CN114212079B

CN114212079B - ACC-based vehicle control method, device and system

Info

Publication number: CN114212079B
Application number: CN202210149323.1A
Authority: CN
Inventors: 周行; 尚进; 丛炜
Original assignee: Guoqi Intelligent Control Beijing Technology Co Ltd
Current assignee: Guoqi Intelligent Control Beijing Technology Co Ltd
Priority date: 2022-02-18
Filing date: 2022-02-18
Publication date: 2022-05-20
Anticipated expiration: 2042-02-18
Also published as: CN114212079A

Abstract

The application discloses a vehicle control method, device and system based on ACC, wherein the method comprises the following steps: acquiring environmental data of a target vehicle, and fusing the environmental data to obtain a fusion result; carrying out map construction on the surrounding environment of the target vehicle based on the fusion result to obtain lane line data; acquiring a lane line based on the lane line data, and detecting the lane line; if the lane line is complete but the running of the vehicle interference ACC exists, performing first adjustment on the running state of the target vehicle, and starting the ACC; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC. The technical scheme of this application based on lane line data, acquires the lane line to monitor the lane line and know in advance that there is the vehicle to approach the target vehicle fast or monitor that the target lane is occupied and in time park or assist the ACC of suitable turn function, and then reduce the collision risk.

Description

ACC-based vehicle control method, device and system

Technical Field

The application belongs to the technical field of automatic driving, and particularly relates to an ACC-based vehicle control method, device and system.

Background

In the running process of a vehicle, a vehicle distance sensor (radar) installed at the front part of the vehicle continuously scans the road in front of the vehicle, and meanwhile, a wheel speed sensor collects a vehicle speed signal. When the distance between the vehicle and the front vehicle is too small, an Adaptive Cruise Control (ACC) unit can appropriately brake the wheels and reduce the output power of an engine by coordinating with a brake anti-lock system and an engine Control system, so that the vehicle and the front vehicle always keep a safe distance. The ACC generally limits the braking deceleration to a level that does not affect comfort when controlling the vehicle braking, and the ACC control unit emits an audible and visual signal to inform the driver to actively take a braking action when a greater deceleration is required. When the distance to the preceding vehicle is increased to a safe distance, the ACC control unit controls the vehicle to travel at a set vehicle speed.

The ACC detects a vehicle in front of the vehicle by using a front radar or a fused front-view camera, controls the speed of the vehicle by using an Engine Management System (EMS) or an Electronic Stability Control (ESC), and maintains a proper following distance from the vehicle. The ACC belongs to an L1-level intelligent driving auxiliary function, and requires two hands of a driver to surely avoid leaving a steering wheel, so that the information of vehicle conditions and road conditions can be observed in real time, and the control on the vehicle can be timely taken over. Accelerating the vehicle to a desired speed value by sending a forward torque to a power system for acceleration control; the vehicle is decelerated to a desired speed value by deceleration control by sending deceleration to the brake system.

However, the conventional ACC has the following technical problems:

1) as shown in fig. 1, when a vehicle a is running, and there is a vehicle C merging into the lane at a turn, the focused front vehicle is switched (from vehicle B to vehicle C), and there is a risk of rear-end collision.

2) As shown in fig. 2, a part of the road in front of the vehicle a is occupied by the other vehicles B, and the ACC detects no front vehicle and a collision occurs.

3) The use of a single sensor in the ACC can only be used as a single component, which is not applicable to a multiple sensor system.

Although a plurality of sensors can be installed to solve the above problems, data fusion is involved, and a data fusion method is an important means for data analysis and mining, however, the requirements of state uncertainty, processing real-time performance and the like in the driving of the automobile pose a serious challenge to the design of the fusion method.

Disclosure of Invention

The present application is directed to solving, at least to some extent, one of the technical problems in the related art. Therefore, one objective of the present application is to provide an ACC-based vehicle control method, apparatus and system.

In order to solve the above technical problem, an embodiment of the present application provides the following technical solutions:

in a first aspect, an embodiment of the present application provides an ACC-based vehicle control method, including:

acquiring environmental data of a target vehicle, and fusing the environmental data to obtain a fusion result;

performing map construction on the surrounding environment of the target vehicle based on the fusion result to acquire lane line data;

acquiring a lane line based on the lane line data, and detecting the lane line;

if the lane line is complete but the running of the vehicle interference ACC exists, performing first adjustment on the running state of the target vehicle, and starting the ACC; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC.

The embodiment of the application acquires the lane line based on the lane line data, monitors the lane line, and foresees that the vehicle is close to the target vehicle quickly or monitors that the target lane is occupied and stops in time or assists the ACC with a proper turning function, thereby reducing the collision risk.

In a possible implementation manner, the acquiring environmental data of the target vehicle and fusing the environmental data to obtain a fusion result includes:

monitoring the surrounding environment of the target vehicle based on a plurality of sensors to obtain monitoring data;

and processing the monitoring number based on a complementary filtering algorithm to obtain the environmental data.

Specifically, the complementary filtering algorithm is implemented based on complementary filters that pass through different filters (high-pass or low-pass, complementary) according to the sensor characteristics, and then add up to obtain the signal of the entire frequency band.

According to the embodiment of the application, the surrounding environment of the target vehicle is monitored in real time based on the sensors, the environment data is obtained, the environment data is fused based on the fusion algorithm, and the safety of the ACC to the running state of the target vehicle is improved.

In one possible implementation manner, acquiring environment data of a target vehicle, and fusing the environment data to obtain a fusion result includes:

processing the environmental data based on a tracking algorithm to obtain a tracking target;

and fusing the tracking target based on a fusion algorithm to obtain fusion data.

In a possible implementation manner, the mapping the surrounding environment of the target vehicle based on the fusion result to obtain lane line data includes:

obtaining a construction result;

determining an obstacle of the surroundings of the target vehicle based on the construction result;

acquiring a target distance between each obstacle and the target vehicle based on the obstacles;

and acquiring the lane line data based on each obstacle and the target distance matched with the obstacle.

In one possible implementation, obtaining the construction result includes:

and carrying out map construction on the surrounding ring of the target vehicle based on the SLAM algorithm and the fusion result to obtain the construction result.

In a possible implementation manner, the acquiring a lane line based on the lane line data and detecting the lane line includes:

and if the lane line is complete and the vehicle does not interfere with the running of the target vehicle, starting the ACC.

In a second aspect, an embodiment of the present application provides an ACC-based vehicle control apparatus including:

the fusion module is used for acquiring the environmental data of the target vehicle and fusing the environmental data to acquire a fusion result;

the construction module is used for carrying out map construction on the surrounding environment of the target vehicle based on the fusion result to obtain lane line data;

the detection module is used for acquiring a lane line based on the lane line data and detecting the lane line;

the adjusting module is used for performing first adjustment on the running state of the target vehicle and starting the ACC if the lane line is complete but the running of the ACC is interfered by the vehicle; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC.

In a third aspect, an embodiment of the present application provides an ACC-based vehicle control system, comprising:

the system comprises a sensor device, a monitoring device and a control device, wherein the sensor device is provided with a plurality of sensors which monitor the surrounding environment of a target vehicle and acquire environmental data;

an ACC for controlling an operation state of a target vehicle;

the control device is respectively connected with the ACC and the sensors and is used for receiving the environmental data sent by the sensor devices and fusing the environmental data to obtain a fusion result; acquiring a lane line based on the fusion result, and detecting the lane line to obtain a detection result; the operating state of the ACC is then controlled based on the detection result.

In a fourth aspect, an embodiment of the present application provides a smart vehicle, including a processor, a memory, and a communication interface, wherein the memory is used for storing information transmission program codes, and the processor is used for calling the vehicle running control program codes to execute the method described above.

In a fifth aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the method as described above when executing the computer program.

In a sixth aspect, an embodiment of the application provides a computer-readable storage medium comprising a stored computer program, wherein the computer program, when executed, controls an apparatus on which the computer-readable storage medium is located to perform the method as described above.

Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.

Drawings

FIG. 1 is an application scenario of the prior art;

FIG. 2 is another application scenario of the prior art;

FIG. 3 is a schematic flow chart diagram of an ACC-based vehicle control method provided herein;

FIG. 4 is an application scenario of multiple sensors provided herein;

FIG. 5 is an example of an ACC-based vehicle control method provided herein;

fig. 6 is a schematic structural diagram of an ACC-based vehicle control device provided by the present application.

Detailed Description

The embodiments of the present application will be described below with reference to the drawings.

The terms "first" and "second," and the like in the description and claims of this application and in the drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

As used in this specification, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between 2 or more computers. In addition, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from two components interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).

First, some terms in the present application are explained so that those skilled in the art can understand that:

(1) SLAM: simultaneous Localization and Mapping, instantaneous Localization and Mapping, or concurrent Mapping and Localization.

(2) MCU: microcontroller Unit, a micro control Unit.

To facilitate understanding of the embodiments of the present application, an ACC-based vehicle control system provided by the embodiments of the present application will be described first, including:

the system comprises a sensor device, a monitoring device and a control device, wherein the sensor device is provided with a plurality of sensors which monitor the surrounding environment of a target vehicle and acquire environmental data; specifically, the sensor device is configured to exchange sensor models to adapt to the selection of different sensor suppliers, the number and the positions of the sensors can be configured, and driving environment models of different application scenes can be realized.

Further, as shown in fig. 3, the sensor device includes a plurality of millimeter wave radar units, an image pickup unit, an alarm unit, and the like; the millimeter wave radar units are arranged at the front part, the A column, the B column, the side face, the rearview mirror and other positions of the body of the target vehicle, the beams of the millimeter wave radar units form a large-scale beam set capable of covering the whole vehicle surrounding environment, the surrounding environment of the target vehicle is detected, and the millimeter wave radar units are used for monitoring the surrounding environment of the target vehicle in real time; the camera shooting unit comprises a plurality of long-distance cameras and a plurality of short-distance cameras; an ACC for controlling an operation state of a target vehicle; the alarm unit is used for timely early warning the potential risk according to the monitoring data so as to reduce the influence of the potential risk.

A control device comprising at least one processor, for example: the control device is respectively connected with the ACC and the sensors and is used for receiving the environmental data sent by the sensor devices and fusing the environmental data to obtain a fusion result; acquiring a lane line based on the fusion result, and detecting the lane line to obtain a detection result; then controlling the running state of the ACC based on the detection result;

the sensor device, the ACC and the control device are installed inside the target vehicle, and the sensor device and the ACC perform data interaction with the control device on the basis of a network, so that the control device can control the sensor device and the ACC on the basis of the network; for example: the control device receives feedback data of the plurality of sensors based on the network, processes the feedback data and generates a control signal, and then sends the control signal to control the operating state of the ACC based on the control signal, for example: opening and closing and the like; furthermore, the control device may also send control signals to the plurality of sensors for controlling the operating states of the plurality of sensors based on the control signals.

Wherein the target vehicle may be an intelligent vehicle; in particular, the smart vehicle may be set to a fully or partially autonomous driving mode, e.g., the smart vehicle may control itself while in the autonomous driving mode; in the autonomous driving mode, the smart vehicle may be set to operate without human interaction.

In an actual application scene, real-time monitoring is carried out on the surrounding environment of the target vehicle in real time based on the plurality of millimeter wave radar units and the camera unit, and the real-time environment data of the surrounding environment of the target vehicle are obtained in real time; and using the environment data for map construction of the surroundings of the target vehicle; the camera shooting unit can obtain the distance between the obstacle and the target vehicle based on the depth camera and directly generate available environment data; or image acquisition is carried out based on a monocular, binocular or fisheye camera, the acquired image is further processed, and then the distance between the obstacle of the surrounding environment of the target vehicle and the target vehicle is indirectly acquired.

As shown in fig. 4, an embodiment of the present application provides an ACC-based vehicle control method, applied to the above system, including:

step S1: acquiring environmental data of a target vehicle, and fusing the environmental data to obtain a fusion result;

specifically, the acquiring of the environmental data of the target vehicle and the fusing of the environmental data include, before the obtaining of the fusion result:

In practical application scenarios, the angles obtained by a single sensor all have disadvantages, such as: some sensors may have good dynamic precision and some sensors may have good static precision, so that the data acquired by the sensors are processed based on a complementary filtering algorithm to improve the precision of the whole system in the acquisition process.

In particular, the complementary filtering algorithm is implemented based on complementary filters that pass through different filters (high-pass or low-pass, complementary) according to the sensor characteristics, and then add up to obtain the signal of the entire frequency band.

Further, acquiring environment data of the target vehicle, and fusing the environment data to obtain a fusion result, including:

Specifically, since different suppliers provide different types of sensors, in order to fuse data of the different types of sensors, raw data acquired by the sensors may not be fused, and sensor data which is preprocessed and integrated with a tracking algorithm may be used.

Further, processing the data obtained by the sensor by adopting a tracking algorithm to obtain a tracking target, and processing the tracking target by utilizing a fusion algorithm to obtain fused data; or the raw data of all the sensors are processed together, such as the position and the direction of the vehicle in the camera image, the distance and the distance change rate of the millimeter wave radar, so that the information provided by all the sensors can be used for data fusion.

Further, in the embodiments of the present application, the fusion algorithm mainly involves matching model design, deep learning network, error function design, relevant and irrelevant feature learning, minimum error function design, adaptive weight adjustment design, and optimization function design.

The method comprises the steps of designing a matching model, and performing deep correlation fusion on environmental data by utilizing the high-level semantic abstract characteristics of a deep learning network, so as to reduce the data deviation and improve the accuracy of a fusion result; the weight is dynamically updated and adjusted through a minimum error function and self-adaptive weight adjustment, and the environment data is subjected to parameter-free incremental fusion division, so that the efficiency of a fusion algorithm is improved; and the integral optimization adjustment is carried out through relevant and irrelevant feature learning and optimization function design, so that the precision of a fusion result is improved.

In practical application scenarios, for example: an incomplete multi-modal data fusion algorithm based on deep semantic matching can be adopted; by utilizing the high-level semantic abstract characteristics of a deep learning network, a uniform depth model for coupling modal private deep network and incomplete modal shared feature learning is designed, the deep correlation fusion of incomplete multi-modal data is realized, and the semantic deviation of modal shared features is reduced; based on the geometric characteristics of the modal space, a regularization factor of a local invariant graph is designed, multi-modal shared features and original modal features in a subspace are coupled, and the accuracy of a fusion result is further improved; and the incomplete multi-mode data is effectively related and matched through deep semantic abstraction, so that the precision of a fusion result is ensured.

Step S2: carrying out map construction on the surrounding environment of the target vehicle based on the fusion result to obtain lane line data;

specifically, the map building of the surrounding environment of the target vehicle based on the fusion result to obtain lane line data includes:

obtaining a construction result;

Further, obtaining the construction result includes:

According to the embodiment of the application, the map of the surrounding environment of the target vehicle is constructed based on the fusion result, and the map is used for accurately acquiring lane line data.

Step S3: detecting the lane line based on the lane line data;

step S4: if the lane line is complete but the running of the vehicle interference ACC exists, performing first adjustment on the running state of the target vehicle, and starting the ACC; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC.

Wherein, there is the operation of vehicle interference target vehicle, specifically can be: the target vehicle is quickly approached, and a lane line and the like of the target vehicle are shielded;

the first adjustment may be: stopping or turning, etc.;

the second adjustment may be: deceleration or stopping, etc.

It should be noted that the first adjustment and the second adjustment mentioned in the present application are control strategies generated for the target vehicle, and there is no substantial difference.

Specifically, according to the embodiment of the application, before the ACC is started to control the running state of the target vehicle, the safety of the surrounding environment is determined based on the environment data, and after the surrounding environment is determined to be in accordance with the ACC, the ACC is started, so that the safety of the ACC for controlling the target vehicle is increased, and the risk of ACC control is reduced.

Further, the detecting the lane line based on the lane line data includes:

That is, the current surroundings of the target vehicle are suitable for turning on the ACC to control the target vehicle without any other risk.

As shown in fig. 5, the above-mentioned embodiment of the present application can be implemented based on the following implementation manners:

1) detecting the lane line, judging whether the lane line is complete, and if the lane line is complete, skipping to the step 2); if the lane line is not complete, skipping to the step 5);

2) judging whether a vehicle is fast approaching the lane line or not, and if the vehicle is fast approaching the lane line, jumping to the step 4); if no vehicle is fast close to the lane line, jumping to the step 5);

3) controlling the target vehicle to stop or controlling the target vehicle to turn to avoid the obstacle, and then starting the ACC;

4) controlling the target vehicle to decelerate or controlling the target vehicle to stop to avoid rear-end collision with other vehicles, and then starting the ACC;

5) the ACC is started.

As shown in fig. 6, an embodiment of the present application also provides an ACC-based vehicle control apparatus 600 including:

the fusion module 601 is configured to obtain environment data of a target vehicle, and fuse the environment data to obtain a fusion result;

a construction module 602, configured to perform map construction on the surrounding environment of the target vehicle based on the fusion result, and acquire lane line data;

a detection module 603, configured to detect the lane line based on the lane line data;

an adjusting module 604, configured to perform a first adjustment on an operation state of the target vehicle and start the ACC if the lane line is complete but there is an operation of a vehicle interfering with the ACC; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC.

Optionally, the obtaining of the environmental data of the target vehicle and the fusion of the environmental data include:

Optionally, the obtaining of the environmental data of the target vehicle and the fusing of the environmental data to obtain a fusion result includes:

and fusing the tracking targets based on a fusion algorithm to obtain fusion data.

Optionally, the map construction of the surrounding environment of the target vehicle based on the fusion result to obtain lane line data includes:

obtaining a construction result;

Optionally, obtaining the construction result includes:

Optionally, the detecting the lane line based on the lane line data includes:

Embodiments of the present application also provide an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the method as described above when executing the computer program.

Embodiments of the present application also provide a computer-readable storage medium comprising a stored computer program, wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the method as described above.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to the related descriptions of other embodiments.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a storage medium, and including several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, and may specifically be a processor in the computer device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. The storage medium may include: a U-disk, a removable hard disk, a magnetic disk, an optical disk, a Read-Only Memory (ROM) or a Random Access Memory (RAM), and the like.

The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.

Claims

1. An ACC-based vehicle control method, comprising:

carrying out map construction on the surrounding environment of the target vehicle based on the fusion result to obtain lane line data; the map construction of the surrounding environment of the target vehicle based on the fusion result to obtain lane line data includes: performing map construction on the surrounding environment of the target vehicle based on a SLAM algorithm and the fusion result to obtain a construction result;

acquiring a lane line based on the lane line data, and detecting the lane line;

if the lane line is complete but the running of the vehicle interference ACC exists, performing first adjustment on the running state of the target vehicle, and starting the ACC; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC;

wherein the presence of the vehicle interferes with operation of the ACC, comprising: rapidly approaching the target vehicle or blocking the lane line driven by the target vehicle;

the first adjusting comprises: stopping or turning; the second adjusting comprises: decelerating or stopping.

2. The method according to claim 1, wherein the obtaining environmental data of the target vehicle and fusing the environmental data before obtaining the fusion result comprises:

3. The method of claim 1, wherein obtaining environmental data of a target vehicle and fusing the environmental data to obtain a fused result comprises:

4. The method according to claim 1, wherein the mapping the surroundings of the target vehicle based on the fusion result to obtain lane line data comprises:

obtaining a construction result;

5. The method of claim 1, wherein the obtaining a lane line based on the lane line data and detecting the lane line comprises:

6. An ACC-based vehicle control apparatus, comprising:

the construction module is used for carrying out map construction on the surrounding environment of the target vehicle based on the fusion result to obtain lane line data; the map construction of the surrounding environment of the target vehicle based on the fusion result to obtain lane line data includes: performing map construction on the surrounding environment of the target vehicle based on a SLAM algorithm and the fusion result to obtain a construction result;

the detection module is used for acquiring a lane line based on the lane line data and detecting the lane line; the adjusting module is used for performing first adjustment on the running state of the target vehicle and starting the ACC if the lane line is complete but the running of the ACC is interfered by the vehicle; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC;

wherein the presence of the vehicle interferes with operation of the ACC, comprising: rapidly approaching the target vehicle or blocking the lane line traveled by the target vehicle;

the first adjusting comprises: stopping or turning; the second adjusting comprises: slowing down or stopping.

7. An ACC-based vehicle control system, comprising:

an ACC for controlling an operation state of a target vehicle;

the control device is respectively connected with the ACC and the sensors and is used for receiving the environmental data sent by the sensor devices and fusing the environmental data to obtain a fusion result; acquiring a lane line based on the fusion result, and detecting the lane line to obtain a detection result; then controlling the running state of the ACC based on the detection result; the controlling the operating state of the ACC based on the detection result includes: if the lane line is complete but the running of the vehicle interference ACC exists, performing first adjustment on the running state of the target vehicle, and starting the ACC; or if the lane line is incomplete, performing second adjustment on the running state of the target vehicle, and starting the ACC;

8. An electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the method of any of claims 1 to 5 when executing the computer program.

9. A computer-readable storage medium, comprising a stored computer program, wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the method of any of claims 1-5.