CN114572219B

CN114572219B - Automatic overtaking method and device, vehicle, storage medium and chip

Info

Publication number: CN114572219B
Application number: CN202210460643.9A
Authority: CN
Inventors: 刘力文; 谭伟; 李�昊; 张弛
Original assignee: Xiaomi Automobile Technology Co Ltd
Current assignee: Xiaomi Automobile Technology Co Ltd
Priority date: 2022-04-28
Filing date: 2022-04-28
Publication date: 2022-07-22
Anticipated expiration: 2042-04-28
Also published as: CN114572219A

Abstract

The disclosure relates to the field of automatic driving, and relates to an automatic overtaking method, an automatic overtaking device, a vehicle, a storage medium and a chip, wherein the method comprises the following steps: the method comprises the steps of responding to the fact that the distance between a vehicle and the front vehicle is smaller than a preset distance threshold value, determining the vehicle type and the first vehicle speed of the front vehicle, determining the overtaking decision result of the vehicle according to the vehicle type, the first vehicle speed, the distance and the second vehicle speed of the vehicle, determining the overtaking lane changing track of the vehicle according to the vehicle type, the first vehicle speed, the distance and the second vehicle speed under the condition that the overtaking decision result is smaller than the preset decision threshold value, and controlling the vehicle to carry out overtaking based on the overtaking lane changing track. Therefore, the vehicle type is taken as a necessary consideration factor of the algorithm, so that the vehicle can accurately execute the overtaking lane changing process based on the current actual situation, and better automatic driving experience is brought to passengers.

Description

Automatic overtaking method, device, vehicle, storage medium and chip

Technical Field

The present disclosure relates to the field of automatic driving, and in particular, to an automatic overtaking method, an automatic overtaking device, a vehicle, a storage medium, and a chip.

Background

The decision-making planning algorithm is a core technology in an automatic driving technology framework, wherein the overtaking lane-changing algorithm is an important component of the decision-making planning algorithm, and the overtaking lane-changing algorithm is used for controlling a vehicle to finish automatic overtaking. In the related art, the overtaking lane-changing algorithm mainly uses a lane-changing acceleration gain model to judge whether to execute lane-changing overtaking according to driving data such as the speed and the distance of a preceding vehicle. However, the influence of the vehicle type on the lane change time and the lane change behavior is not considered in the judging mode, so that the same overtaking lane change logic is difficult to be applied to all types of vehicles, and finally, the user experience is poor during overtaking, and even the lane change overtaking cannot be realized.

Disclosure of Invention

In order to overcome the problems in the related art, the disclosure provides an automatic overtaking method, an automatic overtaking device, a vehicle, a storage medium and a chip, and relates to the field of automatic driving.

According to a first aspect of an embodiment of the present disclosure, there is provided an automatic overtaking method, including:

determining a vehicle type and a first vehicle speed of a front vehicle in response to the vehicle distance between the vehicle and the front vehicle being smaller than a preset distance threshold;

determining a overtaking decision result of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance and a second vehicle speed of the vehicle;

determining the overtaking lane changing track of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance and the second vehicle speed under the condition that the overtaking decision result is smaller than a preset decision threshold;

and controlling the vehicle to carry out overtaking based on the overtaking lane changing track.

Optionally, the determining the vehicle type of the preceding vehicle includes:

acquiring image data of the front vehicle through a monitoring device arranged on the vehicle;

and identifying the image data according to a pre-trained identification model, and determining the vehicle type corresponding to the front vehicle.

Optionally, the determining a passing decision result of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance, and the second vehicle speed of the vehicle includes:

determining a target operation coefficient corresponding to the vehicle type based on a preset coefficient table, wherein the preset coefficient table comprises a plurality of vehicle types and a mapping relation between a plurality of operation coefficients;

and determining the overtaking decision result by utilizing a decision function according to the first vehicle speed, the vehicle distance, the target operation coefficient and the second vehicle speed.

Optionally, the decision function comprises:

D=k*（V₁*d/V₂）

wherein D is the overtaking decision result, k is the target operation coefficient, and V₁Is the first vehicle speed, d is the vehicle distance, V₂The second vehicle speed.

Optionally, the determining the passing lane-changing trajectory of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance, and a second vehicle speed corresponding to the vehicle includes:

determining a first safe vehicle distance and a second safe vehicle distance between the vehicle and the front vehicle according to the vehicle type, wherein the first safe vehicle distance is the distance between the vehicle and the front vehicle when the vehicle can complete safe overtaking, and the second safe vehicle distance is the distance between the front vehicle and the vehicle when the vehicle can complete safe returning;

determining a first time interval corresponding to the vehicle steering overtaking process according to the first safe vehicle distance, the first vehicle speed and the second vehicle speed;

determining a second time period corresponding to the vehicle steering regression process according to the second safe vehicle distance, the first vehicle speed and the second vehicle speed;

and determining the overtaking lane change track of the vehicle according to the first time interval, the second time interval and the overtaking steering angle.

Optionally, the determining the passing lane change trajectory of the vehicle according to the first time period, the second time period and a passing steering angle includes:

determining the overtaking steering angle of the vehicle according to the vehicle type;

determining a lane change track of the vehicle according to the first time period and the overtaking steering angle, and determining a return track of the vehicle according to the second time period and the overtaking steering angle;

and determining the overtaking lane changing track of the vehicle according to the lane changing track and the return track.

Optionally, the controlling the vehicle to perform passing based on the passing lane-changing track includes:

determining whether other vehicles exist on the overtaking lane changing track according to the overtaking lane changing track;

and under the condition that other vehicles do not exist on the overtaking lane changing track, controlling the vehicles to overtake according to the overtaking lane changing track.

According to a second aspect of the embodiments of the present disclosure, there is provided an automatic overtaking device including:

a first determination module configured to determine a vehicle type and a first vehicle speed of a preceding vehicle in response to a vehicle distance between the vehicle and the preceding vehicle being less than a preset distance threshold;

a second determination module configured to determine a passing decision result of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance, and a second vehicle speed of the vehicle;

the third determining module is configured to determine a passing lane changing track of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance and the second vehicle speed under the condition that the passing decision result is smaller than a preset decision threshold;

an execution module configured to control the vehicle to execute the passing based on the passing lane change trajectory.

According to a third aspect of the embodiments of the present disclosure, there is provided a vehicle including:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to:

determining the overtaking lane changing track of the vehicle according to the type of the vehicle, the first vehicle speed, the vehicle distance and the second vehicle speed under the condition that the overtaking decision result is smaller than a preset decision threshold;

According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of any of the automatic overtaking methods provided by the first aspect of the present disclosure.

According to a fifth aspect of embodiments of the present disclosure, there is provided a chip comprising a processor and an interface; the processor is configured to read instructions to perform the steps of any of the automated overtaking methods provided in the first aspect of the present disclosure.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

according to the scheme, the vehicle type and the first vehicle speed of the front vehicle are determined in response to the fact that the vehicle distance between the vehicle and the front vehicle is smaller than the preset distance threshold, the overtaking decision result of the vehicle is determined according to the vehicle type, the first vehicle speed, the vehicle distance and the second vehicle speed of the vehicle, the overtaking lane changing track of the vehicle is determined according to the vehicle type, the first vehicle speed, the vehicle distance and the second vehicle speed under the condition that the overtaking decision result is smaller than the preset decision threshold, and the vehicle is controlled to overtake based on the overtaking lane changing track. And when the vehicle is determined to need to overtake through the algorithm, generating an overtaking lane changing track corresponding to the vehicle through the vehicle type and the related driving data, so that the vehicle can automatically overtake according to the overtaking lane changing track. The vehicle type is taken as a necessary consideration factor of the algorithm, so that the vehicle can accurately execute the overtaking lane changing process based on the current actual situation, and better automatic driving experience is brought to passengers.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1 is a flow chart illustrating an automatic overtaking method according to one exemplary embodiment.

FIG. 2 is a flow chart illustrating a method for determining a cut-in trajectory, according to an exemplary embodiment.

FIG. 3 is a block diagram of an automatic overtaking device according to one exemplary embodiment.

FIG. 4 is a block diagram of a vehicle shown in accordance with an exemplary embodiment.

FIG. 5 is a functional block diagram of another vehicle shown in accordance with an exemplary embodiment.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below do not represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

It should be noted that all the actions of acquiring signals, information or data in the present application are performed under the premise of complying with the corresponding data protection regulation policy of the country of the location and obtaining the authorization given by the owner of the corresponding device.

FIG. 1 is a flow chart illustrating an automatic overtaking method, as shown in FIG. 1, for use in a vehicle, according to an exemplary embodiment, including the following steps.

In step S11, a vehicle type and a first vehicle speed of a preceding vehicle are determined in response to a vehicle distance between the vehicle and the preceding vehicle being less than a preset distance threshold.

In step S12, a passing decision result of the vehicle is determined according to the vehicle type, the first vehicle speed, the vehicle distance, and the second vehicle speed of the vehicle.

In step S13, when the overtaking decision result is smaller than the preset decision threshold, the overtaking lane change trajectory of the vehicle is determined according to the vehicle type, the first vehicle speed, the vehicle distance, and the second vehicle speed.

In step S14, the vehicle is controlled to perform a passing based on the passing lane change trajectory.

For example, in step S11, the automatic driving method in the present embodiment is applied to a fully automatically driven vehicle or a vehicle with an automatic driving function, which can realize automatic driving by analyzing the surrounding vehicle conditions and the road conditions. When the vehicle is in an automatic driving mode, the distance between the driving vehicle and other surrounding vehicles can be determined through the sensing devices arranged on the periphery of the vehicle, and when other vehicles in front of the vehicle are detected, and the distance between the other vehicles and the driving vehicle is smaller than a preset distance threshold value, the vehicle type of the front vehicle and the first vehicle speed of the front vehicle are determined. It can be understood that, before the decision of overtaking and lane changing is made, the overtaking and lane changing algorithm is triggered only when the vehicle ahead is within a preset distance range, and the overtaking and lane changing is judged, wherein the preset distance needs to be set within a reasonable range, so that poor overtaking and lane changing experience caused by false triggering or untimely triggering of the overtaking and lane changing algorithm is avoided, for example, the preset distance threshold is set to be 8m-16m, and when the distance between the vehicle ahead and the driven vehicle is detected to be smaller than the preset distance threshold, the vehicle is controlled to execute the overtaking and lane changing decision algorithm, and the vehicle type of the vehicle ahead and the first vehicle speed of the vehicle ahead are determined. It should be noted that, when the distance between the driving vehicle and the preceding vehicle is short, even smaller than the safe vehicle distance, the overtaking vehicle is likely to collide, so in this embodiment, it is necessary to determine the distance between the driving vehicle and the preceding vehicle, and when the distance is smaller than the preset distance threshold and larger than the safe vehicle distance, it is determined that the overtaking lane changing algorithm needs to be executed, and the vehicle type and the first vehicle speed of the preceding vehicle are determined. When the distance is smaller than the safe distance, the overtaking lane-changing algorithm is not executed, and for example, the vehicle can be controlled to decelerate according to the safe driving algorithm. The safe vehicle distance can be set according to the length of the vehicle body of the driving vehicle, and for example, the safe vehicle distance can be set to be 1.5 times of the length of the vehicle body of the driving vehicle; alternatively, the safe vehicle distance can be determined according to the relative speed between the driving vehicle and the front vehicle in the driving process. This embodiment is not limited to this.

The vehicle type of the front vehicle can determine the actual size of the front vehicle through a camera arranged on the driving vehicle, and the vehicle type of the front vehicle is determined to be a car, a small truck, a minibus, a large truck and the like through analysis of the size. The first vehicle speed corresponding to the front vehicle can be obtained by determining the relative speed of the front vehicle and the driving vehicle through a speed measuring instrument arranged on the driving vehicle and reading the current vehicle speed of the driving vehicle.

Optionally, the step S11 includes:

the image data of the front vehicle is collected through a monitoring device arranged on the vehicle.

And identifying the image data according to a pre-trained identification model, and determining the type of the vehicle corresponding to the front vehicle.

It can be understood that, in this embodiment, the image data of the preceding vehicle is collected by the monitoring device provided at the front end of the driving vehicle. Due to the influence of a high vehicle speed in the driving process, the data processing process on the driving vehicle needs to ensure low time delay so as to ensure that the automatic driving error is within a reasonable range. Therefore, in a normal situation, the image data of the leading vehicle collected by the monitoring device is one or more frames of vehicle tail image data. According to the unified international standard of vehicle manufacturing, the corresponding size proportion or area proportion of the tail images of the same vehicle model is similar. The image data is recognized through a pre-trained vehicle tail image recognition model, so that the vehicle type corresponding to the front vehicle can be determined. The vehicle type identification method comprises the steps that an identification model is obtained through mass vehicle tail image identification and manual inspection and correction, for example, the vehicle type can be determined through identifying elements in the vehicle tail images and applying a rule classification method, and the identification model is trained on the basis of the identification rule; a machine learning method based on the decision tree can be used for training the decision tree, and the vehicle type can be directly solved on line according to the currently obtained image data; the vehicle type may also be determined by pre-training a network model using the classification network model and analyzing currently acquired image data based on the pre-trained network model.

For example, in step S12, it is understood that in the actual manual overtaking decision process, it is necessary to perform an integrated judgment of overtaking according to the vehicle speed of the driving vehicle, the distance between the driving vehicle and the preceding vehicle, and the vehicle speed of the preceding vehicle, and therefore, in the present embodiment, in the automatic driving mode, a decision operation is performed on whether to perform overtaking according to the vehicle type and the first vehicle speed of the preceding vehicle, and the vehicle distance between the preceding vehicle and the driving vehicle, so as to obtain an overtaking decision result of the driving vehicle. For example, the factors influencing the overtaking decision result can be converted into corresponding data, the overtaking decision algorithm is applied to obtain the numerical value corresponding to the overtaking decision result, and the overtaking decision result is represented by the numerical value, so that the machine algorithm can make a decision whether to execute overtaking more quickly and accurately.

Optionally, the step S12 includes:

and determining a target operation coefficient corresponding to the vehicle type based on a preset coefficient table, wherein the preset coefficient table comprises a plurality of vehicle types and a mapping relation between the plurality of operation coefficients.

And determining the overtaking decision result by using a decision function according to the first vehicle speed, the vehicle distance, the target operation coefficient and the second vehicle speed.

It can be understood that the vehicle type obtained through the above steps is text type information, for example, a car, a mid-sized off-road vehicle, a small truck, a large truck, etc., when the overtaking decision calculation is performed, different vehicle types need to be converted into different values, so that the machine can perform the decision calculation based on the data, thereby obtaining the overtaking decision result. Therefore, in the present embodiment, in the driving vehicle control system, a preset coefficient table is set in advance, the preset coefficient table includes a plurality of vehicle types and a plurality of operation coefficients, and the vehicle types and the operation coefficients exhibit a one-to-one mapping relationship. After the vehicle type is obtained, the target operation coefficient corresponding to the vehicle type can be determined by inquiring the preset coefficient table. And determining the overtaking decision result of the vehicle by utilizing a decision function according to the target operation coefficient, the second vehicle speed of the driven vehicle, the first vehicle speed of the front vehicle and the vehicle distance between the front vehicle and the driven vehicle. The decision function is a specific numerical value obtained by calculation based on a certain calculation process according to the target calculation coefficient, the first vehicle speed, the second vehicle speed and the vehicle distance.

Optionally, the decision function may include:

D=k*（V₁*d/V₂）

It will be appreciated that, in the context of safe driving, driving a vehicle has different intent to cut-in for different vehicle types in front of the vehicle. For example, in general, when a car is driven to run in the trail, the car has less threat to safe driving of the driven car, and the overtaking intention of the driven car in the automatic driving mode is smaller; when a large truck drives a vehicle to a corresponding distance, the large truck has the characteristics of low speed, long occupied road, high danger coefficient and the like when driving on the road, and the overtaking intention of the vehicle driven in the automatic driving mode is high. Therefore, based on the above characteristics, it is possible to set the operation coefficient of the large truck to be smaller than that of the small car, and gradually decrease the value of the operation coefficient from the small car to the large truck based on the safety of the vehicle type. Determining a target operation coefficient k corresponding to the type of the vehicle through a preset coefficient table in the steps, and acquiring and obtaining a first vehicle speed V of the front vehicle according to a speed detection device arranged on the driving vehicle₁Driving a second vehicle speed V of the vehicle₂And the distance D between the front vehicle and the driving vehicle, and obtaining a numerical value corresponding to the overtaking decision result D through a decision function. It should be noted that, in this embodiment, the first vehicle speed and the second vehicle speed may be instantaneous vehicle speeds of a preceding vehicle and a driving vehicle, or may also be average vehicle speeds within a period of time, and in the overtaking decision process, the current second vehicle speed of the driving vehicle is always greater than the first vehicle speed of the preceding vehicle, if the current second vehicle speed is calculated in the overtaking decision process, the current second vehicle speed is greater than the first vehicle speed of the preceding vehicle, and the current second vehicle speed is calculated in the overtaking decision processIn the process, when the first vehicle speed of the front vehicle is detected to be greater than the second vehicle speed, the overtaking decision can be interrupted, and the vehicle is controlled to continue to run according to the current vehicle speed.

For example, in step S13, after the passing decision result of the vehicle is determined by the above calculation, the passing decision result is compared with a preset decision threshold, and when the passing decision result is smaller than the preset decision threshold, it indicates that when the vehicle is driven to keep the driving state at this time and continues to run, a safety accident is easily caused, and the driving safety is affected, so that the vehicle needs to be controlled to perform lane change passing. And converting each influence factor into unified data according to the vehicle type, the first vehicle speed, the vehicle distance and the second vehicle speed, and calculating and determining the overtaking lane change track of the vehicle through a track algorithm. It can be understood that, by comparing the overtaking decision result with the preset decision threshold, it is determined that, after the driving vehicle needs to be controlled to perform lane changing overtaking in the current automatic driving state, the overtaking lane changing track of the driving vehicle can be calculated and obtained by the second vehicle speed of the driving vehicle, the first vehicle speed and the vehicle distance of the front vehicle and combining the corresponding safe overtaking rule.

Fig. 2 is a flowchart illustrating a method for determining a passing lane-change trajectory according to an exemplary embodiment, referring to fig. 2, where the step S13 includes:

in step S131, a first safe distance and a second safe distance between the vehicle and the preceding vehicle are determined according to the vehicle type, where the first safe distance is a distance between the vehicle and the preceding vehicle when the vehicle can complete a safe overtaking, and the second safe distance is a distance between the preceding vehicle and the preceding vehicle when the vehicle can complete a safe returning.

In step S132, a first time interval corresponding to the vehicle steering overtaking process is determined according to the first safe vehicle distance, the first vehicle speed and the second vehicle speed.

In step S133, a second time period corresponding to the vehicle steering regression process is determined according to the second safe vehicle distance, the first vehicle speed, and the second vehicle speed.

In step S134, an overtaking lane change trajectory of the vehicle is determined according to the first time period, the second time period, and the overtaking steering angle.

It can be understood that, in this embodiment, the first safe inter-vehicle distance is a minimum distance between the driving vehicle and the preceding vehicle before the overtaking is not performed, and after the first safe inter-vehicle distance is exceeded, because the overtaking safety of the driving vehicle cannot be ensured, at this time, the driving vehicle needs to be controlled to stop performing the overtaking, and the current driving vehicle speed of the driving vehicle is reduced according to the first vehicle speed of the preceding vehicle. The second safe vehicle distance is the minimum distance between the front vehicle and the driving vehicle in the driving direction when the driving vehicle needs to return to the initial driving lane from the current driving lane after the driving vehicle carries out overtaking lane change, when the distance is lower than the second safe vehicle distance, the driving vehicle can not be ensured to safely return to the initial driving lane, and the driving vehicle can be controlled to turn from the current driving lane to return to the initial driving lane after the distance is determined to reach the second safe vehicle distance through the monitoring device. It should be noted that the different types of the preceding vehicles correspond to different overtaking lane changing tracks of the determined vehicles, for example, when the type of the preceding vehicle is a large truck, in order to ensure overtaking safety, both the first safe vehicle distance and the second safe vehicle distance need to be controlled within a larger range, so as to ensure that the driven vehicle has a longer safe steering distance, thereby ensuring overtaking lane changing safety of the driven vehicle; for the front car with the car type of a sedan, the danger to driving the car is low when the car overtakes and changes lanes due to small car type, and at the moment, the first safe distance and the second safe distance can be determined to be within a certain range. Illustratively, it is determined by limited experimentation that in general, the initial first safe vehicle distance is d₁The initial second safe distance is d₂If the calculation coefficient corresponding to the vehicle type is determined to be k according to the preset coefficient table in the above embodiment, it may be determined that the first safe vehicle distance is d in this embodiment₁K, the second safe distance is d₂/k。

In this embodiment, when the distance between the driving vehicle and the preceding vehicle in the driving direction reaches the first safe vehicle distance, the driving vehicle needs to turn to go out of the initial driving lane, and when the driving vehicle runs in the current lane and the distance between the driving vehicle and the preceding vehicle in the driving direction reaches the second safe vehicle distance, the driving vehicle needs to turn to return to the initial driving lane. Therefore, by determining the first safe distance and the second safe distance and combining the second vehicle speed of the driving vehicle and the first vehicle speed of the front vehicle, the time point of starting the steering of the driving vehicle, the first time period corresponding to the steering overtaking process and the second time period corresponding to the vehicle steering returning process can be determined. The overtaking lane change track of the vehicle can be determined through the preset overtaking steering angle, the first time period and the second time period.

Optionally, the step S134 includes:

and determining the overtaking steering angle of the vehicle according to the type of the vehicle.

And determining the lane changing track of the vehicle according to the first time period and the overtaking steering angle, and determining the lane returning track of the vehicle according to the second time period and the overtaking steering angle.

And determining the overtaking track changing track of the vehicle according to the track changing track and the return track.

It can be understood that during the process of overtaking and changing lane, the overtaking steering angle influences the transverse distance between the driving vehicle and the front vehicle after changing lane. Under the normal condition, the proportion of the large truck occupying the road is large, and in order to avoid the occurrence of the scratch, when a driving vehicle and the large truck run side by side, the transverse distance needs to be controlled within a large range so as to ensure the running safety; the proportion of the car occupying the road is small, and when a driver drives a vehicle and the car to run side by side, the transverse distance needs to be controlled within a small range so as to ensure that the driver can overtake the vehicle as soon as possible. Therefore, different overtaking steering angles can be set according to different vehicle types, and for example, different overtaking steering angles can be determined according to the target operation coefficient k determined in the preset coefficient table so as to ensure that the overtaking steering angle of a large truck is larger than that of a small car.

In this embodiment, the overtaking steering angle in the overtaking process is complementary to the steering angle in the returning process, that is, the steering angle when the driving vehicle returns to the initial driving lane can be determined by the overtaking steering angle. According to the steering angles corresponding to the first time period and the second time period, the lane changing track when the vehicle is driven to change lanes and pass a lane and the return track when the vehicle is driven to turn back can be determined. The overtaking track changing track of the vehicle can be determined by connecting the track changing track with the return track.

For example, in step S14, after the passing lane change trajectory of the driven vehicle is determined through the above steps, the driven vehicle may be controlled to perform the passing lane change along the trajectory.

Optionally, the step S14 includes:

and determining whether other vehicles exist on the overtaking lane changing track according to the overtaking lane changing track.

It can be understood that, in this embodiment, after the overtaking lane change trajectory is generated, the vehicle within a certain range on the overtaking lane needs to be monitored, and when it is determined that no other vehicle exists on the overtaking lane within a certain distance range, the vehicle is controlled to overtake according to the overtaking lane change trajectory. When other vehicles exist on the overtaking lane, the driving vehicle is not suitable for executing lane change overtaking at the moment, and the vehicle can be controlled to reduce the speed so as to avoid collision with the front vehicle.

According to the scheme, the vehicle type and the first vehicle speed of the front vehicle are determined in response to the fact that the vehicle distance between the vehicle and the front vehicle is smaller than the preset distance threshold, the overtaking decision result of the vehicle is determined according to the vehicle type, the first vehicle speed, the vehicle distance and the second vehicle speed of the vehicle, the overtaking lane changing track of the vehicle is determined according to the vehicle type, the first vehicle speed, the vehicle distance and the second vehicle speed under the condition that the overtaking decision result is smaller than the preset decision threshold, and the vehicle is controlled to carry out overtaking based on the overtaking lane changing track. And when the vehicle is determined to need to overtake through the algorithm, generating an overtaking lane changing track corresponding to the vehicle through the vehicle type and the related driving data, so that the vehicle can automatically overtake according to the overtaking lane changing track. The vehicle type is taken as a necessary consideration factor of the algorithm, so that the vehicle can accurately execute the overtaking lane changing process based on the current actual situation, and better automatic driving experience is brought to passengers.

FIG. 3 is a block diagram illustrating an automatic overtaking device according to an exemplary embodiment. Referring to fig. 3, the overtaking apparatus 100 includes a first determining module 110, a second determining module 120, a third determining module 130, and an executing module 140.

The first determination module 110 is configured to determine a vehicle type and a first vehicle speed of a preceding vehicle in response to a vehicle distance between the vehicle and the preceding vehicle being less than a preset distance threshold.

The second determination module 120 is configured to determine a passing decision result of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance and a second vehicle speed of the vehicle.

The third determining module 130 is configured to determine the passing lane-changing trajectory of the vehicle according to the vehicle type, the first vehicle speed, the vehicle distance, and the second vehicle speed when the passing decision result is smaller than a preset decision threshold.

The execution module 140 is configured to control the vehicle to execute the passing based on the passing lane change track.

Optionally, the first determining module 110 may be further configured to:

Optionally, the second determining module 120 may be further configured to:

Optionally, the decision function in the second determining module 120 may include:

D=k*（V₁*d/V₂）

wherein D is the overtaking decision result, and k isThe target operation coefficient, V₁Is the first vehicle speed, d is the vehicle distance, V₂The second vehicle speed.

Optionally, the third determining module 130 may include:

the first determining submodule is configured to determine a first safe vehicle distance and a second safe vehicle distance between the vehicle and the front vehicle according to the type of the vehicle, wherein the first safe vehicle distance is the distance between the vehicle and the front vehicle under the condition that the vehicle can complete safe overtaking, and the second safe vehicle distance is the distance between the front vehicle and the vehicle under the condition that the vehicle can complete safe returning.

And the second determining submodule is configured to determine a first time period corresponding to the vehicle steering overtaking process according to the first safe vehicle distance, the first vehicle speed and the second vehicle speed.

And the third determining submodule is configured to determine a second time period corresponding to the vehicle steering regression process according to the second safe vehicle distance, the first vehicle speed and the second vehicle speed.

And the fourth determination submodule is configured to determine the overtaking lane change track of the vehicle according to the first time interval, the second time interval and the overtaking steering angle.

Optionally, the fourth determining sub-module may be further configured to:

Optionally, the execution module may be further configured to:

With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.

The present disclosure also provides a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the passing lane change method provided by the present disclosure.

FIG. 4 is a block diagram illustrating a vehicle 400 according to an exemplary embodiment. Referring to fig. 4, a vehicle 400 may include one or more of the following components: a processing component 402, a memory 404, a power component 406, a multimedia component 408, an audio component 410, an interface for input/output (I/O) 412, a sensor component 414, and a communication component 416.

The processing component 402 generally controls overall operation of the vehicle 400, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 402 may include one or more processors 420 to execute instructions to perform all or a portion of the steps of the above-described cut-in lane change method. Further, the processing component 402 can include one or more modules that facilitate interaction between the processing component 402 and other components. For example, the processing component 402 may include a multimedia module to facilitate interaction between the multimedia component 408 and the processing component 402.

The memory 404 is configured to store various types of data to support operation at the vehicle 400. Examples of such data include instructions for any application or method operating on the vehicle 400, contact data, phone book data, messages, pictures, videos, and so forth. The memory 404 may be implemented by any type or combination of volatile and non-volatile storage devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

The power components 406 provide power to the various components of the vehicle 400. The power components 406 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the vehicle 400.

The multimedia component 408 includes a screen providing an output interface between the vehicle 400 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 408 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the vehicle 400 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 410 is configured to output and/or input audio signals. For example, the audio component 410 includes a Microphone (MIC) configured to receive an external audio signal when the vehicle 400 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in the memory 404 or transmitted via the communication component 416. In some embodiments, audio component 410 also includes a speaker for outputting audio signals.

The I/O interface 412 provides an interface between the processing component 402 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 414 includes one or more sensors for providing various aspects of state assessment for the vehicle 400. For example, the sensor assembly 414 may detect the open/closed status of the vehicle 400, the relative positioning of the components, such as the display and keypad of the vehicle 400, the sensor assembly 414 may also detect a change in the position of the vehicle 400 or a component of the vehicle 400, the presence or absence of user contact with the vehicle 400, the orientation or acceleration/deceleration of the vehicle 400, and a change in the temperature of the vehicle 400. The sensor assembly 414 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 414 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 414 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 416 is configured to facilitate wired or wireless communication between the vehicle 400 and other devices. The vehicle 400 may access a wireless network based on a communication standard, such as WiFi, 4G or 5G, or a combination thereof. In an exemplary embodiment, the communication component 416 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 416 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the vehicle 400 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic components for performing the above-described lane change method for passing vehicles.

In the exemplary embodiment, a non-transitory computer-readable storage medium including instructions, such as memory 404, is also provided that is executable by processor 420 of vehicle 400 to perform the above-described cut-in lane change method. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

The apparatus may be a part of a stand-alone electronic device, for example, in an embodiment, the apparatus may be an Integrated Circuit (IC) or a chip, where the IC may be one IC or a set of multiple ICs; the chip may include, but is not limited to, the following categories: a GPU (Graphics Processing Unit), a CPU (Central Processing Unit), an FPGA (Field Programmable Gate Array), a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an SOC (System on Chip, SOC, System on Chip, or System on Chip), and the like. The integrated circuit or chip may be configured to execute executable instructions (or code) to implement the above-described passing lane change method. Where the executable instructions may be stored in the integrated circuit or chip or may be retrieved from another device or apparatus, such as an integrated circuit or chip that includes a processor, memory, and an interface for communicating with other devices. The executable instructions can be stored in the processor, and when the executable instructions are executed by the processor, the overtaking lane changing method is realized; alternatively, the integrated circuit or chip may receive the executable instructions through the interface and transmit the executable instructions to the processor for execution, so as to implement the above-mentioned passing lane change method.

Referring to fig. 5, fig. 5 is a functional block diagram of another vehicle 500, shown according to an exemplary embodiment. The vehicle 500 may be configured in a fully or partially autonomous driving mode. For example, the vehicle 500 may acquire environmental information around the vehicle through the sensing system 520 and derive an automatic driving strategy based on an analysis of the surrounding environmental information to implement fully automatic driving, or present the analysis result to the user to implement partially automatic driving.

The vehicle 500 may include various subsystems such as an infotainment system 510, a perception system 520, a decision control system 530, a drive system 540, and a computing platform 550. Alternatively, vehicle 500 may include more or fewer subsystems, and each subsystem may include multiple components. In addition, each of the sub-systems and components of the vehicle 500 may be interconnected by wire or wirelessly.

In some embodiments, the infotainment system 510 may include a communication system 511, an entertainment system 512, and a navigation system 513.

The communication system 511 may comprise a wireless communication system that may communicate wirelessly with one or more devices, either directly or via a communication network. For example, the wireless communication system may use 3G cellular communication, such as CDMA, EVD0, GSM/GPRS, or 4G cellular communication, such as LTE. Or 5G cellular communication. The wireless communication system may communicate with a Wireless Local Area Network (WLAN) using WiFi. In some embodiments, the wireless communication system may communicate directly with the device using an infrared link, bluetooth, or ZigBee. Other wireless protocols, such as various vehicular communication systems, for example, a wireless communication system may include one or more Dedicated Short Range Communications (DSRC) devices that may include public and/or private data communications between vehicles and/or roadside stations.

The entertainment system 512 may include a display device, a microphone, and a sound box, and a user may listen to a broadcast in the car based on the entertainment system, playing music; or the mobile phone is communicated with the vehicle, the screen projection of the mobile phone is realized on the display equipment, the display equipment can be in a touch control mode, and a user can operate the display equipment by touching the screen.

In some cases, the voice signal of the user may be acquired through a microphone, and certain control of the vehicle 500 by the user, such as adjusting the temperature in the vehicle, etc., may be implemented according to the analysis of the voice signal of the user. In other cases, music may be played to the user through a sound.

The navigation system 513 may include a map service provided by a map provider to provide navigation of the route traveled by the vehicle 500, and the navigation system 513 may be used in conjunction with the global positioning system 521 and the inertial measurement unit 522 of the vehicle. The map service provided by the map supplier can be a two-dimensional map or a high-precision map.

The perception system 520 may include several types of sensors that sense information about the environment surrounding the vehicle 500. For example, the sensing system 520 may include a global positioning system 521 (the global positioning system may be a GPS system, a beidou system, or other positioning system), an Inertial Measurement Unit (IMU) 522, a lidar 523, a millimeter-wave radar 524, an ultrasonic radar 525, and a camera 526. The sensing system 520 may also include sensors of internal systems of the monitored vehicle 500 (e.g., an in-vehicle air quality monitor, a fuel gauge, an oil temperature gauge, etc.). Sensor data from one or more of these sensors may be used to detect the object and its corresponding characteristics (position, shape, orientation, velocity, etc.). Such detection and identification is a critical function of the safe operation of the vehicle 500.

Global positioning system 521 is used to estimate the geographic location of vehicle 500.

The inertial measurement unit 522 is used to sense a pose change of the vehicle 500 based on the inertial acceleration. In some embodiments, inertial measurement unit 522 may be a combination of an accelerometer and a gyroscope.

The lidar 523 utilizes laser light to sense objects in the environment in which the vehicle 500 is located. In some embodiments, lidar 523 may include one or more laser sources, laser scanners, and one or more detectors, among other system components.

Millimeter-wave radar 524 utilizes radio signals to sense objects within the surrounding environment of vehicle 500. In some embodiments, in addition to sensing objects, millimeter-wave radar 524 may also be used to sense the speed and/or heading of objects.

The ultrasonic radar 525 may sense objects around the vehicle 500 using ultrasonic signals.

The camera 526 is used to capture image information of the surrounding environment of the vehicle 500. The camera 526 may include a monocular camera, a binocular camera, a structured light camera, a panoramic camera, and the like, and the image information acquired by the camera 526 may include still images or video stream information.

Decision control system 530 includes a computing system 531 that makes analytical decisions based on information obtained by sensing system 520, and decision control system 530 further includes a vehicle control unit 532 that controls the powertrain of vehicle 500, and a steering system 533, throttle 534, and braking system 535 for controlling vehicle 500.

The computing system 531 may be operable to process and analyze various information acquired by the perception system 520 in order to identify objects, and/or features in the environment surrounding the vehicle 500. The targets may include pedestrians or animals, and the objects and/or features may include traffic signals, road boundaries, and obstacles. The computing system 531 may use object recognition algorithms, Motion from Motion (SFM) algorithms, video tracking, and the like. In some embodiments, the computing system 531 may be used to map an environment, track objects, estimate the speed of objects, and the like. The computing system 531 may analyze the various information obtained and derive a control strategy for the vehicle.

Vehicle control unit 532 may be used to coordinate control of the vehicle's power battery and engine 541 to improve the power performance of vehicle 500.

The steering system 533 is operable to adjust the heading of the vehicle 500. For example, in one embodiment, a steering wheel system.

The throttle 534 is used to control the operating speed of the engine 541 and, in turn, the speed of the vehicle 500.

The braking system 535 is used to control the deceleration of the vehicle 500. The braking system 535 may use friction to slow the wheel 544. In some embodiments, the braking system 535 may convert kinetic energy of the wheel 544 into an electrical current. The braking system 535 may take other forms to slow the rotational speed of the wheels 544 to control the speed of the vehicle 500.

The drive system 540 may include components that provide powered motion to the vehicle 500. In one embodiment, drive system 540 may include an engine 541, an energy source 542, a transmission 543, and wheels 544. The engine 541 may be an internal combustion engine, an electric motor, an air compression engine, or other type of engine combination, such as a hybrid engine consisting of a gasoline engine and an electric motor, a hybrid engine consisting of an internal combustion engine and an air compression engine. The engine 541 converts the energy source 542 into mechanical energy.

Examples of energy source 542 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 542 may also provide energy to other systems of the vehicle 500.

The transmission 543 may transmit mechanical power from the engine 541 to the wheels 544. The drivetrain 543 may include a gearbox, a differential and a drive shaft. In one embodiment, the transmission 543 may also include other devices, such as clutches. Wherein the drive shaft may include one or more axles that may be coupled to one or more wheels 544.

Some or all of the functions of the vehicle 500 are controlled by the computing platform 550. The computing platform 550 may include at least one processor 551, and the processor 551 may execute instructions 553 stored in a non-transitory computer-readable medium, such as the memory 552. In some embodiments, the computing platform 550 may also be a plurality of computing devices that control individual components or subsystems of the vehicle 500 in a distributed manner.

The processor 551 may be any conventional processor, such as a commercially available CPU. Alternatively, the processor 551 may also include a processor such as a Graphics Processing Unit (GPU), a Field Programmable Gate Array (FPGA), a System On Chip (SOC), an Application Specific Integrated Circuit (ASIC), or a combination thereof. Although fig. 5 functionally illustrates a processor, memory, and other elements of a computer in the same block, those skilled in the art will appreciate that the processor, computer, or memory may actually comprise multiple processors, computers, or memories that may or may not be stored within the same physical housing. For example, the memory may be a hard drive or other storage medium located in a different housing than the computer. Thus, reference to a processor or computer will be understood to include reference to a collection of processors or computers or memories that may or may not operate in parallel. Rather than using a single processor to perform the steps described herein, some of the components, such as the steering and deceleration components, may each have their own processor that performs only computations related to the component-specific functions.

In the disclosed embodiment, the processor 551 may perform the above-described passing lane change method.

In various aspects described herein, the processor 551 may be located remotely from the vehicle and in wireless communication with the vehicle. In other aspects, some of the processes described herein are executed on a processor disposed within the vehicle and others are executed by a remote processor, including taking the steps necessary to perform a single maneuver.

In some embodiments, the memory 552 may contain instructions 553 (e.g., program logic), which instructions 553 may be executed by the processor 551 to perform various functions of the vehicle 500. Memory 552 may also contain additional instructions, including instructions to send data to, receive data from, interact with, and/or control one or more of infotainment system 510, perception system 520, decision control system 530, drive system 540.

In addition to instructions 553, memory 552 may also store data such as road maps, route information, the location, direction, speed of the vehicle, and other such vehicle data, as well as other information. Such information may be used by the vehicle 500 and the computing platform 550 during operation of the vehicle 500 in autonomous, semi-autonomous, and/or manual modes.

Computing platform 550 may control functions of vehicle 500 based on inputs received from various subsystems, such as drive system 540, perception system 520, and decision-making control system 530. For example, computing platform 550 may utilize input from decision control system 530 in order to control steering system 533 to avoid obstacles detected by sensing system 520. In some embodiments, the computing platform 550 is operable to provide control over many aspects of the vehicle 500 and its subsystems.

Optionally, one or more of these components described above may be mounted or associated separately from the vehicle 500. For example, the memory 552 may reside partially or completely separate from the vehicle 500. The aforementioned components may be communicatively coupled together in a wired and/or wireless manner.

Optionally, the above components are only an example, in an actual application, components in the above modules may be added or deleted according to an actual need, and fig. 5 should not be construed as limiting the embodiment of the present disclosure.

An autonomous automobile traveling on a road, such as vehicle 500 above, may identify objects within its surrounding environment to determine an adjustment to the current speed. The object may be another vehicle, a traffic control device, or another type of object. In some examples, each identified object may be considered independently, and based on the respective characteristics of the object, such as its current speed, acceleration, separation from the vehicle, etc., may be used to determine the speed at which the autonomous vehicle is to be adjusted.

Optionally, the vehicle 500 or a sensing and computing device associated with the vehicle 500 (e.g., computing system 531, computing platform 550) may predict the behavior of the identified object based on characteristics of the identified object and the state of the surrounding environment (e.g., traffic, rain, ice on the road, etc.). Optionally, each of the identified objects is dependent on the behavior of each other, so all of the identified objects can also be considered together to predict the behavior of a single identified object. The vehicle 500 is able to adjust its speed based on the predicted behavior of the identified object. In other words, the autonomous vehicle is able to determine what steady state the vehicle will need to adjust to (e.g., accelerate, decelerate, or stop) based on the predicted behavior of the object. Other factors may also be considered in this process to determine the speed of the vehicle 500, such as the lateral position of the vehicle 500 in the road being traveled, the curvature of the road, the proximity of static and dynamic objects, and so forth.

In addition to providing instructions to adjust the speed of the autonomous vehicle, the computing device may provide instructions to modify the steering angle of the vehicle 500 to cause the autonomous vehicle to follow a given trajectory and/or to maintain a safe lateral and longitudinal distance from objects in the vicinity of the autonomous vehicle (e.g., vehicles in adjacent lanes on the road).

The vehicle 500 may be any type of vehicle, such as a car, a truck, a motorcycle, a bus, a boat, an airplane, a helicopter, a recreational vehicle, a train, etc., and the disclosed embodiment is not particularly limited.

In another exemplary embodiment, a computer program product is also provided, which comprises a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-described passing lane change method when executed by the programmable apparatus.

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 in 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

1. An automatic overtaking method, comprising:

determining a vehicle type and a first vehicle speed of a front vehicle in response to a vehicle distance between the vehicle and the front vehicle being less than a preset distance threshold;

determining a overtaking decision result by utilizing a decision function according to the first vehicle speed, the vehicle distance, the target operation coefficient and the second vehicle speed of the vehicle;

2. The method of overtaking of claim 1 wherein said determining the vehicle type of the preceding vehicle comprises:

3. The method of claim 1, wherein the decision function comprises:

D=k*（V₁*d/V₂）

4. The method of claim 1, wherein determining the passing lane change trajectory of the vehicle according to the vehicle type, the first vehicle speed, the inter-vehicle distance and a second vehicle speed corresponding to the vehicle comprises:

determining a first time period corresponding to the vehicle steering overtaking process according to the first safe vehicle distance, the first vehicle speed and the second vehicle speed;

and determining the overtaking lane changing track of the vehicle according to the first time period, the second time period and the overtaking steering angle.

5. The method of claim 4, wherein said determining the passing lane change trajectory of the vehicle based on the first time period, the second time period, and a passing steering angle comprises:

6. The method of claim 1, wherein controlling the vehicle to perform the cut-in based on the cut-in lane change trajectory comprises:

7. An automatic overtaking device, characterized by comprising:

the second determination module is configured to determine a target operation coefficient corresponding to the vehicle type based on a preset coefficient table, wherein the preset coefficient table comprises a plurality of vehicle types and a plurality of mapping relations among operation coefficients;

determining an overtaking decision result by utilizing a decision function according to the first vehicle speed, the vehicle distance, the target operation coefficient and the second vehicle speed of the vehicle;

8. A vehicle, characterized by comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to:

9. A computer-readable storage medium, on which computer program instructions are stored, which program instructions, when executed by a processor, carry out the steps of the method according to any one of claims 1 to 6.

10. A chip comprising a processor and an interface; the processor is configured to read instructions to perform the method of any of claims 1-6.