CN111301420A - Vehicle lane change control method and device, readable storage medium and vehicle - Google Patents

Vehicle lane change control method and device, readable storage medium and vehicle Download PDF

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Publication number
CN111301420A
CN111301420A CN202010099971.1A CN202010099971A CN111301420A CN 111301420 A CN111301420 A CN 111301420A CN 202010099971 A CN202010099971 A CN 202010099971A CN 111301420 A CN111301420 A CN 111301420A
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vehicle
lane
occupied
vehicles
determining
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彭程
陈新
李彪
纪明君
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Beijing Automotive Group Co Ltd
Beijing Automotive Research Institute Co Ltd
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Beijing Automotive Group Co Ltd
Beijing Automotive Research Institute Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18—Propelling the vehicle
    • B60W30/18009—Propelling the vehicle related to particular drive situations
    • B60W30/18163—Lane change; Overtaking manoeuvres
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B60W2520/105—Longitudinal acceleration

Abstract

The disclosure relates to a vehicle lane change control method and device, a readable storage medium and a vehicle. The method comprises the following steps: acquiring current running information of the vehicle and current running environment information of the vehicle, wherein the running information at least comprises the current position of the vehicle, and the environment information at least comprises lane line information of a current running road of the vehicle; respectively determining the state of each lane of the current driving road of the vehicle according to the current position of the vehicle and lane line information, wherein the state comprises one of idle, occupied or semi-occupied; and controlling the lane change of the vehicle according to the state of each lane. Therefore, the requirement of the vehicle on real-time performance during lane changing can be met, and the accuracy of the determined lane state can be improved to a certain extent. In addition, the state of each lane of the current driving road of the vehicle is determined only according to the current position of the vehicle and the lane line information, so that the calculation process can be simplified to a certain extent, and the lane changing efficiency of the vehicle can be improved.

Description

Vehicle lane change control method and device, readable storage medium and vehicle
Technical Field
The disclosure relates to the technical field of vehicles, in particular to a vehicle lane change control method and device, a readable storage medium and a vehicle.
Background
An automatic driving vehicle is also called as an unmanned vehicle, and is an intelligent vehicle which realizes unmanned driving through a computer system. The automatic driving vehicle depends on the cooperation of artificial intelligence, visual calculation, radar, monitoring device and global positioning system, so that the computer can automatically and safely operate the motor vehicle without any active operation of human.
Autonomous vehicles travel on roads, often requiring lane changes. When a vehicle is driven on a lane change, traffic safety problems may occur, and in order to avoid accidents and improve the driving safety of the vehicle, the lane change of an automatically driven vehicle needs to be controlled, so that a vehicle lane change control method is needed.
Disclosure of Invention
The disclosure aims to provide a vehicle lane change control method, a vehicle lane change control device, a readable storage medium and a vehicle, so as to solve the problems in the related art.
In order to achieve the above object, a first aspect of the present disclosure provides a lane change control method for a vehicle, the method including:
acquiring current running information of a vehicle and current running environment information of the vehicle, wherein the running information at least comprises the current position of the vehicle, and the environment information at least comprises lane line information of a current running road of the vehicle;
respectively determining the state of each lane of the current driving road of the vehicle according to the current position of the vehicle and the lane line information, wherein the state comprises one of idle, occupied or semi-occupied;
and controlling the lane change of the vehicle according to the state of each lane.
Optionally, the determining, according to the current position of the host vehicle and the lane line information, a state of each lane of a current driving road of the host vehicle respectively includes:
dividing a preset driving area taking the current position of the vehicle as a center into M multiplied by N grids with equal size according to the current position of the vehicle and the lane line information, wherein N is the number of lanes of the current driving road of the vehicle, and M is the number of grids in each lane;
and determining the probability of each grid in the lane being occupied by other vehicles aiming at each lane, and determining the state of the lane according to the probability of the grid in the lane being occupied by other vehicles.
Optionally, the determining, for each lane, a probability that each mesh in the lane is occupied by other vehicles includes:
determining the probability of each grid in the lane being occupied by other vehicles according to the following formula:
Figure BDA0002386619330000021
Figure BDA0002386619330000023
wherein P represents grid CmThe probability of being occupied by other vehicles,ZC、ZVrespectively representing the positions of the other vehicles and the positions of grids occupied by the other vehicles; σ is the variance of the standard normal distribution;
Figure BDA0002386619330000022
characterization grid CmThe area occupied by said other vehicle, AVCharacterizing the area occupied by said other vehicle, A characterizing the area occupied by said other vehicle and a grid CmUnder the condition that the intersection of the areas occupied by the other vehicles is not empty, the grid CmA union of an area occupied by the other vehicle and an area occupied by the other vehicle.
Optionally, the running information further includes a running speed and an acceleration at which the host vehicle is currently running; the environment information also comprises the positions and the running speeds of other vehicles in the preset running area; the method further comprises the following steps:
for each lane, the following process is performed:
according to the positions of the other vehicles, determining a target vehicle closest to the current position of the vehicle from the other vehicles on the lane;
determining a safe distance between the host vehicle and the target vehicle in the lane according to the following formula according to the current running speed and acceleration of the host vehicle, the running speed of the target vehicle and the safe time:
Figure BDA0002386619330000031
wherein S represents a safe distance, V, between the subject vehicle and the target vehicleeCharacterizing the current driving speed of the vehicle, aeCharacterizing the current running acceleration, V, of the vehicleo
Characterizing the speed of travel, t, of the target vehiclesCharacterizing the safe time.
Determining an effective grid in the lane according to the safe distance and the current position of the vehicle;
for each lane, determining the state of the lane according to the probability that the grid in the lane is occupied by other vehicles includes:
determining the state probability of the lane according to the probability that the effective grid in the lane is occupied by other vehicles and the following formula:
Figure BDA0002386619330000032
wherein, PiState probability, k, characterizing the ith laneiCharacterizing the number of active meshes, k, in the ith laneiIs an integer with a value range of [1, M]，PjRepresenting the probability that the jth effective grid in the ith lane is occupied by other vehicles;
and determining the state corresponding to the state probability according to the corresponding relation between the preset state probability and the state of the lane.
Optionally, the determining an effective grid in the lane according to the safe distance and the current position of the host vehicle includes:
determining an arc intersected with the left lane line and the right lane line of the lane by taking the current position of the vehicle as a circle center and the safe distance as a radius;
and determining the grids which pass by the straight line taking the current position of the vehicle as a starting point and the point on the circular arc as an end point and are positioned in the lane as effective grids in the lane.
The second aspect of the present disclosure also provides a lane change control apparatus for a vehicle, the apparatus comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring the current running information of a vehicle and the current running environment information of the vehicle, the running information at least comprises the current position of the vehicle, and the environment information at least comprises the lane line information of the current running road of the vehicle;
the first determining module is used for respectively determining the state of each lane of the current driving road of the vehicle according to the current position of the vehicle and the lane line information, wherein the state comprises one of idle, occupied or semi-occupied;
and the control module controls the vehicle to change lanes according to the state of each lane.
Optionally, the first determining module includes:
the segmentation submodule is used for dividing a preset driving area taking the current position of the vehicle as a center into M multiplied by N grids with equal size according to the current position of the vehicle and the lane line information, wherein N is the number of lanes of the current driving road of the vehicle, and M is the number of grids in each lane;
the first determining submodule is used for determining the probability of each grid in each lane being occupied by other vehicles according to the lane, and determining the state of each lane according to the probability of the grid in each lane being occupied by other vehicles.
Optionally, the determining sub-module is configured to determine a probability of each grid in the lane being occupied by other vehicles according to the following formula:
Figure BDA0002386619330000041
Figure BDA0002386619330000042
wherein P represents grid CmThe probability of being occupied by other vehicles,ZC、ZVrespectively representing the positions of the other vehicles and the positions of grids occupied by the other vehicles; σ is the variance of the standard normal distribution;
Figure BDA0002386619330000051
characterization grid CmThe area occupied by said other vehicle, AVCharacterizing the area occupied by said other vehicle, A characterizing the area occupied by said other vehicle and a grid CmUnder the condition that the intersection of the areas occupied by the other vehicles is not empty, the grid CmA union of an area occupied by the other vehicle and an area occupied by the other vehicle.
Optionally, the running information further includes a running speed and an acceleration at which the host vehicle is currently running; the environment information also comprises the positions and the running speeds of other vehicles in the preset running area; the device further comprises:
the second determination module is used for determining a target vehicle which is closest to the current position of the vehicle from other vehicles on the lane according to the positions of the other vehicles for each lane;
a third determining module, configured to determine, for each lane, a safe distance between the host vehicle and the target vehicle in the lane according to the traveling speed and acceleration of the host vehicle currently traveling, the traveling speed of the target vehicle, and a safe time according to the following formula:
Figure BDA0002386619330000052
wherein S represents a safe distance, V, between the subject vehicle and the target vehicleeCharacterizing the current driving speed of the vehicle, aeCharacterizing the current running acceleration, V, of the vehicleoCharacterizing the speed of travel, t, of the target vehiclesCharacterizing the safe time.
The fourth determination module is used for determining effective grids in each lane according to the safe distance and the current position of the vehicle;
the first determining submodule is further used for determining the state probability of the lane according to the probability that the effective grids in the lane are occupied by other vehicles and the following formula:
Figure BDA0002386619330000053
wherein, PiState probability, k, characterizing the ith laneiCharacterizing the number of active meshes, k, in the ith laneiIs an integer with a value range of [1, M]，PjRepresenting the probability that the jth effective grid in the ith lane is occupied by other vehicles; and
and determining the state corresponding to the state probability according to the corresponding relation between the preset state probability and the state of the lane.
Optionally, the fourth determining module includes:
the second determining submodule is used for determining an arc intersected with the left lane line and the right lane line of the lane by taking the current position of the vehicle as the center of a circle and the safe distance as the radius;
and the third determining submodule is used for determining the grid which passes by the straight line taking the current position of the vehicle as a starting point and the point on the circular arc as an end point and is positioned in the lane as the effective grid in the lane.
The third aspect of the present disclosure also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method provided by the first aspect of the present disclosure.
The fourth aspect of the present disclosure also provides a vehicle including: the vehicle lane change control device provided by the second aspect of the present disclosure.
Through the technical scheme, the state of each lane of the current driving road of the vehicle can be respectively determined according to the current position of the vehicle and the lane line information, and then the vehicle is controlled to change lanes according to the state of the lane, so that the requirement of the vehicle on real-time performance during lane changing can be met, and the accuracy of the determined lane state can be improved to a certain extent. In addition, the state of each lane of the current driving road of the vehicle is determined only according to the current position of the vehicle and the lane line information, so that the calculation process can be simplified to a certain extent, and the lane changing efficiency of the vehicle can be improved.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
fig. 1 is a flowchart of a vehicle lane-change control method according to an exemplary embodiment of the present disclosure.
FIG. 2 is a flow chart of a vehicle lane-change control method according to another exemplary embodiment of the present disclosure.
Fig. 3 is a schematic diagram of determining an active mesh according to another exemplary embodiment of the present disclosure.
Fig. 4 is a block diagram of a vehicle lane-change control apparatus according to an exemplary embodiment of the present disclosure.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
The existing lane change decision of the automatic driving vehicle is generally based on a vehicle road model with the minimum Safe distance (MSS) (minimum Safe spacing), or based on a vehicle lane change model with Time-To-Collision (TTC) Collision Time, and in addition, some vehicle lane change methods based on deep learning and reinforcement learning are provided. But these methods are mainly to perform a static lane change. Since the minimum distance between vehicles on a structured road (e.g., an expressway) changes rapidly, a large amount of calculation is required, and it is difficult for the existing technology to satisfy a sufficiently large amount of calculation, a method for performing lane change behavior based on a model such as a minimum distance is difficult to implement on the structured road. In order to solve the above problems in the related art, the present disclosure provides a vehicle lane change control method, device, readable storage medium, and vehicle.
Fig. 1 is a flowchart of a vehicle lane-change control method according to an exemplary embodiment of the present disclosure. As shown in fig. 1, the method may include the following steps.
In step 11, the traveling information on the current traveling of the own vehicle and the environmental information on the current traveling of the own vehicle are acquired. The driving information at least includes the current position of the vehicle, and the environment information at least includes lane line information of the current driving road of the vehicle.
In order to obtain environmental information within a range of 360 ° around the vehicle and take vehicle cost into consideration, a driving environment sensing device including an on-vehicle GPS (Global Positioning System), a front-end/rear-end camera, and a front-end/rear-end/left-side/right-side radar may be provided in the vehicle. In one embodiment, the environment information of the current running of the vehicle can be acquired based on the environment sensing device. However, considering that the processing is relatively complicated when the environment sensing device is used to acquire the lane information in the environment information, for example, after the lane line is acquired according to the camera, the number of lanes, the lane width, and the like are further calculated, in a preferred embodiment, the lane information in the environment information may be acquired through a high-precision map, and the lane information may include the number of lanes of the current driving road of the vehicle, the lane width, and the like. Further, the current location of the own vehicle may be determined based on an onboard GPS. The determination of the current position by the vehicle-mounted GPS belongs to the prior art, and is not described herein again.
In step 12, the state of each lane of the road on which the vehicle is currently traveling is determined based on the current position of the vehicle and the lane line information. Wherein the state comprises one of idle, occupied, or semi-occupied.
When the lane is in the idle state, the other vehicles in the lane do not affect the running of the vehicle, so that the vehicle can change lanes. When the lane is in the occupied state, other vehicles in the lane may affect the running of the vehicle, and therefore, the vehicle may be prohibited from changing lanes. When the lane is in the semi-occupied state, whether to change lanes may be further determined with reference to other factors (e.g., whether to change lanes is confirmed by a user, etc.), which is not particularly limited by the present disclosure.
In one embodiment, the current position of the vehicle and the positions of other vehicles in the left and right lanes of the vehicle can be determined through the current position of the vehicle and lane line information, and the lane state can be determined according to the positions of the other vehicles. Taking the left lane of the host vehicle as an example, if the distance between the host vehicle and another vehicle which is located in the left lane and in front of the host vehicle and is closest to the host vehicle is greater than a first threshold value, it is determined that the lane is in an idle state; if the distance is smaller than the first threshold and larger than the second threshold, determining that the lane is in a semi-occupied state; and if the distance is smaller than a second threshold value, determining that the lane is in an occupied state.
In another possible embodiment, the lane may be divided into meshes, and the state of the vehicle may be determined according to the probability of occupation by other vehicles per mesh.
Specifically, as shown in fig. 2, step 12 in fig. 1 may specifically include the following steps.
In step 121, a preset driving area centered on the current position of the vehicle is divided into M × N grids of equal size according to the current position of the vehicle and the lane line information. Wherein, N is the number of lanes of the road where the vehicle is currently running, and M is the number of grids in each lane.
Specifically, a preset traveling area is determined according to the current position of the host vehicle in an effective traveling area (e.g., a road) of the host vehicle. For example, the area of-20 m to 30m in the longitudinal direction and-5 m to 5m in the transverse direction of the center is determined as the preset driving area in the effective driving area by taking the current position of the vehicle as the center. And finally, dividing the preset driving area into M multiplied by N grids with equal size. The length and width of each grid are respectively greater than or equal to the length and width of a vehicle running in the lane (for example, if the lane is a bus running lane, the length and width of the grid in the lane are respectively greater than or equal to the length and width of the bus), the width of the grid in each lane is equal to the width of the lane, N is the number of lanes of a road on which the vehicle is currently running, and M is the number of grids in each lane.
In step 122, for each lane, a probability that each mesh in the lane is occupied by other vehicles is determined, and a state of the lane is determined according to the probability that the mesh in the vehicle is occupied by other vehicles.
In particular, the probability of each mesh within a lane being occupied by other vehicles may be determined according to the following equation (1):
Figure BDA0002386619330000091
wherein P represents grid CmThe probability of being occupied by other vehicles,ZC、ZVrespectively representing the positions of other vehicles and the positions of grids occupied by the other vehicles; σ is the variance of the standard normal distribution; a. thecmCharacterization grid CmArea occupied by other vehicles, AVCharacterizing the area occupied by other vehicles, A characterizing the area occupied by other vehicles and grid CmUnder the condition that the intersection of the areas occupied by other vehicles is not empty, grid CmThe union of the area occupied by other vehicles and the area occupied by other vehicles.
It should be noted that the area occupied by other vehicles can be obtained by: the length and the width of the other vehicle are obtained through the vehicle image collected by the camera, and the area occupied by the other vehicle is further determined according to the length and the width; or, models of different types of vehicles (including cars, trucks, buses, etc.) can be directly set in the system (the areas of the vehicles of the same type are not different, and the vehicles of the same type can be considered to be the same in the present disclosure), the types of the other vehicles are determined according to the vehicle images collected by the camera, and then the models of the vehicles are selected to determine the area occupied by the vehicles of the type. The area occupied by other vehicles can be determined by using the existing method for determining the area occupied by the vehicle, and the disclosure is not particularly limited.
For each grid, the probability that the grid is occupied by other vehicles can be determined according to the above formula. In this manner, the probability of each mesh in each lane being occupied by other vehicles may be calculated. Wherein a higher probability indicates a higher probability that the grid is occupied by other vehicles, and a lower probability indicates a lower probability that the grid is occupied by other vehicles.
In addition, since the probability of collision of the host vehicle is extremely low when there is no vehicle within the safe distance of the host vehicle when the host vehicle changes lanes, the present disclosure may only consider the state of the lane within the safe distance before controlling the vehicle to change lanes. Specifically, the following process may be performed for the lane in which the host vehicle is located, and the left and right lanes thereof:
firstly, the obtained running information of the current running of the vehicle can also comprise the running speed and the acceleration of the current running of the vehicle besides the current position of the vehicle; the current driving environment information of the vehicle may include, in addition to lane line information, positions and driving speeds of other vehicles located in a preset driving area.
And then, according to the positions of other vehicles, determining a target vehicle closest to the current position of the vehicle from the other vehicles on the lane.
Then, according to the running speed and the acceleration of the current running of the host vehicle, the running speed of the target vehicle and the safe time, the safe distance between the host vehicle and the target vehicle in the lane is determined by the following formula (2):
Figure BDA0002386619330000101
wherein S represents the safe distance between the vehicle and the target vehicle, VeCharacterizing the current running speed of the vehicle, aeCharacterised by the current running acceleration, V, of the vehicleoCharacterizing the speed of travel, t, of the target vehiclesCharacterizing the safe time.
It should be noted that the running speed and the acceleration of the current running of the vehicle may be acquired through a CAN (Controller Area Network) bus, and the running speed of the target vehicle may be determined by a radar in the running environment sensing device. The safety time can be set according to the user requirement, and for example, it can be 2 s. After these parameters are determined, the safe distance of the own vehicle from the target vehicle is calculated based on the formula (2).
And finally, determining the effective grid in the lane according to the safe distance and the current position of the vehicle. Specifically, an arc intersecting the left lane line and the right lane line of the lane is determined with the current position of the vehicle as the center of a circle and the safe distance as the radius. Determining the grids which pass by the straight line with the current position of the vehicle as a starting point and the point on the circular arc as an end point and are positioned in the lane as effective grids in the lane
For example, as shown in fig. 3, assuming that the host vehicle a, the target vehicle being the vehicle b in the left lane of the host vehicle a, the safe distance between the host vehicle a and the target vehicle b is determined as described above, and the safe distance is taken as the safe distance in the left lane. Determining an arc C intersected with the left lane line and the right lane line of the left lane by taking the vehicle a as the center of a circle and the safe distance as the radius1The grids passing through the straight line with the current position of the vehicle a as the starting point and the point on the arc as the end point and located in the left lane are respectivelyGrid C12Grid C13Grid C14Grid C15. In the same manner, in the middle lane where the host vehicle a is located, the target vehicle is the vehicle C, and the arc intersecting the left and right lane lines in the lane is the arc C2The effective grid determined in the lane is grid C21Grid C22Grid C23Grid C24Grid C25And grid C26. Similarly, in the right lane, the target vehicle is a vehicle d, and the arc intersecting the left and right lane lines in the lane is an arc C3The effective grid determined in the lane is grid C32Grid C33Grid C24And grid C34。
After determining the effective grid in each lane according to the above manner, for each lane, determining the state of the lane according to the probability that the grid in the lane is occupied by other vehicles may specifically be: determining the state probability of the lane according to the probability that the effective grid in the lane is occupied by other vehicles and the following formula (3):
Figure BDA0002386619330000121
wherein, PiState probability, k, characterizing the ith laneiCharacterizing the number of active meshes, k, in the ith laneiIs an integer with a value range of [1, M]，PjAnd representing the probability that the jth effective grid in the ith lane is occupied by other vehicles. Where i may characterize the left lane, the center lane, and the right lane.
For example, taking the center lane where the vehicle a is located as an example, the grid C is calculated according to the above formula (1)21Grid C22Grid C23Grid C24Grid C25And grid C26The probability of being occupied by other vehicles, and then the state probability of the middle lane is determined according to formula (3).
By adopting the technical scheme, the state probability of the lane is determined only according to the probability that the effective grid in the safe distance is occupied by other vehicles, so that the lane changing safety is ensured, the calculation workload is reduced, and the efficiency of determining the state probability of the lane is improved.
After the state probability of the lane is determined, the state corresponding to the state probability is determined according to the corresponding relation between the preset state probability and the state of the lane.
The correspondence between the state probability and the state of the lane may be represented in a curved form, a functional form, or a table form. For example, it is assumed that the correspondence between the preset state probability and the lane state is represented in a table form, and is as shown in table 1.
TABLE 1 correspondence between state probabilities and states of lanes
State of lane Probability of state
Free up 0＜P≤0.4
Occupancy 0.7＜P≤1.0
Semi-occupied 0.4＜P≤0.7
In step 13, the own vehicle is controlled to change lanes according to the state of each lane.
After the state of each lane is determined, the vehicle can be controlled to change lanes according to the state of each lane. For example, if the middle lane where the vehicle is located is in an occupied state and the left and right lanes are both in an idle state, the vehicle may be controlled to change lanes to the left lane or the right lane. It should be noted that the lane change of the vehicle is controlled only when the lane is in an idle or semi-occupied state and the lane line is a broken line.
By adopting the technical scheme, the state of each lane of the current driving road of the vehicle can be respectively determined according to the current position of the vehicle and the lane line information, and the vehicle is controlled to change lanes according to the state of the lane, so that the requirement of the vehicle on real-time performance during lane changing can be met, and the accuracy of the determined lane state can be improved to a certain extent. In addition, the state of each lane of the current driving road of the vehicle is determined only according to the current position of the vehicle and the lane line information, so that the calculation process can be simplified to a certain extent, and the lane changing efficiency of the vehicle can be improved.
Based on the same invention concept, the invention also provides a vehicle lane change control device. Fig. 4 is a block diagram of a vehicle lane-change control apparatus according to an exemplary embodiment of the present disclosure. As shown in fig. 4, the apparatus may include:
an obtaining module 41, configured to obtain driving information of current driving of a host vehicle and environment information of current driving of the host vehicle, where the driving information at least includes a current location of the host vehicle, and the environment information at least includes lane line information of a current driving road of the host vehicle;
a first determining module 42, configured to respectively determine, according to the current position of the host vehicle and the lane line information, a state of each lane of a current driving road of the host vehicle, where the state includes one of idle, occupied, or semi-occupied;
and the control module 43 controls the vehicle to change lanes according to the state of each lane.
Optionally, the first determining module 42 may include:
the segmentation submodule is used for dividing a preset driving area taking the current position of the vehicle as a center into M multiplied by N grids with equal size according to the current position of the vehicle and the lane line information, wherein N is the number of lanes of the current driving road of the vehicle, and M is the number of grids in each lane;
the first determining submodule is used for determining the probability of each grid in each lane being occupied by other vehicles according to the lane, and determining the state of each lane according to the probability of the grid in each lane being occupied by other vehicles.
Optionally, the determining sub-module may be configured to determine the probability of each mesh in the lane being occupied by other vehicles according to the following formula:
Figure BDA0002386619330000141
Figure BDA0002386619330000142
wherein P represents grid CmThe probability of being occupied by other vehicles,ZC、ZVrespectively representing the positions of the other vehicles and the positions of grids occupied by the other vehicles; σ is the variance of the standard normal distribution;
Figure BDA0002386619330000143
characterization grid CmThe area occupied by said other vehicle, AVCharacterizing the area occupied by said other vehicle, A characterizing the area occupied by said other vehicle and a grid CmUnder the condition that the intersection of the areas occupied by the other vehicles is not empty, the grid CmA union of an area occupied by the other vehicle and an area occupied by the other vehicle.
Optionally, the running information further includes a running speed and an acceleration at which the host vehicle is currently running; the environment information also comprises the positions and the running speeds of other vehicles in the preset running area; the apparatus may further include:
the second determination module is used for determining a target vehicle which is closest to the current position of the vehicle from other vehicles on the lane according to the positions of the other vehicles for each lane;
a third determining module, configured to determine, for each lane, a safe distance between the host vehicle and the target vehicle in the lane according to the traveling speed and acceleration of the host vehicle currently traveling, the traveling speed of the target vehicle, and a safe time according to the following formula:
Figure BDA0002386619330000144
wherein S represents a safe distance, V, between the subject vehicle and the target vehicleeCharacterizing the current driving speed of the vehicle, aeCharacterizing the current running acceleration, V, of the vehicleoCharacterizing the speed of travel, t, of the target vehiclesCharacterizing the safe time.
The fourth determination module is used for determining effective grids in each lane according to the safe distance and the current position of the vehicle;
the first determining submodule is further used for determining the state probability of the lane according to the probability that the effective grids in the lane are occupied by other vehicles and the following formula:
Figure BDA0002386619330000151
wherein, PiState probability, k, characterizing the ith laneiCharacterizing the number of active meshes, k, in the ith laneiIs an integer with a value range of [1, M]，PjRepresenting the probability that the jth effective grid in the ith lane is occupied by other vehicles; and
and determining the state corresponding to the state probability according to the corresponding relation between the preset state probability and the state of the lane.
Optionally, the fourth determining module may include:
the second determining submodule is used for determining an arc intersected with the left lane line and the right lane line of the lane by taking the current position of the vehicle as the center of a circle and the safe distance as the radius;
and the third determining submodule is used for determining the grid which passes by the straight line taking the current position of the vehicle as a starting point and the point on the circular arc as an end point and is positioned in the lane as the effective grid in the lane.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
In an exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the vehicle lane-change control method described above is also provided.
In another exemplary embodiment, a vehicle is also provided, and the vehicle lane change control device provided by the disclosure is included.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, various possible combinations will not be separately described in this disclosure.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.

Claims (10)

1. A vehicle lane change control method, characterized by comprising:
acquiring current running information of a vehicle and current running environment information of the vehicle, wherein the running information at least comprises the current position of the vehicle, and the environment information at least comprises lane line information of a current running road of the vehicle;
respectively determining the state of each lane of the current driving road of the vehicle according to the current position of the vehicle and the lane line information, wherein the state comprises one of idle, occupied or semi-occupied;
and controlling the lane change of the vehicle according to the state of each lane.
2. The method according to claim 1, wherein the determining the state of each lane of the road on which the host vehicle is currently traveling, respectively, based on the current location of the host vehicle and the lane line information, comprises:
dividing a preset driving area taking the current position of the vehicle as a center into M multiplied by N grids with equal size according to the current position of the vehicle and the lane line information, wherein N is the number of lanes of the current driving road of the vehicle, and M is the number of grids in each lane;
and determining the probability of each grid in the lane being occupied by other vehicles aiming at each lane, and determining the state of the lane according to the probability of the grid in the lane being occupied by other vehicles.
3. The method of claim 2, wherein determining, for each lane, a probability that each mesh within the lane is occupied by other vehicles comprises:
determining the probability of each grid in the lane being occupied by other vehicles according to the following formula:
Figure FDA0002386619320000011
Figure FDA0002386619320000012
wherein P represents grid CmProbability of being occupied by other vehicles, ZC、ZVRespectively characterize the sameThe location of his vehicle, the location of the grid occupied by said other vehicle; σ is the variance of the standard normal distribution;
Figure FDA0002386619320000021
characterization grid CmThe area occupied by said other vehicle, AVCharacterizing the area occupied by said other vehicle, A characterizing the area occupied by said other vehicle and a grid CmUnder the condition that the intersection of the areas occupied by the other vehicles is not empty, the grid CmA union of an area occupied by the other vehicle and an area occupied by the other vehicle.
4. The method according to claim 2, wherein the travel information further includes a travel speed and an acceleration at which the host vehicle is currently traveling; the environment information also comprises the positions and the running speeds of other vehicles in the preset running area; the method further comprises the following steps:
for each lane, the following process is performed:
according to the positions of the other vehicles, determining a target vehicle closest to the current position of the vehicle from the other vehicles on the lane;
determining a safe distance between the host vehicle and the target vehicle in the lane according to the following formula according to the current running speed and acceleration of the host vehicle, the running speed of the target vehicle and the safe time:
Figure FDA0002386619320000022
wherein S represents a safe distance, V, between the subject vehicle and the target vehicleeCharacterizing the current driving speed of the vehicle, aeCharacterizing the current running acceleration, V, of the vehicleoCharacterizing the speed of travel, t, of the target vehiclesCharacterizing the safe time.
Determining an effective grid in the lane according to the safe distance and the current position of the vehicle;
for each lane, determining the state of the lane according to the probability that the grid in the lane is occupied by other vehicles includes:
determining the state probability of the lane according to the probability that the effective grid in the lane is occupied by other vehicles and the following formula:
Figure FDA0002386619320000031
wherein, PiState probability, k, characterizing the ith laneiCharacterizing the number of active meshes, k, in the ith laneiIs an integer with a value range of [1, M]，PjRepresenting the probability that the jth effective grid in the ith lane is occupied by other vehicles;
and determining the state corresponding to the state probability according to the corresponding relation between the preset state probability and the state of the lane.
5. The method of claim 4, wherein determining the active mesh within the lane based on the safe distance and the current position of the host vehicle comprises:
determining an arc intersected with the left lane line and the right lane line of the lane by taking the current position of the vehicle as a circle center and the safe distance as a radius;
and determining the grids which pass by the straight line taking the current position of the vehicle as a starting point and the point on the circular arc as an end point and are positioned in the lane as effective grids in the lane.
6. A lane change control apparatus for a vehicle, characterized by comprising:
the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring the current running information of a vehicle and the current running environment information of the vehicle, the running information at least comprises the current position of the vehicle, and the environment information at least comprises the lane line information of the current running road of the vehicle;
the first determining module is used for respectively determining the state of each lane of the current driving road of the vehicle according to the current position of the vehicle and the lane line information, wherein the state comprises one of idle, occupied or semi-occupied;
and the control module controls the vehicle to change lanes according to the state of each lane.
7. The apparatus of claim 6, wherein the first determining module comprises:
the segmentation submodule is used for dividing a preset driving area taking the current position of the vehicle as a center into M multiplied by N grids with equal size according to the current position of the vehicle and the lane line information, wherein N is the number of lanes of the current driving road of the vehicle, and M is the number of grids in each lane;
the first determining submodule is used for determining the probability of each grid in each lane being occupied by other vehicles according to the lane, and determining the state of each lane according to the probability of the grid in each lane being occupied by other vehicles.
8. The apparatus of claim 7, wherein the determination sub-module is configured to determine the probability of each grid in the lane being occupied by other vehicles according to the following formula:
Figure FDA0002386619320000041
Figure FDA0002386619320000042
wherein P represents grid CmProbability of being occupied by other vehicles, ZC、ZVRespectively representing the positions of the other vehicles and the positions of grids occupied by the other vehicles; σ is the variance of the standard normal distribution;
Figure FDA0002386619320000043
characterization grid CmThe area occupied by said other vehicle, AVCharacterizing the area occupied by said other vehicle, A characterizing the area occupied by said other vehicle and a grid CmUnder the condition that the intersection of the areas occupied by the other vehicles is not empty, the grid CmA union of an area occupied by the other vehicle and an area occupied by the other vehicle.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
10. A vehicle, characterized by comprising: the vehicle lane-change control apparatus of any one of claims 6-8.
CN202010099971.1A 2020-02-18 2020-02-18 Vehicle lane change control method and device, readable storage medium and vehicle Pending CN111301420A (en)

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