follows: the target vehicle enters a first preset distance of the candidate driving lane (if the first preset distance is 0.2 m);

the passive removing conditions for changing the lane and avoiding the obstacle are as follows: after triggering lane changing and obstacle avoidance, if the vehicle deviates from the current driving lane within a second preset distance (the second preset distance is 0.3 m), the rear safety is not met, or the road passing efficiency of the candidate driving lane is smaller than a first preset passing threshold (if the first preset passing threshold is 0.6), or the road passing efficiency of the current driving lane is larger than a second preset passing threshold (if the second preset passing threshold is 0.8);

the conditions for actively removing the lane-borrowing obstacle avoidance are as follows: returning the target vehicle to the current driving lane, driving in the middle and returning to the current driving lane within a first preset distance transversely;

the passive removing condition of the lane-borrowing obstacle avoidance is as follows: after the lane borrowing and obstacle avoidance are triggered, the target vehicle deviates from the current driving lane within a second preset distance, the rear safety is not met, or the road passing efficiency of the candidate driving lane is smaller than a first preset passing threshold value, or the road passing efficiency of the current driving lane is larger than a second preset passing threshold value.

According to the technical scheme, the road passing efficiency of the current driving lane, the road passing efficiency of the candidate driving lane, the preset efficiency threshold value, the first efficiency difference value, the second efficiency difference value and the rear safety of the candidate driving lane are analyzed, whether the current driving lane or the candidate driving lane can allow the target vehicle to normally pass or not is accurately judged, and then a proper obstacle avoidance control decision is matched for the target vehicle, so that the target vehicle is accurately controlled, and the target vehicle is prevented from being influenced by obstacles to safely drive.

According to the technical scheme of the embodiment of the invention, the driving lane in front of the target vehicle is divided into several areas by carrying out area division on the driving lane with the preset length in front of the target vehicle, so that the driving lane in front of the target vehicle can be divided into several areas, and the obstacles in the several areas are subjected to key analysis; further determining an obstacle influence range on the driving lane according to the obstacle information on the driving lane, so that the influence range of the obstacle in each area on the driving lane is more clear, and the filling value of each area is determined according to the coverage information of the obstacle influence range in each area on the driving lane; then, introducing a driving style risk factor to enable the region weight to more accurately represent the influence proportion of the obstacles in each region on the region, and further accurately determining the road filling value of the driving lane through a formula by combining the filling value and the region weight of each region so as to enable the road traffic efficiency of the driving lane determined by the road filling value and the road traffic influence parameter to be more accurate; and finally, analyzing the road traffic efficiency to determine the traffic condition of the driving lane, and further matching a proper obstacle avoidance control decision for the target vehicle according to the traffic condition.

EXAMPLE III

Fig. 8 is a schematic structural diagram of a vehicle obstacle avoidance control device according to an embodiment of the present invention. As shown in fig. 8, the apparatus includes:

the region division module 310 is configured to perform region division on a driving lane with a preset length in front of the target vehicle; wherein the driving lanes comprise a candidate driving lane and a current driving lane, and the driving direction of the candidate driving lane is the same as that of the current driving lane;

a range determining module 320, configured to determine an obstacle influence range on the driving lane according to the obstacle information on the driving lane;

a filling value determining module 330, configured to determine a filling value of each region according to coverage information of an obstacle influence range in each region on the driving lane;

the efficiency determining module 340 is configured to determine road traffic efficiency of the driving lane according to the filling values of the regions and the road traffic influence parameters;

and a decision module 350, configured to determine an obstacle avoidance control decision of the target vehicle according to the road passing efficiency of the driving lane.

Optionally, the range determining module is specifically configured to:

determining a target obstacle of a target driving lane according to obstacle motion information on the target driving lane based on obstacle screening conditions;

determining an obstacle influence range on the target driving lane according to the movement track of the target obstacle in a preset time period;

Optionally, the filling value determining module is specifically configured to:

determining the width of a travelable channel in the target area according to the coverage information of the obstacle influence range in the target area;

if the width of the drivable channel in the target area is smaller than a preset width threshold, determining that the filling value of the target area is 0; the preset width threshold value is determined according to the width of the target vehicle;

if the width of the travelable channel in the target area is greater than or equal to a preset width threshold, the obstacle influence range in the target area and the obstacle influence range in the adjacent area are respectively positioned on two sides of a vehicle driving guide line of a driving lane where the target area is positioned, and the longitudinal distance between the obstacles in the target area and the adjacent area is smaller than a longitudinal threshold, determining that the filling values of the target area and the adjacent area are 0;

otherwise, determining a target filling value in the target area according to the mapping relation between the travelable channel width and the candidate filling value; wherein the candidate padding value is greater than 0.

Optionally, the efficiency determining module is specifically configured to:

determining the road filling value of the driving lane according to the filling value and the region weight of each region;

and determining the road passing efficiency of the driving lane according to the road filling value and the road passing influence parameter.

The road traffic influence parameters comprise regional weight and driving style risk factors; the region weight is determined according to the driving style risk factor and the longitudinal distance from the region center to the target vehicle;

optionally, the efficiency determining module includes an arithmetic unit, and is specifically configured to:

determining road traffic efficiency of the driving lane according to the following formula:

wherein P represents the road passing efficiency of the driving lane,

Optionally, the region weight is determined according to the following formula:

wherein, w _i The area weight of the ith area on the driving lane is represented, C represents the maximum weight value in a preset close range, and L _w Representing the mean lane change trigger distance, σ _w A fluctuation variance representing a lane change trigger distance, gamma representing the driving style risk factor, s _i Indicating the longitudinal distance of the zone center of the i-th zone from the target vehicle.

Optionally, the decision module is specifically configured to:

if the road passing efficiency of the current driving lane is smaller than a preset efficiency threshold value, the difference value between the road passing efficiency of the candidate driving lane and the road passing efficiency of the current driving lane is larger than a first efficiency difference value, the road passing efficiency of the candidate driving lane is larger than or equal to the preset efficiency threshold value, and the rear of the candidate driving lane is safe, determining that the obstacle avoidance control decision of the target vehicle is lane borrowing and obstacle avoidance;

if the road passing efficiency of the current driving lane is smaller than a preset efficiency threshold value, the difference value between the road passing efficiency of the candidate driving lane and the road passing efficiency of the current driving lane is larger than a second efficiency difference value, the road passing efficiency of the candidate driving lane is larger than or equal to the preset efficiency threshold value, and the rear of the candidate driving lane is safe, determining that the obstacle avoidance control decision of the target vehicle is lane changing obstacle avoidance;

otherwise, determining the obstacle avoidance control decision of the target vehicle as an in-lane obstacle avoidance;

And the obstacle avoidance control decision comprises in-lane obstacle avoidance, lane changing obstacle avoidance and lane borrowing obstacle avoidance.

Optionally, before the efficiency determining module, the apparatus further includes a forced decision determining unit, specifically configured to:

determining whether to issue a forced control decision for the target vehicle according to the running task information and the running environment information of the target vehicle; wherein the forced control decision comprises a forced lane change decision and a forced non-lane change decision;

if the current driving lane is in the forced lane changing decision, setting the filling value of the area in the current driving lane as 0;

and if the decision of not changing the lane is made, setting the filling value of the area in the candidate driving lane as 0.

The vehicle obstacle avoidance control device provided by the embodiment of the invention can execute the vehicle obstacle avoidance control method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

According to the technical scheme, the data acquisition, storage, use, processing and the like meet relevant regulations of national laws and regulations and do not violate the good custom of the public order.

Example four

The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.

FIG. 9 illustrates a schematic diagram of an electronic device 10 that may be used to implement embodiments of the present invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 9, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The processor 11 performs the various methods and processes described above, such as a vehicle obstacle avoidance control method.

In some embodiments, the vehicle obstacle avoidance control method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the vehicle obstacle avoidance control method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the vehicle obstacle avoidance control method by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.

The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle obstacle avoidance control method is characterized by comprising the following steps:

determining the road passing efficiency of the driving lane according to the filling values of the regions and the road passing influence parameters;

2. The method of claim 1, wherein determining the obstacle impact range on the driving lane from the obstacle information on the driving lane comprises:

wherein the obstacle screening condition includes at least one of: the method comprises the steps of reserving an obstacle which is located on a target driving lane and has the speed of 0, reserving an obstacle which is located on other driving lanes, changes lanes from the other driving lanes to the target driving lane within a preset time period and has the speed smaller than a preset speed threshold value, and reserving the obstacle which is located on the target driving lane continuously within the preset time period.

3. The method according to claim 1, wherein determining the filling value for each region based on coverage information for the range of influence of the obstacle in each region on the driving lane comprises:

if the width of the travelable channel in the target area is greater than or equal to a preset width threshold, the obstacle influence range in the target area and the obstacle influence range in the adjacent area are respectively positioned on two sides of a vehicle travel guide line of a travel lane in which the target area is positioned, and the longitudinal distance between the obstacles in the target area and the adjacent area is smaller than a longitudinal threshold, determining that the filling values of the target area and the adjacent area are 0;

4. The method of claim 1, wherein the road traffic impact parameters include regional weights and driving style risk factors; the region weight is determined according to the driving style risk factor and the longitudinal distance between the region center and the target vehicle;

correspondingly, determining the road traffic efficiency of the driving lane according to the filling values and the road traffic influence parameters of the regions comprises the following steps:

5. The method according to claim 4, wherein determining the road traffic efficiency of the driving lane from the road filling value and the road traffic influencing parameter comprises:

wherein P represents road passing efficiency of the driving lane,

representing a nominal road mean area fill value, σ _p Representing the fluctuating variance of the road region filling value,

6. The method according to claim 4 or 5, wherein the region weight is determined according to the following formula:

7. The method according to claim 1, wherein the obstacle avoidance control decision comprises in-lane obstacle avoidance, lane change obstacle avoidance, and lane borrowing obstacle avoidance;

correspondingly, determining an obstacle avoidance control decision of the target vehicle according to the road traffic efficiency of the driving lane comprises the following steps:

if the road passing efficiency of the current driving lane is smaller than a preset efficiency threshold value, the difference value between the road passing efficiency of the candidate driving lane and the road passing efficiency of the current driving lane is larger than a second efficiency difference value, the road passing efficiency of the candidate driving lane is larger than or equal to the preset efficiency threshold value, and the rear of the candidate driving lane is safe, determining that the obstacle avoidance control decision of the target vehicle is lane changing and obstacle avoidance;

otherwise, determining the obstacle avoidance control decision of the target vehicle as an in-road obstacle avoidance;

8. The method according to claim 1, characterized in that before determining the road traffic efficiency of the driving lane from the filling values and road traffic influencing parameters of the regions, the method further comprises:

determining whether to issue a forced control decision to the target vehicle according to the running task information and the running environment information of the target vehicle; wherein the forced control decision comprises a forced lane change decision and a forced lane change-free decision;

9. A vehicle obstacle avoidance control device, comprising:

10. An electronic device, characterized in that the electronic device comprises:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the vehicle obstacle avoidance control method of any of claims 1-8.