Path planning method and device, autonomous vehicle and storage medium

Abstract

The present disclosure discloses a path planning method and device, an automatic driving vehicle and a storage medium, and relates to the field of vehicles, in particular to the field of automatic driving. The specific implementation scheme is: according to a gap information set and target driving information of a target automatic driving vehicle, a first merging condition set between the target automatic driving vehicle and a first vehicle is obtained, and a second merging condition set between the target automatic driving vehicle and a second vehicle is obtained; according to the first merging condition and the second merging condition, a merging initial time point and a merging end time point are determined; according to the merging initial time point and the merging end time point, a merging start position and a merging end position of the target automatic driving vehicle are determined; and according to the merging start position and the merging end position, a lane-changing merging path of the target automatic driving vehicle is planned. The present disclosure adopting the above scheme can improve the lane-changing capability of the automatic driving vehicle.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of vehicles, in particular to the field of automatic driving, and specifically to a path planning method and device, an automatic driving vehicle and a storage medium. BACKGROUND

[0002] With the development of science and technology and the continuous improvement of people's living standards, the proportion of individuals owning vehicles is increasing, and vehicles have become increasingly popular household goods. In the related art, an automatic driving vehicle has the function of automatically or automatically assisting lane switching. However, when switching lanes, it mainly adopts a passive merging into traffic flow mode and cannot actively merge into traffic flow, and the lane changing ability is poor. SUMMARY

[0003] The present disclosure provides a path planning method and device, an automatic driving vehicle and a storage medium, and the main purpose is to improve the lane changing ability of the automatic driving vehicle.

[0004] According to an aspect of the present disclosure, a path planning method is provided, comprising:

[0005] According to the gap information set and the target driving information of the target automatic driving vehicle, a first merging condition set between the target automatic driving vehicle and a first vehicle is obtained, and a second merging condition set between the target automatic driving vehicle and a second vehicle is obtained, wherein the first vehicle is a rear vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges into a lane, the second vehicle is a front vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges into a lane, and the gap information set includes gap information between a plurality of adjacent vehicle pairs on a target driving lane, and the target driving lane is a driving lane after the target driving vehicle merges into a lane;

[0006] According to the first merging condition set and the second merging condition set, a merging initial time point and a merging end time point are determined;

[0007] According to the merging initial time point and the merging end time point, a merging start position and a merging end position of the target automatic driving vehicle are determined;

[0008] According to the merging start position and the merging end position, a lane merging path of the target automatic driving vehicle is planned.

[0009] According to another aspect of the present disclosure, a path planning device is provided, comprising:

[0010] The condition acquisition unit is configured to acquire a first merging condition set between the target automatic driving vehicle and a first vehicle and a second merging condition set between the target automatic driving vehicle and a second vehicle according to the gap information set and target driving information of the target automatic driving vehicle, wherein the first vehicle is a rear vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges into a lane, the second vehicle is a front vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges into a lane, and the gap information set includes gap information between a plurality of adjacent vehicle pairs on a target driving lane, which is a driving lane after the target driving vehicle merges into a lane;

[0011] The time determination unit is configured to determine a merging initial time point and a merging end time point according to the first merging condition set and the second merging condition set.

[0012] The position determination unit is configured to determine a merging start position and a merging end position of the target automatic driving vehicle according to the merging initial time point and the merging end time point.

[0013] The path planning unit is configured to plan a lane-merging path of the target automatic driving vehicle according to the merging start position and the merging end position.

[0014] According to another aspect of the present disclosure, an automatic driving vehicle is provided, comprising:

[0015] at least one processor; and

[0016] a memory connected with the at least one processor; wherein

[0017] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of the preceding aspects.

[0018] According to another aspect of the present disclosure, a non-transitory computer readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to perform the method of any one of the preceding aspects.

[0019] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method of any one of the preceding aspects.

[0020] In one or more embodiments of the present disclosure, a first merging condition set between the target automatic driving vehicle and a first vehicle and a second merging condition set between the target automatic driving vehicle and a second vehicle are obtained according to a gap information set and target driving information of the target automatic driving vehicle, the first vehicle is a rear vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges into a target lane, the second vehicle is a front vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges into the target lane, the gap information set includes gap information between a plurality of adjacent vehicle pairs on a target driving lane, and the target driving lane is a driving lane after the target driving vehicle merges into the target lane; a merging start time point and a merging end time point are determined according to the first merging condition set and the second merging condition set; a merging start position and a merging end position of the target automatic driving vehicle are determined according to the merging start time point and the merging end time point; and a merging path of the target automatic driving vehicle is planned according to the merging start position and the merging end position. Therefore, the lane changing capability of the automatic driving vehicle can be improved.

[0021] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present disclosure, nor to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0022] The accompanying drawings are used to better understand the present scheme and do not limit the present disclosure. Among them:

[0023] Figure 1 is a flowchart of a path planning method according to a first embodiment of the present disclosure;

[0024] Figure 2 is a flowchart of a path planning method according to a second embodiment of the present disclosure;

[0025] Figure 3 is an example schematic diagram of a path planning method according to a second embodiment of the present disclosure;

[0026] Figure 4 is an example schematic diagram of a gap information set according to a second embodiment of the present disclosure;

[0027] Figure 5 is an example schematic diagram of a merging into a lane according to a second embodiment of the present disclosure;

[0028] FIG. 6(a) is a structural schematic diagram of a first path planning device for implementing a path planning method according to an embodiment of the present disclosure;

[0029] FIG. 6(b) is a structural schematic diagram of a second path planning device for implementing a path planning method according to an embodiment of the present disclosure;

[0030] Fig. 6(c) is a structural schematic diagram of a third path planning device for implementing the path planning method according to an embodiment of the present disclosure;

[0031] Fig. 6(d) is a structural schematic diagram of a fourth path planning device for implementing the path planning method according to an embodiment of the present disclosure;

[0032] Fig. 6(e) is a structural schematic diagram of a fifth path planning device for implementing the path planning method according to an embodiment of the present disclosure;

[0033] Fig. 6(f) is a structural schematic diagram of a sixth path planning device for implementing the path planning method according to an embodiment of the present disclosure;

[0034] Figure 7 Fig. 7 is a block diagram of an autonomous vehicle for implementing the path planning method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] Exemplary embodiments of the present disclosure are described herein with reference to the accompanying drawings, which are meant to be exemplary. Therefore, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, for the sake of brevity and clarity, descriptions of well-known functions and constructions are omitted herein.

[0036] With the development of science and technology, the development of autonomous vehicles is also increasingly rapid, and the requirements of people for autonomous vehicles are also increasing day by day. In the related art, an autonomous vehicle can have the function of automatically or automatically assisting lane switching.

[0037] As can be easily understood, when an autonomous vehicle automatically or automatically assists lane switching, it mainly adopts the passive merging into traffic flow mode and cannot actively merge into the traffic flow, and the lane changing ability is poor. At the same time, it does not have the ability to actively exclude conditions, for example, when there is an obstacle in front or a car accident occurs in front, the autonomous vehicle has no lane changing avoidance action.

[0038] The present disclosure will be described in detail below with reference to specific embodiments.

[0039] In a first embodiment, as shown in Figure 1 , Figure 1 Fig. 1 is a flowchart of a path planning method according to a first embodiment of the present disclosure. The method can be implemented by relying on a computer program and can be run on a device for path planning. The computer program can be integrated in an application or run as an independent tool application.

[0040] The path planning device can be an autonomous vehicle with a path planning function, including but not limited to a cargo vehicle, an off-road vehicle, a dump truck, a tractor vehicle, a special vehicle, a passenger car, a sedan, a semi-trailer, and other vehicles with autonomous driving function.

[0041] Specifically, the path planning method comprises:

[0042] S101, obtaining a first merging condition between the target autonomous vehicle and the first vehicle according to the gap information set and the target driving information of the target autonomous vehicle, and obtaining a second merging condition between the target autonomous vehicle and the second vehicle;

[0043] According to some embodiments, the gap information refers to the information of the gap between the target autonomous vehicle and the surrounding obstacles. The gap information is not specific to a fixed information. The gap information includes but is not limited to front vehicle gap information, target gap information, rear vehicle gap information, etc. The target gap information may, for example, be the autonomous vehicle gap corresponding to the target autonomous vehicle merging point. The front vehicle gap information may, for example, be the gap between the adjacent vehicle pairs in the same direction as the target autonomous vehicle and located in front of the target autonomous vehicle when the target autonomous vehicle merges by changing lanes. The rear vehicle gap information may, for example, be the gap between the adjacent vehicle pairs in the same direction as the target autonomous vehicle and located behind the target autonomous vehicle when the target autonomous vehicle merges by changing lanes.

[0044] In some embodiments, the gap information set refers to a set aggregated by at least one gap information. The gap information set can include the gap information between multiple adjacent vehicle pairs on the target driving lane, that is, the gap information between multiple adjacent vehicle pairs on the driving lane after the target driving vehicle merges by changing lanes, that is, at least one of the front vehicle gap information, the target gap information, and the rear vehicle gap information.

[0045] The gap information between adjacent vehicle pairs is used to indicate the gap information between two adjacent vehicles.

[0046] According to some embodiments, the target autonomous vehicle refers to an autonomous vehicle that needs to perform a lane change merging operation.

[0047] According to some embodiments, the driving information refers to the relevant information of the autonomous vehicle during driving. The driving information includes but is not limited to vehicle speed, driving acceleration, driving path, etc. The target driving information refers to the driving information corresponding to the target autonomous vehicle required when the target autonomous vehicle changes lanes and merges. The target driving information includes but is not limited to the speed of the target autonomous vehicle, the position of the target autonomous vehicle, etc.

[0048] In some embodiments, the first vehicle is a rear vehicle of the target autonomous vehicle when the target autonomous vehicle changes lanes to merge, and the second vehicle is a front vehicle of the target autonomous vehicle when the target autonomous vehicle changes lanes to merge.

[0049] In some embodiments, the first set of merging conditions refers to a set of safety conditions between the target autonomous vehicle and the first vehicle when the target autonomous vehicle merges, and the second set of merging conditions refers to a set of safety conditions between the target autonomous vehicle and the second vehicle when the target autonomous vehicle merges.

[0050] It is easy to understand that when the autonomous vehicle plans a path, the autonomous vehicle can obtain the first set of merging conditions between the target autonomous vehicle and the first vehicle according to the set of gap information and the target driving information of the target autonomous vehicle, and obtain the second set of merging conditions between the target autonomous vehicle and the second vehicle.

[0051] S102, determining a merging initial time point and a merging end time point according to the first set of merging conditions and the second set of merging conditions;

[0052] According to some embodiments, the merging initial time point refers to a time point when the target autonomous vehicle starts to change lanes to merge into any lane, and the merging end time point refers to a time point when the target autonomous vehicle ends to change lanes to merge into any lane.

[0053] It is easy to understand that when the autonomous vehicle obtains the first set of merging conditions and the second set of merging conditions, the autonomous vehicle can determine the merging initial time point and the merging end time point according to the first set of merging conditions and the second set of merging conditions.

[0054] S103, determining a merging start position and a merging end position of the target autonomous vehicle according to the merging initial time point and the merging end time point;

[0055] According to some embodiments, the merging start position refers to a position when the target autonomous vehicle starts to change lanes to merge into any lane, and the merging end position refers to a position when the target autonomous vehicle ends to change lanes to merge into any lane.

[0056] It is easy to understand that when the autonomous vehicle obtains the merging initial time point and the merging end time point, the autonomous vehicle can determine the merging start position and the merging end position of the target autonomous vehicle according to the merging initial time point and the merging end time point.

[0057] S104, planning a lane-changing merging path of the target autonomous vehicle according to the merging start position and the merging end position.

[0058] According to some embodiments, the lane-changing merging path refers to a driving path of the target autonomous vehicle when merging into any lane.

[0059] It is easy to understand that when the autonomous vehicle obtains the merging start position and the merging end position, the autonomous vehicle can plan the lane-changing merging path of the target autonomous vehicle according to the merging start position and the merging end position.

[0060] In the embodiments of the present disclosure, by obtaining a first merging condition set between the target autonomous vehicle and the first vehicle according to the gap information set and target driving information of the target autonomous vehicle, a second merging condition set between the target autonomous vehicle and the second vehicle is obtained; according to the first merging condition set and the second merging condition set, a merging initial time point and a merging end time point are determined; according to the merging initial time point and the merging end time point, a merging start position and a merging end position of the target autonomous vehicle are determined; and according to the merging start position and the merging end position, a lane-changing merging path of the target autonomous vehicle is planned. Therefore, by determining the merging time point according to the gap information set, and determining the merging position according to the merging time point, the lane-changing merging path planning of the target autonomous vehicle is performed according to the merging position, so that the autonomous vehicle can actively merge according to the planned lane-changing merging path under the traffic flow, and the lane-changing ability of the autonomous vehicle can be improved.

[0061] Please refer to Figure 2 , Figure 2 is a flowchart of a path planning method according to the second embodiment of the present disclosure. Specifically,

[0062] S201, according to the gap information set and the target driving information of the target autonomous vehicle, the target gap information corresponding to the target autonomous vehicle in the gap information set is determined;

[0063] According to some embodiments, Figure 3 is an example schematic diagram of a path planning method according to the second embodiment of the present disclosure. Wherein, the target autonomous vehicle may, for example, be a C vehicle, the first vehicle may, for example, be a B vehicle, and the second vehicle may, for example, be an A vehicle.

[0064] In some embodiments, Figure 4 is an example schematic diagram of a gap information set according to the second embodiment of the present disclosure. The gap information set may, for example, include front vehicle gap information, target gap information, and rear vehicle gap information, wherein the number of target gap information may be one, and the number of front vehicle gap information and rear vehicle gap information may be at least one.

[0065] In some embodiments, the target gap information is used to indicate a target gap when the target autonomous vehicle changes lanes and merges. The target gap information may, for example, be greater than the length of the target autonomous vehicle. When the autonomous vehicle obtains the target gap information corresponding to the target autonomous vehicle, the first vehicle, i.e., the rear vehicle, when the target autonomous vehicle changes lanes and merges can be determined according to the target gap information. The second vehicle, i.e., the front vehicle, when the target autonomous vehicle changes lanes and merges can also be determined according to the target gap information.

[0066] S202, according to the target gap information, determining the first vehicle and the second vehicle, obtaining first driving information of the first vehicle and second driving information of the second vehicle;

[0067] It is easy to understand that the first driving information refers to the driving information corresponding to the first vehicle. The second driving information refers to the driving information corresponding to the second vehicle.

[0068] According to some embodiments, the first driving information of the first vehicle and the second driving information of the second vehicle can be obtained. For example, the first driving information of the B vehicle and the second driving information of the C vehicle can be obtained, specifically, the speed of the B vehicle and the speed of the C vehicle can be obtained.

[0069] S203, according to the target gap information, the target driving information of the target autonomous vehicle and the first driving information, determining a first merging condition set;

[0070] According to some embodiments, the autonomous vehicle can also determine a distance information set between the target autonomous vehicle and the first vehicle according to the target driving information of the target autonomous vehicle and the first driving information.

[0071] According to some embodiments, the distance information set refers to a collective formed by at least one distance information. The distance information set may, for example, include at least one distance information.

[0072] It is easy to understand that the distance information set includes a first distance corresponding to a merging initial time point and a second distance corresponding to a merging end time point. The first distance refers to the distance between the target autonomous vehicle and the first vehicle at the merging initial time point, and the second distance refers to the distance between the target autonomous vehicle and the first vehicle at the merging end time point.

[0073] According to some embodiments, when the first distance and the second distance are obtained by the autonomous vehicle, the autonomous vehicle can obtain a half vehicle length of the target autonomous vehicle, and subtract the half vehicle length from the first distance and the second distance to obtain an adjusted first distance and an adjusted second distance. That is, if the position of the head of the target autonomous vehicle is needed, the half vehicle length needs to be added, and if the position of the tail of the target autonomous vehicle is needed, the half vehicle length needs to be subtracted, which can improve the accuracy of obtaining at least one merging condition and improve the accuracy of the lane changing path planning.

[0074] According to some embodiments, the autonomous vehicle can also determine the target speed of the target autonomous vehicle at the initial merging time point according to the current speed and acceleration of the target autonomous vehicle.

[0075] It is easy to understand that, Figure 5 is an example schematic diagram of a lane change merging according to a second embodiment of the present disclosure. Wherein the lane change merging can be divided into two stages of lane change preparation and straight lane change, as Figure 5 As shown, the former part is uniform acceleration motion, and the time range is (0, t1), that is, the time point corresponding to t1 is the initial merging time point, and the latter part is uniform motion, and the time range is (t1, t1+t2). That is, the time point corresponding to t1 is the end time point of merging, and a fixed constant t3 (0≤t3≤t2) is defined, then (t1, t1+t3) is the time range that needs to be considered for the safety of the following vehicle during the merging gap process.

[0076] According to some embodiments, when 0≤t≤t1:

[0077] v(t)=v1(t)=v0+at

[0078] s(t)=s1(t)=s0+v0t+0.5at 2

[0079] Wherein v(t) is the speed of the target autonomous vehicle between 0≤t≤t1; s(t) is the driving distance of the target autonomous vehicle; a is the driving acceleration of the target autonomous vehicle; v1(t) is the speed of the target autonomous vehicle at t1;

[0080] In some embodiments, when t≥t1:

[0081] v(t)=v2(t)=v0+at1

[0082] s(t)=s2(t)=s0+v0t+0.5at 2 +(v0+at1)*(t-t1)

[0083] It is easy to understand that the speed and position of the first vehicle:

[0084] sB (t) = s B0 + v B t

[0085] where s B0 is the first vehicle head position; s B (t) is the first vehicle travel distance.

[0086] It is easy to understand that the second vehicle speed and position:

[0087] s A (t) = s A0 + v A t

[0088] where s A0 is the first vehicle head position; s A (t) is the first vehicle travel distance.

[0089] According to some embodiments, the first merging condition set can include a first merging condition, a second merging condition, a third merging condition, and a fourth merging condition. At this time, when the autonomous vehicle determines the first merging condition set, the autonomous vehicle can:

[0090] determine the first merging condition in the first merging condition set, wherein the first merging condition is that the first distance is greater than the first distance threshold, and the first distance threshold is determined based on the headway time of the first vehicle and the first vehicle speed in the first traffic information;

[0091] determine the second merging condition in the first merging condition set, wherein the second merging condition is that the first distance is greater than the second distance threshold, and the second distance threshold is determined based on the collision time of the first vehicle, the first vehicle speed and the target vehicle speed;

[0092] determine the third merging condition in the first merging condition set, wherein the third merging condition is that the second distance is greater than the first distance threshold;

[0093] determine the fourth merging condition in the first merging condition set, wherein the fourth merging condition is that the second distance is greater than the second distance threshold.

[0094] It is easy to understand that, at t1≤t≤t1+t3, the first merging condition to the fourth merging condition can be, for example:

[0095] First merging condition: s2(t1)-s B (t1) > B*v B ;

[0096] Second merging condition: s2(t1)-s B (t1) > TTC B *(v B-v0-at1);

[0097] The third merging condition: s2(t1+t3)-s B (t1+t3) > THW B *v B ;

[0098] The fourth merging condition: s2(t1+t3)-s B (t1+t3) > TTC B *(v B -v0-at1);

[0099] wherein THW refers to the estimated time for the target autonomous vehicle to reach the current position of the second vehicle by keeping the current running state, i.e., the inter-vehicle distance; THW B refers to the estimated time for the first vehicle to reach the current position of the target autonomous vehicle by keeping the current running state; TTC refers to the estimated time for the target autonomous vehicle and the second vehicle to collide by keeping the current running state, i.e., the collision time; TTC B refers to the estimated time for the first vehicle and the target autonomous vehicle to collide by keeping the current running state.

[0100] S204, determining a second merging condition set according to the target gap information, the target driving information of the target autonomous vehicle and the second driving information.

[0101] According to some embodiments, the autonomous vehicle can determine a distance information set between the target autonomous vehicle and the second vehicle according to the target driving information of the target autonomous vehicle and the second driving information.

[0102] In some embodiments, the distance information set includes a third distance corresponding to the merging initial time point and a fourth distance corresponding to the merging end time point.

[0103] It is easy to understand that the distance information set includes a third distance corresponding to the merging initial time point and a fourth distance corresponding to the merging end time point. Wherein the third distance refers to the distance between the target autonomous vehicle and the second vehicle at the merging initial time point, and the fourth distance refers to the distance between the target autonomous vehicle and the second vehicle at the merging end time point.

[0104] According to some embodiments, when the autonomous vehicle obtains the third distance and the fourth distance, the autonomous vehicle can obtain a half vehicle length of the target autonomous vehicle, and add the half vehicle length to the third distance and the fourth distance to obtain an adjusted third distance and an adjusted fourth distance. That is, if the head position of the target autonomous vehicle is needed, the half vehicle length needs to be added, and if the tail position of the target autonomous vehicle is needed, the half vehicle length needs to be subtracted, which can improve the accuracy of obtaining at least one merging condition and improve the accuracy of the lane changing path planning.

[0105] According to some embodiments, the second merging condition set can include a fifth merging condition, a sixth merging condition, a seventh merging condition, and an eighth merging condition. At this time, when the autonomous vehicle determines the second merging condition set, the autonomous vehicle can:

[0106] determine the fifth merging condition in the second merging condition set, wherein the fifth merging condition is that the third distance is greater than a third distance threshold, and the third distance is determined based on the inter-vehicle time interval of the target autonomous vehicle and the target vehicle speed in the target traffic information;

[0107] determine the sixth merging condition in the second merging condition set, wherein the sixth merging condition is that the third distance is greater than a fourth distance threshold, and the fourth distance is determined based on the collision time of the target autonomous vehicle, the second vehicle speed in the second traffic information, and the target vehicle speed;

[0108] determine the seventh merging condition in the second merging condition set, wherein the seventh merging condition is that the fourth distance is greater than the third distance threshold;

[0109] determine the eighth merging condition in the second merging condition set, wherein the eighth merging condition is that the fourth distance is greater than the fourth distance threshold.

[0110] It is easy to understand that, at t1≤t≤t1+t3, the fifth merging condition to the eighth merging condition can be, for example:

[0111] the fifth merging condition: s A (t1)-s2(t1)>THW*(v0+at1);

[0112] the sixth merging condition: s A (t1)-s2(t1)>TTC*(v0+at1-v A );

[0113] the seventh merging condition: s A (t1+t2)-s2(t1+t2)>THW*(v0+at1);

[0114] the eighth merging condition: s A (t1+t2)-s2(t1+t2)>TTCB (v0+at1-v A );

[0115] According to some embodiments, the THW B , the TTC B , the THW and the TTC are parameters, and the parameters are not specific to a fixed parameter value, and the parameter value can be obtained according to a parameter model, can be set according to a parameter setting instruction, and can be determined according to different application scenarios.

[0116] According to some embodiments, when the autonomous vehicle determines the second merging condition set, the autonomous vehicle can determine a ninth merging condition in the second merging condition set. Specifically, the ninth merging condition is that the merging end time point is greater than the product of the time parameter and the merging initial time point. That is, the autonomous vehicle can also determine the ninth merging condition: t2> λ(v0+at1). Wherein, λ is a time parameter.

[0117] In some embodiments, λ is not specific to a fixed parameter value, and the parameter value can be obtained according to a parameter model, can be set according to a parameter setting instruction, and can be determined according to different application scenarios.

[0118] S205, determining the merging initial time point and the merging end time point according to the first merging condition set and the second merging condition set;

[0119] According to some embodiments, when the autonomous vehicle determines the merging initial time point and the merging end time point according to the first merging condition set and the second merging condition set, first, the autonomous vehicle can determine at least one speed curve corresponding to the merging initial time point according to the first merging condition set. Then, the autonomous vehicle can determine the merging end time point corresponding to the merging initial time according to at least one speed curve and the second merging condition set. Secondly, the autonomous vehicle can score at least one speed curve using a cost function to obtain a target speed curve. Finally, the autonomous vehicle can determine a target merging initial time point and a target merging end time point according to the target speed curve.

[0120] In some embodiments, the cost function can be, for example, a cost function. The target speed curve can be a speed curve with the minimum cost value.

[0121] In some embodiments, the conditions included in the first merging condition set are conditions corresponding to the merging initial time point in at least one merging condition.

[0122] In some embodiments, the conditions included in the second merging condition set are conditions corresponding to the merging end time point in at least one merging condition.

[0123] According to some embodiments, the acceleration a can be sampled to obtain the acceleration limit value a at the initial speed, a e [a min ,a max ], where the sampling interval of a can be t, for example. Based on the given a, the t1 solvable sampling speed curve can be obtained based on the first to sixth merging conditions, i.e., according to the second-order inequality constraint with respect to t1. Meanwhile, the t2 solvable sampling speed curve can also be obtained according to the seventh to ninth merging conditions, i.e., according to the first-order inequality constraint with respect to t2. When there are multiple solutions of t2 in a sampling speed curve, the minimum value of t2 can be taken. Based on this, at least one set of solutions of t1 and t2 can be obtained.

[0124] It is easy to understand that the cost function can be used to score the sampling curve, and the curve with the minimum cost can be selected as the target speed curve.

[0125] For example, the cost function can be:

[0126]

[0127] where w is a constant.

[0128] S206, determining the merging start position and the merging end position of the target autonomous vehicle according to the target merging initial time point and the target merging end time point;

[0129] The specific process is as described above, and will not be repeated here.

[0130] It is easy to understand that when the target merging initial time point and the target merging end time point are obtained, the merging start time point start_s and the merging end time point end_s can be calculated. For example, when a, t1 and t2 are known, start_s = s2(t1) and end_s = s2(t1+t2) can be obtained.

[0131] S207, planning the lane-changing merging path of the target autonomous vehicle according to the merging start position and the merging end position;

[0132] The specific process is as described above, and will not be repeated here.

[0133] It is easy to understand that when the merging start position and the merging end position are obtained by the autonomous vehicle, the autonomous vehicle can plan the lane-changing merging path of the target autonomous vehicle according to the merging start position and the merging end position.

[0134] S208, determining the merging area corresponding to the lane-changing merging path, and obtaining the obstacle information of the merging area;

[0135] According to some embodiments, the merging area refers to an area in which the target autonomous vehicle merges into the corresponding lane according to the lane-changing merging path.

[0136] In some embodiments, the obstacle information of the merging area can be determined according to the decision identification bit. The identification bit can be used to identify the position of the autonomous vehicle. The identification bit is not specific to a fixed identification bit. For example, the identification bit corresponding to the first vehicle can be referred to as a rear vehicle identification bit, the identification bit corresponding to the second vehicle can be referred to as a front vehicle identification bit, and the identification bit corresponding to the target autonomous vehicle can be referred to as a self identification bit.

[0137] In some embodiments, the decision identification bit refers to the identification bit used by the autonomous vehicle when determining the obstacle avoidance information. For example, the decision identification bit can include the front vehicle identification bit and the self identification bit, and the decision identification bit can also include the rear vehicle identification bit and the self identification bit.

[0138] According to some embodiments, the obstacle information can be used to indicate whether the target autonomous vehicle needs to perform obstacle avoidance in the merging area.

[0139] In some embodiments, when the autonomous vehicle determines the obstacle information of the merging area according to the decision identification bit, the autonomous vehicle can determine the distance between the target autonomous vehicle and the second vehicle in the merging area according to the front vehicle identification bit and the self identification bit. If the autonomous vehicle determines that the distance is less than a distance threshold, the autonomous vehicle can determine that the obstacle information indicates that the autonomous vehicle needs to perform obstacle avoidance. If the autonomous vehicle determines that the distance is not less than the distance threshold, the autonomous vehicle can determine that the obstacle information indicates that the autonomous vehicle does not need to perform obstacle avoidance.

[0140] In some embodiments, the distance threshold is not specific to a fixed threshold.

[0141] As can be easily understood, when the autonomous vehicle determines the merging area corresponding to the lane-changing merging path, the autonomous vehicle can obtain the obstacle information of the merging area.

[0142] S209, updating the lane-changing merging path according to the obstacle information to obtain an updated lane-changing merging path.

[0143] According to some embodiments, when the autonomous vehicle updates the lane-changing merging path according to the obstacle information, if the obstacle information indicates that the autonomous vehicle needs to perform obstacle avoidance, the autonomous vehicle can convert the original rear vehicle identification position to a front vehicle identification position, that is, the autonomous vehicle can convert the original first vehicle to a second vehicle, and re-determine the first vehicle. Subsequently, the autonomous vehicle can update the lane-changing merging path according to the re-determined first vehicle and second vehicle to obtain an updated lane-changing merging path.

[0144] In some embodiments, when the autonomous vehicle updates the lane-changing merging path according to the obstacle information, if the obstacle information indicates that the autonomous vehicle does not need to perform obstacle avoidance, the autonomous vehicle determines that the lane-changing merging path is the updated lane-changing merging path.

[0145] As can be easily understood, when the autonomous vehicle obtains the obstacle information of the merging area, the autonomous vehicle can update the lane-changing merging path according to the obstacle information to obtain an updated lane-changing merging path.

[0146] In the embodiments of the present disclosure, first, target gap information corresponding to the target autonomous vehicle in the gap information set is determined according to the gap information set and target driving information of the target autonomous vehicle, and the first vehicle and the second vehicle are determined according to the target gap information, and the first driving information of the first vehicle and the second driving information of the second vehicle are obtained; the first merging condition set is determined according to the target gap information, the target driving information of the target autonomous vehicle and the first driving information; the second merging condition set is determined according to the target gap information, the target driving information of the target autonomous vehicle and the second driving information; the merging initial time point and the merging end time point are determined according to the first merging condition set and the second merging condition set; therefore, the accuracy of the merging time point determination can be improved. Next, the merging start position and the merging end position of the target autonomous vehicle are determined according to the target merging initial time point and the target merging end time point; the lane-changing merging path of the target autonomous vehicle is planned according to the merging start position and the merging end position; therefore, the merging position is determined according to the merging time point, and the lane-changing merging path of the target autonomous vehicle is planned according to the merging position, so that the autonomous vehicle can actively merge according to the planned lane-changing merging path under the traffic flow, and the lane-changing ability of the autonomous vehicle can be improved. Finally, the merging area corresponding to the lane-changing merging path is determined, and the obstacle information of the merging area is obtained; the lane-changing merging path is updated according to the obstacle information to obtain an updated lane-changing merging path. Therefore, by updating the lane-changing merging path according to the obstacle information, the autonomous vehicle can actively eliminate the situation, and the situation of not performing lane-changing avoidance action when the situation appears in front of the autonomous vehicle can be reduced.

[0147] In the technical solutions of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information comply with relevant laws and regulations and do not violate public order and good customs.

[0148] The following is an embodiment of the device of the present disclosure, which can be used to execute the method embodiment of the present disclosure. For details not disclosed in the device embodiment of the present disclosure, please refer to the method embodiment of the present disclosure.

[0149] Please refer to FIG. 6(a), which shows a structural schematic diagram of a first path planning device for implementing the path planning method of the present embodiment. The path planning device can be realized by software, hardware or a combination of both to become all or part of the device. The path planning device 600 includes a condition acquisition unit 601, a time determination unit 602, a position determination unit 603 and a path planning unit 604, wherein:

[0150] The condition acquisition unit 601 is configured to acquire a first merging condition between the target autonomous vehicle and a first vehicle and a second merging condition between the target autonomous vehicle and a second vehicle according to a gap information set and target driving information of the target autonomous vehicle, wherein the first vehicle is a rear vehicle of the target autonomous vehicle when the target autonomous vehicle merges by changing lanes, the second vehicle is a front vehicle of the target autonomous vehicle when the target autonomous vehicle merges by changing lanes, the gap information set includes gap information between a plurality of adjacent vehicle pairs on a target driving lane, and the target driving lane is a driving lane after the target autonomous vehicle merges by changing lanes.

[0151] The time determination unit 602 is configured to determine a merging initial time point and a merging end time point according to the first merging condition set and the second merging condition set.

[0152] The position determination unit 603 is configured to determine a merging start position and a merging end position of the target autonomous vehicle according to the merging initial time point and the merging end time point.

[0153] The path planning unit 604 is configured to plan a lane-changing merging path of the target autonomous vehicle according to the merging start position and the merging end position.

[0154] Optionally, FIG. 6(b) is a structural schematic diagram of a second path planning device for implementing the path planning method of the present embodiment. As shown in FIG. 6(b), the path planning device 600 further includes an information determination unit 605 and a path updating unit 606, which are configured to plan a lane-changing merging path of the target autonomous vehicle according to the merging start position and the merging end position, and then:

[0155] The information determination unit 605 is configured to determine a merging area corresponding to the lane-changing merging path and acquire obstacle information of the merging area.

[0156] The path updating unit 606 is configured to update the lane-changing merging path according to the obstacle information, to obtain an updated lane-changing merging path.

[0157] Optionally, FIG. 6(c) is a structural schematic diagram of a third path planning device for implementing the path planning method according to an embodiment of the present disclosure. As shown in FIG. 6(c), the condition obtaining unit 601 includes an information obtaining subunit 611, an information determining subunit 621, a condition determining subunit 631, and a time determining subunit 641, which are configured to obtain a first merging condition set between the target automatic driving vehicle and the first vehicle, and obtain a second merging condition set between the target automatic driving vehicle and the second vehicle, according to the gap information set and the target driving information of the target automatic driving vehicle.

[0158] The information obtaining subunit 611 is configured to determine target gap information corresponding to the target automatic driving vehicle in the gap information set according to the gap information set and the target driving information of the target automatic driving vehicle, where the target gap information indicates a target gap when the target automatic driving vehicle changes lanes and merges.

[0159] The information determining subunit 621 is configured to determine the first vehicle and the second vehicle according to the target gap information, and obtain first driving information of the first vehicle and second driving information of the second vehicle.

[0160] The condition determining subunit 631 is configured to determine the first merging condition set according to the target gap information, the target driving information of the target automatic driving vehicle, and the first driving information.

[0161] The condition determining subunit 631 is further configured to determine the second merging condition set according to the target gap information, the target driving information of the target automatic driving vehicle, and the second driving information.

[0162] The time determining subunit 641 is configured to determine a merging initial time point and a merging end time point according to the first merging condition set and the second merging condition set.

[0163] Optionally, when the time determining subunit 641 is configured to determine the merging initial time point and the merging end time point according to the first merging condition set and the second merging condition set, the time determining subunit 641 is specifically configured to:

[0164] determine at least one speed curve corresponding to the merging initial time point according to the first merging condition set;

[0165] determine the merging end time point corresponding to the merging initial time according to the at least one speed curve and the second merging condition set;

[0166] score the at least one speed curve by using a cost function, to obtain a target speed curve.

[0167] According to the target speed curve, the target merging initial time point and the target merging end time point are determined.

[0168] Optionally, the position determination unit 603 is configured to determine the merging start position and the merging end position of the target autonomous vehicle according to the merging initial time and the merging end time, specifically configured to:

[0169] According to the target merging initial time point and the target merging end time point, the merging start position and the merging end position of the target autonomous vehicle are determined.

[0170] Optionally, FIG. 6(d) is a structural schematic diagram of a fourth path planning device for implementing the path planning method of the embodiment of the present disclosure. As shown in FIG. 6(d), the path planning device 600 further includes:

[0171] The set determination unit 607 is configured to determine a distance information set between the target autonomous vehicle and the first vehicle according to the target driving information of the target autonomous vehicle and the first driving information, wherein the distance information set includes a first distance corresponding to the merging initial time point and a second distance corresponding to the merging end time point.

[0172] Optionally, the first merging condition set includes a first merging condition, a second merging condition, a third merging condition and a fourth merging condition, and the condition determination subunit 621 is configured to determine the first merging condition set, specifically configured to:

[0173] determine the first merging condition in the first merging condition set, wherein the first merging condition is that the first distance is greater than a first distance threshold, and the first distance threshold is determined based on the inter-vehicle time interval of the first vehicle and the first vehicle speed in the first driving information;

[0174] determine the second merging condition in the first merging condition set, wherein the second merging condition is that the first distance is greater than a second distance threshold, and the second distance threshold is determined based on the collision time of the first vehicle, the first vehicle speed and the target vehicle speed;

[0175] determine the third merging condition in the first merging condition set, wherein the third merging condition is that the second distance is greater than the first distance threshold;

[0176] determine the fourth merging condition in the first merging condition set, wherein the fourth merging condition is that the second distance is greater than the second distance threshold.

[0177] Optionally, the path planning device 600 further includes:

[0178] The set determination unit 607 is configured to determine a distance information set between the target automatic driving vehicle and the second vehicle according to the target driving information of the target automatic driving vehicle and the second driving information, where the distance information set includes a third distance corresponding to the merging initial time point and a fourth distance corresponding to the merging end time point.

[0179] Optionally, the second merging condition set includes a fifth merging condition, a sixth merging condition, a seventh merging condition and an eighth merging condition, and the condition determination subunit 631 is configured to determine the second merging condition set, and specifically configured to:

[0180] determine the fifth merging condition in the second merging condition set, where the fifth merging condition is that the third distance is greater than a third distance threshold, and the third distance is determined based on the inter-vehicle time interval of the target automatic driving vehicle and the target speed in the target driving information;

[0181] determine the sixth merging condition in the second merging condition set, where the sixth merging condition is that the third distance is greater than a fourth distance threshold, and the fourth distance is determined based on the collision time of the target automatic driving vehicle, the second speed in the second driving information and the target speed;

[0182] determine the seventh merging condition in the second merging condition set, where the seventh merging condition is that the fourth distance is greater than the third distance threshold;

[0183] determine the eighth merging condition in the second merging condition set, where the eighth merging condition is that the fourth distance is greater than the fourth distance threshold.

[0184] Optionally, the condition determination subunit 631 is configured to determine the second merging condition set, and specifically configured to:

[0185] determine a ninth merging condition in the second merging condition set, where the ninth merging condition is that the merging end time point is greater than a product of a time parameter and the merging initial time point.

[0186] Optionally, FIG. 6(e) is a structural schematic diagram of a fifth path planning device for implementing the path planning method according to an embodiment of the present disclosure. As shown in FIG. 6(e), the path planning device 600 further includes:

[0187] The speed determination unit 608 is configured to determine the target speed of the target automatic driving vehicle at the initial merging time point according to the current speed and the acceleration of the target automatic driving vehicle.

[0188] Optionally, FIG. 6(f) is a structural schematic diagram of a sixth path planning device for implementing the path planning method according to an embodiment of the present disclosure. As shown in FIG. 6(f), the path planning device 600 further includes:

[0189] The vehicle length acquisition unit 609 is configured to acquire a half vehicle length of the target automatic driving vehicle.

[0190] The distance adjustment unit 610 is configured to subtract the half vehicle length from the first distance and the second distance to obtain an adjusted first distance and an adjusted second distance.

[0191] The distance adjustment unit 610 is further configured to add the half vehicle length to the third distance and the fourth distance to obtain an adjusted third distance and an adjusted fourth distance.

[0192] It should be noted that the path planning device provided in the above embodiments is only used as an example to illustrate the division of the above functional modules. In actual applications, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above-described functions. In addition, the path planning device and the path planning method provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be described here.

[0193] The above sequence numbers of the embodiments of the present disclosure are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0194] In summary, the device provided in the embodiments of the present disclosure acquires, by the condition acquisition unit, a first merging condition set between the target automatic driving vehicle and a first vehicle according to a gap information set and target driving information of the target automatic driving vehicle, and acquires a second merging condition set between the target automatic driving vehicle and a second vehicle, wherein the first vehicle is a rear vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges by changing lanes, the second vehicle is a front vehicle of the target automatic driving vehicle when the target automatic driving vehicle merges by changing lanes, the gap information set includes gap information between a plurality of adjacent vehicle pairs on a target driving lane, and the target driving lane is a driving lane after the target driving vehicle changes lanes and merges; the time determination unit determines a merging initial time point and a merging end time point according to the first merging condition set and the second merging condition set; the position determination unit determines a merging start position and a merging end position of the target automatic driving vehicle according to the merging initial time point and the merging end time point; and the path planning unit plans a lane-changing merging path of the target automatic driving vehicle according to the merging start position and the merging end position. Therefore, the merging time point is determined according to the gap information set, the merging position is determined according to the merging time point, and the lane-changing merging path of the target automatic driving vehicle is planned according to the merging position, so that the automatic driving vehicle can actively merge according to the planned lane-changing merging path in the traffic flow, and the lane-changing ability of the automatic driving vehicle can be improved.

[0195] In the technical solutions of the present disclosure, the acquisition, storage and application of user personal information comply with relevant laws and regulations and do not violate public order and good customs.

[0196] According to an embodiment of the present disclosure, the present disclosure further provides an autonomous vehicle, a readable storage medium and a computer program product.

[0197] Figure 7 A schematic block diagram of an example autonomous vehicle 700 that can be used to implement embodiments of the present disclosure is shown. Among other things, the components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present disclosure described and / or claimed herein.

[0198] As Figure 7 shown, the autonomous vehicle 700 includes a computing unit 701 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 702 or a computer program loaded into a random access memory (RAM) 703 from a storage unit 708. In the RAM 703, various programs and data required for the operation of the autonomous vehicle 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other through a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0199] A plurality of components in the autonomous vehicle 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, a speaker, etc.; a storage unit 708, such as a magnetic disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the autonomous vehicle 700 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0200] The computing unit 701 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 701 performs various methods and processes described above, such as the path planning method. For example, in some embodiments, the path planning method can be implemented as a computer software program that is tangibly embodied in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program can be loaded and / or installed onto the autonomous vehicle 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded onto the RAM 703 and executed by the computing unit 701, one or more steps of the path planning method described above can be performed. Alternatively, in other embodiments, the computing unit 701 can be configured to perform the path planning method by any other appropriate means, such as by means of firmware.

[0201] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0202] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces the functions / operations specified in the flowcharts and / or the block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or autonomous vehicle.

[0203] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0204] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the 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 can be received in any form (including sound input, voice input, or tactile input).

[0205] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data-driven autonomous vehicles), or middleware components (e.g., applications in autonomous vehicles), or frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), the Internet, and blockchain networks.

[0206] The computer system can include a client and an autonomous driving vehicle. The client and the autonomous driving vehicle are generally far away from each other and usually interact through a communication network. The relationship between the client and the autonomous driving vehicle is generated by computer programs running on respective computers and having a client-autonomous driving vehicle relationship with each other. The autonomous driving vehicle can be a cloud autonomous driving vehicle, also known as a cloud computing autonomous driving vehicle or a cloud host, which is a host product in the cloud computing service system to solve the defects of large management difficulty and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or simply "VPS"). The autonomous driving vehicle can also be a distributed system autonomous driving vehicle or an autonomous driving vehicle combined with a blockchain.

[0207] It should be understood that the steps shown above can be reordered, added, or deleted using various forms of flow. For example, the steps described in the present disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of the present disclosure can be achieved, and the present disclosure is not limited herein.

[0208] The above detailed description does not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A path planning method, comprising: Based on the gap information set and the target driving information of the target autonomous vehicle, a first merging condition set between the target autonomous vehicle and the first vehicle is obtained, and a second merging condition set between the target autonomous vehicle and the second vehicle is obtained. The first vehicle is the vehicle following the target autonomous vehicle when it changes lanes to merge, and the second vehicle is the vehicle preceding the target autonomous vehicle when it changes lanes to merge. The gap information set includes gap information between multiple adjacent vehicle pairs on the target driving lane, and the target driving lane is the driving lane after the target autonomous vehicle changes lanes to merge. Based on the first set of import conditions and the second set of import conditions, determine the initial import time point and the end import time point; Based on the initial merging time point and the merging end time point, determine the merging start position and merging end position of the target autonomous vehicle; Based on the starting and ending positions of the merging, the lane-changing merging path of the target autonomous vehicle is planned.

2. The method according to claim 1, wherein, After planning the lane-changing merging path of the target autonomous vehicle based on the merging start position and merging end position, the method further includes: Determine the merging area corresponding to the lane change merging path, and obtain obstacle information in the merging area; Based on the obstacle information, the lane change merging path is updated to obtain the updated lane change merging path.

3. The method according to claim 1, wherein, The step of obtaining a first merging condition set between the target autonomous vehicle and the first vehicle, and obtaining a second merging condition set between the target autonomous vehicle and the second vehicle, based on the gap information set and the target driving information of the target autonomous vehicle, includes: Based on the gap information set and the target driving information of the target autonomous vehicle, the target gap information corresponding to the target autonomous vehicle in the gap information set is determined, wherein the target gap information indicates the target gap when the target autonomous vehicle merges into the lane. Based on the target gap information, the first vehicle and the second vehicle are determined, and the first driving information of the first vehicle and the second driving information of the second vehicle are obtained. The first set of merging conditions is determined based on the target gap information, the target driving information of the target autonomous vehicle, and the first driving information; The second set of merging conditions is determined based on the target gap information, the target driving information of the target autonomous vehicle, and the second driving information; Based on the first set of import conditions and the second set of import conditions, determine the initial import time point and the end import time point.

4. The method according to claim 3, wherein, The step of determining the initial and final time points of the import based on the first and second import condition sets includes: Based on the first set of merging conditions, at least one velocity curve corresponding to the initial merging time point is determined; Based on the at least one velocity curve and the second set of merging conditions, determine the merging end time point corresponding to the merging initial time; The at least one velocity curve is scored using a cost function to obtain the target velocity curve; Based on the target velocity curve, determine the initial time point and the end time point of the target merging.

5. The method according to claim 4, wherein, Based on the inflow start time and the inflow end time, the inflow start position and inflow end position of the target autonomous vehicle are determined, including: Based on the target merging initial time point and the target merging end time point, determine the merging start position and merging end position of the target autonomous vehicle.

6. The method according to claim 3, wherein, The method further includes: Based on the target driving information of the target autonomous vehicle and the first driving information, a distance information set between the target autonomous vehicle and the first vehicle is determined, wherein the distance information set includes a first distance corresponding to the initial merging time point and a second distance corresponding to the end merging time point.

7. The method according to claim 6, wherein, The first set of import conditions includes a first import condition, a second import condition, a third import condition, and a fourth import condition. Determining the first set of import conditions includes: A first merging condition is determined in the first merging condition set, wherein the first merging condition is that the first distance is greater than the first distance threshold, and the first distance threshold is determined based on the inter-vehicle time distance of the first vehicle and the first vehicle speed in the first driving information; A second merging condition is determined in the first merging condition set, wherein the second merging condition is that the first distance is greater than the second distance threshold, and the second distance threshold is determined based on the collision time of the first vehicle, the first vehicle speed, and the target vehicle speed; A third merging condition is determined in the first merging condition set, wherein the third merging condition is that the second distance is greater than the first distance threshold; Determine a fourth inflow condition in the first inflow condition set, wherein the fourth inflow condition is that the second distance is greater than the second distance threshold.

8. The method according to claim 3, wherein, The method further includes: Based on the target driving information of the target autonomous vehicle and the second driving information, a distance information set between the target autonomous vehicle and the second vehicle is determined, wherein the distance information set includes a third distance corresponding to the initial merging time point and a fourth distance corresponding to the end merging time point.

9. The method according to claim 8, wherein, The second set of import conditions includes a fifth import condition, a sixth import condition, a seventh import condition, and an eighth import condition. Determining the second set of import conditions includes: A fifth inbound condition is determined in the second inbound condition set, wherein the fifth inbound condition is that the third distance is greater than the third distance threshold, and the third distance is determined based on the inter-vehicle distance of the target autonomous vehicle and the target vehicle speed in the target driving information; A sixth merging condition is determined in the second merging condition set, wherein the sixth merging condition is that the third distance is greater than the fourth distance threshold, and the fourth distance is determined based on the collision time of the target autonomous vehicle, the second vehicle speed in the second driving information, and the target vehicle speed; Determine the seventh inflow condition in the second inflow condition set, wherein the seventh inflow condition is that the fourth distance is greater than the third distance threshold; Determine the eighth inflow condition in the second inflow condition set, wherein the eighth inflow condition is that the fourth distance is greater than the fourth distance threshold.

10. The method according to claim 3, wherein, Determining the second set of import conditions includes: Determine the ninth import condition in the second import condition set, wherein the ninth import condition is the product of the import end time point being greater than the time parameter and the import start time point.

11. The method according to claim 7 or 9, wherein, The method further includes: Based on the current speed and acceleration of the target autonomous vehicle, the target speed of the target autonomous vehicle at the initial merging time point is determined.

12. The method according to claim 6, wherein, The method further includes: Obtain the half-length of the target autonomous vehicle; Subtract the half-vehicle length from the first distance and the second distance to obtain the adjusted first distance and the adjusted second distance.

13. The method according to claim 8, wherein, The method further includes: Obtain the half-length of the target autonomous vehicle; Add the half-vehicle length to the third distance and the fourth distance to obtain the adjusted third distance and the adjusted fourth distance.

14. A path planning device, comprising: The condition acquisition unit is used to acquire a first merging condition set between the target autonomous vehicle and the first vehicle, and a second merging condition set between the target autonomous vehicle and the second vehicle, based on the gap information set and the target driving information of the target autonomous vehicle. The first vehicle is the vehicle following the target autonomous vehicle when it changes lanes to merge, and the second vehicle is the vehicle preceding the target autonomous vehicle when it changes lanes to merge. The gap information set includes gap information between multiple adjacent vehicle pairs on the target driving lane, and the target driving lane is the driving lane after the target autonomous vehicle changes lanes to merge. The time determination unit is used to determine the initial time point and the end time point of the import based on the first import condition set and the second import condition set; The location determination unit is used to determine the starting position and ending position of the target autonomous vehicle based on the initial merging time point and the ending merging time point. The path planning unit is used to plan the lane-changing merging path of the target autonomous vehicle based on the merging start position and merging end position.

15. The apparatus according to claim 14, wherein, The path planning device further includes an information determination unit and a path update unit, used to plan the lane-changing merging path of the target autonomous vehicle based on the merging start position and merging end position: The information determining unit is used to determine the merging area corresponding to the lane change merging path and to obtain obstacle information of the merging area; The path update unit is used to update the lane change merging path according to the obstacle information to obtain the updated lane change merging path.

16. The apparatus according to claim 14, wherein, The condition acquisition unit includes an information acquisition subunit, an information determination subunit, a condition determination subunit, and a time determination subunit. It is used to acquire a first set of merging conditions between the target autonomous vehicle and the first vehicle based on the gap information set and the target driving information of the target autonomous vehicle. When acquiring a second set of merging conditions between the target autonomous vehicle and the second vehicle: The information acquisition subunit is used to determine the target gap information corresponding to the target autonomous vehicle in the gap information set according to the gap information set and the target driving information of the target autonomous vehicle, wherein the target gap information indicates the target gap when the target autonomous vehicle merges into the lane. The information determination subunit is used to determine the first vehicle and the second vehicle based on the target gap information, and to obtain the first driving information of the first vehicle and the second driving information of the second vehicle. The condition determination subunit is used to determine the first set of merging conditions based on the target gap information, the target driving information of the target autonomous vehicle, and the first driving information. The condition determination subunit is further configured to determine the second set of merging conditions based on the target gap information, the target driving information of the target autonomous vehicle, and the second driving information; The time determination subunit is used to determine the initial time point and the end time point of the import based on the first import condition set and the second import condition set.

17. The apparatus according to claim 16, wherein, The time determination subunit, when determining the initial and final time points of the import based on the first import condition set and the second import condition set, is specifically used for: Based on the first set of merging conditions, at least one velocity curve corresponding to the initial merging time point is determined; Based on the at least one velocity curve and the second set of merging conditions, determine the merging end time point corresponding to the merging initial time; The at least one velocity curve is scored using a cost function to obtain the target velocity curve; Based on the target velocity curve, determine the initial time point and the end time point of the target merging.

18. The apparatus according to claim 17, wherein, The location determination unit, when determining the merging start and end positions of the target autonomous vehicle based on the merging start time and the merging end time, specifically performs the following functions: Based on the target merging initial time point and the target merging end time point, determine the merging start position and merging end position of the target autonomous vehicle.

19. The apparatus according to claim 16, wherein, The device further includes: The set determination unit is used to determine a set of distance information between the target autonomous vehicle and the first vehicle based on the target driving information of the target autonomous vehicle and the first driving information, wherein the set of distance information includes a first distance corresponding to the initial merging time point and a second distance corresponding to the end merging time point.

20. The apparatus according to claim 19, wherein, The first set of import conditions includes a first import condition, a second import condition, a third import condition, and a fourth import condition. The condition determination subunit, when determining the first set of import conditions, is specifically used for: A first merging condition is determined in the first merging condition set, wherein the first merging condition is that the first distance is greater than the first distance threshold, and the first distance threshold is determined based on the inter-vehicle time distance of the first vehicle and the first vehicle speed in the first driving information; A second merging condition is determined in the first merging condition set, wherein the second merging condition is that the first distance is greater than the second distance threshold, and the second distance threshold is determined based on the collision time of the first vehicle, the first vehicle speed, and the target vehicle speed; A third merging condition is determined in the first merging condition set, wherein the third merging condition is that the second distance is greater than the first distance threshold; Determine a fourth inflow condition in the first inflow condition set, wherein the fourth inflow condition is that the second distance is greater than the second distance threshold.

21. The apparatus according to claim 16, wherein, The device further includes: The set determination unit is used to determine a set of distance information between the target autonomous vehicle and the second vehicle based on the target driving information of the target autonomous vehicle and the second driving information, wherein the set of distance information includes a third distance corresponding to the initial merging time point and a fourth distance corresponding to the end merging time point.

22. The apparatus according to claim 21, wherein, The second set of import conditions includes a fifth import condition, a sixth import condition, a seventh import condition, and an eighth import condition. The condition determination subunit, when determining the second set of import conditions, is specifically used for: A fifth inbound condition is determined in the second inbound condition set, wherein the fifth inbound condition is that the third distance is greater than the third distance threshold, and the third distance is determined based on the inter-vehicle distance of the target autonomous vehicle and the target vehicle speed in the target driving information; A sixth merging condition is determined in the second merging condition set, wherein the sixth merging condition is that the third distance is greater than the fourth distance threshold, and the fourth distance is determined based on the collision time of the target autonomous vehicle, the second vehicle speed in the second driving information, and the target vehicle speed; Determine the seventh inflow condition in the second inflow condition set, wherein the seventh inflow condition is that the fourth distance is greater than the third distance threshold; Determine the eighth inflow condition in the second inflow condition set, wherein the eighth inflow condition is that the fourth distance is greater than the fourth distance threshold.

23. The apparatus according to claim 16, wherein, When the condition determination subunit is used to determine the second set of inflow conditions, it is specifically used for: Determine the ninth import condition in the second import condition set, wherein the ninth import condition is the product of the import end time point being greater than the time parameter and the import start time point.

24. The apparatus according to claim 20 or 22, wherein, The device further includes: The vehicle speed determination unit is used to determine the target vehicle speed of the target autonomous vehicle at the initial merging time point based on the current vehicle speed and acceleration of the target autonomous vehicle.

25. The apparatus according to claim 19, wherein, The device further includes: The vehicle length acquisition unit is used to acquire half the length of the target autonomous vehicle; The distance adjustment unit is used to subtract the half-vehicle length from the first distance and the second distance to obtain the adjusted first distance and the adjusted second distance.

26. The apparatus according to claim 21, wherein, The device further includes: The vehicle length acquisition unit is used to acquire half the length of the target autonomous vehicle; The distance adjustment unit is also used to add the half-vehicle length to the third distance and the fourth distance to obtain the adjusted third distance and the adjusted fourth distance.

27. An autonomous vehicle, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; characterized in that, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-13.

28. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-13.

29. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-13.

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