CN112078595A

CN112078595A - Vehicle track planning method, control method and related device

Info

Publication number: CN112078595A
Application number: CN202010989690.3A
Authority: CN
Inventors: 闫文龙; 周佳佳
Original assignee: Suzhou Jiaochi Artificial Intelligence Research Institute Co ltd
Current assignee: Suzhou Jiaochi Artificial Intelligence Research Institute Co ltd
Priority date: 2020-09-24
Filing date: 2020-09-24
Publication date: 2020-12-15
Anticipated expiration: 2040-09-24
Also published as: CN112078595B

Abstract

The embodiment of the invention discloses a vehicle track planning method, a control method and a related device, which can improve the safety of autonomous mode operation of a vehicle. The planning method comprises the following steps: tracking at least one other vehicle on a road on which the current vehicle is traveling to obtain a trajectory of the at least one other vehicle, the trajectory including a location through which the at least one other vehicle passes; determining a first trajectory by synthesizing trajectories of the at least one other vehicle; and performing deviation processing on the position of the first track along the width direction of the road by using a processor to obtain a second track, wherein the second track is positioned in a lane at the farthest end of the road facing the lane changing direction of the first track, and is the farthest end of the lane where the current vehicle is positioned.

Description

Vehicle track planning method, control method and related device

Technical Field

The embodiment of the invention relates to the field of automatic driving, in particular to a vehicle track planning method, a vehicle track control method and a related device.

Background

An autonomous vehicle may automatically navigate through a particular path in an autonomous mode with little to no input or operation from a human driver. The specific route includes all routes before reaching the destination or only a specific link during the passing.

Autonomous vehicles typically include various sensors to sense the environment surrounding the vehicle and adjust vehicle control states based on the results of the sensing and decision algorithms.

When the road performs the maintenance work, the corresponding lane may be closed or moved. The geometry of the road may change, which may cause the map obtained from the network or stored locally by the autonomous vehicle to be inaccurate, which may further cause the road model generated based on the map to be inaccurate, and may ultimately affect the safe operation of the autonomous vehicle.

Disclosure of Invention

The embodiment of the invention provides a vehicle track planning method, a control method and a related device, which can improve the safety of autonomous mode operation of a vehicle.

In a first aspect, an embodiment of the present invention provides a method

A vehicle trajectory planning method, comprising:

tracking at least one other vehicle on a road on which the current vehicle is traveling to obtain a trajectory of the at least one other vehicle, the trajectory including a location through which the at least one other vehicle passes;

determining a first trajectory by synthesizing trajectories of the at least one other vehicle;

and performing deviation processing on the position of the first track along the width direction of the road by using a processor to obtain a second track, wherein the second track is positioned in a lane at the farthest end of the road facing the lane changing direction of the first track, and is the farthest end of the lane where the current vehicle is positioned.

In a preferred embodiment, the shifting the position of the first trajectory in the road width direction includes:

shifting each position in the first track by a corresponding shift amount along a first direction;

the first direction is along the width direction of the road and faces to the overall lane changing direction of the first track;

the offset corresponding to each position gradually increases along with the distance between the position and the farthest lane of the road towards the first track lane changing direction.

In a preferred embodiment, the offset corresponding to each position is equal to:

(X3-X0)*(Xd-Xm)/(Xd-X0)；

wherein, X3 is the position of the first track, X0 is the coordinate of the lane where the current lane is located in the road width direction, Xd is the coordinate of the road in the road width direction of the farthest lane of the first track in the lane changing direction, and Xm is the coordinate of the position closest to the farthest lane in the first track in the road width direction.

In a preferred embodiment, the determining the first trajectory by synthesizing the trajectory of the at least one other vehicle comprises:

and carrying out weighted average operation on the track of the at least one other vehicle to obtain a first track.

In a preferred embodiment, the performing a weighted average operation on the trajectory of the at least one other vehicle includes:

determining a weighted weight of each track based on the reliability of the track of the at least one other vehicle, and performing weighted average operation on the position of the track of the at least one other vehicle based on the determined weighted weight.

In a second aspect, an embodiment of the present invention further provides a vehicle control method, including

Planning the vehicle track by using the method;

changing the speed and/or direction of the vehicle based on the vehicle trajectory.

In a third aspect, the present invention also provides an apparatus, comprising:

a processor configured to:

and performing deviation processing on the position of the first track along the width direction of the road to obtain a second track, wherein the second track is positioned in a farthest lane of the road facing the lane changing direction of the first track, and is the farthest end of the lane where the current vehicle is positioned.

In a fourth aspect, an embodiment of the present invention further provides a vehicle, including:

at least one sensor for sensing an environment external to the vehicle;

a computer system configured to:

In a fifth aspect, embodiments of the invention also provide a non-transitory computer-readable medium,

the instructions being executable by a computer system to cause the computer system to perform functions comprising:

By the embodiment of the invention, the vehicle can more safely get around the lane closed by the roadblock.

Drawings

FIG. 1 is a functional block diagram of a vehicle shown in accordance with an exemplary embodiment of the present invention;

FIG. 2 is a schematic illustration of an automated vehicle operation scenario in an example embodiment of the invention;

FIG. 3 is a schematic diagram of a vehicle tracking the trajectory of a nearby vehicle;

4A-4C are schematic diagrams of the trajectory of a vehicle being tracked by the vehicle;

fig. 5A-5D are schematic diagrams of the process of executing the composition and offset process for the traced trajectory.

Detailed Description

The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention.

It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.

1. Overview

The disclosed example of the invention relates to a vehicle trajectory planning method, comprising:

Within the context of the present disclosure, a vehicle may operate in various operating modes. In some embodiments, such modes of operation may include manual, semi-autonomous, fully autonomous modes. In the autonomous mode, the vehicle may be driven with little or no user interaction. In manual and semi-autonomous modes, the vehicle may be driven in full and in part by the user, respectively.

An example of the present invention also provides a vehicle control method including: planning a vehicle track based on the method, and then changing the speed and/or direction of the vehicle based on the planned vehicle track so that the vehicle can avoid a lane closed by a roadblock more safely.

Some methods of the present disclosure may be partially or completely performed by a vehicle in an autonomous mode with or without external interaction (e.g., external interaction from a user of the vehicle).

Other methods disclosed herein may be performed partially or completely by a server. In an example embodiment, a server may obtain sensor data of a vehicle environment from at least one sensor, wherein the vehicle is configured to operate in an autonomous mode.

The at least one sensor may be one or any combination of the following: a camera, a RADAR system, a LIDAR system, an acoustic sensor, a range finder, or other type of sensor.

Embodiments of the present invention also disclose non-transitory computer-readable media having instructions stored thereon that are executable by a computing device to cause the computing device to perform similar functions as disclosed in the above-described methods.

2. Example System

An example system of a vehicle to which embodiments of the present invention are applied is described in detail below. The example system may be implemented in a vehicle. Those skilled in the art will appreciate that the example system may also be implemented in the form of other vehicles, including, but not limited to, cars, trucks, motorcycles, buses, boats, airplanes, helicopters, lawn mowers, excavators, snowmobiles, flight chess, recreational vehicles, amusement park vehicles, farm equipment, construction equipment, trams, golf carts, trains, trams, bicycles, scooters, and balance cars, for example.

FIG. 1 is a functional block diagram of a vehicle 100 shown according to an example embodiment. The vehicle 100 may be configured to operate safely or partially in an autonomous mode. For example, the vehicle 100 may control itself while in the autonomous mode, may determine a current state of the vehicle and its environment, determine a predicted behavior of one or more other road users in the environment, determine a confidence level that may correspond to a likelihood that the one or more other road users performed the predicted behavior, and control the vehicle 100 based on the determined information. In the automatic mode, the vehicle 100 may operate without human driver interaction.

The vehicle 100 may include various subsystems such as a propulsion system 102, a sensor system 104, a control system 106, peripherals 108, a power source 110, a computer system 112, and a user interface 116. The vehicle may include more or fewer subsystems, and each subsystem may include multiple elements. Additionally, each sub-system and component of the vehicle 100 may be interconnected. Thus, one or more of the functional modules in the functional description of the vehicle 100 may be divided into more functional or physical components, or of course combined into fewer functional or physical components.

The propulsion system 102 may include components that provide powered motion to the vehicle 100. In one example embodiment, the propulsion system 102 may include an engine 118, an energy source 119, a transmission 120, and wheels 121. The engine 118 may be an internal combustion engine, an electric motor, a steam engine, a stirling engine, or other type of engine, and may be any combination of the various types of engines described above. For example, in some embodiments, propulsion system 102 may include multiple types of engines, for example, a hybrid vehicle may include a gasoline engine and an electric motor.

The energy source 119 may represent an energy source that may fully or partially power the engine 118. That is, the engine 118 may be configured to convert the energy source 119 into mechanical energy. Examples of energy sources 119 include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electrical power. The energy source 119 may additionally or alternatively include any combination of fuel tanks, batteries, capacitors, or flywheels. The energy source 119 may also provide energy to other systems of the vehicle 100.

The transmission 120 may include elements that transmit mechanical power from the engine 119 to the wheels 121. To this end, the transmission 120 may include a gearbox, a clutch, a differential, and a drive shaft. The transmission 120 may also include other elements. The drive shaft may include one or more axles that may be coupled to one or more wheels.

The wheels 121 of the vehicle 100 may be of various forms including, for example, single-wheeled, two-wheeled (e.g., motorcycle), three-wheeled, or four-wheeled (e.g., car, truck), among others. Other wheel numbers and geometries are possible, such as six and more wheels. The wheels 121 of the vehicle 100 may be mounted at the edges of the transmission 120. The wheel 121 may include any combination of metal and rubber or other material combinations.

The sensor system 104 may include a number of sensors configured to sense environmental information about the vehicle 100. For example, the sensor system 104 may include a positioning system 122, an Inertial Measurement Unit (IMU) 124, a RADAR Unit 126, a LIDAR Unit 128, And a camera 130. The sensor system 104 may also include various sensors that monitor internal systems of the vehicle 100, such as fuel gauges, oil temperature sensors, and the like.

One or more of the sensors in the sensor system 104 may be adjusted in position and orientation as needed to actually detect the need.

The Positioning System 122 may include a Global Positioning System (GPS), which may be any sensor for estimating the physical location of the vehicle 100. The positioning system 122 may include a transceiver device for receiving information regarding the location of the vehicle 100 relative to the earth.

The inertial measurement unit 124 may include any combination of sensors, such as accelerometers or gyroscopes, that sense changes in position and orientation of the vehicle 100 based on inertial acceleration.

The RADAR unit 126 may sense objects near the vehicle 100 using radio signals. In some embodiments, the RADAR unit 126 may also be used to sense the speed and/or heading of an object.

The LIDAR unit 128 may utilize a laser to sense objects in the environment in which the vehicle 100 is located. The LIDAR unit 128 may include one or more laser sources, laser scanners, one or more detectors, and other system components. The LIDAR unit 128 may be configured to operate in a coherent (e.g., utilizing heterodyne detection) or non-coherent detection mode.

The camera 130 may include one or more devices configured to capture a plurality of images of the environment of the vehicle 100. The camera 130 may be a still camera or a video camera.

The control system 106 may be configured to control the operation of the vehicle 100 and its components. The control system 105 may include a steering unit 132, a throttle 134, a braking unit 136, a sensor fusion module 138, a computer vision system 140, a navigation/routing control system 142, and an obstacle avoidance system 144.

Steering unit 132 may include any combination of mechanisms to adjust the foreground direction of vehicle 100.

The throttle 134 may be configured to control, for example, the operating speed of the engine 118 and, in turn, the speed of the vehicle 100.

The brake unit 136 may include any combination of mechanisms for decelerating the vehicle 100. The brake unit 136 may use friction to slow the wheel 121. In other embodiments, the brake unit 136 may convert the kinetic energy of the wheels into electric current.

The sensor fusion module 138 may be configured to receive data from the sensor system 104 as input. The data may include information data sensed by sensors from the sensor system 104. The sensor fusion module 138 may perform fusion operations on the input data using a kalman filter, a bayesian network, or other algorithms. The sensor fusion module 138 may provide various assessments based on data from the sensor system 104. The evaluation may include an evaluation of objects and/or features in the environment of the vehicle 100, an evaluation of the condition of the features, and/or an evaluation of the possible impact based on a particular condition, etc.

The computer vision system 140 is used to perform processing and analysis on the images captured by the camera 130 in order to identify objects and/or features in the environment of the vehicle 100. The objects and/or features herein may include: traffic signals, road boundaries and obstacles. The computer vision system 140 may use object recognition algorithms, Motion from Motion (SFM) algorithms, video tracking, and other computational vision techniques. In some embodiments, the computer vision system 140 may also provide functions for environmental mapping, object tracking, object velocity estimation, and the like.

The navigation/route control system 142 may determine a travel route for the vehicle 100. The navigation/routing control system 142 may also dynamically update the travel route while the vehicle 100 is in operation. In some embodiments, the navigation/route control system 142 may determine a travel route for the vehicle 100 in conjunction with data from the sensor fusion module 138, the positioning system 122, and the map.

The obstacle avoidance system 144 may be used to identify, assess, and avoid or otherwise negotiate potential obstacles in the environment of the vehicle 100.

The peripheral devices 108 may be configured to allow interaction between the vehicle 100 and external sensors, other road users, other computer systems, and/or users. For example, the peripheral devices 108 may include a wireless communication system 146, a touch screen 148, a microphone 150, and/or a speaker 152.

In an example embodiment, the peripheral devices 108 may provide functionality, such as for a user of the vehicle 100 to interact with the user interface 116. The touch screen 148 may provide information to a user of the vehicle 100. The user interface 116 may receive input from a user via the touch screen 148. The touch screen 148 may be configured to sense the position and movement of a user's finger via capacitive sensing, resistive sensing, or surface acoustic wave processes. The touch screen 148 is capable of sensing finger movement in a direction parallel or coplanar with the touch screen surface, in a direction perpendicular to the touch screen surface, or both, and is also capable of sensing the level of pressure applied to the touch screen surface. The touch screen 148 may be comprised of one or more translucent or transparent insulating layers and one or more translucent or transparent conductive layers.

In other cases, the peripheral devices 108 may provide a means for the vehicle 100 to communicate with devices within its environment. Microphone 150 may be configured to receive audio (such as voice instructions or other audio input) from a user of vehicle 100. Similarly, the speaker 152 may be configured to output audio to a user of the vehicle 100.

The wireless communication system 146 may be configured to wirelessly communicate with one or more devices, either directly or via a communication network. For example, the wireless communication system 146 may communicate using a 3G, 4G cellular network, and may also communicate with a wireless local area network using WiFi. In some embodiments, the wireless communication system 146 may communicate directly with the device using an infrared link, bluetooth, or Zigbee.

The power supply 110 may provide power to various components of the vehicle 100 in the form of a rechargeable lithium ion or lead acid battery. In some embodiments, one or more battery packs of such batteries may be configured to provide electrical power. In some embodiments, power source 110 and energy source 119 may be implemented together, such as in an all-electric vehicle.

Some or all of the functionality of the vehicle 100 may be controlled by the computer system 112. The computer system 112 may include at least one processor 113, the processor 113 executing instructions 115 stored in a non-transitory computer readable medium, such as a data storage device 114. The computer system 112 may also represent multiple computing devices used to control individual components or subsystems of the vehicle 100 in a distributed manner.

In some embodiments, the data storage device 114 may contain instructions 115, and the instructions 115 may be executed by the processor 113 to perform various functions of the vehicle 100. In addition to instructions 115, data storage device 114 may also store data, such as road maps, route information, and other information. Such information may be used by the vehicle 100 and the computer system 112 during operation of the vehicle 100 in autonomous, semi-autonomous, and/or manual modes.

The vehicle 100 may include a user interface 116 for providing information to or receiving information from a user of the vehicle 100. The user interface 116 may be controlled by the content and/or layout of the interactive images displayed on the touch screen 148 so that the user may control it. Further, the user interface 116 may be disposed at one or more input/output devices within the set of peripheral devices 108, such as a wireless communication system 146, a touch screen 148, a microphone 150, and a speaker 152.

The computer system 112 may control the functions of the vehicle 100 based on inputs received from various subsystems, such as the propulsion system 102, the sensor system 104, and the control system 106, as well as from the user interface 116. For example, the computer system 112 may utilize input from the control system 106 to control the steering unit 132 to avoid detection of obstacles by the sensor system 104 and the obstacle avoidance system 114.

3. Example implementation

Several example implementations of the present invention will now be described, it being understood that there are many ways to implement the disclosed apparatus, systems, and methods. The following examples are therefore not intended to limit the scope of the present disclosure.

FIG. 2 shows a schematic diagram of an automated vehicle operation scenario in an example embodiment of the invention. In this example, a vehicle (not shown) is traveling on the road 230. Affected by the barrier 220, both lanes on the road 230 are closed. When the vehicle is operating in autonomous mode, it is necessary to detect the closed lane condition and move ahead to the left lane to avoid breaking into the lane closed by the barrier 220.

Fig. 3 shows a schematic diagram of the vehicle 210 tracking the trajectories of

nearby vehicles

310, 320, 330. In this example, the vehicle 210 monitors the trajectories of three vehicles, in other examples, the vehicle 210 may also monitor the trajectories of any number of vehicles. The monitoring range of the vehicle 210 is often large, and in order to reduce workload, the vehicle 210 may select a vehicle track satisfying a specific condition for monitoring, for example, only monitor vehicles having a distance from the vehicle 210 within a first threshold range.

After the vehicle 210 selects the vehicles that need to be monitored, the trajectories of these vehicles can be observed using various methods. For example, the vehicle 210 may track the vehicle 310 along 330 using a camera and corresponding image processing algorithm, or may detect the trajectory of the vehicle 310 along 330 past the vehicle 210 using sensors disposed on the road, or the vehicle 310 along 330 may itself transmit their respective geographic locations to the vehicle 210, or the trajectory of the vehicle 310 along 330 may be obtained from the back-end server 380. Vehicle 210 is not limited to tracking the trajectories of other vehicles by any particular means.

Fig. 4A-4C illustrate the trajectory of the

vehicle

310 and 330 tracked by the vehicle 210. The trajectory of the vehicle 310 is the trajectory 410 in fig. 4A, the trajectory of the vehicle 320 is the trajectory 420 in fig. 4B, and the trajectory of the vehicle 330 is the trajectory 430 in fig. 4C. As can be seen from the trajectory tracking results, the

vehicles

310 and 330 make a lane change to the left in advance before encountering the road block 220 to avoid the lane closed by the road block 220. Fig. 4A-4C also show the position of the vehicle 210 in the form of arrows.

Fig. 5A-5D illustrate the process of performing the synthesis and migration process for the

traces

410 and 420 to be traced.

Fig. 5A shows the tracked

trajectories

410 and 420, and also shows the position of the vehicle 210 relative to the road. Trajectory 420 begins in the lane in which vehicle 210 is located, but trajectory 410 begins in a different lane. For the tracks starting from the lanes where the vehicle 210 is located, the tracks need to be translated in the lane width direction in advance, so that the translated tracks start from the lanes where the vehicle 210 is located, as shown in fig. 5B.

Fig. 5B shows a preprocessing step of merging the

trajectories

410 and 420, i.e. translating the trajectory 410 starting from different lanes, so that the translated trajectory 410' starts from the lane in which the vehicle 210 is located. One specific example implementation method is: identifying the closest position of each position in the trajectory 410 to the vehicle 210; this position is then determined to be a minimum distance from the vehicle 210, and each position of the trajectory 410 is then incremented or decremented by this minimum distance value, such that the trajectory 410 translates to the trajectory 410'. The increase or decrease here depends on the coordinate system direction and the relative position direction between the lane where the trajectory 410 starts and the lane where the vehicle 210 is located. The distance here may be a euclidean distance, a distance in the X direction, a distance in the Y direction, or any other type of distance.

FIG. 5C illustrates the process of merging the translated trajectory 410' of trajectory 410 with the trajectory 420. For each location of the track 410', a corresponding location of the track 420 may be determined. The positions of the track 410 'corresponding to the track 420 may be two corresponding positions having the shortest distance in the road extending direction, for example, a pair of corresponding positions of the tracks 410' and 420 (see the solid dots in the dashed box) enclosed by the dashed box 540 in fig. 5C. The process of merging the traces 410' and 420 may be performed using a weighted average operation. Specifically, taking two corresponding positions shown by a dotted line frame as an example, the coordinates of the corresponding position 410a on the trajectory 410' are (X1, Y1), the coordinates of the corresponding position 420a on the trajectory 420 are (X2, Y2), and the coordinates of the corresponding position 530a on the synthesized trajectory (e.g., the trajectory formed by the hollow dots in fig. 5C) are (X3, Y3).

In one example, X3 ═ (k1 × X1+ k2 × X2)/2, and Y3 ═ (k1 × Y1+ k2 × Y2)/2. Where k1 and k2 are the weights of the weighted average. k1 and k2 may be determined based on the reliability of the

traces

410 and 420, respectively. For example, when the trajectory 410 is not reliable at all, then k1 may be set to 0 and k2 may be set to 2. In a more general case, k1 and k2 may both be selected within the ranges of 0 and 2 and so on.

In another alternative example, X3 ═ k 1X 1+ k 2X 2)/(k1+ k2) and Y3 ═ k 1Y 1+ k 2Y 2)/(k1+ k2), where weights k1 and k2 do not need to be normalized to interval [0,2 ].

The reliability of the trajectory on which the weights are determined may be measured using various reference factors. For example, in one embodiment, the starting point of the track is closer to the lane in which the vehicle 201 is located, and the track is weighted more heavily. In another specific scheme, the more concentrated the statistical distribution of all positions in the track, the greater the weight, wherein the concentration of the statistical distribution can be measured using information such as the statistical variance of the coordinate values. In another specific scheme, if the track has excessive curvature, the weight of the track is smaller, because when the curvature of the track is excessive, the vehicle of the track usually finds the road closure near the roadblock and then performs a large-angle lane changing operation.

Through the process, the process of synthesizing the tracks of other vehicles to obtain the first track is realized. However, it is obvious to those skilled in the art that the synthesized trajectory is still close to the lane enclosed by the roadblock, mainly because although the above-mentioned merging process can avoid the unreasonable effect of individual trajectories, the translation and weighted average calculation adopted in the merging process can make the synthesized trajectory approach toward the enclosed lane. For example, if the lane at the start of the trajectory is far from the lane in which the current lane 201 is located in the trajectory of another vehicle, or if the trajectory of another vehicle is traveling close to a closed lane, the above problem may be aggravated.

In order to solve the above problem, the position of the synthesized first track may be subjected to offset processing along the road width direction, so as to obtain a second track, and the second track is located in a farthest lane of the road facing the lane change direction of the first track, where the farthest lane is located from a lane where the current vehicle is located.

Fig. 5D is a schematic diagram illustrating the process of performing the offset processing on the first track. In this example, the synthesized trajectory 530 in fig. 5C needs to be subjected to an offset process so as to reach the result that the trajectory 530 is laterally stretched in the road width direction as a whole, and finally so that the offset trajectory 530 'still starts from the lane where the lane 210 is located, and the trajectory 530' near the closed lane defined by the roadblock 220 is located on the lane farthest from the closed lane.

To implement the offset process described above, each location of the track 530 may be determined with a corresponding offset that increases as the distance between the location in the road width direction and the farthest end lane in the lane change direction of the track 530 increases. And then, the position is deviated towards the direction of the farthest lane by the deviation amount, so that the deviated position is obtained. Taking an example of a position 530a on the track 530 shown in fig. 5D, the coordinates thereof are (X3, Y3), and the corresponding position on the shifted track 530 'is 530 a', the coordinates thereof are (X4, Y4). In one example, X4 is X3+ (X3-X0) × (Xd-Xm)/(Xd-X0), where X0 is the coordinates of the lane in which the vehicle 210 is located in the X direction (i.e., the road width direction) (e.g., the coordinates of the center line of the lane), Xd is the coordinates of the farthest lane in the lane changing direction of the track 530 (i.e., the leftmost lane in fig. 5D) in the X direction, and Xm is the X direction coordinates of the position in the track 530 closest to the farthest lane. Here, (X3-X0) (Xd-Xm)/(Xd-X0) is the offset corresponding to the position 530 a.

Through the above offset processing, the offset trajectory can be further away from the closed lane, and the safety of the vehicle 210 in the autonomous mode operation is improved.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A vehicle trajectory planning method, comprising:

2. The method of claim 1, wherein shifting the position of the first trajectory in the road width direction comprises:

3. The method of claim 2, wherein the offset corresponding to each position is equal to:

(X3-X0)*(Xd-Xm)/(Xd-X0)；

4. The method of claim 1, wherein determining the first trajectory by synthesizing the trajectory of the at least one other vehicle comprises:

5. The method of claim 2, wherein the performing a weighted average of the trajectory of the at least one other vehicle comprises:

6. A vehicle control method characterized by comprising:

planning a vehicle trajectory using the method of any one of claims 1 to 5;

7. An apparatus, comprising: a processor configured to:

8. A vehicle, characterized by comprising:

at least one sensor for sensing an environment external to the vehicle;

a computer system configured to:

9. A non-transitory computer readable medium having stored therein instructions executable by a computer system to cause the computer system to perform functions comprising: