CN111256714A - Path planning method and device and vehicle - Google Patents
Path planning method and device and vehicle Download PDFInfo
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- CN111256714A CN111256714A CN201811457437.2A CN201811457437A CN111256714A CN 111256714 A CN111256714 A CN 111256714A CN 201811457437 A CN201811457437 A CN 201811457437A CN 111256714 A CN111256714 A CN 111256714A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/343—Calculating itineraries, i.e. routes leading from a starting point to a series of categorical destinations using a global route restraint, round trips, touristic trips
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- 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
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- 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
Abstract
The disclosure relates to a path planning method, a path planning device and a vehicle, wherein the current position information and the driving environment information of a first vehicle are acquired; then determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually driven vehicle at the current position; and determining the target path of the first vehicle according to the target driving parameter information and the driving environment information. The technical scheme disclosed by the invention can plan the running path of the automatic driving vehicle according to the driving behavior parameters of the public driving vehicle, can enable the driving behavior of the unmanned driving vehicle to be closer to the driving behavior of human beings, and can solve the technical problem of difficult path planning of the unmanned driving vehicle under complex working conditions.
Description
Technical Field
The disclosure relates to the technical field of vehicles, in particular to a path planning method, a path planning device and a vehicle.
Background
Path planning for autonomous vehicles presumably involves global path planning and local path planning. The overall path planning means that a driving route from a departure place to a destination is set for the unmanned vehicle; the local path planning refers to how to obtain an ideal traveling path when encountering obstacles, pedestrians, vehicles, even small animals and the like in the driving process. In the current general path planning, an ideal path is usually planned on a structured road (a driving road with clear and regular edges, flat road surface and obvious lane lines and other artificial marks) by using satellite positioning and an off-line map stored by the self. Wherein in order to guarantee that the automatic driving vehicle can drive stably, all adopt the mode of vision to monitor the lane line, when the lane line disappears (for example face the comparatively complicated environment that some bends, crossroads, toll station etc. lack the lane line), most automatic driving system all can judge that current operating mode does not satisfy the automatic driving operating condition, hardly obtains stable only driving route, can produce the condition that can't drive a vehicle even.
Disclosure of Invention
The invention aims to provide a path planning method, a path planning device and a vehicle, which are used for solving the technical problem that a stable driving path cannot be planned under the complex driving environment of the current automatic driving vehicle facing partial curves, crossroads, toll stations and the like which lack lane lines.
In order to achieve the above object, a first aspect of the present disclosure provides a path planning method applied to a first vehicle, the method including:
acquiring current position information and driving environment information of the first vehicle;
determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position;
and determining a target path of the first vehicle according to the target driving parameter information and the driving environment information.
Optionally, the method further comprises:
acquiring a destination position of the first vehicle;
the determining the target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position comprises:
acquiring driving paths of a plurality of target vehicles between the current position and the target position within a preset distance range from the current position;
acquiring the driving parameter information of a plurality of target vehicles on the driving path;
determining target driving parameter information of the first vehicle according to the driving parameter information of a plurality of target vehicles.
Optionally, the determining target driving parameter information of the first vehicle according to the driving parameter information of a plurality of target vehicles includes:
acquiring a mean value of the driving parameter information of a plurality of the target vehicles at the same position;
determining an average of the driving vehicle parameter information as the target driving parameter information of the first vehicle.
Optionally, the determining the target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position includes:
determining a first path of the first vehicle according to driving paths of a plurality of target vehicles;
acquiring the driving parameter information of the target vehicle of which the driving path is the first path;
determining the driving parameter information of the target vehicle at the current location as a target driving parameter of the first vehicle at the current location.
In a second aspect of the present disclosure, there is provided a path planning apparatus for use with a first vehicle, the apparatus comprising:
the acquisition module is used for acquiring the current position information and the driving environment information of the first vehicle;
the first determination module is used for determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position;
and the second determining module is used for determining the target path of the first vehicle according to the target driving parameter information and the driving environment information.
Optionally, the obtaining module is further configured to:
acquiring a destination position of the first vehicle;
the first determining module includes:
the first obtaining submodule is used for obtaining driving paths of a plurality of target vehicles within a preset distance range from the current position between the current position and the target position;
the second obtaining submodule is used for obtaining the driving parameter information of the target vehicles on the driving path;
the first determining submodule is used for determining target driving parameter information of the first vehicle according to the driving parameter information of the target vehicles.
Optionally, the first determining sub-module is configured to:
acquiring a mean value of the driving parameter information of a plurality of the target vehicles at the same position;
determining an average of the driving vehicle parameter information as the target driving parameter information of the first vehicle.
Optionally, the first determining module further includes:
a second determination submodule for determining a first path of the first vehicle according to driving paths of a plurality of the target vehicles;
a third obtaining sub-module, configured to obtain the driving parameter information of the target vehicle of which the driving path is the first path;
a third determining sub-module for determining the driving parameter information of the target vehicle at the current location as a target driving parameter of the first vehicle at the current location.
In a third aspect of the present disclosure, there is provided a vehicle comprising the path planning apparatus described in the second aspect above.
According to the technical scheme, the current position information and the driving environment information of the first vehicle are obtained; then, determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position; and determining a target path of the first vehicle according to the target driving parameter information and the driving environment information. The technical scheme disclosed by the invention can plan the running path of the automatic driving vehicle according to the driving behavior parameters of the manual driving vehicle, can enable the driving behavior of the automatic driving vehicle or the unmanned driving vehicle to be closer to the human driving behavior, and can solve the technical problem of difficult path planning of the unmanned driving vehicle under the complex working condition.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
fig. 1 is a flowchart of a path planning method according to an exemplary embodiment of the present disclosure;
FIG. 2 is a flow chart of a method of path planning according to the embodiment shown in FIG. 1;
FIG. 3 is a flow chart of a method of path planning according to the embodiment shown in FIG. 2;
FIG. 4 is a flow chart of another path planning method according to the embodiment shown in FIG. 2;
fig. 5 is a block diagram of a path planning apparatus according to another exemplary embodiment of the present disclosure;
FIG. 6 is a block diagram of a path planner according to the embodiment shown in FIG. 5;
fig. 7 is a block diagram of a path planning apparatus according to the embodiment shown in fig. 5.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a flowchart of a path planning method according to an exemplary embodiment of the present disclosure; referring to fig. 1, the path planning method is applied to a first vehicle, and includes:
Illustratively, the first vehicle is an unmanned vehicle or an automatic vehicle, wherein the automatic vehicle refers to a vehicle comprising a manual driving mode and an automatic driving mode, and the driver can select manual driving or automatic driving according to requirements. For example, companies such as audi, walvo, and speed develop automobiles with an automatic driving function, and a driver selects a manual driving mode when he wants to drive the automobile by himself or selects an automatic driving mode when he wants to drive the automobile automatically for a while. The unmanned vehicle completely gives the driving task to the machine, and also calls the vehicle to drive autonomously. For example, in the case of google unmanned vehicles, the starting and stopping buttons are provided without a steering wheel and an accelerator, and only the destination needs to be set, and the driving route and the driving speed are determined by the vehicles. The current position of the vehicle may be obtained by a GPS (Global Positioning System) System in combination with a high-precision map, and the driving environment information may include road conditions around the first vehicle, the shape, size, position, and whether or not to move an obstacle, the position, driving direction, and speed of another vehicle, the position and moving direction of a pedestrian, and the like. The driving environment information can be acquired through various sensors or cameras.
And 102, determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually driven vehicle at the current position.
For example, when the first vehicle is an autonomous vehicle, the manually driven vehicle may be the first vehicle itself, and the driving parameter information of the manually driven vehicle at the current position may refer to driving parameter information of the first vehicle when passing through the position in the manual driving mode. The driving parameter information may be at least one of a driving speed of the vehicle, a steering wheel angle, a brake pedal signal, an accelerator pedal signal, a vehicle longitudinal acceleration, a vehicle lateral acceleration, and a vehicle yaw rate. In one embodiment, the autonomous vehicle may determine the target driving parameter information of the first vehicle at the current position at the current moment according to the driving parameter information of the manually-driven vehicle at the current position at which the first vehicle is located within a historical time (within a preset time period from the current time, for example, half a month, one week or three days ago). In another embodiment, the autonomous vehicle may also determine the target driving parameter information of the first vehicle at the current position at the current time according to the driving parameter information of the manually-driven vehicle at the current position at which the first vehicle is located within the current time (which may be the driving parameter information of the vehicle driving ahead of the first vehicle at the time).
Illustratively, the unmanned vehicle travels a route in conjunction with a driving environment surrounding the first vehicle based on driving parameter information of the manned vehicle at a current location. The target driving parameter may be a main driving behavior parameter, and the target driving parameter information may be finely adjusted according to a road condition around the first vehicle and a real-time obstacle condition (for example, a situation of avoiding pedestrians and surrounding vehicles) to adapt to a current driving environment, where the target path is a driving path closest to human driving.
According to the technical scheme, the current position information and the driving environment information of the first vehicle are obtained; then determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually driven vehicle at the current position; and determining the target path of the first vehicle according to the target driving parameter information and the driving environment information. The technical scheme disclosed by the invention can plan the running path of the automatic driving vehicle according to the driving behavior parameters of the public driving vehicle, can enable the driving behavior of the unmanned driving vehicle to be closer to the driving behavior of human beings, and can solve the technical problem of difficult path planning of the unmanned driving vehicle under complex working conditions.
Further, the method further comprises:
step 104, a destination location of the first vehicle is obtained.
For example, the destination location may be a final destination address of the first vehicle in the current trip, or may be a primary destination location before the final destination address of the current trip is reached (for example, a distance of 3 kilometers is included in one end of the trip, where a traffic light intersection is located at 1.5 kilometers, and the destination location may be an end point at 3 kilometers, or a traffic light intersection located at 1.5 kilometers).
Further, in one embodiment, the target driving parameter information of the first vehicle is determined by parameter information of a plurality of target vehicles. FIG. 2 is a flow chart of a method of path planning according to the embodiment shown in FIG. 1; referring to fig. 2, the step 102 of determining the target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually driven vehicle at the current position may include the following steps:
For example, the target vehicle may be a man-powered vehicle or a vehicle in a man-powered mode that is the same as at least one of the vehicle model, power parameters, body length, height, track, wheel base of the first vehicle. For example, the destination location of the first vehicle is a school 3 kilometers away from the current location of the first vehicle, and a driving track (driving path) of the manually driven vehicle within 800 meters ahead of the current location of the first vehicle on the way from the current location of the first vehicle to the school is obtained. Driving paths of a plurality of target vehicles within 800 meters ahead of a current position of the first vehicle are acquired. Wherein, the preset distance range may be 800 meters, 500 meters, 300 meters or 100 meters, and the driving track may be acquired by a GPS positioning system provided on the target vehicle in combination with a high-precision map.
In step 1022, the driving parameter information of a plurality of target vehicles on the driving path is obtained.
Illustratively, driving parameter information of a plurality of target vehicles on respective driving paths is acquired respectively. The driving parameters may include: at least one of a travel speed of the vehicle, a steering wheel angle, a brake pedal signal, an accelerator pedal signal, a vehicle longitudinal acceleration, a vehicle lateral acceleration, and a vehicle yaw rate.
In step 1023, target driving parameter information of the first vehicle is determined according to the driving parameter information of a plurality of target vehicles.
For example, the driving parameter information of the target vehicle on the respective driving paths may be filtered, data with a large deviation in the plurality of driving parameter information is removed, a numerical range of the driving parameter information is determined, the numerical range may be determined as the target driving parameter information, and the driving parameter of the first vehicle is guaranteed to be within the numerical range and perform path planning according to the real-time driving environment of the first vehicle.
FIG. 3 is a flow chart of a method of path planning according to the embodiment shown in FIG. 2; referring to fig. 3, the step 1023 of determining target driving parameter information of the first vehicle according to the driving parameter information of a plurality of target vehicles may include the following steps:
For example, the same position may be a position that is the same distance from the departure point on the way of the first vehicle to the destination, or may be a position of a road on a high-precision map, for example: at the entrance gateway of a toll station on a highway. The method comprises the steps of acquiring positions where six automatic driving vehicles with the same vehicle model pass through once in a manual driving mode at the current position of the automatic driving vehicle, acquiring accelerator amount, driving speed and steering wheel angle of the six automatic driving vehicles at the positions, respectively averaging the accelerator amount of the six target vehicles to serve as target accelerator amount parameter information of the first vehicle, averaging the driving speed of the six target vehicles to serve as target driving speed information of the first vehicle, and averaging the steering wheel angle of the six target vehicles to serve as target steering wheel angle information of the first vehicle.
And step 10232, determining the average value of the driving vehicle parameter information as the target driving parameter information of the first vehicle.
For example, the driving parameter information of the target vehicle may be obtained, stored, sorted, and when the first vehicle enters the automatic driving mode at the current position, the driving parameter information of the target vehicle that is a preset distance away from the current position is sent to the platform, and after receiving the relevant command, the platform screens out corresponding data according to the vehicle model or other power parameters of the first vehicle, and performs corresponding averaging processing on the data, and sends the data to a controller ECU (Electronic Control Unit) of the first vehicle, where the ECU of the first vehicle plans a path most similar to a human driving path according to the relevant target parameter in combination with the current driving environment information.
In another real-time mode, the first path may be determined by driving paths of a plurality of target vehicles, and then target driving parameter information of the first vehicle may be determined by acquiring driving parameters of the target vehicle whose driving track at the current position where the first vehicle is located is the first path. FIG. 4 is a flow chart of another path planning method according to the embodiment shown in FIG. 2; referring to fig. 4, the step 102 of determining the target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually driven vehicle at the current position may further include the following steps:
For example, driving paths of a plurality of target vehicles within a preset distance range from the current position between the current position and the destination position are obtained, where the first path may be a path that appears most frequently in the driving paths of the plurality of target vehicles, or may be an optimal path obtained by fitting path tracks of the plurality of target vehicles after map projection.
Illustratively, the driving parameter information of the target vehicle, of which the driving route within a preset distance range from the current position between the current position and the destination position is the first route, is acquired.
In step 1026, the driving parameter information of the target vehicle at the current position is determined as the target driving parameter of the first vehicle at the current position.
For example, the driving parameter information that the driving path is a target vehicle on the first path may include driving parameter information on the entire path, and the parameter information of the target vehicle on the first path corresponding to the current position of the first vehicle is determined as the target driving parameter information at the current position of the first vehicle.
According to the technical scheme, the driving paths of a plurality of target vehicles within a preset distance range from the current position to the target position are obtained; acquiring the driving parameter information of a plurality of target vehicles on the driving path; determining target driving parameter information of the first vehicle according to the driving parameter information of a plurality of target vehicles; and finally, determining the target path of the first vehicle according to the target driving parameter information and the driving environment information. The technical scheme disclosed by the invention can plan the running path of the automatic driving vehicle according to the driving behavior parameters of the public driving vehicle, can enable the driving behavior of the unmanned driving vehicle to be closer to the driving behavior of human beings, and can solve the technical problem of difficult path planning of the unmanned driving vehicle under complex working conditions.
Fig. 5 is a block diagram of a path planning apparatus according to another exemplary embodiment of the present disclosure; referring to fig. 5, the path planning apparatus 500 is applied to a first vehicle, and the apparatus 500 includes:
an obtaining module 501, configured to obtain current location information and driving environment information of the first vehicle;
a first determining module 502, configured to determine, according to the driving parameter information of the manually-driven vehicle at the current position, target driving parameter information of the first vehicle at the current position;
a second determining module 503, configured to determine a target path of the first vehicle according to the target driving parameter information and the driving environment information.
According to the technical scheme, the current position information and the driving environment information of the first vehicle are obtained through the obtaining module; then, determining target driving parameter information of the first vehicle at the current position through a first determination module according to the driving parameter information of the manually-driven vehicle at the current position; and determining the target path of the first vehicle by a second determining module according to the target driving parameter information and the driving environment information. The technical scheme disclosed by the invention can plan the running path of the automatic driving vehicle according to the driving behavior parameters of the public driving vehicle, can enable the driving behavior of the unmanned driving vehicle to be closer to the driving behavior of human beings, and can solve the technical problem of difficult path planning of the unmanned driving vehicle under complex working conditions.
Further, the obtaining module 501 is further configured to:
acquiring a destination position of the first vehicle;
FIG. 6 is a block diagram of a path planner according to the embodiment shown in FIG. 5; referring to fig. 6, the first determining module 502 includes:
the first obtaining sub-module 5021 is used for obtaining driving paths of a plurality of target vehicles between the current position and the target position within a preset distance range from the current position;
the second obtaining sub-module 5022 is used for obtaining driving parameter information of a plurality of target vehicles on the driving path;
the first determining sub-module 5023 is configured to determine the target driving parameter information of the first vehicle according to the driving parameter information of a plurality of target vehicles.
Further, the first determining sub-module 5023 is configured to:
acquiring the average value of the driving parameter information of a plurality of target vehicles at the same position;
determining an average of the driving vehicle parameter information as the target driving parameter information of the first vehicle.
FIG. 7 is a block diagram of a path planner according to the embodiment shown in FIG. 5; referring to fig. 7, the first determining module 502 further includes:
a second determining submodule 5024 for determining a first path of the first vehicle according to a plurality of driving paths of the target vehicle;
a third obtaining sub-module 5025, configured to obtain the driving parameter information of the target vehicle of which the driving path is the first path;
a third determining sub-module 5026, configured to determine the driving parameter information of the target vehicle at the current position as the target driving parameter of the first vehicle at the current position.
Yet another example embodiment of the present disclosure provides a vehicle including the path planning apparatus 500 described above in fig. 5-7.
According to the technical scheme, the driving paths of a plurality of target vehicles within a preset distance range from the current position between the current position and the target position are obtained through the first obtaining sub-module; the driving parameter information of a plurality of target vehicles on the driving path is obtained through a second obtaining sub-module; determining target driving parameter information of the first vehicle according to the driving parameter information of a plurality of target vehicles through a first determination submodule; and finally, determining the target path of the first vehicle according to the target driving parameter information and the driving environment information. The technical scheme disclosed by the invention can plan the running path of the automatic driving vehicle according to the driving behavior parameters of the public driving vehicle, can enable the driving behavior of the unmanned driving vehicle to be closer to the driving behavior of human beings, and can solve the technical problem of difficult path planning of the unmanned driving vehicle under complex working conditions.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (9)
1. A path planning method applied to a first vehicle is characterized by comprising the following steps:
acquiring current position information and driving environment information of the first vehicle;
determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position;
and determining a target path of the first vehicle according to the target driving parameter information and the driving environment information.
2. The method of claim 1, further comprising:
acquiring a destination position of the first vehicle;
the determining the target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position comprises:
acquiring driving paths of a plurality of target vehicles between the current position and the target position within a preset distance range from the current position;
acquiring driving parameter information of a plurality of target vehicles on the driving path;
determining target driving parameter information of the first vehicle according to the driving parameter information of a plurality of target vehicles.
3. The method of claim 2, wherein determining target driving parameter information for the first vehicle from the driving parameter information for a plurality of the target vehicles comprises:
acquiring a mean value of the driving parameter information of a plurality of the target vehicles at the same position;
determining an average of the driving vehicle parameter information as the target driving parameter information of the first vehicle.
4. The method of claim 2, wherein determining the target driving parameter information of the first vehicle at the current location from the driving parameter information of the human-driven vehicle at the current location comprises:
determining a first path of the first vehicle according to driving paths of a plurality of target vehicles;
acquiring the driving parameter information of the target vehicle of which the driving path is the first path;
determining the driving parameter information of the target vehicle at the current location as a target driving parameter of the first vehicle at the current location.
5. A path planning apparatus for use with a first vehicle, the apparatus comprising:
the acquisition module is used for acquiring the current position information and the driving environment information of the first vehicle;
the first determination module is used for determining target driving parameter information of the first vehicle at the current position according to the driving parameter information of the manually-driven vehicle at the current position;
and the second determining module is used for determining the target path of the first vehicle according to the target driving parameter information and the driving environment information.
6. The apparatus of claim 5, wherein the obtaining module is further configured to:
acquiring a destination position of the first vehicle;
the first determining module includes:
the first obtaining submodule is used for obtaining driving paths of a plurality of target vehicles within a preset distance range from the current position between the current position and the target position;
the second obtaining submodule is used for obtaining the driving parameter information of the target vehicles on the driving path;
the first determining submodule is used for determining target driving parameter information of the first vehicle according to the driving parameter information of the target vehicles.
7. The apparatus of claim 6, wherein the first determining submodule is configured to:
acquiring a mean value of the driving parameter information of a plurality of the target vehicles at the same position;
determining an average of the driving vehicle parameter information as the target driving parameter information of the first vehicle.
8. The apparatus of claim 6, wherein the first determining module further comprises:
a second determination submodule for determining a first path of the first vehicle according to driving paths of a plurality of the target vehicles;
a third obtaining sub-module, configured to obtain the driving parameter information of the target vehicle of which the driving path is the first path;
a third determining sub-module for determining the driving parameter information of the target vehicle at the current location as a target driving parameter of the first vehicle at the current location.
9. A vehicle comprising a path planner according to any of the claims 5-8.
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