CN112277944B - Road cruising method, device and medium - Google Patents
Road cruising method, device and medium Download PDFInfo
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- CN112277944B CN112277944B CN202011196409.7A CN202011196409A CN112277944B CN 112277944 B CN112277944 B CN 112277944B CN 202011196409 A CN202011196409 A CN 202011196409A CN 112277944 B CN112277944 B CN 112277944B
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- 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
- B60W30/14—Adaptive cruise control
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Abstract
The application discloses a road cruising method, a device and a medium, which are characterized in that vehicle condition data of a current vehicle and vehicle condition data of at least one target vehicle are obtained; when the preset conditions are met, performing driver operation analysis processing on the vehicle condition data of at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of at least one target vehicle; predicting a lane-changing driving track of the current vehicle based on vehicle condition data of the current vehicle; predicting a driving track of at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver operation habit data of the at least one target vehicle; determining control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of at least one target vehicle; the current vehicle is controlled to carry out road cruising operation based on the control strategy data, so that the safety and the stability of the lane change of the automatic driving vehicle on the road can be greatly improved, and the passenger experience is improved.
Description
Technical Field
The invention relates to the field of automatic driving, in particular to a road cruising method, a device and a medium.
Background
In current road cruise designs, the decision to control whether the current vehicle changes lanes comes primarily from the data input of the angle radar. Under the condition that the current vehicle stably follows the vehicle, if the set vehicle speed of the current vehicle is lower than the vehicle speed of the front vehicle, the system can continuously collect data signals from the angle radar, whether vehicles exist in the range in front of and behind the target lane is determined through the data signals of the angle radar, if the vehicles are not detected within 5 seconds continuously, a lane changing request can be sent, and the system can control the vehicles to change lanes to the target lane. If the vehicle is detected, the system does not control the vehicle to change lane and continue to follow the vehicle. However, since the detection distance of the angle radar is only 30 to 50 meters in the lateral direction, the distance in the travel direction may be less than 20 meters in terms of conversion, and on a highway, the distance of 20 meters is not long enough with respect to the vehicle speed by performing automatic driving control of the vehicle using a HWP (high way pilot). If a vehicle lane change is made primarily on the data signal of the angle radar, a fast approaching trailing vehicle or a suddenly braked leading vehicle may be encountered during the lane change. Also, the angle radar has a blind spot, and for example, a vehicle parallel to the current vehicle may not be detected by the angle radar. Therefore, the road cruise design in the prior art has the problems that passengers in the vehicle experience is poor, and the vehicle is unsafe to change lanes.
Disclosure of Invention
In order to solve the technical problems, the invention provides a road cruising method, a device and a medium, which can greatly improve the safety and the stability of changing the lane of an automatic driving vehicle on a road and improve the experience of passengers.
To achieve the object of the above application, the present application provides a road cruising method, comprising:
acquiring vehicle condition data of a current vehicle and vehicle condition data of at least one target vehicle;
when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet preset conditions, performing driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle;
predicting a lane change driving track of the current vehicle based on the vehicle condition data of the current vehicle;
predicting a driving trajectory of the at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver operating habit data of the at least one target vehicle;
determining control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of the at least one target vehicle;
and controlling the current vehicle to carry out road cruise operation based on the control strategy data of the current vehicle.
In another aspect, the present application also provides a road cruise apparatus, the apparatus comprising:
the data acquisition module is used for acquiring the vehicle condition data of the current vehicle and the vehicle condition data of at least one target vehicle;
the analysis module is used for analyzing and processing the vehicle condition data of the at least one target vehicle by utilizing a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle;
the first prediction module is used for predicting the lane-changing running track of the current vehicle based on the vehicle condition data of the current vehicle;
a second prediction module for predicting a travel track of the at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver's operation habit data of the at least one target vehicle;
the control strategy data determining module is used for determining control strategy data of the current vehicle according to the lane change running track of the current vehicle and the running track of the at least one target vehicle;
and the control module is used for controlling the current vehicle to carry out expressway cruise operation based on the control strategy data of the current vehicle.
In addition, the present application also provides a storage medium, where at least one instruction or at least one program is stored, and the at least one instruction or the at least one program is loaded and executed by a processor to implement any one of the above road cruise methods.
The application has the following beneficial effects:
the method comprises the steps of obtaining vehicle condition data of a current vehicle and vehicle condition data of at least one target vehicle; when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet preset conditions, performing driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle; predicting a lane change driving track of the current vehicle based on the vehicle condition data of the current vehicle; predicting a driving trajectory of the at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver operating habit data of the at least one target vehicle; determining control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of the at least one target vehicle; the current vehicle is controlled to carry out road cruising operation based on the control strategy data of the current vehicle, so that the safety and the stability of lane changing of the automatic driving vehicle on the road can be greatly improved, and the passenger experience is improved.
Drawings
In order to more clearly illustrate the technical solutions of the present application, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flow chart of a road cruising method provided in an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a process for determining driver operating habit data of at least one target vehicle according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of a process for constructing a driver operation analysis model according to an embodiment of the present application;
FIG. 4 is a schematic flow chart illustrating a method for road cruising according to another embodiment of the present application;
fig. 5 is a schematic structural diagram of a road cruising device provided in the embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In order to implement the technical solution of the present application, so that more engineering workers can easily understand and apply the present application, the working principle of the present application will be further described with reference to specific embodiments.
The method can be applied to the field of automatic driving, vehicle condition data of at least one target vehicle are obtained by obtaining vehicle condition data of a current vehicle and utilizing a V2V (vehicle to vehicle communication) module, and when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet a lane change preset condition, whether intersection can be generated between the current vehicle and the at least one target vehicle or not is judged based on the vehicle condition data of the current vehicle and the vehicle condition data of the at least one target vehicle, so that a control strategy for the current vehicle is determined.
In the embodiments, the at least one target vehicle may include a preceding vehicle located in the same lane as the current vehicle, and a vehicle located in a lane adjacent to the current vehicle. When the method is applied to a left-rudder vehicle scene, the lane-changing overtaking is performed by changing lanes to a left lane, and the acquired vehicle condition data of at least one target vehicle mainly comprises vehicle condition data of a vehicle positioned in the left lane of the current vehicle; when the lane-changing overtaking method is applied to a right-steering vehicle scene, the lane-changing overtaking is performed by changing the lane to a right lane, and the acquired vehicle condition data of the at least one target vehicle mainly comprises vehicle condition data of a vehicle positioned in the right lane of the current vehicle.
An embodiment of a road cruising method according to the present application is described below, and fig. 1 is a schematic flow chart of the road cruising method according to the embodiment of the present application, and the method operation steps described in the embodiment or the flow chart are provided in the present specification, but more or less operation steps may be included based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of sequences, and does not represent a unique order of performance. Specifically, as shown in fig. 1, the method may include:
s101: vehicle condition data of a current vehicle and vehicle condition data of at least one target vehicle are acquired.
Specifically, the current vehicle condition data refers to operation data generated by operating the current vehicle based on the current control strategy data, for example, current vehicle condition data such as a steering wheel angle, a steering wheel torque, a driving direction, an accelerator depth, a brake depth, a driving speed, and a vehicle position of the current vehicle. The vehicle condition data of the at least one target vehicle is vehicle condition data of vehicles located around the current vehicle, for example, vehicle condition data such as a traveling speed of a vehicle located in front of the same lane as the current lane, a traveling speed, a traveling direction, and a vehicle position of a vehicle located in a lane adjacent to the current vehicle.
In some embodiments, vehicle condition data for the current vehicle may be collected using sensors, which may include angle radar, front-facing camera, front-facing radar, GPS sensor, etc. mounted on the current vehicle. The vehicle condition data of at least one target vehicle is acquired by the target vehicle through a sensor of the target vehicle, and the current vehicle utilizes the V2V module to receive the vehicle condition data sent by the target vehicle. The communication distance of the V2V is far away from 500 meters, in actual application, in order to reduce data processing amount, vehicles in a circular area with the current vehicle as a circle center and five hundred meters as a radius are selected as target vehicles, data analysis is carried out based on the vehicles in the area, and the data processing amount of the current vehicle can be reduced while safe lane changing operation is controlled.
S103: and when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet preset conditions, performing driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle.
Specifically, the condition data of the current vehicle, and/or the condition data of the at least one target vehicle satisfying the preset condition may include the following cases:
(1) The vehicle condition data of the current vehicle includes a traveling speed of the current vehicle, and the vehicle condition data of the at least one target vehicle includes: the running speed of a front vehicle in the same lane as the current vehicle is higher than that of the front vehicle in the same lane as the current vehicle;
(2) The vehicle condition data of the current vehicle comprise a front image collected by a camera, and the obstacle in front of the current vehicle is determined based on the front image;
(3) The vehicle condition data of the at least one target vehicle comprises that the distance between a parallel vehicle positioned in the adjacent lane of the current vehicle and the current vehicle is less than a preset safety distance.
When any one of the above conditions is met, the feasibility analysis of lane changing operation is required to be performed on the current vehicle, so as to determine whether lane changing is performed, and if so, which way is adopted.
Specifically, the driver operation analysis model may include different operation habit data corresponding to different types of drivers. As shown in fig. 2, the performing, by using a preset driver operation analysis model, driver operation analysis processing on the vehicle condition data of the at least one target vehicle, and obtaining driver operation habit data of the at least one target vehicle may include:
s1041: and determining a driver type corresponding to the vehicle condition data of at least one target vehicle based on the second mapping relation in the driver operation analysis model.
Specifically, the preset driver operation analysis model may include a second mapping relationship between a plurality of driver types and corresponding vehicle condition data. The vehicle condition data may be represented as different kinds of operation data in different embodiments, and the vehicle condition data may be data such as switching time of accelerator and brake, driving acceleration, or turning angle/moment of a steering wheel. Taking the driving acceleration of the vehicle as an example, if the driver is aggressive, the brake and accelerator depths are large, the displayed driving acceleration value of the vehicle is also large, and if the driver is conservative, the brake and accelerator depths are small, the displayed driving acceleration value of the vehicle is small.
In some embodiments, the current vehicle is a left-handed vehicle, the left lane of the current vehicle has only one target vehicle, and if the current vehicle changes to the left lane, the target vehicle in the left lane needs to be analyzed. Firstly, the vehicle condition data of the target vehicle is obtained by using a V2V module, and the vehicle condition data of the target vehicle comprises a plurality of switching times of an accelerator and a brake. The current vehicle acquires the switching time of a plurality of throttles and brakes of the target vehicle, the abnormal switching time of the throttles and the brakes can be removed, average calculation processing is carried out on the remaining switching time of the plurality of throttles and the brakes of the target vehicle, and the average switching time of the throttles and the brakes of the target vehicle is determined. And comparing the average switching time of the accelerator and the brake of the target vehicle with the switching time of the accelerator and the brake of the vehicles driven by different types of drivers in the driver operation analysis model, and determining the type of the driver to which the driver of the target vehicle in the left lane belongs.
S1042: and determining driver operation habit data corresponding to the driver type based on the first mapping relation in the driver operation analysis model, wherein the driver operation habit data are used as the driver operation habit data of at least one target vehicle.
Specifically, the pre-established driver operation analysis model may include a first mapping relationship between each of the plurality of driver types and the corresponding operation habit data, and the corresponding operation habit data may be determined by the driver type corresponding to the at least one target vehicle, so as to obtain the driver operation habit data of the at least one target vehicle.
In this embodiment, the data of the driver operation analysis model is derived from the operation habits of a large number of drivers under typical conditions. For example, on a highway, a driver can obtain information within an observation distance of about two hundred meters through two side rearview mirrors, including whether a vehicle exists or not, and visually observe motion state information of at least one target vehicle around, so as to artificially plan an optimal driving route. And determining the driver operation habit data of the at least one target vehicle based on the data of the driver operation analysis model, so that the determination process of the driver operation habit data of the at least one target vehicle is more reliable and is closer to the actual operation habit of the driver.
In some embodiments, as shown in FIG. 3, the predetermined driver operation analysis model may be determined using the following steps:
s1031: operation habit data of a plurality of drivers is acquired.
Specifically, the plurality of drivers may include various types of drivers, such as a plurality of aggressive drivers, a plurality of normal drivers, a plurality of conservative drivers, and the like. The method comprises the steps of obtaining operation habit data of a plurality of drivers, wherein the operation habit data specifically comprises data such as switching time of an accelerator and a brake, stepping depth and gradient of the accelerator, and speed and moment of a steering wheel.
S1032: the method comprises the steps of classifying a plurality of drivers based on operation habit data of the plurality of drivers to obtain operation habit data corresponding to a plurality of driver types and a driver set corresponding to the plurality of driver types.
Specifically, classifying the drivers based on the operation habit data of the drivers means that the operation habit data of the drivers are divided into different sections, and then the drivers are classified into different types according to the operation habit data of different sections, for example, the operation habit data may include switching time of the accelerator and the brake, the driver with the switching time of the accelerator and the brake of 0.7 to 1.2 seconds is an aggressive driver, the driver with the switching time of the accelerator and the brake of 1.2 to 1.7 seconds is a normal driver, and the driver with the switching time of the accelerator and the brake of 1.7 to 2.2 seconds is an aggressive driver. Thus, a mapping relation between the driver type and the corresponding operation habit data is established.
S1033: a first mapping relation between each of the plurality of driver types and the corresponding operation habit data is established.
S1034: and acquiring vehicle condition data corresponding to the vehicle driven by the driver in each driver set.
Specifically, after obtaining the different types of driver classifications, vehicle condition data corresponding to the vehicles driven by the drivers in each driver set is collected, and the vehicle condition data corresponding to the vehicles driven by the drivers refers to data of vehicle running states under the operation of the drivers, for example, running speed of one aggressive driver driven vehicle, change data of an accelerator, change data of a brake, and running speed change data of the vehicle.
S1035: and determining the vehicle condition data of the driver type driving vehicle corresponding to the driver set according to the vehicle condition data corresponding to the vehicle driven by the driver in each driver set.
S1036: and establishing a second mapping relation between the plurality of driver types and the corresponding vehicle condition data.
S1037: and taking the first mapping relation and the second mapping relation as a driver operation analysis model.
Specifically, according to the specific vehicle condition data value corresponding to each driver driving the vehicle in each driver set, the value range of each vehicle condition data in the vehicle condition data of the driver type driving the vehicle corresponding to the driver set can be determined, so as to obtain the vehicle condition data of each driver type driving the vehicle.
In this embodiment, by acquiring operation habit data of a plurality of drivers; classifying the plurality of drivers based on the operation habit data to obtain a driver set corresponding to the plurality of driver types; acquiring vehicle condition data corresponding to vehicles driven by drivers in each driver set; and determining the vehicle condition data of the driver type driving vehicle corresponding to the driver set according to the vehicle condition data corresponding to the vehicle driven by the driver in each driver set, so as to obtain a first mapping relation and a second mapping relation, namely a driver operation analysis model.
S105: and predicting the lane change driving track of the current vehicle based on the vehicle condition data of the current vehicle.
Specifically, the vehicle condition data of the current vehicle may include vehicle condition data such as a steering wheel angle, a steering wheel torque, a driving direction, an accelerator depth, a brake depth, a driving speed, and a vehicle position of the current vehicle. By changing part or all of data in the angle of the steering wheel, the torque of the steering wheel, the driving direction, the depth of an accelerator, the depth of a brake, the driving speed and the position of the vehicle, the lane changing operation of the current vehicle within the preset time is realized, and the position of the vehicle at each moment within the preset time can be determined, so that the lane changing driving track of the current vehicle is obtained.
S107: and predicting the running track of the at least one target vehicle based on the vehicle condition data of the at least one target vehicle and the driver operating habit data of the at least one target vehicle.
Specifically, in the embodiment of the present application, the at least one target vehicle refers to a vehicle around the current vehicle, which will affect lane change of the current vehicle. In a practical application scenario, a preceding vehicle located in the same lane as the current vehicle, a vehicle parallel to the current vehicle in the target lane, and a vehicle located in front of, behind, and closest to the current vehicle in the target lane may be determined. For example, if the current vehicle is a left-handed vehicle, a vehicle a is located on a left lane of the current vehicle and parallel to the current vehicle, a vehicle B is located 20 meters ahead of the current vehicle, a vehicle C is located 50 meters ahead of the current vehicle, a vehicle D is located 20 meters behind the current vehicle, and a vehicle E is located 50 meters behind the current vehicle, then at least one target vehicle in the current scene may be the vehicle a, the vehicle B, and the vehicle D. In this embodiment, the vehicle condition data of the vehicle a, the vehicle B, and the vehicle D and the respective corresponding driver operating habit data are analyzed to determine the traveling trajectories of the vehicle a, the vehicle B, and the vehicle D.
S109: and determining the control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of at least one target vehicle.
Specifically, whether the lane change measure of the current vehicle is safe or not can be determined by judging whether the intersection exists between the lane change running track of the current vehicle and the running track of at least one target vehicle. When it is determined that the intersection does not exist between the lane-changing running track of the current vehicle and the running track of the at least one target vehicle, determining the steering angle and the running speed of the current vehicle within preset time based on the lane-changing running track of the current vehicle, and taking the steering angle and the running speed of the current vehicle within the preset time as control strategy data of the current vehicle. Specifically, at each moment in the preset time, the steering angle and the running speed of the current vehicle may be changed, and the control mode of the corresponding component of the current vehicle at the corresponding moment is determined according to the steering angle and the running speed of the current vehicle at each moment and is used as the control strategy data of the current vehicle at each moment.
And if the judgment result is that intersection exists, controlling the current vehicle not to change the lane, and simultaneously performing deceleration braking operation. For example, a target vehicle F exists 100 meters behind the left lane of the current vehicle, the target vehicle F is accelerating, and before the current vehicle changes to the left lane, it is determined that there is an intersection between the traveling tracks of the target vehicle F and the current vehicle, and then according to the determination result, the current vehicle is controlled not to change, and at the same time, a deceleration braking operation can be performed.
S111: and controlling the current vehicle to carry out road cruise operation based on the control strategy data of the current vehicle.
The embodiment obtains the vehicle condition data of the current vehicle and the vehicle condition data of at least one target vehicle; when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet preset conditions, performing driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle; predicting a lane-changing driving track of the current vehicle based on the vehicle condition data of the current vehicle; predicting a driving trajectory of the at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver operating habit data of the at least one target vehicle; determining control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of the at least one target vehicle; the current vehicle is controlled to carry out road cruising operation based on the control strategy data of the current vehicle, so that the safety and the stability of lane changing of the automatic driving vehicle on the road can be greatly improved, and the adverse emotions of passengers, such as stress and the like, caused by sudden actions of surrounding vehicles of the passengers in the current vehicle are avoided.
In other embodiments, as shown in fig. 4, the method may include:
s101: vehicle condition data of a current vehicle and vehicle condition data of at least one target vehicle are acquired.
Specifically, the current vehicle condition data refers to operation data generated by operating the current vehicle based on the current control strategy data, for example, current vehicle condition data such as a steering wheel angle, a steering wheel torque, a driving direction, an accelerator depth, a brake depth, a driving speed, and a vehicle position of the current vehicle. The vehicle condition data of the at least one target vehicle refers to vehicle condition data of vehicles located around the current vehicle, for example, vehicle condition data such as a traveling speed of a vehicle located in front of the same lane as the current lane, a traveling speed, a traveling direction, and a vehicle position of a vehicle located in a lane adjacent to the current vehicle.
S103: and when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet preset conditions, performing driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle.
S104: and acquiring preset operation habit data of the current vehicle.
Specifically, the preset operation habit data of the current vehicle may be operation habit data considered to be set in advance, for example, if there is an infant in the current vehicle, the operation habit data may be preset to be operation habit data corresponding to a conservative driver driving the vehicle; the passenger in the current vehicle is an aggressive driver, and the operation habit data can be preset as operation habit data corresponding to the aggressive driver driving the vehicle.
S105': and predicting the lane change running track of the current vehicle based on the vehicle condition data of the current vehicle and the preset operation habit data of the current vehicle.
Specifically, the current vehicle condition data may include current vehicle condition data such as a steering wheel angle, a steering wheel torque, a driving direction, an accelerator depth, a brake depth, a driving speed, and a vehicle position. By changing part or all of the data in the steering wheel angle, the steering wheel torque, the driving direction, the accelerator depth, the brake depth, the driving speed and the vehicle position and changing the data according to the trend of preset operation habit data, the lane changing operation of the current vehicle within preset time is realized, the position of the vehicle within the preset time at each moment can be determined, the lane changing driving track of the current vehicle is obtained, meanwhile, the lane changing process approaches to the operation habit data preset by a passenger, and the riding experience of the passenger can be improved.
S107: and predicting the running track of the at least one target vehicle based on the vehicle condition data of the at least one target vehicle and the driver operating habit data of the at least one target vehicle.
S109: and determining the control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of at least one target vehicle.
S111: and controlling the current vehicle to carry out road cruise operation based on the control strategy data of the current vehicle.
According to the embodiment, by acquiring the vehicle condition data of the current vehicle and the vehicle condition data of at least one target vehicle, when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet preset conditions, a preset driver operation analysis model is used for carrying out driver operation analysis processing on the vehicle condition data of the at least one target vehicle to obtain the driver operation habit data of the at least one target vehicle; acquiring preset operation habit data of a current vehicle, and predicting a lane-changing running track of the current vehicle based on vehicle condition data of the current vehicle and the preset operation habit data of the current vehicle; the method comprises the steps of predicting a running track of at least one target vehicle based on vehicle condition data of at least one target vehicle and driver operation habit data of at least one target vehicle, determining control strategy data of the current vehicle according to a lane changing running track of the current vehicle and the running track of the at least one target vehicle, and finally controlling the current vehicle to carry out road cruise operation based on the control strategy data of the current vehicle, so that the safety and the stability of the lane changing of the automatic driving vehicle on a road are greatly improved, customized riding requirements of users are met, and user experience is improved.
The following describes an embodiment of a road cruise device according to the present application, and fig. 5 is a schematic structural diagram of a road cruise device according to the present application, and as shown in the figure, the device may include:
the vehicle condition data acquiring module 501 is configured to acquire vehicle condition data of a current vehicle and vehicle condition data of at least one target vehicle.
The analysis module 502 is configured to perform analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle.
The first prediction module 503 is configured to predict a lane-changing driving track of the current vehicle based on vehicle condition data of the current vehicle.
A second prediction module 504 for predicting a driving trajectory of the at least one target vehicle based on the vehicle condition data of the at least one target vehicle and the driver operating habit data of the at least one target vehicle.
And the control strategy data determining module 505 is configured to determine the control strategy data of the current vehicle according to the lane change running track of the current vehicle and the running track of at least one target vehicle.
And a control module 506 for controlling the current vehicle to perform the highway cruise operation based on the control strategy data of the current vehicle.
In further embodiments, the apparatus may further comprise:
and the sample operation data acquisition module is used for acquiring operation habit data of a plurality of drivers.
And the driver type determining module is used for classifying the plurality of drivers based on the operation habit data to obtain a driver set corresponding to the plurality of driver types.
And the sample vehicle condition data acquisition module is used for acquiring vehicle condition data corresponding to vehicles driven by the drivers in each driver set.
And the mapping relation determining module is used for determining the vehicle condition data of the driver type driving vehicle corresponding to the driver set according to the vehicle condition data corresponding to the driver driving vehicle in each driver set.
In some embodiments, the vehicle condition data acquisition module may include:
the first data acquisition unit is used for acquiring the vehicle condition data of the current vehicle by using the sensor.
And the second data acquisition unit is used for acquiring the vehicle condition data of at least one target vehicle by using the vehicle-to-vehicle communication module.
In further embodiments, the apparatus may further include:
and the preset operation data acquisition module is used for acquiring the preset operation habit data of the current vehicle.
Correspondingly, the first prediction module can be further used for predicting the lane-changing running track of the current vehicle based on the vehicle condition data of the current vehicle and the preset operation habit data of the current vehicle.
In another embodiment, the apparatus may further include a driver operation analysis model building module, and specifically, the module may include:
and the comparison unit is used for comparing the vehicle condition data of at least one target vehicle with the vehicle condition data of different types of drivers driving the vehicles in the preset driver operation analysis model, and determining the driver type corresponding to the at least one target vehicle.
And the operation data determining unit is used for searching the driver operation habit data corresponding to the driver type corresponding to the at least one target vehicle in the preset driver operation analysis model based on the driver type corresponding to the at least one target vehicle to obtain the driver operation habit data of the at least one target vehicle.
In further embodiments, the control policy data determination module may include:
the first judging unit is used for judging whether the lane-changing running track of the current vehicle and the running track of at least one target vehicle have intersection or not.
The control strategy data determining unit is used for determining the steering angle and the running speed of the current vehicle within preset time based on the lane-changing running track of the current vehicle; and taking the steering angle and the running speed of the current vehicle in preset time as the control strategy data of the current vehicle.
The present application further provides an embodiment of a computer-readable storage medium, where at least one instruction or at least one program is stored in the storage medium, and the at least one instruction or the at least one program is loaded and executed by a processor to implement the road cruise method in any one of the above embodiments.
The embodiment is characterized in that the vehicle condition data of the current vehicle and the vehicle condition data of at least one target vehicle are obtained; when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet preset conditions, performing driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle; predicting a lane change driving track of the current vehicle based on the vehicle condition data of the current vehicle; predicting a driving trajectory of the at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver operating habit data of the at least one target vehicle; determining control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of the at least one target vehicle; the current vehicle is controlled to carry out road cruising operation based on the control strategy data of the current vehicle, so that the safety and the stability of lane changing of the automatic driving vehicle on the road can be greatly improved, and the passenger experience is improved.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: rather, the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that although embodiments described herein include some features included in other embodiments, not other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims of the present invention, any of the claimed embodiments may be used in any combination.
The present invention may also be embodied as apparatus or system programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps or the like not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several systems, several of these systems may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering and these words may be interpreted as names.
Claims (10)
1. A method of road cruising, the method comprising:
acquiring vehicle condition data of a current vehicle and vehicle condition data of at least one target vehicle; the vehicle condition data of the current vehicle refers to operation data generated by operation based on control strategy data; the vehicle condition data of the current vehicle comprises at least one or more of a steering wheel angle, a steering wheel torque, a driving direction, an accelerator depth, a brake depth, a driving speed and a vehicle position of the current vehicle; the vehicle condition data of the at least one target vehicle refers to vehicle condition data of vehicles around the current vehicle, and the vehicle condition data of the at least one target vehicle comprises at least one or more of driving speed, driving direction and vehicle position;
when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet lane change preset conditions, performing driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using a preset driver operation analysis model to obtain driver operation habit data of the at least one target vehicle;
predicting a lane change driving track of the current vehicle based on the vehicle condition data of the current vehicle;
predicting a driving trajectory of the at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver operating habit data of the at least one target vehicle;
determining control strategy data of the current vehicle according to the lane-changing running track of the current vehicle and the running track of the at least one target vehicle;
and controlling the current vehicle to carry out road cruise operation based on the control strategy data of the current vehicle.
2. The method of claim 1, wherein the predetermined driver operation analysis model comprises determining using the steps of:
acquiring operation habit data of a plurality of drivers;
classifying the drivers based on the operation habit data of the drivers to obtain operation habit data corresponding to a plurality of driver types and a driver set corresponding to the driver types;
establishing a first mapping relation between each of the plurality of driver types and corresponding operation habit data;
acquiring vehicle condition data corresponding to vehicles driven by drivers in each driver set;
determining vehicle condition data of the driver type driving vehicle corresponding to the driver set according to the vehicle condition data corresponding to the driver driving vehicle in each driver set;
establishing a second mapping relation between the multiple driver types and the corresponding vehicle condition data;
and taking the first mapping relation and the second mapping relation as a driver operation analysis model.
3. The method according to claim 2, wherein the performing the driver operation analysis processing on the vehicle condition data of the at least one target vehicle by using the preset driver operation analysis model to obtain the driver operation habit data of the at least one target vehicle comprises:
determining a driver type corresponding to the vehicle condition data of the at least one target vehicle based on a second mapping relation in the driver operation analysis model;
and determining the driver operation habit data corresponding to the driver type based on the first mapping relation in the driver operation analysis model, wherein the driver operation habit data is used as the driver operation habit data of the at least one target vehicle.
4. The method of claim 1, wherein the obtaining vehicle condition data for a current vehicle and vehicle condition data for at least one target vehicle comprises:
acquiring vehicle condition data of the current vehicle by using a sensor;
vehicle condition data of the at least one target vehicle is collected using a vehicle-to-vehicle communication module.
5. The method of claim 1, wherein prior to predicting the lane-change travel trajectory of the current vehicle based on the vehicle condition data of the current vehicle, the method further comprises:
acquiring preset operation habit data of a current vehicle;
correspondingly, the predicting of the lane-changing running track of the current vehicle based on the vehicle condition data of the current vehicle is replaced by:
and predicting the lane-changing running track of the current vehicle based on the vehicle condition data of the current vehicle and the preset operation habit data of the current vehicle.
6. The method of claim 1, wherein determining control strategy data for a current vehicle based on the lane change trajectory of the current vehicle and the trajectory of the at least one target vehicle comprises:
judging whether intersection exists between the lane-changing running track of the current vehicle and the running track of the at least one target vehicle;
if the intersection does not exist, determining the steering angle and the running speed of the current vehicle within preset time based on the lane-changing running track of the current vehicle;
and taking the steering angle and the running speed of the current vehicle in preset time as control strategy data of the current vehicle.
7. The method of claim 6, further comprising:
and if the intersection exists, controlling the vehicle not to change the lane.
8. The method of claim 1, wherein the at least one target vehicle comprises: and taking the current vehicle as the center of a circle and taking five hundred meters as the radius.
9. A road cruise apparatus, characterised in that the apparatus comprises:
the data acquisition module is used for acquiring the vehicle condition data of the current vehicle and the vehicle condition data of at least one target vehicle; the vehicle condition data of the current vehicle is operation data generated by operation based on control strategy data; the vehicle condition data of the current vehicle comprises at least one or more of a steering wheel angle, a steering wheel torque, a driving direction, an accelerator depth, a brake depth, a driving speed and a vehicle position of the current vehicle; the vehicle condition data of the at least one target vehicle refers to vehicle condition data of vehicles positioned around the current vehicle, and the vehicle condition data of the at least one target vehicle comprises at least one or more of driving speed, driving direction and vehicle position;
the analysis module is used for analyzing and processing the vehicle condition data of the at least one target vehicle by utilizing a preset driver operation analysis model when the vehicle condition data of the current vehicle and/or the vehicle condition data of the at least one target vehicle meet lane change preset conditions to obtain driver operation habit data of the at least one target vehicle;
the first prediction module is used for predicting the lane change running track of the current vehicle based on the vehicle condition data of the current vehicle;
a second prediction module for predicting a travel track of the at least one target vehicle based on vehicle condition data of the at least one target vehicle and driver's operation habit data of the at least one target vehicle;
the control strategy data determining module is used for determining control strategy data of the current vehicle according to the lane change running track of the current vehicle and the running track of the at least one target vehicle;
and the control module is used for controlling the current vehicle to carry out expressway cruise operation based on the control strategy data of the current vehicle.
10. A computer-readable storage medium, in which at least one instruction or at least one program is stored, which is loaded and executed by a processor to implement the road cruising method as claimed in any one of claims 1 to 8.
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| CN112477884B (en) * | 2020-11-11 | 2022-03-08 | 东风汽车集团有限公司 | Automatic driving control method and device and vehicle |
| CN114407930B (en) * | 2022-02-11 | 2023-09-05 | 福思(杭州)智能科技有限公司 | Vehicle track prediction method and device, electronic equipment and vehicle |
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