CN113978465A - Lane-changing track planning method, device, equipment and storage medium - Google Patents
Lane-changing track planning method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN113978465A CN113978465A CN202111142043.XA CN202111142043A CN113978465A CN 113978465 A CN113978465 A CN 113978465A CN 202111142043 A CN202111142043 A CN 202111142043A CN 113978465 A CN113978465 A CN 113978465A
- Authority
- CN
- China
- Prior art keywords
- integral term
- lane change
- cost
- lane
- vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 73
- 230000008859 change Effects 0.000 claims abstract description 297
- 238000013209 evaluation strategy Methods 0.000 claims abstract description 37
- 230000036461 convulsion Effects 0.000 claims description 26
- 230000001133 acceleration Effects 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 11
- 238000011156 evaluation Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 description 32
- 238000004891 communication Methods 0.000 description 8
- 238000010586 diagram Methods 0.000 description 8
- 230000033001 locomotion Effects 0.000 description 6
- 238000012545 processing Methods 0.000 description 6
- 230000006870 function Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000009471 action Effects 0.000 description 2
- 238000006073 displacement reaction Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- 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
- 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
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
-
- 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
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0025—Planning or execution of driving tasks specially adapted for specific operations
-
- 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
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Human Computer Interaction (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
- Traffic Control Systems (AREA)
Abstract
The disclosure provides a lane change trajectory planning method, a lane change trajectory planning device, lane change trajectory planning equipment and a storage medium, and relates to the field of computers, in particular to the field of automatic driving. The specific implementation scheme is as follows: obtaining a plurality of candidate lane changing tracks of the lane changing of the vehicle, wherein the candidate lane changing tracks are used for describing characteristic parameters of the lane changing operation executed by the vehicle; respectively determining a lane change cost integral term corresponding to each candidate lane change track according to the characteristic parameters corresponding to each candidate lane change track; determining a lane change cost value corresponding to each candidate lane change track according to a lane change cost integral term of each candidate lane change track and a preset lane change cost evaluation strategy; and determining the candidate lane change track with the minimum lane change cost value as the execution lane change track of the vehicle.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a lane change trajectory planning method, apparatus, device, and storage medium in the field of automatic driving.
Background
In the lane changing process of the automatic driving vehicle, a reasonable lane changing track needs to be planned to ensure that the lane changing cost of the automatic driving vehicle is optimal; the evaluation of the lane change cost needs to consider the smoothness of the lane change of the vehicle, the safety requirement and the like, which is also the key point of the industry research.
Disclosure of Invention
The present disclosure provides a lane change trajectory planning method, apparatus, device, and storage medium for ensuring at least smoothness during a lane change of an autonomous vehicle.
According to one aspect of the disclosure, a lane-changing trajectory planning method is provided, in which multiple candidate lane-changing trajectories for changing lanes of a vehicle are obtained, and the candidate lane-changing trajectories are used for describing characteristic parameters of lane-changing operation executed by the vehicle;
determining a lane change cost integral term corresponding to each candidate lane change track according to the characteristic parameters corresponding to each candidate lane change track;
determining a lane change cost value corresponding to each candidate lane change track according to a lane change cost integral term of each candidate lane change track and a preset lane change cost evaluation strategy;
and determining the candidate lane change track with the minimum lane change cost value as the execution lane change track of the vehicle.
According to another aspect of the present disclosure, there is provided a lane-changing trajectory planning apparatus, including:
the lane change candidate track obtaining unit is used for obtaining a plurality of lane change candidate tracks of the lane change of the vehicle, and the lane change candidate tracks are used for describing characteristic parameters of lane change operation executed by the vehicle;
a lane change cost integral term obtaining unit, configured to determine a lane change cost integral term corresponding to each candidate lane change trajectory according to the characteristic parameter corresponding to each candidate lane change trajectory;
a lane change cost value obtaining unit, configured to determine a lane change cost value corresponding to each candidate lane change track according to a lane change cost integral term of each candidate lane change track and a preset lane change cost evaluation policy;
and the execution lane change track determining unit is used for determining the candidate lane change track with the minimum lane change cost value as the execution lane change track of the vehicle.
According to still another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the methods of the present disclosure.
According to yet another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the present disclosure.
According to yet another aspect of the disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method of the disclosure.
According to still another aspect of the present disclosure, there is provided an autonomous automobile including the electronic device of the present disclosure.
The method comprises the steps of obtaining corresponding characteristic parameters from a plurality of candidate lane changing tracks of the lane changing of the vehicle, calculating a lane changing cost integral term corresponding to each candidate lane changing track according to the characteristic parameters, carrying out weighted summation on the lane changing cost integral terms based on a preset lane changing cost evaluation strategy to calculate the lane changing cost value of each candidate lane changing track, and selecting the candidate lane changing track with the minimum lane changing cost value as the execution lane changing track of the vehicle. Therefore, the stability of the automatic driving vehicle in the lane changing process can be at least guaranteed, and the lane changing track with the optimal cost is obtained.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic flow chart of a lane-change trajectory planning method according to a first embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a candidate lane change trajectory according to a first embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a lane-changing trajectory planning device according to a tenth embodiment of the present disclosure;
FIG. 4 is a block diagram of an electronic device for implementing a lane change trajectory planning method of an embodiment of the present disclosure;
FIG. 5 is a block diagram of an autonomous vehicle for implementing the lane change trajectory planning method of the disclosed embodiments.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The invention provides a lane change track planning method capable of ensuring stability in the lane change process of an automatic driving vehicle so as to obtain a lane change track with optimal cost. The present disclosure may be applied to a vehicle with an automatic driving or driving assistance function, and the lane change in the present disclosure may refer to a vehicle lane change process such as a stick lane change, an autonomous lane change, and the like in the automatic driving or driving assistance process of the vehicle.
Fig. 1 is a schematic flow chart of a lane-changing trajectory planning method according to a first embodiment of the present disclosure, and as shown in fig. 1, the method mainly includes:
In the automatic driving or auxiliary driving process, before the lane change action is executed, a module in charge of path planning plans a lane change track according to the current driving state of the vehicle and by combining external monitoring environment parameters, and certainly, a plurality of candidate lane change tracks can be planned.
The candidate lane change trajectory generation mode can be various, and the appropriate path planning strategy and the candidate lane change trajectory generation mode can be selected by combining the actual application scenario and the technical requirements in the specific implementation process of the method. Path planning and generation of candidate lane change trajectories are mature technologies in the field and are not described in any greater detail in this disclosure.
For the candidate lane change track, the candidate lane change track is a traveling track for planning the lane change of the vehicle from the current lane to the target lane, the track is formed by connecting a plurality of track points, and the motion parameters of the vehicle are specified at each track point; and the general description of the candidate lane-changing track, the position description of each track point and the corresponding vehicle motion parameter description form the main description content of one candidate lane-changing track. Fig. 2 is a schematic diagram of a lane change candidate trajectory according to an embodiment of the present disclosure, and as shown in fig. 2, one lane change candidate trajectory for the vehicle 1 to change from the lane 1 to the lane 2 is formed by connecting a plurality of trajectory points.
The vehicle motion parameters of each track point include at least one of: longitudinal acceleration, lateral acceleration of the vehicle. Wherein, the longitudinal acceleration of the vehicle refers to the acceleration component of the running acceleration of the vehicle in the longitudinal direction; the lateral acceleration of the vehicle refers to an acceleration component of the vehicle running acceleration in the lateral direction.
The general description of the candidate lane change trajectory includes at least one of: the lane change total time, the speed of a lane change end point, the cruising speed of a target lane, the transverse distance between a current lane and the target lane, the maximum transverse distance in the candidate lane change track and vehicle lane change collision parameters. Wherein,
and the lane change total time refers to the total time spent by the vehicle for executing the lane change process according to the corresponding candidate lane change track.
The speed of the lane change end point refers to the vehicle speed corresponding to the end track point of the corresponding candidate lane change track.
The target lane cruising speed refers to the cruising speed corresponding to the target lane planned by the corresponding candidate lane changing track, and the target lane refers to the lane to which the planned vehicle in the candidate lane changing track is switched, such as: the candidate lane change trajectory plans that the vehicle changes from the current lane to the adjacent left lane, so that the adjacent left lane is the target lane, and the cruising speed of the adjacent left lane is the cruising speed of the target lane, for example: the upper speed limit specified for the target lane is 80KM/h, and the so-called cruising speed of the target lane may be 80 KM/h.
The lateral distance between the current lane and the target lane refers to the distance between the target lane to which the vehicle is to be switched and the lane where the vehicle is located, and this can be characterized by the relative distance relationship between the lane where the vehicle is located and the lane center line of the target lane.
The maximum lateral distance in the candidate lane change trajectory refers to the maximum lateral distance that the vehicle will run when actually changing lanes according to the candidate lane change trajectory, for example: ideally, it is desirable that the vehicle lane change is directly changed to a position where the center line of the vehicle coincides with the center line of the target lane, but in the actual lane change process, due to vehicle inertia or other factors, the lane change operation cannot be completed as in the ideal case, but the vehicle center line corresponding to the maximum transverse distance of the vehicle in the lane change process often exceeds the center line of the target lane, so that the vehicle moves to the position corresponding to the maximum transverse distance and then returns to the position where the center line of the vehicle coincides with the center line of the target lane. The above is an explanation of the maximum lateral distance that the vehicle will travel when actually changing lanes according to the candidate lane change trajectory, that is, the maximum lateral distance of the planned trajectory.
The vehicle lane-changing collision parameter is a parameter for evaluating collision risk of an obstacle on a candidate lane-changing track, and the parameter can be set to 0 if no collision risk exists, and can be set to infinity or other specified values if collision risk exists.
After the module responsible for path planning plans a plurality of candidate lane-changing tracks, the corresponding characteristic parameters can be obtained from the description of each candidate lane-changing track, including the overall description of the candidate lane-changing tracks, the position description of each track point, the corresponding vehicle motion parameter description and the like. The obtaining mode of the parameters can be selected by combining practical application scenes and technical requirements, belongs to a mature technology in the field, and is not described in detail in the disclosure.
And step 102, determining a lane change cost integral term corresponding to each candidate lane change track according to the characteristic parameters corresponding to each candidate lane change track.
The lane change cost integral term of the candidate lane change trajectory is used for evaluating the lane change cost of the candidate lane change trajectory, and will be explained in detail in the subsequent embodiments of the present disclosure.
And 103, determining the lane change cost value corresponding to each candidate lane change track according to the lane change cost integral term of each candidate lane change track and a preset lane change cost evaluation strategy.
In the specific implementation process of the disclosure, according to the difference of the lane change cost integral terms selected for lane change cost evaluation, different lane change cost evaluation strategies can be provided to calculate and obtain the lane change cost values corresponding to each candidate lane change track. Or, based on different lane change cost evaluation strategies, different lane change cost integral terms can be selected to be used for lane change cost evaluation.
And 104, determining the candidate lane change track with the minimum lane change cost value as the lane change execution track of the vehicle.
And (4) screening lane change cost values of the candidate lane change tracks obtained in the step 103, and selecting the candidate lane change track with the minimum lane change cost value as an execution track for lane change of the vehicle, so that the vehicle can be controlled and guided to execute a corresponding lane change process according to the determined execution track.
By implementing the lane change trajectory planning method disclosed by the first embodiment of the disclosure, the lane change cost integral terms corresponding to each candidate lane change trajectory are calculated according to the characteristic parameters, then the lane change cost value of each candidate lane change trajectory is calculated by performing weighted summation on the lane change cost integral terms based on a preset lane change cost evaluation strategy, and the candidate lane change trajectory with the minimum lane change cost value is selected as the execution lane change trajectory of the vehicle. Therefore, the stability of the automatic driving vehicle in the lane changing process can be at least ensured, and the lane changing track with the optimal cost is obtained.
In the second embodiment of the present disclosure, the lane change cost integral term includes: a first integral term, a second integral term, and a third integral term; the first integral term is an integral term for characterizing the longitudinal jerk of the vehicle, the second integral term is an integral term for characterizing the lateral jerk of the vehicle, and the third integral term is an integral term for characterizing the distance that the lane change path of the vehicle exceeds the target lane.
The first integral term may be calculated by:
Costjerk_sThe longitudinal stability of the vehicle in the lane changing process can be reflected to a certain extent, namely the intensity of longitudinal movement change in the lane changing process of the vehicle is reflected.
The second integral term can be calculated by:
Costjerk_dThe method can reflect the stability of the transverse direction of the vehicle in the lane changing process to a certain extent, namely reflect the intensity of the transverse motion change in the lane changing process of the vehicle.
The third integral term can be calculated by:
Costover＝(ddst-dmax)2，ddstrepresenting the lateral distance of the current lane from the target lane in the candidate lane-change trajectory, dmaxRepresenting the maximum lateral distance, Cost, in the candidate lane change trajectoryoverRepresenting a third integral term.
CostoverThe method can reflect the transverse displacement deviation of the vehicle in the lane changing process, wherein the transverse displacement deviation is the difference value between the maximum transverse distance in the candidate lane changing track and the transverse distance of the target lane, and can reflect the stability of the vehicle in the lane changing process to a certain extent.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sRepresenting a first integral term, w1Representing a first weight; costjerk_dRepresenting a second integral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Representing a third weight. w is a1、w2、w3The value of (a) can be an empirical value, w, according to actual needs1、w2、w3OfThe same value is used for respectively adjusting Costjerk_s、Costjerk_d、CostoverThe degree of importance or influence of the weighted result is measured. For example: in practical application, Cost is raised if necessarytotalThe influence on the weighting result can be increased by1(ii) a Otherwise, turn down w1。
The second embodiment of the disclosure comprehensively considers the influence of a first integral term, a second integral term and a third integral term on the lane-changing cost value, wherein the first integral term is an integral term for representing the longitudinal jerk of the vehicle, the second integral term is an integral term for representing the transverse jerk of the vehicle, and the third integral term is an integral term for representing the distance of the lane-changing path of the vehicle exceeding the target lane; therefore, the lane change cost evaluation strategy corresponding to the embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of ensuring the stability of the automatic driving vehicle in the lane change process.
In the third embodiment of the present disclosure, the lane change cost integral term includes: a first integral term, a second integral term, a third integral term and a fourth integral term; the first integral term is an integral term used for representing the longitudinal jerk of the vehicle, the second integral term is an integral term used for representing the transverse jerk of the vehicle, the third integral term is an integral term used for representing the distance of the lane changing path of the vehicle exceeding the target lane, and the fourth integral term is an integral term used for representing the total time of the lane changing of the vehicle.
The calculation methods of the first integral term, the second integral term and the third integral term are the same as those in the second embodiment, and are not described herein again. The fourth integral term can be expressed as Costtime＝tsum，CosttimeRepresenting a fourth integral term, tsumIndicating the total time of lane change of the vehicle, CosttimeThe timeliness and the stationarity of the vehicle in the lane changing process of the vehicle can be reflected to a certain extent.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover+w4*Costtime；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sRepresenting a first integral term, w1Representing a first weight; costjerk_dRepresenting a second integral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Represents a third weight; costtimeRepresenting a fourth integral term, w4Representing a fourth weight. w is a1、w2、w3、w4The value of (a) can be an empirical value, w, according to actual needs1、w2、w3、w4Are used for respectively adjusting Costjerk_s、Costjerk_d、Costover、CosttimeThe degree of importance or influence of the weighted result is measured.
Under the third corresponding lane change cost evaluation strategy in the embodiment of the disclosure, due to comprehensive consideration of the influence of a first integral term, a second integral term, a third integral term and a fourth integral term on the lane change cost value, the first integral term is an integral term used for representing the longitudinal jerk of the vehicle, the second integral term is an integral term used for representing the transverse jerk of the vehicle, the third integral term is an integral term used for representing the distance of the lane change path of the vehicle exceeding the target lane, and the fourth integral term is an integral term used for representing the total time of the lane change of the vehicle; therefore, the lane change cost evaluation strategy of the third embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of considering timeliness and stationarity in the lane change process of the automatic driving vehicle.
In the fourth embodiment of the present disclosure, the lane change cost integral term includes: a first integral term, a second integral term, a third integral term and a fifth integral term; the first integral term is an integral term used for representing the longitudinal jerk of the vehicle, the second integral term is an integral term used for representing the transverse jerk of the vehicle, the third integral term is an integral term used for representing the distance of the lane-changing path of the vehicle exceeding the target lane, and the fifth integral term is an integral term used for representing the difference between the final speed of the lane-changing of the vehicle and the cruising speed of the target lane.
The calculation methods of the first integral term, the second integral term and the third integral term are the same as those in the second embodiment, and are not described herein again. The fifth integral term can be calculated by:
Costv_end＝(Vend-Vcruise)2，Vendindicating the speed, V, of the vehicle at the end of the candidate lane change trajectorycruiseRepresenting the cruising speed, Cost, of the vehicle in the target lane of the candidate lane-changing trackv_endRepresents the fifth integral term. Costv_endThe stability of the vehicle in the lane changing process of the vehicle can be reflected to a certain extent.
Costv_endThe difference between the final speed of the vehicle during lane change and the cruising speed of the target lane can be reflected, and the stationarity of the vehicle during the lane change can be reflected.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover+w5*Costv_end；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sRepresenting a first integral term, w1Representing a first weight; costjerk_dRepresenting a second integral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Represents a third weight; costv_endRepresents a fifth integral term, w5Representing a fifth weight. w is a1、w2、w3、w5The value of (a) can be an empirical value, w, according to actual needs1、w2、w3、w5Are used for respectively adjusting Costjerk_s、Costjerk_d、Costover、Costv_endThe degree of importance or influence of the weighted result is measured.
Under the lane change cost evaluation strategy corresponding to the fourth embodiment of the disclosure, due to comprehensive consideration of the influence of a first integral term, a second integral term, a third integral term and a fifth integral term on the lane change cost value, the first integral term is an integral term used for representing the longitudinal jerk of the vehicle, the second integral term is an integral term used for representing the transverse jerk of the vehicle, the third integral term is an integral term used for representing the distance that the lane change path of the vehicle exceeds the target lane, and the fifth integral term is an integral term used for representing the difference between the final lane change speed of the vehicle and the cruising speed of the target lane; therefore, the lane change cost evaluation strategy corresponding to the fourth embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of ensuring the stability of the automatic driving vehicle in the lane change process.
In a fifth embodiment of the present disclosure, the lane change cost integral term includes: a first integral term, a second integral term, a third integral term and a sixth integral term; the first integral term is an integral term used for representing the longitudinal jerk of the vehicle, the second integral term is an integral term used for representing the transverse jerk of the vehicle, the third integral term is an integral term used for representing the distance of the lane changing path of the vehicle exceeding the target lane, and the sixth integral term is an integral term used for representing the lane changing collision parameters of the vehicle.
The calculation methods of the first integral term, the second integral term and the third integral term are the same as those in the second embodiment, and are not described herein again. The sixth integral term can be expressed as CostobstObtaining Cost from a collision or obstacle avoidance module of the vehicleobstCost without collision riskobstIs 0, Cost is determined if there is a collision riskobstIs infinite or other specified value, CostobstThe safety of the vehicle in the lane changing process of the vehicle can be reflected to a certain extent.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover+w6*Costobst；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sRepresenting a first integral term, w1Representing a first weight; costjerk_dRepresents the secondIntegral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Represents a third weight; costobstRepresenting a sixth integral term, w6Representing a sixth weight. w is a1、w2、w3、w6The value of (a) can be an empirical value, w, according to actual needs1、w2、w3、w6Are used for respectively adjusting Costjerk_s、Costjerk_d、Costover、CostobstThe degree of importance or influence of the weighted result is measured.
Under the lane change cost evaluation strategy corresponding to the fifth embodiment of the disclosure, due to comprehensive consideration of the influence of a first integral term, a second integral term, a third integral term and a sixth integral term on the lane change cost value, the first integral term is an integral term used for representing the longitudinal jerk of the vehicle, the second integral term is an integral term used for representing the transverse jerk of the vehicle, the third integral term is an integral term used for representing the distance of the lane change path of the vehicle exceeding the target lane, and the sixth integral term is an integral term used for representing the lane change collision parameter of the vehicle; therefore, the lane change cost evaluation strategy corresponding to the fifth embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of considering both the stability and the safety of the automatic driving vehicle in the lane change process.
In a sixth embodiment of the present disclosure, the lane change cost integral term includes: a first integral term, a second integral term, a third integral term, a fourth integral term, and a fifth integral term. The calculation method of each integral term is described in the foregoing embodiments, and is not described herein again.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover+w4*Costtime+w5*Costv_end；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sA first integral term is represented by a first integral term,w1representing a first weight; costjerk_dRepresenting a second integral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Represents a third weight; costtimeRepresenting a fourth integral term, w4Represents a fourth weight; costv_endRepresents a fifth integral term, w5Representing a fifth weight. w is a1、w2、w3、w4、w5The value of (a) can be an empirical value, w, according to actual needs1、w2、w3、w4、w5Are used for respectively adjusting Costjerk_s、Costjerk_d、Costover、Costtime、Costv_endThe degree of importance or influence of the weighted result is measured.
Under the lane change cost evaluation strategy corresponding to the sixth embodiment of the disclosure, due to comprehensive consideration of the influence of a first integral term, a second integral term, a third integral term, a fourth integral term and a fifth integral term on the lane change cost value, the first integral term is an integral term for representing the longitudinal jerk of the vehicle, the second integral term is an integral term for representing the transverse jerk of the vehicle, the third integral term is an integral term for representing the distance that the lane change path of the vehicle exceeds the target lane, the fourth integral term is an integral term for representing the total time of the lane change of the vehicle, and the fifth integral term is an integral term for representing the difference between the final speed of the lane change of the vehicle and the speed of the target cruise; therefore, the lane change cost evaluation strategy corresponding to the sixth embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of considering timeliness and stability in the lane change process of the automatic driving vehicle.
In an embodiment seven of the present disclosure, the lane change cost integral term includes: a first integral term, a second integral term, a third integral term, a fourth integral term, and a sixth integral term. The calculation method of each integral term is described in the foregoing embodiments, and is not described herein again.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover+w4*Costtime+w6*Costobst；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sRepresenting a first integral term, w1Representing a first weight; costjerk_dRepresenting a second integral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Represents a third weight; costtimeRepresenting a fourth integral term, w4Represents a fourth weight; costobstRepresenting a sixth integral term, w6Representing a sixth weight. w is a1、w2、w3、w4、w6The value of (a) can be an empirical value, w, according to actual needs1、w2、w3、w4、w6Are used for respectively adjusting Costjerk_s、Costjerk_d、Costover、Costtime、CostobstThe degree of importance or influence of the weighted result is measured.
Under the seventh corresponding lane-changing cost evaluation strategy of the embodiment of the disclosure, due to comprehensive consideration of the influence of a first integral term, a second integral term, a third integral term, a fourth integral term and a sixth integral term on the lane-changing cost value, the first integral term is an integral term for representing the longitudinal jerk of the vehicle, the second integral term is an integral term for representing the transverse jerk of the vehicle, the third integral term is an integral term for representing the distance that the lane-changing path of the vehicle exceeds the target lane, the fourth integral term is an integral term for representing the total time of the lane-changing of the vehicle, and the sixth integral term is an integral term for representing the lane-changing collision parameter of the vehicle; therefore, the lane change cost evaluation strategy corresponding to the seventh embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of considering timeliness, stability and safety in the lane change process of the automatic driving vehicle.
In an eighth embodiment of the present disclosure, the lane change cost integral term includes: a first integral term, a second integral term, a third integral term, a fifth integral term, and a sixth integral term. The calculation method of each integral term is described in the foregoing embodiments, and is not described herein again.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover+w5*Costv_end+w6*Costobst；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sRepresenting a first integral term, w1Representing a first weight; costjerk_dRepresenting a second integral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Represents a third weight; costv_endRepresents a fifth integral term, w5Represents a fifth weight; costobstRepresenting a sixth integral term, w6Representing a sixth weight. w is a1、w2、w3、w5、w6The value of (a) can be an empirical value, w, according to actual needs1、w2、w3、w5、w6Are used for respectively adjusting Costjerk_s、Costjerk_d、Costover、Costv_end、CostobstThe degree of importance or influence of the weighted result is measured.
Under the lane change cost evaluation strategy corresponding to the eighth embodiment of the disclosure, due to comprehensive consideration of the influence of a first integral term, a second integral term, a third integral term, a fifth integral term and a sixth integral term on the lane change cost value, the first integral term is an integral term for representing the longitudinal jerk of the vehicle, the second integral term is an integral term for representing the transverse jerk of the vehicle, the third integral term is an integral term for representing the distance that the lane change path of the vehicle exceeds the target lane, the fifth integral term is an integral term for representing the final speed of the lane change of the vehicle and the cruise speed difference of the target lane, and the sixth integral term is an integral term for representing the lane change collision parameter of the vehicle; therefore, the lane change cost evaluation strategy corresponding to the eighth embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of considering both the stability and the safety of the lane change process of the automatic driving vehicle.
In an embodiment nine of the present disclosure, the lane change cost integral term includes: the first integral term, the second integral term, the third integral term, the fourth integral term, the fifth integral term and the sixth integral term. The calculation method of each integral term is described in the foregoing embodiments, and is not described herein again.
Correspondingly, the lane change cost value of each candidate lane change track can be calculated according to the following lane change cost evaluation strategy:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover+w4*Costtime+w5*Costv_end+w6*Costobst；
among them, CosttotalLane-change Cost value, Cost, representing candidate lane-change trajectoriesjerk_sRepresenting a first integral term, w1Representing a first weight; costjerk_dRepresenting a second integral term, w2Representing a second weight; costoverRepresenting a third integral term, w3Represents a third weight; costtimeRepresenting a fourth integral term, w4Represents a fourth weight; costv_endRepresents a fifth integral term, w5Represents a fifth weight; costobstRepresenting a sixth integral term, w6Representing a sixth weight. w is a1、w2、w3、w4、w5、w6The value of (a) can be an empirical value, w, according to actual needs1、w2、w3、w4、w5、w6Are used for respectively adjusting Costjerk_s、Costjerk_d、Costover、Costtime、Costv_end、CostobstThe degree of importance or influence of the weighted result is measured.
Under the lane change cost evaluation strategy corresponding to the ninth embodiment of the disclosure, due to comprehensive consideration of influences of a first integral term, a second integral term, a third integral term, a fourth integral term, a fifth integral term and a sixth integral term on the lane change cost value, the first integral term is an integral term used for representing the longitudinal jerk of the vehicle, the second integral term is an integral term used for representing the transverse jerk of the vehicle, the third integral term is an integral term used for representing the distance that the lane change path of the vehicle exceeds the target lane, the fourth integral term is an integral term used for representing the total time of the lane change of the vehicle, the fifth integral term is an integral term used for representing the difference between the final speed of the lane change of the vehicle and the cruising speed of the target lane, and the sixth integral term is an integral term used for representing the collision parameter of the lane change of the vehicle; therefore, the lane change cost evaluation strategy corresponding to the ninth embodiment of the disclosure obtains the lane change track with the optimal cost on the basis of considering timeliness, stability and safety in the lane change process of the automatic driving vehicle.
It should be noted that, in practical applications, the w of the above embodiment is applied to different vehicle models1～w6The values can be different, and the w for different vehicle types1～w6The empirical values obtained by adjusting the road test performance of different vehicle types are different, and the empirical values are mainly dependent on the hardware performance of different types of vehicles. This disclosure is not to w1～w6The manner of obtaining it is explained too much.
There is also provided according to a tenth embodiment of the present disclosure a lane change trajectory planning apparatus, as shown in fig. 3, the apparatus including:
a candidate lane-changing track obtaining unit 10, configured to obtain multiple candidate lane-changing tracks for lane changing of a vehicle, where the candidate lane-changing tracks are used to describe characteristic parameters of a lane changing operation performed by the vehicle;
a lane change cost integral term obtaining unit 20, configured to determine a lane change cost integral term corresponding to each candidate lane change trajectory according to the characteristic parameter corresponding to each candidate lane change trajectory;
a lane change cost value obtaining unit 30, configured to determine a lane change cost value corresponding to each candidate lane change trajectory according to a lane change cost integral term of each candidate lane change trajectory and a preset lane change cost evaluation policy;
and an execution lane change trajectory determination unit 40 configured to determine a candidate lane change trajectory having the smallest lane change cost value as an execution lane change trajectory of the vehicle.
In one possible embodiment, the lane change cost integral term includes: a first integral term, a second integral term, and a third integral term. The lane change cost evaluation strategy comprises the following steps: and taking the result of weighted summation of the first integral term, the second integral term and the third integral term as the lane change cost value of the corresponding candidate lane change track.
In another possible embodiment, at least one of the following may be further included: a fourth integral term, a fifth integral term, and a sixth integral term. The lane change cost evaluation strategy comprises the following steps: and taking the weighted summation result of at least one of the fourth integral term, the fifth integral term and the sixth integral term, and the first integral term, the second integral term and the third integral term as the lane change cost value of the corresponding candidate lane change track.
For different lane change cost evaluation strategies, reference may be made to the foregoing method embodiments two to nine, which are not described herein again.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, a computer program product, and an autonomous vehicle including the electronic device of the present disclosure, according to embodiments of the present disclosure.
FIG. 4 shows a schematic block diagram of an example electronic device 300 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 4, the apparatus 300 includes a computing unit 301 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)302 or a computer program loaded from a storage unit 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The calculation unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Various components in device 300 are connected to I/O interface 305, including: an input unit 306 such as a keyboard, a mouse, or the like; an output unit 307 such as various types of displays, speakers, and the like; a storage unit 308 such as a magnetic disk, optical disk, or the like; and a communication unit 309 such as a network card, modem, wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The computing unit 301 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 301 performs the respective methods and processes described above, such as the lane-change trajectory planning method. For example, in some embodiments, the lane-change trajectory planning method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 300 via ROM 302 and/or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the lane-change trajectory planning method described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the lane change trajectory planning method by any other suitable means (e.g., by means of firmware).
FIG. 5 shows a schematic block diagram of an example autonomous vehicle that may be used to implement embodiments of the present disclosure. The autonomous vehicle 500 includes an electronic device of an embodiment of the present disclosure, which may be the electronic device 300 of the foregoing example, provided within the autonomous vehicle 500. According to the automatic driving automobile disclosed by the embodiment of the disclosure, the lane change cost integral items corresponding to the candidate lane change tracks are calculated according to the characteristic parameters, then the lane change cost value of each candidate lane change track is calculated by performing weighted summation on the lane change cost integral items based on a preset lane change cost evaluation strategy, and the candidate lane change track with the minimum lane change cost value is selected as the execution lane change track of the automobile. Therefore, the stability of the automatic driving vehicle in the lane changing process can be at least ensured, and the lane changing track with the optimal cost is obtained.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (12)
1. A lane-changing trajectory planning method comprises the following steps:
obtaining a plurality of candidate lane changing tracks of a lane changing of a vehicle, wherein the candidate lane changing tracks are used for describing characteristic parameters of lane changing operation executed by the vehicle;
determining a lane change cost integral term corresponding to each candidate lane change track according to the characteristic parameters corresponding to each candidate lane change track;
determining a lane change cost value corresponding to each candidate lane change track according to a lane change cost integral term of each candidate lane change track and a preset lane change cost evaluation strategy;
and determining the candidate lane change track with the minimum lane change cost value as the execution lane change track of the vehicle.
2. The method of claim 1, wherein the lane change cost integral term comprises: a first integral term, a second integral term, and a third integral term; the first integral term is an integral term for characterizing the longitudinal jerk of the vehicle, the second integral term is an integral term for characterizing the lateral jerk of the vehicle, and the third integral term is an integral term for characterizing the distance that the lane change path of the vehicle exceeds the target lane.
3. The method of claim 2, wherein the lane change cost evaluation strategy comprises: and taking the weighted summation result of the first integral term, the second integral term and the third integral term as the lane change cost value of the corresponding candidate lane change track:
Costtotal＝w1*Costjerk_s+w2*Costjerk_d+w3*Costover；
among them, CosttotalRepresenting the lane change Cost value, Cost, of the candidate lane change trajectoryjerk_sRepresenting said first integral term, w1Representing a first weight; costjerk_dRepresenting said second integral term, w2Representing a second weight; costoverRepresenting said third integral term, w3Representing a third weight.
4. The method of claim 2, wherein the lane change cost integral term further comprises at least one of: a fourth integral term, a fifth integral term and a sixth integral term; the fourth integral term is an integral term used for representing the total lane-changing time of the vehicle, the fifth integral term is an integral term used for representing the difference between the final lane-changing speed of the vehicle and the cruising speed of the target lane, and the sixth integral term is an integral term used for representing the lane-changing collision parameter of the vehicle;
the lane change cost evaluation strategy comprises the following steps: and taking a weighted summation result of at least one of the fourth integral term, the fifth integral term and the sixth integral term, and the first integral term, the second integral term and the third integral term as a lane change cost value of the corresponding candidate lane change track.
5. The method according to any one of claims 2 to 4,
the first integral term is obtained by calculation in the following way:
the second integral term is obtained by calculation in the following way:
6. The method of claim 4 or 5, wherein the third integral term is obtained by: costover＝(ddst-dmax)2；
ddstRepresenting the lateral distance of the current lane from the target lane in the candidate lane-change trajectory, dmaxRepresenting the maximum lateral distance, Cost, in the candidate lane change trajectoryoverRepresenting the third integral term.
7. The method of claim 4 or 5, wherein the fifth integral term is calculated by: costv_end＝(Vend-Vcruise)2；
VendIndicating the speed, V, of the vehicle at the end of the candidate lane change trajectorycruiseRepresenting the cruising speed, Cost, of the vehicle in the target lane of the candidate lane-changing trackv_endRepresents the fifth integral term.
8. A lane-change trajectory planning device comprising:
the lane change candidate track obtaining unit is used for obtaining a plurality of lane change candidate tracks of the lane change of the vehicle, and the lane change candidate tracks are used for describing characteristic parameters of lane change operation executed by the vehicle;
a lane change cost integral term obtaining unit, configured to determine a lane change cost integral term corresponding to each candidate lane change trajectory according to the characteristic parameter corresponding to each candidate lane change trajectory;
a lane change cost value obtaining unit, configured to determine a lane change cost value corresponding to each candidate lane change track according to a lane change cost integral term of each candidate lane change track and a preset lane change cost evaluation policy;
and the execution lane change track determining unit is used for determining the candidate lane change track with the minimum lane change cost value as the execution lane change track of the vehicle.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-7.
11. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-7.
12. An autonomous vehicle comprising the electronic device of claim 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111142043.XA CN113978465A (en) | 2021-09-28 | 2021-09-28 | Lane-changing track planning method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111142043.XA CN113978465A (en) | 2021-09-28 | 2021-09-28 | Lane-changing track planning method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113978465A true CN113978465A (en) | 2022-01-28 |
Family
ID=79737026
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111142043.XA Pending CN113978465A (en) | 2021-09-28 | 2021-09-28 | Lane-changing track planning method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113978465A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115195743A (en) * | 2022-09-16 | 2022-10-18 | 毫末智行科技有限公司 | Automatic lane changing method, device, equipment and medium for vehicle based on unmanned driving |
| CN117601867A (en) * | 2024-01-18 | 2024-02-27 | 杭州鉴智机器人科技有限公司 | Vehicle lane changing method, vehicle lane changing device, storage medium and vehicle control system |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109712421A (en) * | 2019-02-22 | 2019-05-03 | 百度在线网络技术（北京）有限公司 | The speed planning method, apparatus and storage medium of automatic driving vehicle |
| CN110329263A (en) * | 2019-07-05 | 2019-10-15 | 西南交通大学 | The adaptive lane-change method for planning track of automatic driving vehicle |
| CN110481562A (en) * | 2019-08-27 | 2019-11-22 | 重庆长安汽车股份有限公司 | The automatic lane-change optimal trajectory planning of automobile, control method and system |
| CN111081046A (en) * | 2020-01-03 | 2020-04-28 | 北京百度网讯科技有限公司 | Vehicle lane changing method, device, electronic equipment and medium |
| CN111338335A (en) * | 2019-12-31 | 2020-06-26 | 清华大学 | Vehicle local track planning method under structured road scene |
| CN111338346A (en) * | 2020-03-05 | 2020-06-26 | 中国第一汽车股份有限公司 | Automatic driving control method and device, vehicle and storage medium |
| CN111712414A (en) * | 2018-02-19 | 2020-09-25 | 马自达汽车株式会社 | Vehicle control device |
| CN111845774A (en) * | 2020-07-20 | 2020-10-30 | 上海大学 | Automatic driving automobile dynamic trajectory planning and tracking method based on transverse and longitudinal coordination |
| CN113165648A (en) * | 2018-10-31 | 2021-07-23 | Zf汽车德国有限公司 | Control system and control method for planning possible trajectories of a motor vehicle on the basis of sampling |
| CN113276848A (en) * | 2021-04-09 | 2021-08-20 | 江苏大学 | Intelligent driving lane changing and obstacle avoiding track planning and tracking control method and system |
| CN113386795A (en) * | 2021-07-05 | 2021-09-14 | 西安电子科技大学芜湖研究院 | Intelligent decision-making and local track planning method for automatic driving vehicle and decision-making system thereof |
-
2021
- 2021-09-28 CN CN202111142043.XA patent/CN113978465A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111712414A (en) * | 2018-02-19 | 2020-09-25 | 马自达汽车株式会社 | Vehicle control device |
| CN113165648A (en) * | 2018-10-31 | 2021-07-23 | Zf汽车德国有限公司 | Control system and control method for planning possible trajectories of a motor vehicle on the basis of sampling |
| CN109712421A (en) * | 2019-02-22 | 2019-05-03 | 百度在线网络技术（北京）有限公司 | The speed planning method, apparatus and storage medium of automatic driving vehicle |
| CN110329263A (en) * | 2019-07-05 | 2019-10-15 | 西南交通大学 | The adaptive lane-change method for planning track of automatic driving vehicle |
| CN110481562A (en) * | 2019-08-27 | 2019-11-22 | 重庆长安汽车股份有限公司 | The automatic lane-change optimal trajectory planning of automobile, control method and system |
| CN111338335A (en) * | 2019-12-31 | 2020-06-26 | 清华大学 | Vehicle local track planning method under structured road scene |
| CN111081046A (en) * | 2020-01-03 | 2020-04-28 | 北京百度网讯科技有限公司 | Vehicle lane changing method, device, electronic equipment and medium |
| CN111338346A (en) * | 2020-03-05 | 2020-06-26 | 中国第一汽车股份有限公司 | Automatic driving control method and device, vehicle and storage medium |
| CN111845774A (en) * | 2020-07-20 | 2020-10-30 | 上海大学 | Automatic driving automobile dynamic trajectory planning and tracking method based on transverse and longitudinal coordination |
| CN113276848A (en) * | 2021-04-09 | 2021-08-20 | 江苏大学 | Intelligent driving lane changing and obstacle avoiding track planning and tracking control method and system |
| CN113386795A (en) * | 2021-07-05 | 2021-09-14 | 西安电子科技大学芜湖研究院 | Intelligent decision-making and local track planning method for automatic driving vehicle and decision-making system thereof |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115195743A (en) * | 2022-09-16 | 2022-10-18 | 毫末智行科技有限公司 | Automatic lane changing method, device, equipment and medium for vehicle based on unmanned driving |
| CN117601867A (en) * | 2024-01-18 | 2024-02-27 | 杭州鉴智机器人科技有限公司 | Vehicle lane changing method, vehicle lane changing device, storage medium and vehicle control system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113753077A (en) | Method and device for predicting movement locus of obstacle and automatic driving vehicle | |
| CN113682318B (en) | Vehicle running control method and device | |
| CN112526999B (en) | Speed planning method, device, electronic equipment and storage medium | |
| CN113978465A (en) | Lane-changing track planning method, device, equipment and storage medium | |
| CN114506343B (en) | Track planning method, device, equipment, storage medium and automatic driving vehicle | |
| CN112763995A (en) | Radar calibration method and device, electronic equipment and road side equipment | |
| CN114030486B (en) | Track prediction method and device for dynamic obstacle, electronic equipment and storage medium | |
| CN113050621B (en) | Track planning method, track planning device, electronic equipment and storage medium | |
| CN114386599A (en) | Method and device for training trajectory prediction model and trajectory planning | |
| CN117912295A (en) | Vehicle data processing method and device, electronic equipment and storage medium | |
| CN116499487A (en) | Vehicle path planning method, device, equipment and medium | |
| CN113799798B (en) | Method and device for determining running track of vehicle, electronic equipment and memory | |
| CN115782876A (en) | Lane changing track generation method, device and equipment and automatic driving vehicle | |
| CN115959154A (en) | Method and device for generating lane change track and storage medium | |
| CN115214722A (en) | Automatic driving method, device, electronic equipment, storage medium and vehicle | |
| CN115497322A (en) | Narrow road meeting method, device, equipment and storage medium | |
| CN114954532A (en) | Lane line determination method, device, equipment and storage medium | |
| CN113715821A (en) | Method, apparatus, electronic device, and medium for controlling vehicle | |
| CN115230721B (en) | Perception data processing method and device and automatic driving vehicle | |
| CN114132344B (en) | Decision method, device and equipment for automatic driving vehicle and storage medium | |
| CN114771501A (en) | Vehicle lateral control method and device, storage medium and automatic driving vehicle | |
| CN114802279A (en) | ASIL grade information determination method and device for automatic driving vehicle and electronic equipment | |
| CN116572990A (en) | Vehicle control method and device, electronic equipment and vehicle | |
| CN117068198A (en) | Track planning method and device, electronic equipment and automatic driving vehicle | |
| CN116811872A (en) | Lane changing method and apparatus for vehicle, electronic device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |