CN115798261B

CN115798261B - Vehicle obstacle avoidance control method, device and equipment

Info

Publication number: CN115798261B
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: 2023-11-07
Anticipated expiration: 2042-11-22
Also published as: CN115798261A

Abstract

The invention discloses a vehicle obstacle avoidance control method, device and equipment. The method comprises the following steps: dividing the area of 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 areas according to coverage information of obstacle influence ranges in all areas on a driving lane; determining the road traffic efficiency of the driving lane according to the filling value of each area and the road traffic influence parameter; and determining an obstacle avoidance control decision of the target vehicle according to the road traffic 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 obstacle, the filling value and the road traffic influence parameters are analyzed to determine the traffic efficiency of the lane, and finally the obstacle avoidance efficiency of the vehicle 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 the vehicle-mounted sensing system. In the running process of the vehicle, when an obstacle appears on a running road or the running speed of a front vehicle is slower and the like to influence the normal running of the vehicle, the unmanned vehicle needs to obtain the information of the vehicle and the external environment information through the vehicle-mounted device, and the lane changing action is completed under the double constraints of safety and efficiency. If the traffic lane is not changed properly, the traffic efficiency of road traffic is affected, and collision accidents can occur.

In the prior art, the control decision of the vehicle when the vehicle encounters an obstacle still has inaccurate problems, such as screening of the obstacle, the probability of trafficability of a road and the like, so that the control decision of the vehicle when the vehicle encounters the obstacle can be greatly influenced. Therefore, when there is an obstacle on the road, it is important 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, which are used for solving the problem that road obstacles influence the safe forward movement of a vehicle.

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

dividing the area of a driving lane with a preset length in front of a target vehicle; the driving lanes comprise candidate driving lanes and current driving lanes, and the driving direction of the candidate driving lanes is the same as that of the current driving lanes;

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 coverage information of obstacle influence ranges in all areas on the driving lane;

determining the road traffic efficiency of the driving lane according to the filling value of each region and the road traffic influence parameter;

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

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

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

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

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

the efficiency determining module is used for determining the road traffic efficiency of the driving lane according to the filling value of each area and the road traffic influence parameter;

and the decision module is used for determining obstacle avoidance control decisions of the target vehicle according to the road traffic 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 to enable the at least one processor to perform the vehicle obstacle avoidance control method of any of the embodiments of the present invention.

According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute the vehicle obstacle avoidance control method according to any one of the embodiments of the present invention.

According to the technical scheme, the area division is carried out on the driving lanes with the preset length in front of the 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 areas according to coverage information of obstacle influence ranges in all areas on a driving lane; determining the road traffic efficiency of the driving lane according to the filling value of each area and the road traffic influence parameter; and determining an obstacle avoidance control decision of the target vehicle according to the road traffic 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 obstacle, the filling value and the road traffic influence parameters are analyzed to determine the traffic efficiency of the lane, and finally the obstacle avoidance efficiency of the vehicle is improved according to the traffic efficiency.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a vehicle obstacle avoidance control method according to a first embodiment of the present invention;

fig. 2 is an exemplary diagram of area division of a travel lane of a preset length in front of a target vehicle to which the embodiment of the present invention is applied;

FIG. 3 is an exemplary diagram of an obstacle impact range and runnability channel width to which embodiments of the invention are applicable;

FIG. 4 is an exemplary diagram of the application of the present invention with obstacle ranges of influence on both sides of a vehicle drive-guide line on a drive lane in which a target area is located, respectively;

FIG. 5 is a flow chart of a vehicle obstacle avoidance control method provided in accordance with an embodiment of the present invention;

FIG. 6 is a graph of the correspondence between weights and lane change trigger distance for an embodiment of the present invention;

FIG. 7 is a flow chart of a method for determining obstacle avoidance control decisions provided in accordance with 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 for implementing the vehicle obstacle avoidance control method according to the embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "candidate," "target," "first," and "second," and the like in the description and claims of the present invention and in the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, 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 1

Fig. 1 is a flowchart of a vehicle obstacle avoidance control method according to an embodiment of the present invention, where the method may be performed by a vehicle obstacle avoidance control device, and the vehicle obstacle avoidance control device may be implemented in 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, after an autonomous vehicle senses a road environment during road driving. As shown in fig. 1, the method includes:

S110, dividing areas of a driving lane with a preset length in front of a target vehicle; 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 can be a lane adjacent to the current driving lane, can be one of the left and right adjacent lanes or two lanes adjacent to the left and right, and has the same driving direction 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 driving lane is a lane in which the target vehicle is currently driving.

Specifically, in the current lane driving process, the target vehicle senses the condition of the road environment through a sensing system on the vehicle, so that the target vehicle can perform corresponding operation according to the condition of the road environment in time. In order to accurately judge the condition of the road environment, the driving lanes with preset length in front of the target vehicle need to be divided into areas so as to analyze the road environment of each area and accurately obtain the condition of the road environment. The method comprises the steps of dividing a region with a preset length in front of a target to ensure the integrity of road condition analysis as far as possible, and avoiding the influence of too much acquired useless information on the analysis of the road condition caused by too long region setting. For example, referring to fig. 2, the driving lanes of the preset length L in front of the target vehicle are divided into regions, and each region is divided according to the size of the length d, so that the number of the divided regions n=l/d can be obtained.

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

The obstacle information may be information such as position information, movement locus, speed information, and size of an obstacle that affects the target vehicle to travel 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 a square meters on the driving lane, the target vehicle cannot drive on the area, and the area a square meters is the obstacle influence range.

Specifically, a dividing region of a driving lane with a preset length in front of a target vehicle is obtained, obstacle information in each region is determined, then the obstacle information is analyzed to judge the influence of the obstacles in each region 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, the influence degree is greater than or equal to a preset threshold value, so that the obstacle can prevent the target vehicle from safely driving on the driving road, and the influence range of the obstacle on the driving lane needs to be determined according to the obstacle information; if the influence degree is smaller than the preset threshold value, the obstacle is indicated not to influence the safe running of the target vehicle on the running road, and the obstacle can be eliminated, namely, the influence range of the obstacle on the running lane is not calculated. Therefore, the obstacle influencing the safe running of the target vehicle can be accurately determined according to the obstacle information, and the influence range of the obstacle on the running lane can be accurately obtained.

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

and A1, determining a target obstacle of the target driving lane according to the obstacle movement information on the target driving lane based on the obstacle screening condition.

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

Wherein the obstacle screening conditions include at least one of: the method includes the steps of reserving an obstacle which is positioned on a target driving lane and has a speed of 0, reserving an obstacle which is positioned on other driving lanes and is changed 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 an obstacle which is continuously positioned on the target driving lane within the preset time period.

The obstacle screening condition can be a condition for screening the obstacle on the driving lane, namely, the obstacle which can influence the safe driving of the target vehicle can be accurately determined through the condition, namely, the accurate positioning of the obstacle is realized. The obstacle movement information may be information such as speed, acceleration, position, and movement locus of the obstacle on the traveling lane. The target travel lane may be one of a candidate travel lane and a current travel lane.

Specifically, after each area of a target driving lane with a preset length in front of a target vehicle is determined, obstacle information on each area is acquired, and the obstacle is screened according to the obstacle screening condition and the obstacle movement information of the obstacle on the target driving lane, so that the target obstacle influencing the traffic of the target driving lane is accurately determined, and further, the obstacle influence range on the target driving lane can be accurately determined according to the movement track of the target obstacle in a preset time period, and a rectangular shadow a in fig. 3 is the obstacle influence range of the target obstacle on the area.

For example, if the obstacle a stops on the target driving lane and the speed is zero, it is stated 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 the target obstacle, and since the obstacle a does not move, the obstacle influence 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 positioned 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 not leave the target driving lane, if the speed of the obstacle A is detected to be smaller than the 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 the target obstacle, and the relative relation between the moving position of the obstacle A and the target driving lane within the preset time period is projected so as to accurately determine the 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 is not influenced by the traffic of the target driving lane, so that 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 within the preset time period, the fact that the obstacle has no influence on the traffic of the target lane is indicated, and the obstacle influence range of the obstacle does not need to be recorded;

if the obstacle a is on the other driving lane, but the speed is smaller than the preset speed threshold value and the lane is changed from the other driving lane to the target driving lane in the preset time period, it is stated that the obstacle a is not on the target driving lane in the preset time period, but the obstacle a can travel on the target driving lane in the preset time period, and the speed is smaller than the preset speed threshold value, so that the obstacle a cannot leave the target driving lane in the preset time period, the traffic on the target driving lane is influenced, the obstacle a needs to be marked as the target obstacle, and the relative relation between the moving position of the obstacle a in the preset time period and the target driving lane is projected, so that the influence range of the obstacle a on the target driving lane is accurately determined.

According to the technical scheme, based on the obstacle screening conditions, by analyzing the obstacle movement information on the target driving lane, whether the obstacle can influence the traffic of the target driving lane or not is accurately judged, so that the target obstacle of the target driving lane is accurately determined, the accurate screening of the obstacle is realized, and the situation that the obstacle with no influence or smaller influence is not marked is avoided; and then analyzing the movement track of the target obstacle on the target driving lane within a preset time period to accurately determine the area, which is influenced by the target obstacle, of the target driving lane, namely the obstacle influence range, so that the accurate determination of the obstacle influence range is realized, and the filling value of each area is conveniently determined through the obstacle influence range.

S130, determining filling values of all areas according to coverage information of obstacle influence ranges in all 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 conversely, the more unobstructed the area is.

Specifically, the influence range of the obstacle in each area on the driving lane is obtained, and the coverage information of the influence range of the obstacle in each area is analyzed to accurately obtain the influence condition of the obstacle in each area on the target driving lane, and further, each area is accurately filled, namely, each area is provided 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-B4:

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

Step B2, 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 is determined according to the width of the target vehicle.

And B3, if the width of the drivable path in the target area is greater than or equal to a preset width threshold, respectively positioning the influence range of the obstacle in the target area and the influence range of the obstacle in the adjacent area on two sides of a vehicle driving guide line of a driving lane where the target area is positioned, and if the longitudinal distance between the obstacle in the target area and the obstacle in the adjacent area is smaller than a longitudinal threshold, determining that the filling value of the target area and the adjacent area is 0.

Step B4, if not, 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 fill value is greater than 0.

The travelable road width can be the distance of the obstacle from the road boundary, see distance l in 3. The preset width threshold may be a minimum travel path 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 travel safety distance. The road-boundary travel safety distance may be a minimum distance that allows the vehicle to be away from the road boundary for vehicle travel safety in the road travel norm. The candidate filling value may be a value determined from experience of the history of the vehicle traveling in the traveling lane.

Specifically, acquiring coverage information of an obstacle influence range in a target area, acquiring position information of an obstacle from the coverage information, determining a road boundary distance of the obstacle from the obstacle according to the position information of the obstacle and the position information of the road boundary, namely, a width of a drivable channel, and determining a preset width threshold by adding a road boundary driving safety distance to a body width of a target vehicle; comparing the width of the travelable channel with a preset width threshold value, there are three cases:

first case: if the width of the drivable path in the target area is smaller than the preset width threshold value, which indicates that the area of the driving lane is blocked, the target vehicle cannot pass through the area, and the filling value of the target area is assigned to 0.

Second case: if the width of the travelable lane in the target area is greater than or equal to the preset width threshold value, but the influence range of the obstacle in the target area and the influence range of the obstacle in the adjacent area are respectively located on both sides of the vehicle driving guide line of the driving lane in which the target area is located (see fig. 4), and the longitudinal distance between the obstacle in the target area and the obstacle in the adjacent area is smaller than the longitudinal threshold value, which indicates that the target vehicle cannot pass through the area of the driving lane regardless of detouring, the filling values of the target area and the adjacent area are assigned to 0. For example, the longitudinal threshold in fig. 4 is 10cm, and when the longitudinal distance between the target area and the obstacle in the adjacent area is less than 10cm, the filling value of the target area and the adjacent area needs to be assigned to 0.

Third case: in addition to the above two cases, the target filling value in the target area is determined according to the mapping relationship of the drivable path width and the candidate filling value. The mapping relation can be obtained according to experience information of the historical vehicle driving in the road, namely the obtained one-to-one correspondence relation between the historical drivable channel width and the historical filling value is analyzed, and the mapping relation between the drivable channel width and the candidate filling value is accurately obtained. For example, the mapping relationship between the width of the travelable lane and the candidate filling value may be that the larger the width of the travelable lane is, the larger the candidate filling value is, and the smaller the width of the travelable lane is, the smaller the candidate filling value is. According to the technical scheme, the width of the drivable channel in the target area is compared with the preset width threshold value, so that the passable degree of the target area, which is related to the width of the drivable channel and the preset width threshold value under different conditions, is accurately determined, the filling value of the target area is accurately assigned, and the subsequent misjudgment of road passing efficiency caused by the error of the filling value is avoided, and the control decision of a vehicle is further influenced.

And S140, determining the road traffic efficiency of the driving lane according to the filling value of each area and the road traffic influence parameter.

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

Specifically, the filling value and the road traffic influence parameter of each area on the driving lane are obtained, and the filling value and the road traffic influence parameter of each area are analyzed and processed, so that the road traffic efficiency of the driving lane is accurately determined. For example, the filling value of each area and the influence probability of the road traffic influence parameter on the driving lane are analyzed, the influence probability is analyzed to determine the accurate road traffic efficiency, or the filling value of each area and the road traffic influence parameter are calculated through a formula to obtain an accurate calculated value, and the calculated 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 value of each region and the road traffic influencing parameter, 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 channel switching decision and a forced channel non-switching 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 forced lane-changing decision is made, setting the filling value of the area in the candidate driving lane to be 0.

The driving task information may be information that a user takes a task in advance or temporarily for the target vehicle, for example, the target vehicle is allowed to perform a driving task according to a specified route. The driving environment information can be information of surrounding environment encountered by the target vehicle in the driving process, such as traffic lights or special conditions of stops (buses arrive at the stops and need to stop at the sides), and the like.

Specifically, when the target vehicle encounters some emergency situations during running, in order to ensure that the target vehicle can normally run, whether to issue a forced control decision to the target vehicle needs to be judged, if so, the road traffic efficiency of the driving lane needs to be set to be changed in a rule forced manner, that is, the minimum range (such as all areas of the driving lane needing to be filled) in front of the road is virtually filled, so that the road traffic efficiency of the lane where the vehicle runs is ensured to be greater than the road traffic efficiency of other lanes, and the vehicle can be ensured to run safely.

The specific rules are as follows: judging whether the target vehicle is in a forced lane change decision or a forced lane non-change decision; if the forced lane change decision is made, if a task is temporarily issued to the target vehicle to change lanes, virtually filling the area in the current driving lane of the target vehicle, wherein the filling value is set to 0 so as to ensure that the road traffic efficiency of the current driving lane is smaller than that of the candidate driving lane and further complete the forced lane change of the target vehicle; if the decision of not changing lanes is forced, such as the situation of meeting traffic lights, the target vehicle can not change lanes according to traffic rules, so that virtual filling of the area in the candidate driving lane is required, and the filling value is set to 0, so that the road traffic efficiency of the candidate driving lane is ensured to be smaller than that of the current driving lane, and no lane changing operation of the target vehicle is ensured.

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 a forced control decision to the target vehicle, so that the target vehicle can safely run according to the issued forced control decision.

And 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 makes safe driving for avoiding an obstacle.

Specifically, the road traffic efficiency of the driving lane of the target vehicle is obtained, and the road traffic efficiency is analyzed and processed, for example, by comparing the road traffic efficiency with the historical experience, whether the road traffic efficiency of the driving lane can ensure that the target vehicle can safely drive or whether the road traffic efficiency of the driving lane can ensure that the target vehicle can safely drive is determined by setting a new analysis rule for the road traffic efficiency, so that the accurate determination of the obstacle avoidance control decision of the target vehicle is realized, and the target vehicle can safely drive on the driving lane.

According to the technical scheme, the area division is carried out on the driving lanes with the preset length in front of the 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 areas according to coverage information of obstacle influence ranges in all areas on a driving lane; determining the road traffic efficiency of the driving lane according to the filling value of each area and the road traffic influence parameter; and determining an obstacle avoidance control decision of the target vehicle according to the road traffic efficiency of the driving lane. According to the technical scheme, the driving lane in front of the target vehicle is divided into a plurality of areas according to the preset length, so that the driving lane in front of the target vehicle can be accurately determined, the obstacles in the plurality of 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 target obstacle information on the driving lane, and the influence range of the obstacles on each area on the driving lane is more definite; and then, the coverage information of the obstacle influence range 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 parameters 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, thereby solving the problem that the road obstacle influences the safe forward movement of the vehicle.

Example two

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

s210, dividing the area of a driving lane with a preset length in front of the target vehicle.

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

S230, determining filling values of all areas according to coverage information of obstacle influence ranges in all areas on a 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 regional weight is determined according to the driving style risk factor and the longitudinal distance between the regional center and the target vehicle. The driving style risk factors can be determined according to the historical driving conditions of the driver, namely, the historical driving conditions of the driver are evaluated, and the driving style is more aggressive, the corresponding lane distance is shorter, and the corresponding driving style risk factors are correspondingly larger.

Specifically, the attention degree to the front driving lane is different in different driving styles, so 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, further the subsequent road filling value determination can be more accurate, and then the filling values of the regions are combinedAccurate determination of the road filling value of a driving lane +.>Ketong (Chinese character)The determination is made by the following formula:

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

wherein w is _i The region weight of the ith region on the driving lane is represented, C represents the maximum weight value in a preset short-distance range, L _w Represents the average lane change trigger distance, sigma _w Representing the fluctuation variance of the lane change triggering distance, and gamma represents the driving style risk factor, s _i The longitudinal distance of the region center of the i-th region from the target vehicle is represented.

The maximum weight value in the preset short-distance range can be adjusted according to summary analysis on historical experience. The average lane change trigger 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 situation, lane lines, vehicle execution tasks, lane change styles and the like, and the data are analyzed to determine a corresponding relation diagram (as shown in fig. 6) between the weight and the lane change trigger distance, so that the average lane change trigger distance can be accurately determined. The fluctuation variance of the channel switching trigger distance can be the range of the channel switching trigger distance allowed to float up and down, and can be set according to actual conditions.

Specifically, for determination of the zone weight, the longitudinal distance s from the zone center to the target vehicle may be determined _i Average lane change distance γl combined with driving style risk _w Judging; if the longitudinal distance between the center of the region and the target vehicle is smaller than or equal to the average lane change distance, the region weight is a first weight threshold; if the longitudinal distance between the center of the region and the target vehicle is greater than the average lane change distance, the region weight is a second weight threshold; wherein the first weight threshold is greater than the second weight threshold.

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

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

Wherein the road traffic impact parameters include zone weights and driving style risk factors.

Specifically, a road filling value and a road traffic influence parameter are obtained, and the road filling value and the road traffic influence parameter are analyzed, for example, the road filling value and the road traffic influence parameter are combined together for analysis, the influence degree on the road traffic is determined, and then the road traffic efficiency of a driving lane is judged according to the influence degree, or the filling value and the road traffic influence parameter are calculated through a formula, so that the road traffic efficiency of the driving lane is accurately obtained; and making an obstacle avoidance control decision for the target vehicle according to the 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,represents the average area filling value, sigma of the calibration road _p Representing the fluctuating variance of the road area filling value, +.>And representing the road filling value, W represents the total weight of the area on the driving lane, and gamma represents the driving style risk factor.

In particular, the method comprises the steps of,training and obtaining 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 the vehicle, obstacle distribution situation, lane lines, vehicle execution tasks or lane changing style, and the like, and the historical driving data is trained to obtain the filling value of the historical driving data and the average area filling value of the calibration road- >Then the filling value of the average area of the calibration road can be accurately determined by the mapping relation>

The total weight W of the areas on the driving lane is obtained by weighting the areas of each area _i The formula obtained by summing is as follows:

according to the technical scheme, the road filling value and the road traffic influence parameter are combined together through the formula, so that the road traffic efficiency is accurately determined; the driving style risk factors are introduced to enable the road traffic efficiency to be closer to the actual driving situation, errors in determination of the road traffic efficiency caused by too large deviation from the actual driving situation are avoided to influence the running of the vehicle, meanwhile, errors possibly occurring in the actual process are considered in consideration of the fluctuation variance of the average area filling value of the calibration road and the filling value of the road area, the determination of the road traffic efficiency is enabled to be more fit with the actual situation, namely the road traffic efficiency is more representative, and obstacle avoidance control decisions of the target vehicle finally determined according to the road traffic efficiency are enabled to be more accurate.

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

Wherein, the obstacle avoidance control decision comprises intra-road obstacle avoidance, lane changing obstacle avoidance and lane borrowing obstacle avoidance. The in-lane obstacle avoidance can be that the target vehicle does not change lanes and only runs in the lane where the vehicle is currently running to avoid the obstacle. The lane change obstacle avoidance can be that the lane where the current target vehicle runs cannot continue to run, the lane needs to be changed to other lanes for running, and the lane after the lane change can be kept on the lane after the lane change for continuing to run. The obstacle avoidance by road can be that the target vehicle needs to temporarily borrow other lanes to avoid the obstacle when the current driving lane cannot be driven, and the target vehicle returns to the original driving lane to continue driving after the obstacle avoidance is successful.

In a 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:

and D1, if the road traffic efficiency of the current driving lane is smaller than a preset efficiency threshold, the difference between the road traffic efficiency of the candidate driving lane and the road traffic efficiency of the current driving lane is larger than a first efficiency difference, the road traffic 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 obstacle avoidance by road.

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

And D3, otherwise, determining that the obstacle avoidance control decision of the target vehicle is an in-track 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 in fig. 7, P1 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 for the target vehicle may be assigned as follows:

when P1 is less than Q, indicating that the current driving lane is blocked or other special conditions exist, and the target vehicle cannot normally pass, comparing the difference value of P2 and P1 with the difference value of G1 and G2 respectively, and simultaneously determining whether P2 is greater than or equal to Q and whether the safety behind the candidate driving lane is safe or not, so as to allocate a proper obstacle avoidance control decision for the target vehicle; if P2-P1> G1, P2 is more than or equal to Q and the rear of the candidate driving lane is safe, the candidate driving lane is clear, but the road traffic efficiency of the candidate driving lane can not enable the target vehicle to continuously drive on the lane, the road can be used as a temporary obstacle avoidance channel, namely a command of the target vehicle for issuing a road-borrowing obstacle avoidance, and the target vehicle needs to return to the original current driving lane to continue driving after the road-borrowing obstacle avoidance task is executed; if P2-P1> G2 and P2 are more than or equal to Q and the rear of the candidate driving lane is safe, the candidate driving lane is clear, the road traffic efficiency of the candidate driving lane can enable the target vehicle to continuously drive on the lane, namely, a lane changing and obstacle avoidance instruction can be issued for the target vehicle, and the target vehicle can keep driving in the candidate driving lane after lane changing; except for the situations that the target vehicle needs to change the lane to avoid the obstacle or borrow the lane to avoid the obstacle, the other situations that the current driving lane can enable the target vehicle to avoid the obstacle successfully so as to normally pass, namely, the target vehicle gives an instruction of avoiding the obstacle in the lane so as to enable the target vehicle to avoid the obstacle to drive.

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

the active release conditions of lane change obstacle avoidance are as follows: the target vehicle enters a first preset distance (e.g., the first preset distance is 0.2 m) of the candidate driving lane;

the conditions of the lane change obstacle avoidance passive release are as follows: after the lane change is triggered to avoid the obstacle, 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 traffic efficiency of the candidate driving lane is smaller than a first preset traffic threshold (for example, the first preset traffic threshold is 0.6), or the road traffic efficiency of the current driving lane is larger than the second preset traffic threshold (for example, the second preset traffic threshold is 0.8);

the conditions of the active relief of obstacle avoidance by passage are as follows: the target vehicle returns to the current driving lane, runs centrally and returns to the current driving lane within a first preset distance transversely;

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

According to the technical scheme, the road traffic efficiency of the current driving lane, the road traffic efficiency of the candidate driving lane, the preset efficiency threshold value, the first efficiency difference value, the second efficiency difference value and the safety behind the candidate driving lane are analyzed and processed, whether the current driving lane or the candidate driving lane can normally pass through a target vehicle or not is accurately judged, and then a proper obstacle avoidance control decision is matched with the target vehicle, so that accurate control of the target vehicle is realized, and the influence on safe driving of the target vehicle due to obstacles is avoided.

According to the technical scheme, the driving lanes in front of the target vehicle are divided into the areas by the preset length of the driving lanes, so that the driving lanes in front of the target vehicle can be determined to be divided into the areas, and the obstacles in the areas are subjected to key analysis; further determining the influence range of the obstacle on the driving lane according to the obstacle information on the driving lane, so that the influence range of the obstacle on each area on the driving lane is more definite, and the filling value of each area is determined according to the coverage information of the influence range of the obstacle 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 obstacle of each region on the region, and further accurately determining the road filling value of the driving lane by combining the filling value of each region and the region weight through a formula, so that the road traffic efficiency of the driving lane is more accurately determined through the road filling value and the road traffic influence parameter; and finally, analyzing the road traffic efficiency to determine the traffic situation of the driving lane, and further matching a proper obstacle avoidance control decision for the target vehicle according to the traffic situation.

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 area dividing module 310 is configured to divide areas of a driving lane with a preset length in front of the target vehicle; the driving lanes comprise candidate driving lanes and current driving lanes, and the driving direction of the candidate driving lanes is the same as that of the current driving lanes;

a range determining module 320, configured to determine an obstacle impact 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;

an efficiency determining module 340, configured to determine road traffic efficiency of the driving lane according to the filling value and the road traffic influencing parameter of each region;

the decision module 350 is configured to determine an obstacle avoidance control decision of the target vehicle according to the road traffic 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 movement information on the target driving lane based on the obstacle screening condition;

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

wherein the obstacle screening conditions include at least one of: and reserving an obstacle which is positioned on the target driving lane and has a speed of 0, reserving an obstacle which is positioned on other driving lanes and is changed from the other driving lanes to the target driving lane within a preset time period and has a speed of less than a preset speed threshold value, and reserving an obstacle which is continuously positioned on the target driving lane within the 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 is determined according to the width of the target vehicle;

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

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 fill 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 of each region and the region weight;

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

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

optionally, the efficiency determining module includes an operation unit, specifically configured to:

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

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

Optionally, the decision module is specifically configured to:

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

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

Otherwise, determining that the obstacle avoidance control decision of the target vehicle is an intra-track obstacle avoidance;

Wherein the obstacle avoidance control decision comprises intra-road obstacle avoidance, lane changing obstacle avoidance and lane borrowing obstacle avoidance.

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

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 channel switching decision and a forced channel non-switching decision;

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

and if the forced lane-changing decision is made, setting the filling value of the area in the candidate driving lane to 0.

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

The technical scheme of the application is used for acquiring, storing, using and processing the data, and the like, which accords with the relevant regulations of national laws and regulations and does not violate the popular public order.

Example IV

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

Fig. 9 shows a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the 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. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, 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, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may 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.

Various 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, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an 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 specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. 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 on 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, processor 11 may be configured to perform the vehicle obstacle avoidance control method in any other suitable manner (e.g., by means of firmware).

Various implementations of the systems and techniques described here above can be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On 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, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for carrying out 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 implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the 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. The 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 portable 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) through 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 may 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 input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background 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 background, 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. The client and server are typically 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 hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims

1. A vehicle obstacle avoidance control method, comprising:

Determining filling values of all areas according to coverage information of obstacle influence ranges in all areas on the driving lane; the filling value of each region is used for representing the congestion condition of each region on a driving lane, and the smaller the filling value is, the more congested the region is;

determining the road traffic efficiency of the driving lane according to the filling value of each region and the road traffic influence parameter; the road traffic influencing parameter is a factor influencing the safe traffic of the target vehicle on the road; road traffic efficiency is the probability that a target vehicle passes through a road safely and efficiently;

determining an obstacle avoidance control decision of the target vehicle according to the road traffic efficiency of the driving lane, wherein the obstacle avoidance control decision comprises intra-lane obstacle avoidance, lane changing obstacle avoidance and lane borrowing obstacle avoidance;

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

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

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

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; the candidate filling value is larger than 0, the width of the drivable channel and the candidate filling value are in a forward relation, and the mapping relation is determined according to the one-to-one correspondence relation between the historical drivable channel width of the historical vehicle driving in the road and the historical filling value.

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

correspondingly, determining the road traffic efficiency of the driving lane according to the filling value of each region and the road traffic influence parameter comprises the following steps:

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

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

7. The method of claim 1, wherein prior to determining the road traffic efficiency of the travel lane based on the fill value and the road traffic impact parameter for each zone, the method further comprises:

8. A vehicle obstacle avoidance control device, comprising:

the filling value determining module is used for determining the filling value of each region according to the coverage information of the obstacle influence range in each region on the driving lane; the filling value of each region is used for representing the congestion condition of each region on a driving lane, and the smaller the filling value is, the more congested the region is;

the efficiency determining module is used for determining the road traffic efficiency of the driving lane according to the filling value of each area and the road traffic influence parameter; the road traffic influencing parameter is a factor influencing the safe traffic of the target vehicle on the road; road traffic efficiency is the probability that a target vehicle passes through a road safely and efficiently;

the decision module is used for determining an obstacle avoidance control decision of the target vehicle according to the road traffic efficiency of the driving lane, wherein the obstacle avoidance control decision comprises intra-lane obstacle avoidance, lane changing obstacle avoidance and lane borrowing obstacle avoidance;

Correspondingly, the decision module is specifically configured to:

9. An electronic device, the electronic device comprising:

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 1-7.