A vehicle lane change planning method, apparatus, computer equipment, and storage medium

Abstract

This application relates to a vehicle lane change planning method, apparatus, computer equipment, and storage medium. The method includes: acquiring environmental image information of the vehicle; obtaining nearby lane information of the vehicle based on the environmental image information; obtaining a first driving speed of the vehicle directly in front of the vehicle and a second driving speed of the vehicle diagonally in front of the vehicle based on the nearby lane information; obtaining a first steady-state speed and a second steady-state speed based on the first driving speed and the second driving speed, wherein the first steady-state speed is the predicted driving speed of the vehicle in the current lane, and the second steady-state speed is the predicted driving speed of the vehicle in the nearby lane; determining whether the second steady-state speed is greater than the first steady-state speed, and if so, performing a lane change for the vehicle, which can solve problems such as unreasonable lane change timing and high time cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving vehicles, in particular to a vehicle lane changing planning method and device, computer equipment and a storage medium. BACKGROUND

[0002] During the driving process of a vehicle, the driver will usually change lanes due to road congestion in front or changes in his own destination. With the development of intelligent driving technology, more and more vehicles are equipped with intelligent driving assistance systems, which provide environmental information around the vehicle to assist the driver in changing lanes. However, the existing intelligent driving assistance systems / methods can only play a role when the driver actually changes lanes, and cannot inform the driver when to change lanes in advance, nor can they evaluate the time cost of this lane change. In particular, for autonomous vehicles, this can lead to unreasonable lane changing timing and high time cost. SUMMARY

[0003] Therefore, it is necessary to provide a vehicle lane changing planning method, device, computer equipment and storage medium to solve the above technical problems, and to improve the problem of poor lane changing timing selection during the driving process of a vehicle.

[0004] In one aspect, a vehicle lane changing planning method is provided, which comprises:

[0005] obtaining environmental image information of a vehicle, and obtaining nearby lane information of the vehicle according to the environmental image information;

[0006] obtaining a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle diagonally in front of the vehicle according to the nearby lane information, and obtaining a first steady speed and a second steady speed according to the first driving speed and the second driving speed, wherein the first steady speed is a predicted driving speed of the vehicle in the current lane, and the second steady speed is a predicted driving speed of the vehicle in the nearby lane;

[0007] determining whether the second steady speed is greater than the first steady speed, and if so, performing lane changing processing on the vehicle.

[0008] In one embodiment, the step of obtaining environmental image information of a vehicle and obtaining nearby lane information of the vehicle according to the environmental image information comprises:

[0009] obtaining a first environmental image corresponding to a first time, and obtaining first position information of the nearby vehicle and first lane type information of the nearby lane according to the first environmental image;

[0010] acquire a second environment image corresponding to a second time, and obtain second position information of the nearby vehicle and second lane type information of the nearby lane according to the second environment image;

[0011] The nearby lane information includes the first position information, the first lane type information, the second position information, and the second lane type information.

[0012] In one of the embodiments, the step of obtaining a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle diagonally in front of the vehicle according to the nearby lane information includes:

[0013] obtaining a front driving speed of a plurality of the vehicles in front according to the first position information and the second position information, and obtaining the first driving speed according to the plurality of the front driving speeds, wherein the vehicles in front belong to the same lane as the vehicle and are in front of the vehicle in the driving direction;

[0014] obtaining a diagonal driving speed of a plurality of the vehicles diagonally in front according to the first position information, the second position information, the first lane type information, and the second lane type information, and obtaining the second driving speed according to the plurality of the diagonal driving speeds, wherein the vehicles diagonally in front belong to different lanes from the vehicle and are in front of the vehicle in the driving direction.

[0015] In one of the embodiments, the step of obtaining a first steady speed and a second steady speed according to the first driving speed and the second driving speed includes:

[0016] traversing a plurality of the first driving speeds corresponding to the sampling time, and obtaining a first intermediate steady speed according to a preset first weight value, wherein the first intermediate steady speed is mathematically expressed as:

[0017] V1 m (t)=w1*V1 d (t)+(1-w1)*V1 m (t-1)

[0018] wherein V1 m (t) represents the first intermediate steady speed, w1 represents the first weight value, t represents a time corresponding to the sampling time, and V1 d represents the first driving speed.

[0019] traversing a plurality of the first intermediate steady speeds corresponding to the sampling time according to the first intermediate steady speed and a preset second weight value, and obtaining the first steady speed, wherein the first steady speed is mathematically expressed as:

[0020] V1a (t) = w2*V1 m (t) + (1-w2)*V1 a (t-1)

[0021] wherein V1 a (t) represents the first steady speed, and w2 represents the second weight value;

[0022] traversing the second driving speeds corresponding to the sampling time according to the first weight value, obtaining a second intermediate steady speed, and the mathematical expression of the second intermediate steady speed is:

[0023] V2 m (t) = w1*V2 d (t) + (1-w1)*V2 m (t-1)

[0024] wherein V2 m (t) represents the second intermediate steady speed, w1 represents the first weight value, t represents the corresponding time within the sampling time, and V2 d represents the second driving speed;

[0025] traversing the second intermediate steady speeds corresponding to the sampling time according to the second intermediate steady speed and the second weight value, obtaining the second steady speed, and the mathematical expression of the second steady speed is:

[0026] V2 a (t) = w2*V2 m (t) + (1-w2)*V2 a (t-1)

[0027] wherein V2 a (t) represents the second steady speed, and w2 represents the second weight value.

[0028] In one of the embodiments, the step of obtaining the nearby lane information of the vehicle further comprises:

[0029] obtaining obstacle information of the nearby lane according to the nearby lane information, wherein the obstacle information comprises: size of the obstacle, distance length between the obstacle and the vehicle;

[0030] obtaining a first drivable width of the vehicle in the current lane and a second drivable width of the vehicle in the nearby lane according to the obstacle information;

[0031] determining whether the first driving width is greater than the width of the vehicle; if yes, the vehicle is in normal driving; if no, determining whether the second driving width is greater than the width of the vehicle, if yes, the vehicle is in lane changing treatment, if no, the vehicle is in deceleration treatment.

[0032] In one of the embodiments, the step of obtaining the nearby lane information of the vehicle further comprises:

[0033] obtaining the drivable lane type corresponding to the vehicle;

[0034] obtaining the lane type of the current lane outside the preset sampling distance;

[0035] determining whether the drivable lane type is consistent with the lane type of the current lane; if yes, the vehicle is in normal driving; if no, the vehicle is in lane changing treatment.

[0036] In one of the embodiments, the step of obtaining the nearby lane information of the vehicle further comprises:

[0037] obtaining the driving destination of the vehicle, and obtaining the preset driving path of the vehicle according to the driving destination;

[0038] determining whether the driving lane corresponding to the vehicle outside the preset sampling distance is consistent with the current lane according to the preset driving path and the nearby lane information; if yes, the vehicle is in normal driving; if no, the vehicle is in lane changing treatment.

[0039] On the other hand, a vehicle lane changing planning device is provided, which comprises:

[0040] a first obtaining module for obtaining the environmental image information of the vehicle, and obtaining the nearby lane information of the vehicle according to the environmental image information;

[0041] a second obtaining module for obtaining the first driving speed of the vehicle in front of the vehicle and the second driving speed of the vehicle in front of the vehicle according to the nearby lane information, and obtaining the first steady speed and the second steady speed according to the first driving speed and the second driving speed, wherein the first steady speed is the predicted driving speed of the vehicle in the current lane, and the second steady speed is the predicted driving speed of the vehicle in the nearby lane;

[0042] a determining module for determining whether the second steady speed is greater than the first steady speed, if yes, the vehicle is in lane changing treatment.

[0043] In still another aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0044] obtaining environment image information of the vehicle, and obtaining nearby lane information of the vehicle according to the environment image information;

[0045] obtaining a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle diagonally in front of the vehicle according to the nearby lane information, and obtaining a first steady speed and a second steady speed according to the first driving speed and the second driving speed, wherein the first steady speed is a predicted driving speed of the vehicle in a current lane, and the second steady speed is a predicted driving speed of the vehicle in a nearby lane;

[0046] determining whether the second steady speed is greater than the first steady speed, and if so, performing a lane change process on the vehicle.

[0047] In still another aspect, a computer readable storage medium is provided, having a computer program stored thereon, wherein the computer program is executable by a processor to implement the following steps:

[0048] obtaining environment image information of the vehicle, and obtaining nearby lane information of the vehicle according to the environment image information;

[0049] obtaining a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle diagonally in front of the vehicle according to the nearby lane information, and obtaining a first steady speed and a second steady speed according to the first driving speed and the second driving speed, wherein the first steady speed is a predicted driving speed of the vehicle in a current lane, and the second steady speed is a predicted driving speed of the vehicle in a nearby lane;

[0050] determining whether the second steady speed is greater than the first steady speed, and if so, performing a lane change process on the vehicle.

[0051] The vehicle lane change planning method, device, computer device, and storage medium described above obtain nearby lane information of the vehicle according to environment image information, obtain a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle diagonally in front of the vehicle according to the nearby lane information, and obtain a first steady speed and a second steady speed according to the first driving speed and the second driving speed. It is determined whether the second steady speed is greater than the first steady speed, and if so, a lane change process is performed on the vehicle, thereby solving the problems of unreasonable timing and high time cost of automatic driving vehicle lane change. BRIEF DESCRIPTION OF DRAWINGS

[0052] Figure 1 An application environment diagram of a vehicle lane change planning method in an embodiment;

[0053] Figure 2 A flowchart of a vehicle lane change planning method in an embodiment;

[0054] Figure 3 A flowchart of obtaining front road information in an embodiment;

[0055] Figure 4 A flowchart of obtaining a first driving speed and a second driving speed in an embodiment;

[0056] Figure 5 A flowchart of obtaining a first steady speed and a second steady speed in an embodiment;

[0057] Figure 6 A flowchart of obtaining nearby lane information in an embodiment;

[0058] Figure 7 A flowchart of obtaining nearby lane information in another embodiment;

[0059] Figure 8 A flowchart of obtaining nearby lane information in still another embodiment;

[0060] Figure 9 A structure block diagram of a vehicle lane change planning device in an embodiment;

[0061] Figure 10 An internal structure diagram of a computer device in an embodiment. DETAILED DESCRIPTION

[0062] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not intended to limit the present application.

[0063] The vehicle lane change planning method provided by the present application can be applied to, for example, Figure 1The application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. For example, the vehicle lane changing planning method provided by the application can be applied to the scene of planning lane changing in the driving process of an autonomous vehicle. During the driving process of the vehicle, the driver will usually change lanes because of the congestion in front of the road or the change of his own destination. With the development of intelligent driving technology, more and more vehicles are equipped with intelligent driving assistance systems, which provide environmental information around the vehicle to assist the driver in changing lanes. However, the existing intelligent driving assistance systems / methods can only play a role when the driver actually changes lanes, and cannot inform the driver when to change lanes in advance, and evaluate the time cost of this lane change. In particular, for autonomous vehicles, it also causes problems such as unreasonable lane changing time and high time cost. Therefore, by obtaining environmental image information of the vehicle, the nearby lane information of the vehicle is obtained according to the environmental image information; the first driving speed of the vehicle in front of the vehicle and the second driving speed of the vehicle in the oblique front of the vehicle are obtained according to the nearby lane information, and the first steady speed and the second steady speed are obtained according to the first driving speed and the second driving speed; if the second steady speed is greater than the first steady speed, the vehicle is processed for lane changing, which can solve the problems of unreasonable lane changing time and high time cost of the vehicle. In some implementation processes, the environmental image information of the autonomous vehicle can be collected by the terminal 102, and the environmental image information is uploaded to the server 104 for data analysis and calculation to obtain a lane changing strategy, and then the server 104 sends the lane changing strategy to the terminal 102. Among them, the terminal 102 can be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, portable wearable devices or sub-servers, and the server 104 can be realized by an independent server or a server cluster composed of multiple servers or a cloud computing platform.

[0064] In one embodiment, as Figure 2 shown, a vehicle lane changing planning method is provided, comprising the following steps:

[0065] S1: obtaining environmental image information of a vehicle, and obtaining nearby lane information of the vehicle according to the environmental image information;

[0066] S2: obtaining the first driving speed of the vehicle in front of the vehicle and the second driving speed of the vehicle in the oblique front of the vehicle according to the nearby lane information, and obtaining the first steady speed and the second steady speed according to the first driving speed and the second driving speed, wherein the first steady speed is the predicted driving speed of the vehicle in the current lane, and the second steady speed is the predicted driving speed of the vehicle in the nearby lane;

[0067] S3: judging whether the second steady speed is greater than the first steady speed, if yes, performing lane changing treatment on the vehicle.

[0068] Through the above steps, the problems of unreasonable lane changing time of the autonomous vehicle and high time cost can be improved.

[0069] Before planning the lane changing of the autonomous vehicle, the environmental image information near the vehicle needs to be obtained. In step S1, it is exemplarily illustrated that the environmental image information of the vehicle is obtained, and the nearby lane information of the vehicle is obtained according to the environmental image information. For example, the environmental image information can be obtained by the vehicle-mounted camera, such as the other vehicle information, the lane information, and the obstacle information around the vehicle at any angle. For example, the video information of the front, rear, left and right of the autonomous vehicle (the current vehicle) is obtained, and then the video is segmented, intercepted and analyzed according to a preset period. In some implementation processes, the preset period can be 200 milliseconds or 500 milliseconds. The specific value is not limited here, and the implementer can adjust the value of the period according to the real-time requirement of image analysis. It needs to be explained that the nearby lane information can not only include the nearby lane of the current vehicle, but also the lane to which the current vehicle belongs. In some implementation processes, the environmental image information of the current vehicle can also be directly photographed and stored according to the preset period. After obtaining the environmental image information, the front and rear information of the lane of the current vehicle and the front and rear information of the nearby lane can be obtained therefrom. The front and rear information further includes whether there is other vehicle on the lane, the number of vehicles, the type of lane, the shape of lane and other information. The above information is fused to obtain the nearby lane information, which is used as the data basis for subsequent lane planning and decision-making of the vehicle. In another implementation process, the nearby lane information of the driving lane of the vehicle can also be obtained through the map.

[0070] After obtaining the nearby lane information, in order to further evaluate the time cost of the vehicle's lane change, in step S2, it is exemplarily illustrated that a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle obliquely in front of the vehicle are obtained according to the nearby lane information, and a first steady speed and a second steady speed are obtained according to the first driving speed and the second driving speed. For example, the driving speed of the vehicle in front of the vehicle belonging to the same lane as the current vehicle and in front of the current vehicle can be obtained as the first driving speed, and the driving speed of the vehicle obliquely in front of the current vehicle belonging to a different lane from the current vehicle and in front of the current vehicle can be obtained as the second driving speed. Since the number of nearby lanes, the number of other vehicles and the positions of the other vehicles in the nearby lanes are included in the nearby lane information, the relative positions between the other vehicles (the vehicle in front and the vehicle obliquely in front) and the current vehicle can be obtained according to the nearby lane information. It should be noted that there can be more than one other vehicle, so the first driving speed and the second driving speed can actually be a collection of driving speeds of multiple other vehicles. According to the first driving speed, the average driving speed or the maximum driving speed that the current vehicle can reach in a period of time if it continues to drive in the current lane can be predicted, i.e. the first steady speed. Since the second driving speed of the other vehicles in the nearby lanes is known, the average driving speed or the maximum driving speed that the current vehicle can reach in a period of time if it changes lanes and drives in the nearby lanes can be predicted, i.e. the second steady speed.

[0071] After obtaining the first steady speed and the second steady speed, the two can be compared, and a lane change planning decision can be obtained according to the comparison result. In step S3, it is exemplarily illustrated that it is determined whether the second steady speed is greater than the first steady speed. If so, the vehicle is processed for lane change, for example, when the first steady speed is 50 km / h and the second steady speed is 60 km / h, it can be considered that if the vehicle continues to drive in the current lane, the speed that can be reached is 50 km / h, which is less than the speed that can be reached if the vehicle changes lanes and drives in the nearby lanes, which is 60 km / h. When the overall path to the destination is not affected, the vehicle can be processed for lane change to enable the vehicle to reach a faster driving speed, thereby saving driving time. However, if the first steady speed is 60 km / h and the second steady speed is 50 km / h, it is considered that the current vehicle can reach a faster driving speed when it continues to drive in the current lane. km / h represents the unit of speed: kilometers per hour. In this way, the driving information of other vehicles on the current lane and the nearby lanes of the autonomous vehicle can be analyzed before the actual lane change, so that the decision of the lane change planning can be obtained in advance, the time cost of the vehicle's lane change is saved, and repeated lane changes are avoided.

[0072] In some embodiments, as Figure 3As shown, the steps of acquiring environmental image information of a vehicle and obtaining nearby lane information of the vehicle based on the environmental image information include:

[0073] S11: Obtain the first environmental image corresponding to the first moment, and obtain the first location information of the nearby vehicle and the first lane type information of the nearby lane based on the first environmental image;

[0074] S12: Obtain the second environmental image corresponding to the second time moment, and obtain the second location information of the nearby vehicle and the second lane type information of the nearby lane based on the second environmental image;

[0075] S13: The nearby lane information includes: the first location information, the first lane type information, the second location information, and the second lane type information.

[0076] like Figure 3 As shown, in steps S11 to S13, it is exemplarily explained that a first environmental image and a second environmental image at a first time and a second time are acquired respectively. For example, the current time is taken as the first time, and a first environmental image at the first time is acquired. The first environmental image can be a photo taken in real time by a camera, or it can be an image of a frame in a real-time video. It includes lane information, vehicle information, and obstacle information in front of and behind the current vehicle in its lane. Based on the above information, the first position information (position coordinates) of other vehicles and the first lane type information of nearby lanes (e.g., truck lane, bus lane, emergency lane, straight lane, etc.) can be acquired. Then, 1 second or 2 seconds are added to the first time to obtain the second time. At a certain moment, the second environmental image corresponding to the second moment is obtained, and the updated second position information of nearby vehicles and the second lane type information of nearby lanes are obtained based on the second environmental image. It should be noted that the first environmental image and the second environmental image only represent the surrounding environment images that the current vehicle can collect at different moments, and since the current vehicle is in motion, the surrounding environment images that can be collected will change accordingly. This application does not limit the specific values ​​of the first moment and the second moment. The implementer can set them according to its own real-time requirements for image acquisition. Preferably, the first moment and the second moment are not just a single time point, but can be a set of multiple time points. For example, the implementer can use two or more times as the first moment or the second moment.

[0077] like Figure 4 As shown, in some embodiments, the step of obtaining a first speed of the vehicle directly in front of the vehicle and a second speed of the vehicle diagonally in front of the vehicle based on the nearby lane information includes:

[0078] S21: Obtain the forward driving speeds of multiple vehicles directly ahead based on the first location information and the second location information, and obtain the first driving speed based on the multiple forward driving speeds, wherein the vehicles directly ahead belong to the same lane as the vehicle and are ahead of the vehicle in the direction of travel.

[0079] S22: Obtain the diagonal driving speeds of multiple vehicles diagonally ahead based on the first location information, the second location information, the first lane type information, and the second lane information; obtain the second driving speed based on the multiple diagonal driving speeds, wherein the vehicles diagonally ahead belong to different lanes from the vehicle and are ahead of the vehicle in its driving direction.

[0080] like Figure 4 As shown, in steps S21 to S22, it is exemplarily explained that the forward driving speeds of multiple vehicles directly ahead are obtained based on the first position information and the second position information; a first driving speed is obtained based on the multiple forward driving speeds; the diagonal driving speeds of multiple vehicles diagonally ahead are obtained based on the first position information, the second position information, the first lane type information, and the second lane information; and a second driving speed is obtained based on the multiple diagonal driving speeds. For example, based on the first position information corresponding to the first moment and the second position information at the second moment, the position information of the vehicles directly ahead of the current vehicle can be obtained. Multi-frame detection of multiple position information can then be performed to obtain the forward driving speeds of the vehicles directly ahead. It should be noted here that the first moment and the second moment are merely descriptive terms representing different moments and do not limit the specific number of moments obtained. Therefore, two (…) can be obtained. Multi-frame fusion analysis of forward driving speeds (two or more frames) can yield the first driving speed of the vehicle directly ahead. It should be noted that the vehicle directly ahead is in the same lane as the current vehicle and is ahead of the current vehicle in its direction of travel. For the second driving speed, the diagonal driving speed of the vehicle diagonally ahead can be obtained based on the first and second position information, the first lane type, and the second lane type. Multi-frame detection of multiple diagonal driving speeds yields the second driving speed. Again, the diagonal vehicle diagonally ahead is in a different lane from the current vehicle and is ahead of the current vehicle in its direction of travel. In some implementations, the driving speeds of other vehicles can also be calculated using historical multi-frame information from the current vehicle's perception module, i.e., the first driving speed of the vehicle directly ahead and the second driving speed of the vehicle diagonally ahead.

[0081] To obtain the first steady-state velocity and the second steady-state velocity, such as Figure 5 As shown, the steps for obtaining the first steady-state speed and the second steady-state speed based on the first driving speed and the second driving speed include:

[0082] S31: Iterate through the multiple first driving speeds corresponding to the sampling time, and obtain a first intermediate steady-state speed according to a preset first weight value. The mathematical expression of the first intermediate steady-state speed is:

[0083] V1 m (t)=w1*V1 d (t)+(1-w1)*V1 m (t-1)

[0084] Among them, V1 m (t) represents the first intermediate steady-state velocity, w1 represents the first weight value, t represents the time corresponding to the sampling time, and V1 d This represents the first driving speed;

[0085] S32: Based on the first intermediate steady-state velocity and the preset second weight value, the multiple first intermediate steady-state velocities corresponding to the sampling time are traversed to obtain the first steady-state velocity, which is mathematically expressed as:

[0086] V1 a (t)=w2*V1 m (t)+(1-w2)*V1 a (t-1)

[0087] Among them, V1 a (t) represents the first steady-state velocity, and w2 represents the second weight value;

[0088] S33: Iterate through the multiple second driving speeds corresponding to the sampling time, and obtain the second intermediate steady-state speed according to the first weight value. The mathematical expression of the second intermediate steady-state speed is:

[0089] V2 m (t)=w1*V2 d (t)+(1-w1)*V2 m (t-1)

[0090] Among them, V2 m (t) represents the second intermediate steady-state velocity, w1 represents the first weight value, t represents the time corresponding to the sampling time, and V2 d This represents the second driving speed;

[0091] S34: Based on the second intermediate steady-state velocity and the second weight value, traverse the multiple second intermediate steady-state velocities corresponding to the sampling time to obtain the second steady-state velocity, the mathematical expression of which is:

[0092] V2 a(t)=w2*V2 m (t)+(1-w2)*V2 a (t-1)

[0093] Among them, V2 a (t) represents the second steady-state velocity, and w2 represents the second weight value.

[0094] like Figure 5 As shown, in step S31, it is exemplarily illustrated that multiple first driving speeds corresponding to the sampling time are traversed, and a first intermediate steady-state speed is obtained according to a preset first weight value. For example, taking time t as the sequence, the first intermediate steady-state speed is obtained starting from t=1. In some implementations, the first weight w1 can be set to 0.1, and the value range of t (sampling time) can be 2 seconds or 10 seconds. At the initial time V1 m The value of (0) is 0, and then the traversal starts from t=1 to iterate and update the value of the first intermediate steady-state velocity.

[0095] like Figure 5 As shown, in step S32, it is exemplarily explained that, based on the first intermediate steady-state velocity and the preset second weight value, multiple first intermediate steady-state velocities corresponding to the sampling time are traversed to obtain the first steady-state velocity. For example, taking time t as the sequence, the first steady-state velocity is obtained starting from t=1. In some implementations, the first weight w2 can be set to 0.01, and the value range of t (sampling time) can be 2 seconds or 10 seconds. At the initial moment V1 a The value of (0) is 0, and then the process is repeated starting from t=1 to iterate and update the value of the first steady-state velocity. In this way, the first steady-state velocity can be obtained.

[0096] like Figure 5 As shown, in step S33, it is exemplarily illustrated that multiple second driving speeds corresponding to the sampling time are traversed, and a second intermediate steady-state speed is obtained according to a preset first weight value. For example, taking time t as the sequence, the second intermediate steady-state speed is obtained starting from t=1. In some implementations, the first weight w1 can be set to 0.1, and the value range of t (sampling time) can be 2 seconds or 10 seconds. At the initial time V1 m The value of (0) is 0, and then the traversal starts from t=1, iterating and updating the value of the intermediate steady-state velocity.

[0097] like Figure 5As shown, in step S34, it is exemplarily explained that, based on the second intermediate steady-state velocity and the preset second weight value, multiple second intermediate steady-state velocities corresponding to the sampling time are traversed to obtain the second steady-state velocity. For example, taking time t as the sequence, the second steady-state velocity is obtained starting from t=1. In some implementations, the first weight w2 can be set to 0.01, and the value range of t (sampling time) can be 2 seconds or 10 seconds. At the initial moment V2 a The value of (0) is 0, and then the process starts from t=1 to iterate and update the value of the second steady-state speed. In this way, the second steady-state speed can be obtained, which makes it easier to compare the second steady-state speed with the first steady-state speed in the subsequent process, and to reasonably consider and reduce the time cost of vehicle lane changing.

[0098] In some implementation processes, for autonomous vehicles with larger body sizes, such as trucks, it is also necessary to check whether the lane space within a certain distance in front of the target lane allows the autonomous vehicle to pass. The target lane includes the current lane and nearby lanes.

[0099] like Figure 6 As shown, the steps following obtaining the nearby lane information of the vehicle further include:

[0100] S41: Obtain obstacle information of the nearby lane based on the nearby lane information, wherein the obstacle information includes: the size of the obstacle and the distance between the obstacle and the vehicle;

[0101] S42: Based on the obstacle information, obtain the first drivable width of the vehicle in the current lane and the second drivable width in the nearby lane;

[0102] S43: Determine whether the first driving width is greater than the width of the vehicle; if yes, the vehicle drives normally; if no, determine whether the second driving width is greater than the width of the vehicle; if yes, the vehicle changes lanes; if no, the vehicle decelerates.

[0103] like Figure 6As shown, in steps S41 to S43, it is exemplarily explained that obstacle information of nearby lanes is obtained and it is determined whether the current vehicle can avoid the obstacle. For example, there may be an accident, construction, slow-moving vehicle, etc. (collectively referred to as obstacles) in front of the current lane. In this scenario, the current vehicle needs to perform operations such as deceleration, stopping, and lane changing. The obstacle occupies part of the lane position, so it is necessary to identify the type of obstacle, the size of the obstacle, and the distance between the obstacle and the current vehicle. It should also be noted that the obstacle may be in front of the current lane or in front of a nearby lane. Therefore, it is necessary to obtain the first drivable width of the current vehicle in the current lane and the second drivable width in a nearby lane. Then, it is determined whether the first drivable width is greater than the width required for normal vehicle driving. If so, the current vehicle drives normally in the current lane to avoid the obstacle; if not, it is determined whether the second drivable width is greater than the width required for normal vehicle driving. If so, the current vehicle performs lane changing; if not, the current vehicle is forced to decelerate until it stops.

[0104] like Figure 7 As shown, the steps following obtaining the nearby lane information of the vehicle further include:

[0105] S51: Obtain the type of drivable lane corresponding to the vehicle;

[0106] S52: Obtain the lane type of the current lane outside the preset sampling distance;

[0107] S53: Determine whether the type of the drivable lane is consistent with the type of the current lane; if yes, the vehicle drives normally; if no, the vehicle changes lanes.

[0108] like Figure 7 As shown, in steps S51 to S53, it is exemplarily explained that the determination of whether to change lanes for the current vehicle is based on the lane type in front of the current vehicle. For example, the lane in front of the current vehicle may not be a lane type that the current vehicle is allowed to pass through. For example, for an autonomous vehicle of the truck type, the lane in front may not be a truck lane or trucks may be prohibited from entering the lane in front during the current driving time. In this case, it is necessary to identify the lane type at a certain distance from the lane where the current vehicle is located. That is, a sampling distance is set, which can be set to 50 meters or 100 meters. After obtaining the lane type of the current lane outside the sampling distance, it is combined with the drivable lane type corresponding to the current vehicle to determine whether the two are consistent. If they are consistent, the current vehicle can drive normally. If they are inconsistent, it is necessary to identify other nearby lanes and change lanes for the current vehicle. For example, a lane change decision is made to change lanes to the right lane. In this way, the obstacle information in front can be reasonably identified and the lane change decision can be obtained in advance.

[0109] like Figure 8 As shown, the steps following obtaining the nearby lane information of the vehicle further include:

[0110] S61: Obtain the destination of the vehicle and obtain the preset driving route of the vehicle based on the destination;

[0111] S62: Based on the preset driving path and the nearby lane information, determine whether the driving lane corresponding to the vehicle outside the preset sampling distance is consistent with the current lane; if yes, the vehicle drives normally; if no, the vehicle changes lanes.

[0112] like Figure 8 As shown in steps S61 to S62, it is illustrated that, based on the preset driving path and nearby lane information, it is determined whether the driving lane corresponding to the vehicle outside the preset sampling distance is consistent with the current lane. For example, after the destination is determined or the destination is changed, there may be multiple driving route options. If the current vehicle needs to take the right off-ramp or enter a toll station after traveling a certain distance, lane change planning needs to be carried out in advance to prevent failure to change lanes in time. At this time, it is necessary to determine whether the driving lane corresponding to the vehicle outside the sampling distance is consistent with the current lane based on the driving path and nearby lane information. If they are consistent, the current vehicle can drive normally. If they are inconsistent, the current vehicle needs to change lanes. In this way, lane change strategies can be obtained in a timely manner in scenarios where lane changes need to be made in advance due to route reasons, avoiding errors in the actual driving route of the current vehicle.

[0113] In some implementation processes, it is also possible to connect with servers, cloud platforms, and cloud environments to obtain information on the wheel congestion of lanes around the vehicle and plan lane changes in advance for congested road scenarios.

[0114] It should be understood that, although Figures 2 to 8 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figures 2 to 8 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0115] In one embodiment, such as Figure 9As shown, a vehicle lane change planning device is provided, the vehicle lane change planning device comprising:

[0116] The first acquisition module is used to acquire environmental image information of the vehicle and obtain the nearby lane information of the vehicle based on the environmental image information.

[0117] The second acquisition module acquires the first driving speed of the vehicle, obtains the second driving speed of nearby vehicles based on the nearby lane information, and obtains a first steady-state speed and a second steady-state speed based on the first driving speed and the second driving speed, wherein the first steady-state speed is the predicted driving speed of the vehicle in the current lane, and the second steady-state speed is the predicted driving speed of the vehicle in nearby lanes.

[0118] The judgment module is used to determine whether the second steady-state speed is greater than the first steady-state speed. If so, the vehicle is given a lane change.

[0119] In the first acquisition module, the environmental image information of the vehicle is acquired, and the nearby lane information of the vehicle is obtained based on the environmental image information. For example, the environmental image information can be obtained by acquiring information about other vehicles, lanes, and obstacles around the vehicle from any angle through the vehicle-mounted camera. For example, video information from the front, rear, left, and right of the autonomous vehicle (current vehicle) is acquired. Then, the video is segmented and analyzed according to a preset period. In some implementations, the preset period can be 300 milliseconds or 600 milliseconds. The specific value is not limited here. The implementer can adjust the value of the period according to the real-time requirements of image analysis. It should be noted that the nearby lane information can include not only the lanes near the current vehicle, but also the lane to which the current vehicle belongs. In some implementations, the environmental image information of the current vehicle can also be photographed and stored directly according to the preset period. After acquiring environmental image information, the front and rear information of the current vehicle's lane and the front and rear information of nearby lanes can be obtained. The front and rear information also includes information such as whether there are other vehicles in the lane, the number of vehicles, the type of lane, and the shape of the lane. By fusing the above information, the information of nearby lanes is obtained, which serves as the data basis for subsequent lane change planning decisions for the vehicle. In some implementation processes, the information of nearby lanes of the vehicle's driving lane can also be obtained through a map.

[0120] In the second acquisition module, it is exemplarily explained that the first driving speed of the vehicle directly in front of the vehicle and the second driving speed of the vehicle diagonally in front of the vehicle are obtained based on the nearby lane information. Based on the first driving speed and the second driving speed, a first steady-state speed and a second steady-state speed are obtained. For example, the driving speed of the vehicle directly in front of the current vehicle, which belongs to the same lane as the current vehicle, can be obtained as the first driving speed, and the driving speed of the vehicle diagonally in front of the current vehicle, which belongs to a different lane, can be obtained as the second driving speed. Since the nearby lane information includes the number of nearby lanes, the number of other vehicles, and the position of other vehicles in the nearby lanes, the relative position between other vehicles (the vehicle directly in front and the vehicle diagonally in front) and the current vehicle can be obtained based on the nearby lane information. It should be noted that there may be more than one other vehicle, so the first driving speed and the second driving speed can actually be a set of the driving speeds of multiple other vehicles. Based on the first driving speed, we can predict the average or maximum driving speed that the current vehicle can reach within a certain period of time if it continues to drive in the current lane, which is the first steady-state speed. Since the second driving speeds of other vehicles in nearby lanes are known, we can predict the average or maximum driving speed that the current vehicle can reach within a certain period of time if it changes lanes and drives in nearby lanes, which is the second steady-state speed.

[0121] In the judgment module, for example, it determines whether the second steady-state speed is greater than the first steady-state speed. If so, the vehicle performs a lane change. For instance, if the first steady-state speed is 40 km / h and the second steady-state speed is 60 km / h, it can be considered that the speed the vehicle can reach if it continues to travel in the current lane is 40 km / h, which is less than the speed the vehicle can reach in a nearby lane after changing lanes (60 km / h). Without affecting the overall path to the destination, the vehicle can be changed to achieve a faster speed, thus saving travel time. However, if the first steady-state speed is 60 km / h and the second steady-state speed is 50 km / h, it is considered that the vehicle can achieve a faster speed by continuing to travel in the current lane. Here, km / h represents the speed unit: kilometers per hour. In this way, the driving information of other vehicles in the current lane and nearby lanes of the autonomous vehicle can be analyzed before the actual lane change, thereby obtaining lane change planning decisions in advance, saving the time cost of lane changes and avoiding repeated lane changes.

[0122] The aforementioned device can be applied to scenarios where lane changes are planned during the operation of autonomous vehicles. It acquires environmental image information of the vehicle through a first acquisition module, and obtains information about nearby lanes based on this information. A second acquisition module acquires the vehicle's first speed, and obtains the second speed of nearby vehicles based on the nearby lane information. Based on the first and second speeds, a first steady-state speed and a second steady-state speed are obtained. A judgment module determines whether the second steady-state speed is greater than the first steady-state speed; if so, a lane change is initiated. This addresses issues such as unreasonable lane change timing and high time costs.

[0123] Specific limitations regarding the vehicle lane change planning device can be found in the limitations of the vehicle lane change planning method described above, and will not be repeated here. Each module in the aforementioned vehicle lane change planning device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0124] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 10 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores vehicle lane change planning data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a vehicle lane change planning method.

[0125] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0126] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:

[0127] Acquire environmental image information of the vehicle, and obtain nearby lane information of the vehicle based on the environmental image information;

[0128] The first speed of the vehicle directly in front of the vehicle and the second speed of the vehicle diagonally in front of the vehicle are obtained based on the nearby lane information. Based on the first speed and the second speed, a first steady-state speed and a second steady-state speed are obtained, wherein the first steady-state speed is the predicted speed of the vehicle in the current lane and the second steady-state speed is the predicted speed of the vehicle in the nearby lane.

[0129] Determine whether the second steady-state speed is greater than the first steady-state speed. If so, then change lanes for the vehicle.

[0130] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0131] Acquire environmental image information of the vehicle, and obtain nearby lane information of the vehicle based on the environmental image information;

[0132] The first speed of the vehicle directly in front of the vehicle and the second speed of the vehicle diagonally in front of the vehicle are obtained based on the nearby lane information. Based on the first speed and the second speed, a first steady-state speed and a second steady-state speed are obtained, wherein the first steady-state speed is the predicted speed of the vehicle in the current lane and the second steady-state speed is the predicted speed of the vehicle in the nearby lane.

[0133] Determine whether the second steady-state speed is greater than the first steady-state speed. If so, then change lanes for the vehicle.

[0134] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0135] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A vehicle lane change planning method, characterized by, The method comprises the following steps: obtaining environment image information of a vehicle, and obtaining nearby lane information of the vehicle according to the environment image information; obtaining a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle obliquely in front of the vehicle according to the nearby lane information, and obtaining a first steady speed and a second steady speed according to the first driving speed and the second driving speed, wherein the first steady speed is a predicted driving speed of the vehicle in a current lane, and the second steady speed is a predicted driving speed of the vehicle in a nearby lane; the step of obtaining the first steady speed and the second steady speed according to the first driving speed and the second driving speed comprises: traversing a plurality of the first driving speeds corresponding to a sampling time, and obtaining a first intermediate steady speed according to a preset first weight value, wherein the first intermediate steady speed is mathematically expressed as: ； wherein, represents the first intermediate steady-state speed, represents the first weight value, t represents the corresponding time within the sampling time, represents the first driving speed; traversing a plurality of the first intermediate steady speeds corresponding to the sampling time according to the first intermediate steady speed and a preset second weight value, and obtaining the first steady speed, wherein the first steady speed is mathematically expressed as: ； wherein, represents the first steady state speed, represents the second weight value; traversing a plurality of the second driving speeds corresponding to the sampling time, and obtaining a second intermediate steady speed according to the first weight value, wherein the second intermediate steady speed is mathematically expressed as: ； wherein, represents the second intermediate steady speed, represents the first weight value, and t represents the corresponding time within the sampling time, represents the second running speed; traversing a plurality of the second intermediate steady speeds corresponding to the sampling time according to the second intermediate steady speed and the second weight value, and obtaining the second steady speed, wherein the second steady speed is mathematically expressed as: ； wherein, represents the second steady state speed, represents the second weight value; judging whether the second steady speed is greater than the first steady speed, and if yes, performing a lane changing process on the vehicle.

2. The vehicle lane change planning method of claim 1, wherein, The step of obtaining environment image information of a vehicle and obtaining nearby lane information of the vehicle according to the environment image information comprises: obtaining a first environment image corresponding to a first time, and obtaining first position information of a nearby vehicle and first lane type information of the nearby lane according to the first environment image; obtaining a second environment image corresponding to a second time, and obtaining second position information of a nearby vehicle and second lane type information of the nearby lane according to the second environment image; the nearby lane information comprises the first position information, the first lane type information, the second position information and the second lane type information.

3. The vehicle lane change planning method of claim 2, wherein, The step of obtaining a first driving speed of a vehicle in front of the vehicle and a second driving speed of a vehicle obliquely in front of the vehicle according to the nearby lane information comprises: obtaining a forward driving speed of a plurality of the vehicles in front of the vehicle according to the first position information and the second position information, and obtaining the first driving speed according to the plurality of the forward driving speeds, wherein the vehicles in front of the vehicle belong to the same lane as the vehicle and are in front of the vehicle in a driving direction. Obtaining a diagonal driving speed of the diagonal front vehicle according to the first position information, the second position information, the first lane type information and the second lane type information, wherein the diagonal front vehicle belongs to a different lane from the vehicle and is in front of the vehicle in the driving direction of the vehicle.

4. The vehicle lane change planning method of claim 1, wherein, The step of obtaining the nearby lane information of the vehicle further comprises: Obtaining obstacle information of the nearby lane according to the nearby lane information, wherein the obstacle information comprises a size of an obstacle and a distance between the obstacle and the vehicle; Obtaining a first drivable width of the vehicle in the current lane and a second drivable width of the vehicle in the nearby lane according to the obstacle information; Determining whether the first drivable width is greater than the width of the vehicle; if yes, the vehicle is normally driven; if no, determining whether the second drivable width is greater than the width of the vehicle; if yes, the vehicle is subjected to lane changing processing; if no, the vehicle is subjected to speed reduction processing.

5. The vehicle lane change planning method of claim 1, wherein, The step of obtaining the nearby lane information of the vehicle further comprises: Obtaining a drivable lane type corresponding to the vehicle; Obtaining a lane type of the current lane outside a preset sampling distance; Determining whether the drivable lane type is consistent with the lane type of the current lane; if yes, the vehicle is normally driven; if no, the vehicle is subjected to lane changing processing.

6. The vehicle lane change planning method of claim 1, wherein, The step of obtaining the nearby lane information of the vehicle further comprises: Obtaining a driving destination of the vehicle and a preset driving path of the vehicle according to the driving destination; Determining whether a driving lane corresponding to the vehicle outside the preset sampling distance is consistent with the current lane according to the preset driving path and the nearby lane information; if yes, the vehicle is normally driven; if no, the vehicle is subjected to lane changing processing.

7. A vehicle lane change planning device characterized by comprising: The method comprises: A first obtaining module is configured to obtain environmental image information of a vehicle and obtain nearby lane information of the vehicle according to the environmental image information; A second obtaining module is configured to obtain a first driving speed of the vehicle, obtain a second driving speed of a nearby vehicle of the vehicle according to the nearby lane information, and obtain a first steady speed and a second steady speed according to the first driving speed and the second driving speed, wherein the first steady speed is a predicted driving speed of the vehicle in a current lane, and the second steady speed is a predicted driving speed of the vehicle in a nearby lane; the step of obtaining the first steady speed and the second steady speed according to the first driving speed and the second driving speed comprises: Iterating a plurality of first driving speeds corresponding to a sampling time, obtaining a first intermediate steady speed according to a preset first weight value, and the first intermediate steady speed is mathematically expressed as: ； wherein, represents the first intermediate steady-state speed, represents the first weight value, t represents the corresponding time within the sampling time, represents the first travel speed; Iterating a plurality of first intermediate steady speeds corresponding to the sampling time according to the first intermediate steady speed and a preset second weight value, obtaining the first steady speed, and the first steady speed is mathematically expressed as: ； wherein, represents the first steady state speed, represents the second weight value; The second intermediate steady speed is obtained according to the first weight value by traversing the plurality of second driving speeds corresponding to the sampling time, and the mathematical expression of the second intermediate steady speed is: ； wherein, represents the second intermediate steady speed, represents the first weight value, t represents the corresponding time within the sampling time, represents the second running speed; The second steady speed is obtained by traversing the plurality of second intermediate steady speeds corresponding to the sampling time according to the second intermediate steady speed and the second weight value, and the mathematical expression of the second steady speed is: ； wherein, represents the second steady state speed, represents the second weight value; The judging module is configured to judge whether the second steady speed is greater than the first steady speed, and if yes, the vehicle is subjected to lane changing processing.

8. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the vehicle lane changing planning method in any one of claims 1 to 6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the vehicle lane changing planning method in any one of claims 1 to 6.

Images