CN115923842A

CN115923842A - Method, apparatus, electronic device and storage medium for controlling autonomous vehicle

Info

Publication number: CN115923842A
Application number: CN202211662547.9A
Authority: CN
Inventors: 马晚同
Original assignee: Apollo Intelligent Connectivity Beijing Technology Co Ltd; Apollo Zhixing Technology Guangzhou Co Ltd
Current assignee: Apollo Intelligent Connectivity Beijing Technology Co Ltd; Apollo Zhixing Technology Guangzhou Co Ltd
Priority date: 2022-12-23
Filing date: 2022-12-23
Publication date: 2023-04-07

Abstract

The present disclosure provides a method, apparatus, electronic device, and storage medium for controlling an autonomous vehicle, relates to the technical field of automatic driving, the technical problems that in the prior art, the degree of intelligence of an automatic driving process is low and user experience is poor due to the fact that external operation is carried out manually to help the automatic driving vehicle to get rid of trouble are solved at least. The specific implementation scheme is as follows: receiving a request message from an autonomous vehicle, wherein the request message is triggered by road condition information within a preset range around the autonomous vehicle; generating a control instruction based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing driving operation; and issuing the control command to the automatic driving vehicle so that the automatic driving vehicle can carry out lane change driving based on the control command.

Description

Method, apparatus, electronic device and storage medium for controlling autonomous vehicle

Technical Field

The present disclosure relates to the field of autonomous driving technologies, and in particular, to a method and an apparatus for controlling an autonomous vehicle, an electronic device, and a storage medium.

Background

As the amount of automobile keeping in various places increases, the high number of vehicles involved, and the wide variety of vehicles, has resulted in a dramatic increase in the complexity of the transportation system. Autonomous vehicles are important participants in current traffic systems. Autonomous vehicle based on environmental awareness data and presets when making automated driving decisions based on a variety of driving rules, travel restriction dilemma caused by complex road conditions in a traffic system is often encountered. For example, in a non-congested road segment, since the vehicle detects that an obstacle exists in each lane in the current driving direction and the lane line is a solid line, the vehicle may be stranded in performing the self-restraint stop driving.

In the related art, in order to solve the above problems, the above-described restricted travel dilemma of autonomous vehicles is addressed primarily by methods that rely on manual drive takeover or obstacle removal. However, this method is less intelligent, it is difficult to satisfy the demand for automatic driving of the vehicle.

In view of the above there is a problem that, no effective solution has been proposed so far.

Disclosure of Invention

The disclosure provides a method, a device, electronic equipment and a storage medium for controlling an automatic driving vehicle, which are used for at least solving the technical problems of low intelligent degree and poor user experience in the automatic driving process caused by the fact that external operation is carried out by depending on manpower to help the automatic driving vehicle to get rid of difficulties.

In accordance with one aspect of the present disclosure, there is provided a method of controlling an autonomous vehicle, comprising: receiving a request message from an autonomous vehicle, wherein the request message is triggered by road condition information in a preset range around the autonomous vehicle, the request message is used for requesting a driving mode to be executed by the autonomous vehicle, the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range, and the road condition information meets a first preset condition, and the first preset condition comprises: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance; generating a control instruction based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing driving operation; and issuing the control command to the automatic driving vehicle so that the automatic driving vehicle can carry out lane change driving based on the control command.

According to another aspect of the present disclosure, there is provided a method of controlling an autonomous vehicle, comprising: acquiring road condition information in a preset range around the automatic driving vehicle, wherein the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range; responding to the road condition information to meet preset conditions, and sending a request message to a server, wherein the preset conditions comprise: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, the preset type object is used for preventing the automatic driving vehicle from continuing to advance, and the request message is used for requesting the driving mode to be executed of the automatic driving vehicle from the server; receiving a control instruction corresponding to a request message issued by a server, wherein the control instruction is used for controlling an automatic driving vehicle to execute lane changing driving operation; and performing lane change driving based on the control instruction.

According to still another aspect of the present disclosure, there is also provided an apparatus for controlling an autonomous vehicle, including: the system comprises a receiving module and a detection module, wherein the receiving module is used for receiving a request message from an automatic driving vehicle, the request message is triggered by road condition information in a preset range around the automatic driving vehicle, the request message is used for requesting a driving mode to be executed of the automatic driving vehicle, the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range, the road condition information meets a first preset condition, and the first preset condition comprises: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance; the generation module is used for generating a control instruction based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing running operation; and the control module is used for issuing the control command to the automatic driving vehicle so that the automatic driving vehicle can carry out lane change driving based on the control command.

According to still another aspect of the present disclosure, there is also provided an apparatus for controlling an autonomous vehicle, including: the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring road condition information in a preset range around an automatic driving vehicle, and the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range; the sending module is used for responding to the condition information meeting the preset conditions and sending a request message to the server, wherein the preset conditions comprise: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, the preset type object is used for preventing the automatic driving vehicle from continuing to advance, and the request message is used for requesting the driving mode to be executed of the automatic driving vehicle from the server; the receiving module is used for receiving a control instruction corresponding to the request message sent by the server, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing driving operation; and the control module is used for performing lane change driving based on the control instruction.

According to still another aspect of the present disclosure, there is also provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of controlling an autonomous vehicle as set forth in the present disclosure.

According to yet another aspect of the present disclosure, there is also provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of controlling an autonomous vehicle presented by the present disclosure.

According to yet another aspect of the disclosure, a computer program product is also provided, comprising a computer program which, when executed by a processor, performs the method of controlling an autonomous vehicle as set forth in the disclosure.

In the disclosure, a request message from an autonomous vehicle is received, where the request message is triggered by road condition information within a preset range around the autonomous vehicle, the request message is used to request a driving mode to be executed by the autonomous vehicle, the road condition information is used to determine a type of a lane line and a type of a detection object within the preset range, and the road condition information satisfies a first preset condition, where the first preset condition includes: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance; generating a control instruction further based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing running operation; and issuing the control instruction to the automatic driving vehicle so that the automatic driving vehicle performs lane change driving based on the control instruction.

It is easily understood that the technical solution provided by the present disclosure can be operated in the service end to automatically receive and respond to the request message sent by the autonomous vehicle, and generate a control instruction for the autonomous vehicle to help the autonomous vehicle to make lane change driving, so as to get out of the predicament of being blocked from continuing to travel. Therefore, this disclosure has reached through the automatic purpose that generates control command control autopilot vehicle lane change and goes in order to break away from the predicament that is hindered to continue to advance, has realized improving autopilot vehicle's intelligent degree of getting rid of poverty automatically, has promoted user experience's technological effect, has solved among the prior art because rely on the manual work to carry out the technical problem that the help autopilot vehicle gets rid of poverty and lead to that the intelligent degree of autopilot process is low, user experience is poor.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a schematic diagram of an autonomous vehicle escape method according to the prior art;

FIG. 2 is a schematic diagram of another autonomous vehicle escape method according to the prior art;

FIG. 3 is a block diagram of a hardware configuration of a computer terminal (or mobile device) for implementing a method of controlling an autonomous vehicle according to an embodiment of the present disclosure;

FIG. 4 is a flow chart of a method of controlling an autonomous vehicle provided in accordance with an embodiment of the disclosure;

FIG. 5 is a schematic illustration of an alternative process for controlling an autonomous vehicle according to an embodiment of the disclosure;

FIG. 6 is a schematic illustration of an alternative driveable vehicle lane change turning process according to an embodiment of the disclosure;

FIG. 7 is a flow chart of another method of controlling an autonomous vehicle provided in accordance with an embodiment of the disclosure;

FIG. 8 is a schematic diagram of an alternative airport autonomous vehicle control system, in accordance with an embodiment of the present disclosure;

fig. 9 is a block diagram of an apparatus for controlling an autonomous vehicle according to an embodiment of the present disclosure;

FIG. 10 is a block diagram illustrating an alternative apparatus for controlling an autonomous vehicle in accordance with an embodiment of the present disclosure;

fig. 11 is a block diagram of an alternative apparatus for controlling an autonomous vehicle according to an embodiment of the present disclosure.

Detailed Description

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the disclosure described herein are capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Currently, autonomous vehicles often encounter a restricted driving dilemma for the following reasons: based on various road condition information detected by the automatic driving vehicle, when the automatic driving vehicle makes an automatic driving decision according to a plurality of driving constraint conditions, the automatic driving vehicle can stop driving by self constraint and cannot get rid of difficulties automatically. For example, when the autonomous vehicle detects that an obstacle exists in front of the current lane, the original decision is to change lane driving, but the left lane line and the right lane line of the current lane are both solid lines, and the final decision of the autonomous vehicle is to stop driving according to traffic regulation constraint. In this case, the autonomous vehicle will remain on-site waiting until the detected traffic information can be passed driving decisions.

In the prior art, for the above-mentioned restricted driving dilemma of the automatic driving vehicle, there are two methods mainly adopted:

first, manual override of driving allows an autonomous vehicle to escape. Fig. 1 is a schematic diagram of an automated driving vehicle escaping method according to the prior art, as shown in fig. 1, when the automated driving vehicle is in a restricted driving predicament (for example, an obstacle is thrown in front of a lane and the left and right lane lines of the current lane are solid lines), a vehicle-mounted security officer takes over the automated driving vehicle and makes a detour by changing the lane according to a road evacuation rule (for example, an instruction of following traffic police).

Second, manual removal of obstacles traps autonomous vehicles. Fig. 2 is a schematic diagram of another automated driving vehicle escaping method according to the prior art, as shown in fig. 2, when the automated driving vehicle is in a restricted driving predicament (such as throwing an obstacle in front of a lane and making both left and right lane lines of the current lane solid), the on-board safety personnel manually removes the obstacle to enable the automated driving vehicle to pass through.

However, both of the above two methods for automatically driving the vehicle to get rid of the trouble rely on manual external operation (driving take over or manual dredging), and the degree of intelligence is low, so that the requirements of automatic driving are difficult to meet.

Therefore, the automatic driving vehicle escaping method without relying on manual external operation is provided, the intelligent degree of the automatic driving vehicle is improved, and the user experience is improved.

In accordance with an embodiment of the present disclosure, there is provided a method of controlling an autonomous vehicle, it being noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system, such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than presented herein.

The method embodiments provided by the embodiments of the present disclosure may be executed in a mobile terminal, a computer terminal or similar electronic devices. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein. Fig. 3 is a hardware configuration block diagram of a computer terminal (or mobile device) for implementing a method of controlling an autonomous vehicle according to an embodiment of the present disclosure.

As shown in fig. 3, the computer terminal 300 includes a computing unit 301 that can perform various appropriate actions and processes according to a computer program stored in a Read-Only Memory (ROM) 302 or a computer program loaded from a storage unit 308 into a Random Access Memory (RAM) 303. <xnotran>

RAM

303 , 300 . </xnotran> The calculation unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.

A number of components in the computer terminal 300 are connected to the I/O interface 305, including: an input unit 306 such as a keyboard, a mouse, or the like; an output unit 307 such as various types of displays, speakers, and the like; a storage unit 308 such as a magnetic disk, optical disk, or the like; and a communication unit 309 such as a network card, modem, wireless communication transceiver, etc. The communication unit 309 allows the computer terminal 300 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.

The computing unit 301 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing Unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and the like. The computing unit 301 performs the method of controlling an autonomous vehicle described herein. For example, in some embodiments, the method of controlling an autonomous vehicle may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto the computer terminal 300 via the ROM 302 and/or the communication unit 309. When the computer program is loaded into RAM 303 and executed by computing unit 301, one or more steps of the method of controlling an autonomous vehicle described herein may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the method of controlling the autonomous vehicle in any other suitable manner (e.g., by means of firmware).

Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Parts (ASSPs), system On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, data and instructions may be received from, and transmitted to, a storage system, at least one input device, and at least one output device.

<xnotran> , , 3 ( ), ( ), . </xnotran> It should be noted that fig. 3 is only one example of a particular specific example and is intended to illustrate the types of components that may be present in the electronic device described above.

In the operating environment described above, the present disclosure provides a method of controlling an autonomous vehicle as shown in fig. 4, which may be performed by a computer terminal or similar electronic device as shown in fig. 3. FIG. 4 is a flow chart of a method of controlling an autonomous vehicle provided in accordance with an embodiment of the disclosure. As shown in fig. 4, the method may include the steps of:

step S40, receiving a request message from the automatic driving vehicle, wherein the request message is triggered by road condition information in a preset range around the automatic driving vehicle, the request message is used for requesting a driving mode to be executed by the automatic driving vehicle, the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range, and the road condition information meets a first preset condition, and the first preset condition comprises: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance;

the automatic driving vehicle is provided with a video camera, a radar sensor, a laser range finder and other devices to acquire road condition information within a preset range around the automatic driving vehicle. The preset range is a range that can affect the driving behavior of the autonomous vehicle, which is specified in advance by a technician. The road condition information is used for determining the type of the lane line and the type of the detection object within the preset range.

The types of lane lines described above include, but are not limited to: lane center lines (e.g., yellow dashed line, yellow solid line, yellow double solid line, and yellow dotted solid line), lane boundary lines (e.g., white dashed line, white solid line), lane edge lines (e.g., solid line edge line, dashed line edge line), stop lines (e.g., white horizontal solid line), deceleration passing lines (e.g., white double dashed line), pedestrian crossing lines. The types of the detection objects include, but are not limited to: roads, infrastructure traffic facilities pedestrian obstacles and other vehicles.

The request message is triggered by the road condition information within the preset range around the automatic driving vehicle, that is, when the road condition information collected by the automatic driving vehicle meets the first preset condition, the request message is sent out, and the request message is used for requesting the server to acquire the current running mode to be executed. The first preset condition includes: the type of the lane line is a preset type lane line, and the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process; the type of the detection object is a preset type object, and the preset type object is used for preventing the automatic driving vehicle from continuing to travel.

It will be readily appreciated that the first predetermined condition described above is indicative of the autonomous vehicle being currently in a restricted driving dilemma. For example, when the type of the lane line is a solid lane boundary (i.e., a white solid line) and the type of the detection object is a pedestrian obstacle (it is assumed here that the lane line is a left and right lane boundary of the current lane and the detection object is located in the area ahead of the current lane), it is described that the autonomous vehicle is constrained to "stop traveling" and "not allow lane change", that is, the autonomous vehicle is currently in a restricted travel predicament.

And the server is used for receiving the request message sent by the automatic driving vehicle and responding to the request message to make a decision for the automatic driving vehicle to obtain a running mode to be executed. The server may be an autonomous vehicle control platform deployed on a server, and the server may be an independent server, a distributed server cluster, or a cloud server. The connection mode between the automatic driving vehicle and the service end is internet of things protocol (such as MQTT protocol) communication connection or wireless communication network connection, and particularly can be mobile communication network connection (such as 3G, 4G, 5G, 6G and the like).

It is easily understood that, through the above step S40, when the autonomous vehicle is in the restricted driving predicament, one possible way to get rid of the predicament is to send a request message to the server that establishes a communication connection in advance to acquire the driving style to be executed. In this process, the driving mode decision based on the road condition information within the preset range around the autonomous vehicle is completed by the server, which may refer to further description of the embodiments of the present disclosure.

Step S42, generating a control instruction based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane-changing driving operation;

and when the server receives a request message sent by the automatic driving vehicle, generating the control instruction based on the request message. The control command is used for controlling the autonomous vehicle to execute lane-changing running operation, and the lane-changing running operation can help the autonomous vehicle to get out of the restricted running predicament.

Specifically, the generating of the control instruction based on the request message further includes other method steps, which may refer to further descriptions of the embodiments of the present disclosure hereinafter, and are not described herein again.

Step S44, control instructions are sent to the automatic driving vehicle, so that the autonomous vehicle performs lane change traveling based on the control instruction.

<xnotran> S44 , . </xnotran> And the automatic driving vehicle receives and automatically executes the control command issued by the server side to carry out lane change driving. The lane change driving is a lane change detour behavior allowed by a road dispersion rule (for example, temporary lane-crossing and detouring by a solid line when an emergency accident occurs in front allowed by a traffic rule).

It is easily understood that, compared with the methods provided by the prior art, the method for controlling an autonomous vehicle provided by the embodiment of the present disclosure can perform automatic vehicle control by performing message interaction with a service, the decision of the running mode to be executed is automatically carried out by the server side under the condition that external operation is not needed to be carried out manually, the trouble of running of the automatic driving vehicle in a constraint mode is helped, the intelligent degree of the whole process is high, and the user experience can be improved.

According to the present disclosure, in the above steps 40 to 44, a request message from the autonomous vehicle is received, where the request message is triggered by road condition information within a preset range around the autonomous vehicle, the request message is used to request a driving mode to be executed by the autonomous vehicle, the road condition information is used to determine a type of a lane line and a type of a detection object within the preset range, and the road condition information satisfies a first preset condition, where the first preset condition includes: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance; generating a control instruction further based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing running operation; and issuing the control instruction to the automatic driving vehicle so that the automatic driving vehicle performs lane change driving based on the control instruction.

The method for controlling the automatic driving vehicle according to the embodiment of the present disclosure may be applied to, but not limited to, an application scenario for helping the automatic driving vehicle escape in an area such as an urban road, a hospital, a logistics park, an airport, a school, and the like. The technical solution of controlling the autonomous vehicle according to the embodiment of the present disclosure is further described below by taking a trapping scene in which the autonomous vehicle is blocked by a boundary between a left solid lane and a right solid lane and an obstacle and falls into a restricted driving predicament in an airport as an example.

FIG. 5 is a schematic diagram of an alternative process for controlling an autonomous vehicle according to an embodiment of the disclosure. A plurality of running autonomous vehicles in an airport and an airport autonomous control platform (i.e., a server) are connected (e.g., local area network connection, mobile communication network connection, mobile hotspot connection, bluetooth connection, etc.). When the autonomous vehicle is in a restricted driving predicament, by controlling the process of automatically driving the vehicle as shown in figure 5, automated vehicle egress is facilitated by the airport automated control platform without the need for external manipulation by a technician.

As shown in fig. 5, when the autonomous vehicle is in a restricted driving predicament, the site conditions (usually, traffic information within a preset range around the autonomous vehicle) are summarized first, and if the current site conditions cannot be solved by the autonomous vehicle, a trap-free signal is sent, where the trap-free signal is a trap-free request message sent to the airport autonomous driving control platform. <xnotran> , . </xnotran>

As shown in fig. 5, after the autonomous vehicle sends the signal for getting out of trouble, it is continuously monitored whether the autonomous driving control platform of the airport sends a return signal. When the automatic driving vehicle receives a return signal of an airport automatic driving control platform, the automatic driving vehicle is controlled to change lanes according to a control command in the return signal, and a corresponding escaping program is executed, wherein the escaping program can be determined from candidate programs pre-stored in the automatic driving vehicle by the control command, and the escaping program is used for controlling the automatic driving vehicle to synchronously perform other auxiliary operations (such as vehicle indicator light flashing, whistling, detecting whether the vehicle is successfully escaped from the restricted driving predicament at present, and the like) corresponding to the lane changing operation.

As shown in fig. 5, after the autonomous vehicle completes the lane change operation and performs the lane escape procedure, if it is detected that the lane escape restriction driving difficulty is successfully overcome and the current road condition information allows the vehicle to return to the default lane before the lane change, the autonomous vehicle is controlled to return to the model lane for continuous driving.

It is easily understood that, through the process of controlling the autonomous vehicle as shown in fig. 5, it is possible to help the autonomous vehicle to automatically escape from the restricted driving dilemma in the scene of getting out of trouble of the unmanned freight vehicle (such as a baggage truck, an autonomous ferry vehicle, etc.) in the airport without additional auxiliary operations (such as taking over driving, removing obstacles, etc.) performed by airport security personnel, thereby saving the manpower cost for the airport, improving the freight efficiency, and improving the intelligence degree of the airport vehicle.

As an alternative to the above-described embodiment, in the above-mentioned step S42, the step, generating a control instruction based on the request message, further comprising the method steps of:

in step S421, in response to the request message, acquiring road information reported by an automatic driving vehicle in the driving process detecting object information of an object and vehicle information of an autonomous vehicle;

step S422, obtaining lane change information by using the object information and the vehicle information, wherein the lane change information is that the right-angle bend of the automatic driving vehicle passes through the narrowest road width in the lane change process;

step S423, based on the road information, the object information and the lane change information, and generating a control instruction.

And after receiving the request message, the server acquires the road information of the automatic driving vehicle in the driving process, the object information of the detection object and the vehicle information of the automatic driving vehicle based on the request message. The road information is used for representing the road data where the automatic driving vehicle is located currently, such as road width, the number of lanes in the same direction of the road and the like. The object information of the detection object is used to represent object data of the detection object currently detected by the autonomous vehicle, such as the type of the obstacle, the size (width, height, etc.) of the obstacle, and the like. The vehicle information of the autonomous vehicle is used to represent vehicle structure data of the autonomous vehicle corresponding to the request message, such as a vehicle body size (length, width, height, etc.), a wheel base, a maximum steering angle, and the like.

To assist the autonomous vehicle in making decisions about the mode of travel to be performed, and the server side calculates the lane change information through a geometric relationship according to the object information and the vehicle information reported by the automatic driving vehicle. The lane change information is that the right angle bend of the automatic driving vehicle passes through the narrowest road width in the lane change process. Based on the lane change information, it is possible to determine whether the autonomous vehicle can safely change the lane in the current lane.

It is easily understood that the lane change information is that the right angle bend of the autonomous vehicle passes through the narrowest road width during the lane change. The lane change information can also be understood as the narrowest road width occupied by the automatic driving vehicle in the lane change process. When the decision of the driving mode to be executed is made for the automatic driving vehicle, if the road where the automatic driving vehicle is located is found to provide the road space which is not less than the narrowest road width so as to support the automatic driving vehicle to change the lane, it is possible to determine based on the road information, the object information and the lane change information, and generating a control instruction.

And generating a control command based on the road information, the object information and the lane change information. The control command is used for controlling the automatic driving vehicle to execute lane change driving operation, and it is easy to understand that the control command is generated to help the automatic driving vehicle to get rid of the current restricted driving predicament when the conclusion that safe lane change is possible can be obtained based on the road information, the object information and the lane change information.

As an alternative embodiment, in step S422, the method for acquiring lane change information by using the object information and the vehicle information further comprises the following method steps:

step S4221, acquiring a center position of the detection object from the object information;

step S4222, determining a first parameter, a second parameter, a third parameter and a fourth parameter based on the center position and the vehicle information, wherein the first parameter is the maximum steering angle of a front outer wheel of the automatic driving vehicle in the lane changing process, the second parameter is the minimum turning radius of the automatic driving vehicle in the lane changing process, the third parameter is the radius of the innermost moving track of the automatic driving vehicle close to the detection object in the lane changing process, and the fourth parameter is determined based on the length between a front bumper and the front outer wheel of the automatic driving vehicle;

step S4223, obtaining lane change information by using the first parameter, the second parameter, the third parameter, and the fourth parameter.

For example, when an autonomous vehicle is caught by a left-right solid lane boundary and an obstacle in front and falls into a restricted travel trouble in an airport, the position and size of the obstacle and vehicle information of the autonomous vehicle are important criteria for whether the autonomous vehicle can currently perform a lane change and trouble removal operation.

Specifically, the center position of an obstacle (i.e., a detection target) is acquired using target information of the obstacle. For example, the center position of a spherical obstacle may be considered as the center position or the projected position of the center position on the ground, and the center position of an irregular obstacle may be considered as the geometric center position or the projected position of the geometric center on the ground.

The first parameter is the maximum steering angle of the front outer wheel of the automatic driving vehicle in the lane changing process, and when the vehicle keeps the maximum steering angle of the front outer wheel to turn, the lane changing process of the vehicle can occupy the minimum road space.

The second parameter is a minimum turning radius of the autonomous vehicle during the lane change. The second parameter may be determined by the maximum steering angle of the front outer wheel.

The third parameter is a radius of an innermost moving track of the automatic driving vehicle approaching the detection object in the lane changing process, and the third parameter is used for determining a condition that the automatic driving vehicle does not collide with the detection object in the lane changing process.

The fourth parameter is the difference between the radius of the outermost moving track of the automatic driving vehicle in the lane changing process and the minimum turning radius, and the outermost moving track is the moving track of the outermost end point of the front bumper of the vehicle in the lane changing process. The fourth parameter is determined based on a length between a front bumper and a front outer wheel of the autonomous vehicle.

Further, the first parameter, the second parameter, the third parameter, and the fourth parameter are determined based on the center position of the detection object and the vehicle information. And acquiring the right angle bend passing the narrowest road width of the automatic driving vehicle in the lane changing process by calculation by using the first parameter, the second parameter, the third parameter and the fourth parameter, namely lane changing information.

As an optional implementation manner, in step S4222, the determining the first parameter, the second parameter, the third parameter, and the fourth parameter based on the center position and the vehicle information further includes the following steps:

step S4311, obtaining a first axis and a second axis of the autonomous vehicle from the vehicle information, wherein the first axis is a front outer wheel axis of the autonomous vehicle, and the second axis is a rear outer wheel axis of the autonomous vehicle;

in a step S4312, the operation is performed, determining a first parameter by using the center position, the first axis and the second axis;

step S4313, determining a second parameter, a third parameter, and a fourth parameter based on the first parameter and the vehicle information.

Still taking the scenario of controlling the autonomous vehicle to get out of the restricted driving dilemma in the airport as an example, the first parameter, the second parameter, the third parameter, and the fourth parameter can be determined using the vehicle structure information of the autonomous vehicle and the center position of the obstacle in the restricted driving dilemma.

Fig. 6 is a schematic diagram of an alternative turning process of lane changing of an autonomous vehicle according to an embodiment of the disclosure, where as shown in fig. 6, O is a center position of an obstacle, and a rectangular plane coordinate system is established with O point as a coordinate origin. A. B represents the front wheel position of the autonomous vehicle, and C, D represent the rear wheel position of the autonomous vehicle. Based on vehicle configuration information of an autonomous vehicle in an airport, coordinates of a front outer wheel axis of the autonomous vehicle (i.e., the first axis, i.e., the axis of the a wheel) are determined, and coordinates of a rear outer wheel axis of the autonomous vehicle (i.e., the second axis, i.e., the axis of the D wheel) are determined. Further, coordinate calculation is performed by using the axis coordinate of the wheel a and the axis coordinate of the wheel D, and the maximum steering angle of the front outer wheel (i.e., the first parameter, which is denoted as α) of the autonomous vehicle during the lane change process is determined, that is, the first parameter is determined by using the O point position, the first axis, and the second axis.

As shown in fig. 6, the minimum turning radius R2 of the autonomous vehicle during the lane change (i.e., the above-described second parameter) is determined by calculation based on the front outer wheel maximum steering angle α and the vehicle structure information of the autonomous vehicle, the radius R1 of the innermost movement locus of the autonomous vehicle approaching the detection object during lane change (i.e., the above-described third parameter) is determined, and the difference AE between the radius OE of the outermost movement locus of the autonomous vehicle during lane change and the minimum turning radius R2 (length equal to OA) (i.e., the above-described fourth parameter) is determined.

As an optional implementation manner, in step S4222, determining the second parameter based on the first parameter and the vehicle information further includes the following steps:

step S4321, obtaining the wheel base of the automatic driving vehicle from the vehicle information;

step S4322, determining a second parameter based on the first parameter and the wheelbase.

Still taking the scenario of controlling the autonomous vehicle to get out of the restricted driving predicament in the airport as an example, the wheelbase of the autonomous vehicle is obtained from the vehicle structure information of the autonomous vehicle, as shown in fig. 6, the wheelbase of the autonomous vehicle, i.e., the distance between the a and D wheels, is denoted AD. The minimum turning radius R2 (i.e., the second parameter) of the autonomous vehicle during the lane change is determined based on the front outer wheel maximum steering angle α and the wheel base AD.

As shown in fig. 6, the minimum turning radius R2 is equal in length to the line segment OA, from the geometrical relationship it is easy to obtain: OA × sin α = AD, that is,

a second parameter is determined based on the first parameter and the wheelbase.

As an optional implementation manner, in step S4222, determining a third parameter based on the first parameter and the vehicle information further includes the following steps:

step S4331, obtaining the wheel base and the vehicle width of the automatic driving vehicle from the vehicle information;

step S4332 determines a third parameter based on the first parameter, the wheel base, and the vehicle width.

Still taking a scenario of controlling the autonomous vehicle to get out of the restricted driving predicament in the airport as an example, the wheel base and the vehicle width of the autonomous vehicle are obtained from the vehicle structure information of the autonomous vehicle, as shown in fig. 6, the wheel base of the autonomous vehicle, that is, the distance between the wheel a and the wheel D, is denoted as AD; the width of the autonomous vehicle, i.e. the distance between the wheels C and D, is denoted CD. Based on the maximum steering angle α of the front outer wheel, the wheel base AD, and the vehicle width CD, the radius R1 of the innermost movement locus of the autonomous vehicle approaching the detection target during lane change (i.e., the third parameter).

As shown in fig. 6, the radius R1 of the innermost movement track of the autonomous vehicle approaching the detection object during lane change is equal to the length of the line segment OC, and is easily obtained according to the geometric relationship: OC = OD-CD, wherein,

therefore, the temperature of the molten metal is controlled,

that is, the third parameter is determined based on the first parameter, the wheel base, and the vehicle width.

As an optional implementation manner, in step S4222, determining the fourth parameter based on the first parameter and the vehicle information further includes the following steps:

step S43411 of acquiring a length between a front bumper and a front outer wheel of the autonomous vehicle from the vehicle information;

step S43412, determining a fourth parameter based on the first parameter and a length between the front bumper and the front outer wheel.

Still taking the scenario of controlling an autonomous vehicle to escape from a restricted driving dilemma in an airport as an example, the length between the front bumper and the front outer wheel of the autonomous vehicle is acquired from the vehicle structure information of the autonomous vehicle, as shown in fig. 6, the length between the front bumper and the front outer wheel of the autonomous vehicle, i.e., the distance between the a-wheel and the F-point, is denoted as AF. The difference AE between the radius of the outermost moving track and the minimum turning radius of the autonomous vehicle during the lane change (i.e., the fourth parameter) is determined based on the above-described front outer wheel maximum steering angle α and the length AF between the front bumper and the front outer wheel.

As shown in fig. 6, points F and E are all points on the outermost moving track of the autonomous vehicle during the lane change, and the length of arc EF is much smaller than the perimeter of the outermost movement trajectory, therefore, the segments EF and OE are considered to be in a perpendicular relationship (approximation). At this time, it is easy to obtain from the geometrical relationship: the magnitude of the angle EFA is equal to the front outer wheel maximum steering angle α, further, AF × sin α = AE, that is, a fourth parameter is determined based on the first parameter and a length between the front bumper and the front outer wheel.

In summary, the first parameter, the second parameter, the third parameter, and the fourth parameter are determined based on the center position of the detection object and the vehicle information of the autonomous vehicle. Further, according to the step S4223, the right angle bend of the autonomous vehicle passing through the narrowest road width in the lane changing process is obtained by using the first parameter, the second parameter, the third parameter and the fourth parameter, that is, the lane changing information is obtained.

As shown in fig. 6, the quarter turn of the autonomous vehicle during a lane change is designated L through the narrowest road width. It will be readily appreciated that in order to ensure the safety of the autonomous vehicle during a turn, a buffer quantity s (e.g. 0.5 m) may be provided, the result of adding the radius OE of the outermost movement track of the autonomous vehicle during a lane change to the above-mentioned buffer quantity s being the quarter turn of the autonomous vehicle during a lane change through the narrowest road width L, i.e. L = OE + s.

As shown in fig. 6, based on the maximum steering angle α of the front outer wheel (i.e., the first parameter), the minimum turning radius R2 (i.e., the second parameter), the radius R1 of the innermost movement locus approaching the detection object (i.e., the third parameter), and the difference AE between the radius of the outermost movement locus and the minimum turning radius (i.e., the fourth parameter) during the lane change of the autonomous vehicle, it is easy to obtain from the geometrical relationship: OE = R2-R1+ AE, further, L = R2-R1+ AE + s, i.e., lane change information L is calculated.

In particular, from the above geometric relationship, it is easy to obtain:

that is, the lane change information is obtained by calculation from the object information and the vehicle information.

Note that, as shown in fig. 6, the middle shaded circle is a projection of the circumscribed sphere of the obstacle on the ground, and the circle having a radius R2 represents a trajectory of the front outer wheel of the autonomous vehicle that makes one turn while maintaining the maximum steering angle of the front outer wheel (slow passage, without consideration of factors such as slip). The circle with radius R3 represents the trajectory of the outermost point of the vehicle (slow passage, consideration of the amount of cushioning s without consideration of slip, etc.) at which the autonomous vehicle makes one turn while maintaining the maximum steering angle of the front outer wheel.

In addition, according to the method for calculating lane change information provided by the embodiment of the present disclosure, the following three vehicles actually operating in an airport scene are calculated:

vehicle 1: the maximum steering angle of the front outer wheel is 34 degrees, the minimum turning radius is 6 meters, the vehicle wheelbase is 2.7 meters, the vehicle width is 2.07 meters, the width of a right-angled bend of the vehicle 1 passing through the narrowest road in the lane changing process is 4.522 meters through calculation, and the width of the narrowest road is 5 meters after the buffer capacity is considered.

The vehicle 2: the maximum steering angle of the front outer wheel is 33.8 degrees, the minimum turning radius is 7.5 meters, the vehicle wheelbase is 3.32 meters, the vehicle width is 2.52 meters, the width of a right-angled bend of the vehicle 2 passing through the narrowest road in the lane changing process is 6.14 meters through calculation, and the width of the narrowest road is 6.7 meters after the buffer amount is considered.

The vehicle 3: the maximum steering angle of the front outer wheel is 32 degrees, the minimum turning radius is 8 meters, the vehicle wheelbase is 3.8 meters, the vehicle width is 2.38 meters, the width of a right-angled bend of the vehicle 3 passing through the narrowest road in the lane changing process is 4.9 meters through calculation, and the width of the narrowest road is 5.4 meters after the buffer amount is considered.

It should be noted that the calculated data of the above three vehicles only show the main data, the remaining vehicle configuration data (e.g., the length between the front bumper and the front outer wheels) is determined by the model of the vehicle.

As an alternative embodiment, in step S423, generating a control instruction based on the road information, the object information and the lane change information, further comprising the following method steps:

step S4231 of acquiring a road width of the autonomous vehicle during traveling from the road information and acquiring an object width of the detection object from the object information;

step S4232, generating a control instruction in response to the road width, the object width and the right angle bend meeting a second preset condition through the narrowest road width, wherein the second preset condition is used for determining that the current road condition in a preset range meets the lane change condition.

In the above alternative embodiment, the road width of the autonomous vehicle during driving is obtained from the road information, and the road width may include a width of a lane in which the autonomous vehicle is currently located, a total width of co-directional lanes of the autonomous vehicle, a width from an edge of a detection object (such as an obstacle) to both sides of the road (including a width from a left edge of the detection object to a left side of the road, and a width from a right edge of the detection object to a right side of the road), and the like.

In the above-described alternative embodiment, when the object width of the detection object is acquired from the object information, in order to avoid a collision that may occur between the autonomous vehicle and the detection object, the object width may be a width of the widest position of the detection object, and preferably, the object width may be a width of the widest position of the detection object within a vehicle passing height range (such as a vehicle height plus a buffer amount).

Further, it is determined that the road width, the object width, and the right-angled bend passing narrowest road width calculated by the method of the embodiment of the present disclosure are sufficient to satisfy the second preset condition. When the road width is small and generating a control instruction when the object width and the right-angle bend meet a second preset condition through the narrowest road width. The second preset condition is used for determining that the current road condition in the preset range meets the lane change condition. It is easy to understand that the current road condition in the preset range meets the lane change condition specification: based on the road width, the object width and the right angle bend passing through the narrowest road width, the available road width provided by the current road condition in the preset range can support the automatic driving vehicle to carry out safe lane changing driving operation.

In summary, in the method for controlling an autonomous vehicle provided by the embodiment of the disclosure, a server can determine, based on a request message sent by the autonomous vehicle, and determining the current road information, object information and lane change information of the automatic driving vehicle, so as to make a running mode decision to be executed for the automatic driving vehicle and generate a control command. The control command is issued to the automatic driving vehicle to help the automatic driving vehicle to break away from the restricted driving predicament. It is easy to understand that the method for controlling the automatic driving vehicle can help the automatic driving vehicle to get rid of difficulties without relying on manual external operation, has high intelligent degree and can improve the user experience.

As an optional implementation manner, in step S4232, generating a control command further includes the following steps:

step S4233, acquiring a request identifier, an authorization identifier, a timestamp, instruction content and an encryption key corresponding to the request message, wherein the request identifier is used for identifying that the request message is from the automatic driving vehicle, the authorization identifier is used for authorizing the automatic driving vehicle to execute lane-changing driving operation, the instruction content is used for determining the execution process of the lane-changing driving operation, the timestamp is used for determining the aging of the lane-changing driving operation, and the encryption key is used for encrypting the instruction content;

step S4234 encapsulates the request identifier, the authorization identifier, the timestamp, the instruction content, and the encryption key, and generates a control instruction.

In the above optional embodiment, after the server receives the request message sent by the autonomous vehicle, the request identifier, the authorization identifier, the timestamp, the instruction content, and the encryption key corresponding to the request message are obtained. Further, the request identifier, the authorization identifier, the timestamp, the instruction content and the encryption key are packaged to generate the control instruction. Therefore, the content contained in the control command can be used for verifying the control command received by the automatic driving vehicle so as to ensure the accuracy, safety and high efficiency of the subsequent automatic driving vehicle in the lane changing driving operation process according to the control command.

In particular, the request identification is a request code or vehicle code of the autonomous vehicle, which may be used to identify that the request message originated from the autonomous vehicle. Based on the request identification, the accuracy of information interaction (such as request message interaction and control instruction interaction) between the automatic driving vehicle and the service end can be ensured.

Specifically, the authorization identifier may be an authorization code issued by the service end (e.g., an automatic driving control center) to the automatic driving vehicle in advance, and the authorization identifier may be used to authorize the automatic driving vehicle to perform a lane change driving operation. Based on the authorization identifier, the safety of the process of executing the lane-changing driving operation of the automatic driving vehicle based on the control command can be ensured.

Specifically, the instruction content may be instruction content generated according to the foregoing method decision of the embodiment of the present disclosure (i.e., instruction content for controlling the autonomous vehicle to make a lane change, which is decided by the request message). The instruction content is used for determining the execution process of the lane-changing running operation.

Specifically, the timestamp is used to record time information of a key operation (e.g., time when the autonomous vehicle sends the request message, time when the server receives the request message, time when the server issues the control command, expected time when the autonomous vehicle receives the control command, expected time when the autonomous vehicle completes a lane change operation, etc.). The time stamp is used for determining the time efficiency of the lane-changing running operation. Based on the time stamp, the high efficiency of the process of executing lane change driving operation by the automatic driving vehicle based on the control instruction can be ensured. For example, when the server detects that the autonomous vehicle receives the control instruction overtime or completes the lane change driving operation overtime, the server sends out an early warning message or stops controlling the autonomous vehicle.

Specifically, the encryption key is used to encrypt the instruction content. And the decryption key corresponding to the encryption key is stored in the corresponding automatic driving vehicle. And after the encrypted secret key is packaged to the control command and is issued to the automatic driving vehicle, the automatic driving vehicle decrypts the command content by using the decrypted secret key and executes lane-changing driving operation according to the command content. Based on the process of encrypting the instruction content, the safety of the control instruction in the transmission process can be ensured, the safety of the process that the automatic driving vehicle executes the lane-changing running operation based on the control command is further improved.

It is easily understood that, compared with the prior art, by the above method of the embodiment of the present disclosure, when the autonomous vehicle is in the restricted driving predicament, based on the interaction between the autonomous vehicle and the service end (e.g., the autonomous driving control platform), the above method steps performed by the service end generate the control command for the autonomous vehicle to help the autonomous vehicle perform the lane change driving operation to get out of the restricted driving predicament. The method for controlling the automatic driving vehicle can help the automatic driving vehicle to get rid of difficulties without relying on manual external operation, and is high in efficiency, high in intelligent degree and good in user experience.

According to another embodiment of the present disclosure, there is also provided a method of controlling an autonomous vehicle, the method may be performed by an autonomous vehicle. FIG. 7 is a flow chart of another method of controlling an autonomous vehicle provided in accordance with an embodiment of the disclosure. As shown in fig. 7, the method may include the steps of:

step S70, acquiring road condition information in a preset range around the automatic driving vehicle, wherein the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range;

step S72, responding to the road condition information meeting the preset conditions, and sending a request message to the server, wherein the preset conditions comprise: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restricting lane change of the automatic driving vehicle in the driving process, the preset type object is used for preventing the automatic driving vehicle from continuing to advance, and the request message is used for requesting the service end for the driving mode to be executed of the automatic driving vehicle;

step S74, receiving a control instruction corresponding to the request message issued by the server, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing driving operation;

in step S76, lane change running is performed based on the control command.

The above-described method of controlling an autonomous vehicle of the embodiments of the present disclosure can be run in the autonomous vehicle in the form of a computer program. The automatic driving vehicle is provided with a video camera, a radar sensor, a laser range finder and other devices to acquire road condition information within a preset range around the automatic driving vehicle. The preset range is a range that can affect the driving behavior of the autonomous vehicle, which is specified in advance by a technician. The road condition information is used for determining the type of the lane line and the type of the detection object within the preset range.

The specific implementation process for acquiring the road condition information within the preset range around the autonomous vehicle may be any achievable lane line detection and identification method and detection object identification method in the related art, and is not described in detail.

The types of lane lines described above include, but are not limited to: lane center lines (e.g., yellow dashed line, yellow solid line, yellow double solid line, and yellow dotted solid line), lane boundary lines (e.g., white dashed line, white solid line), lane edge lines (e.g., solid line edge line, dashed line edge line), stop lines (e.g., white horizontal solid line), deceleration passing lines (e.g., white double dashed line), pedestrian crossing lines. The types of the detection objects include, but are not limited to: roads, infrastructure, pedestrian barriers, and other vehicles.

Further, whether the road condition information meets a preset condition is judged. And when the road condition information meets the preset condition, sending a request message to a server (such as an automatic driving control platform). The request message is used for requesting the server to acquire the current running mode to be executed. The preset conditions include: the type of the lane line is a preset type lane line, and the preset type lane line is used for restricting lane change of the automatic driving vehicle in the driving process; the type of the detection object is a preset type object, and the preset type object is used for preventing the automatic driving vehicle from continuing to travel.

It will be readily appreciated that the preset conditions described above are used to characterize the current restricted driving dilemma of the autonomous vehicle. For example, when the type of the lane line is a solid lane boundary (i.e., a white solid line) and the type of the detection object is a pedestrian obstacle (it is assumed here that the lane line is a left and right lane boundary of the current lane and the detection object is located in the area ahead of the current lane), it is described that the autonomous vehicle is constrained to "stop traveling" and "not allow lane change", that is, the autonomous vehicle is currently in a restricted travel predicament.

And further, the automatic driving vehicle monitors the server after sending the request message, receives a control instruction corresponding to the request message sent by the server, and performs lane change driving based on the control instruction. The lane change driving is a lane change detour behavior allowed by a road dispersion rule (for example, temporary lane-crossing and detouring by a solid line when an emergency accident occurs in front allowed by a traffic rule).

It is easy to understand that, compared with the method provided by the prior art, the method for controlling the automatic driving vehicle provided by the embodiment of the disclosure can perform message interaction with the server side, and perform lane change driving according to the control instruction returned by the server side without depending on manual external operation, so that the driving restriction dilemma is removed, the intelligent degree of the whole process is higher, and the user experience can be improved.

According to the present disclosure from the step 70 to the step 76, obtaining road condition information within a preset range around the autonomous vehicle, wherein the road condition information is used for determining the type of lane line and the type of the detection object within the preset range; responding to the road condition information to meet preset conditions, and sending a request message to a server, wherein the preset conditions comprise: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, the preset type object is used for preventing the automatic driving vehicle from continuing to advance, and the request message is used for requesting the driving mode to be executed of the automatic driving vehicle from the server; receiving a control instruction corresponding to a request message issued by a server, wherein the control instruction is used for controlling an automatic driving vehicle to execute lane changing driving operation; and performing lane change driving based on the control instruction.

It is easy to understand that the technical scheme provided by the disclosure can be operated in an automatic driving vehicle, and by performing message interaction with the server, lane changing driving is performed according to a control command returned by the server under the condition of not depending on manual external operation, so that the driving restriction dilemma is removed. Therefore, this disclosure has reached through the automatic purpose that generates control command control autopilot vehicle lane change and goes in order to break away from the predicament that is hindered to continue to advance, has realized improving autopilot vehicle's intelligent degree of getting rid of poverty automatically, has promoted user experience's technological effect, has solved among the prior art because rely on the manual work to carry out the technical problem that the help autopilot vehicle gets rid of poverty and lead to that the intelligent degree of autopilot process is low, user experience is poor.

Fig. 8 is a schematic diagram of an alternative airport autonomous vehicle control system according to an embodiment of the present disclosure, as shown in fig. 8, including an environment sensing and positioning portion, a decision planning portion, and an executive control portion.

As shown in fig. 8, in the environment sensing and positioning portion, the camera, the laser radar, the millimeter wave radar, and the ultrasonic radar installed in the airport facility or the autonomous vehicle are used for sensing the environment, so as to obtain the road condition information within the preset range around the autonomous vehicle when the autonomous vehicle is running in the airport. Positioning of an autonomous vehicle by a plurality of positioning means, wherein the plurality of positioning means comprise: satellite positioning, differential positioning, inertial positioning, and sensor positioning. The communication interaction of the automatic driving vehicle is carried out through the vehicle wireless communication technology (V2X), and comprises vehicle-to-vehicle communication (V2V) and vehicle network communication (V2N).

As shown in fig. 8, in the decision planning section, a path is planned for the autonomous vehicle based on the high-precision map and a plurality of path planning algorithms, and a behavior decision is made for the autonomous vehicle through the autonomous behavior prediction model and the autonomous behavior decision model.

As shown in fig. 8, in the execution control section, the accelerator system, the steering system, the brake system, the shift system, and the like of the autonomous vehicle are controlled through a vehicle data bus (such as a CAN bus).

The method for controlling an autonomous vehicle provided by the embodiment of the disclosure can be operated in an airport autonomous vehicle control system as shown in fig. 8. The method comprises the steps of obtaining road condition information of the automatic driving vehicle through environment sensing and positioning, and sending a request message to a server (such as an automatic driving control platform) through V2X when the automatic driving vehicle is in a driving restriction predicament.

In the embodiment of the present disclosure, both the autonomous vehicle and the service end may perform the operation of the decision planning part shown in fig. 8 under a normal condition (when the autonomous vehicle normally travels), but when the autonomous vehicle is in a driving restriction predicament, the autonomous vehicle cannot perform decision planning for itself, and at this time, the service end performs decision planning based on the request message sent by the autonomous vehicle and generates the control instruction.

As shown in fig. 8, after the autonomous vehicle receives the control command returned from the server, the accelerator system, the steering system, the brake system, the gear shift system, and the like of the autonomous vehicle are controlled through a vehicle data bus (such as a CAN bus) to perform lane change driving without restricting the driving predicament according to the content of the control command.

As an alternative embodiment, in step S76, the method for performing lane change driving based on the control command further includes the following steps:

step S761, the control instruction is analyzed to obtain a request identifier, an authorization identifier, a timestamp, encrypted instruction content and an encryption key corresponding to the request message, wherein the request identifier is used for identifying that the request message originates from the automatic driving vehicle, the authorization identifier is used for authorizing the automatic driving vehicle to execute the lane-changing driving operation, the instruction content is used for determining the execution process of the lane-changing driving operation, the timestamp is used for determining the timeliness of the lane-changing driving operation, and the encryption key is used for encrypting the instruction content;

step S762, decrypting the encrypted instruction content by using a decryption key corresponding to the encryption key to obtain the instruction content;

and S763, responding to the condition that the request mark, the authorization mark and the timestamp are verified successfully and no collision risk exists in a preset range, and changing to a second lane from a first lane to bypass the detection object based on the instruction content, wherein the first lane is an initial planned driving lane of the automatic driving vehicle, and the second lane is a lane-changed driving lane of the automatic driving vehicle.

The control instruction is a control instruction which is packaged by the server and is issued to the automatic driving vehicle. The control instruction is analyzed to obtain a request identifier, an authorization identifier, a timestamp, encrypted instruction content and an encryption key corresponding to the request message.

Specifically, the instruction content may be instruction content generated by the server for making a driving mode decision. The instruction content is used for determining the execution process of the lane-changing running operation.

Specifically, the timestamp is used to record time information of a key operation (e.g., time when the autonomous vehicle sends the request message, time when the server receives the request message, time when the server issues the control command, expected time when the autonomous vehicle receives the control command, expected time when the autonomous vehicle completes a lane change operation, etc.). The time stamp is used for determining the time efficiency of the lane-changing running operation. Based on the time stamp, the high efficiency of the process of executing lane change driving operation by the automatic driving vehicle based on the control instruction can be ensured. For example, when the server detects that the automatic driving vehicle receives the control command overtime or the lane change operation is finished overtime, the server sends out an early warning message or stops controlling the automatic driving vehicle.

Specifically, the encryption key is used to encrypt the instruction content. And the decryption key corresponding to the encryption key is stored in the automatic driving vehicle. And the automatic driving vehicle decrypts the encrypted instruction content by using the decryption secret key to obtain the instruction content. Because the instruction content in the control instruction is encrypted, the safety of the control instruction in the transmission process can be ensured, and the safety of the automatic driving vehicle in the process of executing lane-changing driving operation based on the control instruction is further improved.

Further, the automatic driving vehicle checks the request identifier, the authorization identifier and the timestamp in the control command, and if the request identifier, the authorization identifier and the timestamp are checked successfully and no collision risk exists in a preset range (whether the collision risk exists can be decided by a server or detected by the automatic driving vehicle after the instruction content is obtained), the automatic driving vehicle is switched to a second lane from a first lane to bypass a detection object based on the instruction content, wherein the first lane is an initial planned driving lane of the automatic driving vehicle, and the second lane is a lane-changed driving lane of the automatic driving vehicle.

It is easy to understand that the accuracy, the safety and the efficiency of the subsequent automatic driving vehicle in the lane changing driving operation process according to the control command can be ensured by verifying the request identifier, the authorization identifier and the timestamp corresponding to the request message contained in the control command.

As an alternative embodiment, the method for controlling an autonomous vehicle further comprises the following method steps:

step S781, detecting whether the automatic driving vehicle successfully bypasses the detection object;

step S782, in response to the autonomous vehicle successfully bypassing the detection object, switches from the second lane back to the first lane to continue driving.

In the above optional embodiment, after the autonomous vehicle performs the lane change driving operation according to the control instruction returned by the server, it is detected whether the autonomous vehicle successfully bypasses the detection object (i.e. the autonomous vehicle is out of the restricted driving dilemma successfully), and if the autonomous vehicle successfully bypasses the detection object and the current road condition information allows the vehicle to change from the second lane to the first lane, the autonomous vehicle changes from the second lane to the first lane to continue driving

And after the automatic driving vehicle finishes lane changing operation and executes a difficulty getting-out program, if the automatic driving vehicle is detected to be successfully got out of the restricted driving predicament and the current road condition information allows the vehicle to return to a default lane before lane changing, controlling the automatic driving vehicle to return to the model lane for continuous driving.

Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present disclosure may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to enable a terminal device (which may be a mobile phone, a computer, a server, or a network device) to execute the methods described in the embodiments of the present disclosure.

According to another embodiment of the present disclosure, there is also provided a device for controlling an autonomous vehicle, which is used to implement the above embodiments and preferred embodiments, and which has been described above and will not be described again. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Fig. 9 is a block diagram of an apparatus for controlling an autonomous vehicle according to an embodiment of the present disclosure, and as shown in fig. 9, the apparatus 900 for controlling an autonomous vehicle includes: the receiving module 901 is configured to receive a request message from an autonomous vehicle, where the request message is triggered by road condition information in a preset range around the autonomous vehicle, the request message is used to request a driving mode to be executed by the autonomous vehicle, the road condition information is used to determine a type of a lane line and a type of a detection object in the preset range, and the road condition information satisfies a first preset condition, where the first preset condition includes: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance; a generating module 902, configured to generate a control instruction based on the request message, where the control instruction is used to control the autonomous vehicle to perform a lane change driving operation; and the control module 903 is used for sending the control instruction to the automatic driving vehicle so that the automatic driving vehicle can perform lane change driving based on the control instruction.

Optionally, the generating module 902 is further configured to: responding to the request message, and acquiring road information in the driving process, object information of the detection object and vehicle information of the automatic driving vehicle reported by the automatic driving vehicle; acquiring lane change information by using the object information and the vehicle information, wherein the lane change information is that the right-angled bend of the automatic driving vehicle passes through the narrowest road width in the lane change process; and generating a control instruction based on the road information, the object information and the lane change information.

Optionally, the generating module 902 is further configured to: acquiring the central position of a detection object from the object information; determining a first parameter, a second parameter, a third parameter and a fourth parameter based on the center position and the vehicle information, wherein the first parameter is a maximum steering angle of a front outer wheel of the automatic driving vehicle in a lane changing process, the second parameter is a minimum turning radius of the automatic driving vehicle in the lane changing process, the third parameter is a radius of an innermost moving track of the automatic driving vehicle close to a detection object in the lane changing process, and the fourth parameter is determined based on a length between a front bumper and the front outer wheel of the automatic driving vehicle; and acquiring lane change information by using the first parameter, the second parameter, the third parameter and the fourth parameter.

Optionally, the generating module 902 is further configured to: acquiring a first axle center and a second axle center of the automatic driving vehicle from the vehicle information, wherein the first axle center is a front outer wheel axle center of the automatic driving vehicle, and the second axle center is a rear outer wheel axle center of the automatic driving vehicle; determining a first parameter by using the center position, the first axis and the second axis; the second, third, and fourth parameters are determined based on the first parameter and the vehicle information.

Optionally, the generating module 902 is further configured to: obtaining a wheel base of the autonomous vehicle from the vehicle information; a second parameter is determined based on the first parameter and the wheelbase.

Optionally, the generating module 902 is further configured to: obtaining a wheel base and a vehicle width of the automatic driving vehicle from the vehicle information; a third parameter is determined based on the first parameter, the wheelbase, and the vehicle width.

Optionally, the generating module 902 is further configured to: obtaining a length between a front bumper and a front outer wheel of the autonomous vehicle from the vehicle information; a fourth parameter is determined based on the first parameter and a length between the front bumper and the front outer wheel.

Optionally, the generating module 902 is further configured to: acquiring the road width of the automatic driving vehicle in the driving process from the road information and acquiring the object width of the detection object from the object information; and responding to the situation that the road width, the object width and the right angle bend meet a second preset condition through the narrowest road width, and generating a control instruction, wherein the second preset condition is used for determining that the current road condition in a preset range meets the lane change condition.

Optionally, the generating module 902 is further configured to: acquiring a request identifier, an authorization identifier, a timestamp, instruction content and an encryption key corresponding to the request message, wherein the request identifier is used for identifying that the request message is from an automatic driving vehicle, the authorization identifier is used for authorizing the automatic driving vehicle to execute lane change driving operation, the instruction content is used for determining the execution process of the lane change driving operation, the timestamp is used for determining the timeliness of the lane change driving operation, and the encryption key is used for encrypting the instruction content; and packaging the request identifier, the authorization identifier, the timestamp, the instruction content and the encryption key to generate a control instruction.

According to another embodiment of the present disclosure, another apparatus for controlling an autonomous vehicle is provided, which is used to implement the above embodiments and preferred embodiments, and the description of which is already given is omitted.

Fig. 10 is a block diagram illustrating another apparatus for controlling an autonomous vehicle according to an embodiment of the present disclosure, and as shown in fig. 10, the apparatus 1000 for controlling an autonomous vehicle includes: the system comprises an acquisition module 1001, a detection module and a processing module, wherein the acquisition module is used for acquiring road condition information in a preset range around an automatic driving vehicle, and the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range; the sending module 1002 is configured to send a request message to a server in response to that the road condition information meets a preset condition, where the preset condition includes: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, the preset type object is used for preventing the automatic driving vehicle from continuing to advance, and the request message is used for requesting the driving mode to be executed of the automatic driving vehicle from the server; the receiving module 1003 is configured to receive a control instruction corresponding to the request message sent by the server, where the control instruction is used to control the autonomous vehicle to perform a lane change driving operation; and the control module 1004 is used for performing lane change driving based on the control instruction.

Optionally, the control module 1004 is further configured to: analyzing the control instruction to obtain a request identifier, an authorization identifier, a timestamp, encrypted instruction content and an encryption key corresponding to the request message, wherein the request identifier is used for identifying that the request message originates from an automatic driving vehicle, the authorization identifier is used for authorizing the automatic driving vehicle to execute lane-changing driving operation, the instruction content is used for determining the execution process of the lane-changing driving operation, the timestamp is used for determining the time efficiency of the lane-changing driving operation, and the encryption key is used for encrypting the instruction content; decrypting the encrypted instruction content by using a decryption key corresponding to the encryption key to obtain the instruction content; and responding to the request identifier, the authorization identifier and the timestamp which are verified successfully and no collision risk exists in the preset range, and changing from a first lane to a second lane to bypass the detection object based on the instruction content, wherein the first lane is an initial planned driving lane of the automatic driving vehicle, and the second lane is a lane-changed driving lane of the automatic driving vehicle.

Alternatively, fig. 11 is a block diagram of an alternative apparatus for controlling an autonomous vehicle according to an embodiment of the disclosure, and as shown in fig. 11, the apparatus 1000 for controlling an autonomous vehicle includes, in addition to all modules shown in fig. 10: a detection module 1005 for detecting whether the autonomous vehicle successfully bypasses the detection object; and in response to the autonomous vehicle successfully bypassing the detection object, changing from the second lane back to the first lane to continue driving.

It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are located in different processors in any combination.

There is also provided, in accordance with another embodiment of the present disclosure, an electronic device including at least one processor, and a memory communicatively coupled to the at least one processor, the memory having stored therein instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to perform the steps of any one of the method embodiments described above.

Optionally, the electronic device may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.

Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:

step S1, receiving a request message from an automatic driving vehicle, wherein the request message is triggered by road condition information in a preset range around the automatic driving vehicle, the request message is used for requesting a driving mode to be executed of the automatic driving vehicle, the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range, and the road condition information meets a first preset condition, and the first preset condition comprises: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance;

s2, generating a control instruction based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane-changing driving operation;

and S3, issuing the control command to the automatic driving vehicle so that the automatic driving vehicle carries out lane changing driving based on the control command.

Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.

According to another embodiment of the present disclosure, there is also provided a non-transitory computer readable storage medium having stored therein computer instructions, wherein the computer instructions are arranged to perform the steps of any of the above method embodiments when executed.

Alternatively, in the present embodiment, the above-mentioned non-transitory computer-readable storage medium may be configured to store a computer program for causing a computer to execute the steps of:

Alternatively, in the present embodiment, the non-transitory computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a RAM, a ROM, an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

There is also provided, in accordance with another embodiment of the present disclosure, a computer program product, including a computer program, which when executed by a processor, implements the above-described method of controlling an autonomous vehicle.

It should be noted that program code for implementing the disclosed method of controlling an autonomous vehicle may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In several embodiments provided in the present disclosure, descriptions of the respective embodiments are focused, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a Display device (e.g., a Cathode Ray Tube (CRT) or Liquid Crystal Display (LCD) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A method of controlling an autonomous vehicle, comprising:

receiving a request message from an autonomous vehicle, wherein the request message is triggered by road condition information within a preset range around the autonomous vehicle, the request message is used for requesting a driving mode to be executed by the autonomous vehicle, the road condition information is used for determining the type of a lane line and the type of a detection object within the preset range, and the road condition information meets a first preset condition, and the first preset condition comprises: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance;

generating a control instruction based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing driving operation;

and issuing the control command to the automatic driving vehicle so that the automatic driving vehicle carries out lane change driving based on the control command.

2. The method of claim 1, wherein generating the control instruction based on the request message comprises:

responding to the request message, and acquiring road information in a driving process, object information of the detection object and vehicle information of the automatic driving vehicle reported by the automatic driving vehicle;

acquiring lane change information by using the object information and the vehicle information, wherein the lane change information is that the right-angle bend of the automatic driving vehicle passes through the narrowest road width in the lane change process;

and generating the control instruction based on the road information, the object information and the lane change information.

3. The method of claim 2, wherein obtaining the lane change information using the object information and the vehicle information comprises:

acquiring the central position of the detection object from the object information;

determining a first parameter, a second parameter, a third parameter and a fourth parameter based on the center position and the vehicle information, wherein the first parameter is a maximum steering angle of a front outer wheel of the autonomous vehicle during lane changing, the second parameter is a minimum turning radius of the autonomous vehicle during lane changing, the third parameter is a radius of an innermost movement track of the autonomous vehicle approaching the detection object during lane changing, and the fourth parameter is determined based on a length between a front bumper and the front outer wheel of the autonomous vehicle;

and acquiring the lane change information by using the first parameter, the second parameter, the third parameter and the fourth parameter.

4. The method of claim 3, wherein determining the first, second, third, and fourth parameters based on the center location and the vehicle information comprises:

obtaining a first axle center and a second axle center of the autonomous vehicle from the vehicle information, wherein the first axle center is a front outer wheel axle center of the autonomous vehicle, and the second axle center is a rear outer wheel axle center of the autonomous vehicle;

determining the first parameter using the center position, the first axis, and the second axis;

determining the second, third, and fourth parameters based on the first parameter and the vehicle information.

5. The method of claim 3, wherein determining the second parameter based on the first parameter and the vehicle information comprises:

obtaining a wheel base of the autonomous vehicle from the vehicle information;

determining the second parameter based on the first parameter and the wheel base.

6. The method of claim 3, wherein determining the third parameter based on the first parameter and the vehicle information comprises:

obtaining a wheel base and a vehicle width of the autonomous vehicle from the vehicle information;

the third parameter is determined based on the first parameter, the wheel base, and the vehicle width.

7. The method of claim 3, wherein determining the fourth parameter based on the first parameter and the vehicle information comprises:

obtaining a length between a front bumper and a front outer wheel of the autonomous vehicle from the vehicle information;

determining the fourth parameter based on the first parameter and a length between the front bumper and a front outer wheel.

8. The method of claim 2, wherein generating the control instruction based on the road information, the object information, and the lane change information comprises:

acquiring the road width of the automatic driving vehicle in the driving process from the road information and acquiring the object width of the detection object from the object information;

and generating the control instruction in response to the fact that the road width, the object width and the right angle bend meet a second preset condition through the narrowest road width, wherein the second preset condition is used for determining that the current road condition in the preset range meets a lane change condition.

9. The method of claim 8, wherein generating the control instruction comprises:

acquiring a request identifier, an authorization identifier, a timestamp, instruction content and an encryption key corresponding to the request message, wherein the request identifier is used for identifying that the request message originates from the automatic driving vehicle, the authorization identifier is used for authorizing the automatic driving vehicle to execute lane changing driving operation, the instruction content is used for determining the execution process of the lane changing driving operation, the timestamp is used for determining the time limit of the lane changing driving operation, and the encryption key is used for encrypting the instruction content;

and packaging the request identifier, the authorization identifier, the timestamp, the instruction content and the encryption key to generate the control instruction.

10. A method of controlling an autonomous vehicle, comprising:

acquiring road condition information in a preset range around an automatic driving vehicle, wherein the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range;

responding to the road condition information meeting preset conditions, and sending a request message to a server, wherein the preset conditions comprise: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restricting lane change of the automatic driving vehicle in the driving process, the preset type object is used for preventing the automatic driving vehicle from continuing to advance, and the request message is used for requesting the service end for a driving mode to be executed by the automatic driving vehicle;

receiving a control instruction corresponding to the request message issued by the server, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing driving operation;

and performing lane change driving based on the control command.

11. The method of claim 10, wherein performing lane change driving based on the control instruction comprises:

analyzing the control instruction to obtain a request identifier, an authorization identifier, a timestamp, encrypted instruction content and an encryption key corresponding to the request message, wherein the request identifier is used for identifying that the request message originates from the automatic driving vehicle, the authorization identifier is used for authorizing the automatic driving vehicle to execute lane-changing driving operation, the instruction content is used for determining the execution process of the lane-changing driving operation, the timestamp is used for determining the timeliness of the lane-changing driving operation, and the encryption key is used for encrypting the instruction content;

decrypting the encrypted instruction content by adopting a decryption key corresponding to the encryption key to obtain the instruction content;

and responding to the request mark, the authorization mark and the timestamp which are verified successfully and no collision risk exists in the preset range, and changing to a second lane from a first lane to bypass the detection object based on the instruction content, wherein the first lane is an initial planned driving lane of the automatic driving vehicle, and the second lane is a lane-changed driving lane of the automatic driving vehicle.

12. The method of claim 11, wherein the method further comprises:

detecting whether the autonomous vehicle successfully bypasses the detection object;

in response to the autonomous vehicle successfully bypassing the detection object, changing from the second lane back to the first lane to continue driving.

13. An apparatus for controlling an autonomous vehicle, comprising:

a receiving module, configured to receive a request message from an autonomous vehicle, where the request message is triggered by road condition information in a preset range around the autonomous vehicle, the request message is used to request a driving mode to be executed by the autonomous vehicle, the road condition information is used to determine a type of a lane line and a type of a detection object in the preset range, and the road condition information satisfies a first preset condition, where the first preset condition includes: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, and the preset type object is used for preventing the automatic driving vehicle from continuing to advance;

the generation module is used for generating a control instruction based on the request message, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing running operation;

and the control module is used for issuing the control command to the automatic driving vehicle so that the automatic driving vehicle can carry out lane change driving based on the control command.

14. An apparatus for controlling an autonomous vehicle, comprising:

the system comprises an acquisition module, a detection module and a processing module, wherein the acquisition module is used for acquiring road condition information in a preset range around an automatic driving vehicle, and the road condition information is used for determining the type of a lane line and the type of a detection object in the preset range;

the sending module is configured to send a request message to a server in response to that the road condition information satisfies a preset condition, where the preset condition includes: the type of the lane line is a preset type lane line and the type of the detection object is a preset type object, the preset type lane line is used for restraining the lane change of the automatic driving vehicle in the driving process, the preset type object is used for preventing the automatic driving vehicle from continuing to advance, and the request message is used for requesting the service end for the driving mode to be executed of the automatic driving vehicle;

the receiving module is used for receiving a control instruction corresponding to the request message issued by the server, wherein the control instruction is used for controlling the automatic driving vehicle to execute lane changing running operation;

and the control module is used for performing lane change driving based on the control command.

15. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-12.

16. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-12.

17. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-12.