WO2021189210A1

WO2021189210A1 - Vehicle lane changing method and related device

Info

Publication number: WO2021189210A1
Application number: PCT/CN2020/080744
Authority: WO
Inventors: 曾侠; 杜明博
Original assignee: 华为技术有限公司
Priority date: 2020-03-23
Filing date: 2020-03-23
Publication date: 2021-09-30
Also published as: CN112672942A; CN112672942B

Abstract

A vehicle lane changing method and apparatus, the vehicle lane changing method comprising: acquiring the current speed of a target vehicle, N lane-changing gaps in a target lane, and a gap attribute corresponding to each lane-changing gap; according to the mapping between each lane-changing gap template in a gap template set and the vehicle speed, acquiring from the gap template set M lane-changing gap templates matching the current speed; acquiring a target lane-changing gap and a target lane-changing gap template from among N lane-changing gaps and M lane-changing gap templates, wherein the gap attribute corresponding to the target lane-changing gap has the highest similarity to a preset gap attribute corresponding to the target lane-changing gap template; and controlling, by means of the target lane-changing gap template, the target vehicle to change lanes to the target lane-changing gap. When driving a vehicle, a lane-changing road section can be accurately and efficiently selected for driving.

Description

Vehicle lane changing method and related equipment

Technical field

This application relates to the field of automatic driving technology, and in particular to a vehicle lane changing method and related equipment.

Background technique

Lane-changing behavior on high-speed is a high-risk driving behavior, which extremely tests the driver's attention and control, and a little carelessness may lead to tragedy. In order to improve the safety of high-speed lane changing, most of the existing models are equipped with auxiliary devices such as Driver Assisted Driving System (ADAS), which can be activated by the turn signal lever to trigger the active lane changing function.

However, this function still requires the driver to concentrate on the initial selection of the lane-changing gap (lane-changing gap) for lane-changing and interposing vehicles, and then performing lane-changing and interleaving for the selected lane-changing gap according to road conditions. Generally, the default is The nearest lane-changing gap in the adjacent lane of the own vehicle is used for lane-changing to insert the vehicle. Therefore, at present, the following problems still exist in the choice of the vehicle’s active lane-changing gap: the choice of the lane-changing gap still requires the driver to make the choice independently. If the next section of the road is still selected for plug-in and lane-changing by default, the safety will not be better met. need. Especially when the vehicle is parallel to the vehicle in the side lane and the vehicle condition is complicated, the default is the nearest lane-changing gap on the adjacent lane of the vehicle to be used for lane-changing and inserting the vehicle, which can easily cause traffic accidents. However, in the prior art, when the lane-changing Gap needs to be selected for lane-changing and inserting vehicles according to road conditions, many calibration parameters are required, and the post-calibration processing is large, and the best lane-changing opportunity is easily missed; and this method requires high traffic flow stability. , The vehicle in the target lane needs to be in a stable state for a long time during the driving process to prevent safety accidents.

Therefore, how to help the driver to accurately and efficiently select the lane-changing gap for lane-changing when driving the vehicle to change lanes is a problem that needs to be solved urgently.

Summary of the invention

The embodiment of the present application provides a vehicle lane changing method and related equipment, which can automatically, accurately and efficiently select the lane changing gap when the driver is driving the vehicle to change lanes and insert the vehicle.

In the first aspect, an embodiment of the present application provides a method for changing lanes of a vehicle, including:

Acquire the current speed of the target vehicle, the N lane-changing gaps in the target lane, and the Gap attribute corresponding to each lane-changing gap, where the target lane is the lane to which the target vehicle will change lanes, and the lane-changing gap Is the gap between two adjacent vehicles on the target lane, and the Gap attributes include the Gap length of the corresponding lane-changing Gap, the distance between the corresponding lane-changing Gap and the target vehicle, and the corresponding lane-changing Gap. One or more of the speed difference between the Gap and the target vehicle, the distance between the target vehicle and the first vehicle, and the speed difference between the target vehicle and the first vehicle, the first The vehicle is the previous vehicle in the lane where the target vehicle is currently located, and N is an integer greater than or equal to 1; according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, from the Gap template set Obtain M lane-changing Gap templates matching the current speed, and each lane-changing Gap template of the M lane-changing Gap templates includes a preset lane-changing Gap and preset Gap attributes, and the preset Gap attributes are all The Gap attribute corresponding to the preset lane changing Gap, where M is an integer greater than or equal to 1; the target lane changing Gap and the target lane changing Gap are obtained from the N lane changing Gap and the M lane changing Gap templates Template, wherein the Gap attribute corresponding to the target lane-changing Gap has the highest similarity with the preset Gap attribute corresponding to the target lane-changing Gap template; through the target lane-changing Gap template, the target vehicle is controlled to change lanes. The stated goal changes to Gap.

Under normal circumstances, when a vehicle changes lanes automatically, it often defaults to selecting a section of the road closest to the vehicle to complete the lane change operation. However, this lane-changing mode requires high traffic flow stability. If the traffic flow is unstable, you can directly select the road section closest to the vehicle to change lanes, which is likely to cause safety accidents; moreover, when changing lanes on the nearest road section, it is easy to happen. Because the lane change time is too short, the vehicle speeds up or brakes urgently, which makes the passenger's riding experience poor. Therefore, with the method provided in the first aspect, when the vehicle changes from the current lane to the target lane, the vehicle can actively select the appropriate insertion gap Gap (that is, the lane change gap) in the target lane, and change lanes through the insertion gap. The target lane ensures the active selection of the road section where the vehicle is about to change lanes during the lane change process of the target vehicle, which can better meet the driving needs of the target vehicle and avoid the default selection of the nearest lane change gap to the target vehicle. There is no guarantee that the target vehicle can change lanes safely and comfortably. Among them, when the vehicle insertion gap is actively selected, the preset Gap attributes corresponding to multiple lane-changing gap templates are compared with the Gap attributes corresponding to multiple lane-changing gaps, and the pair with the highest similarity is selected as the target lane-changing gap. Template and target lane-changing Gap, so that the target vehicle can pass the target lane-changing Gap template to safely and efficiently insert the vehicle to the target lane-changing Gap. For example, the target vehicle can select the front or rear lane change gap according to the lane change gap template to realize the acceleration or deceleration of the vehicle and merge into the target lane to ensure that the target vehicle can safely change lanes on the road without overspeeding or The collision caused a safety accident and improved the driving safety of the vehicle. Moreover, by comparing the Gap attribute similarity between the lane-changing Gap template and the lane-changing Gap, the lane-changing Gap with the highest similarity among the existing lane-changing Gap templates is selected from multiple lane-changing Gaps. The lane-changing gap for the target vehicle can ensure that the vehicle does not need to detect the driving state of the vehicle in the target lane for a long time during the lane-changing process. It only needs to determine multiple lane-changing gaps and directly compare the lane-changing gap template to determine multiple lane-changes. The target lane-changing Gap in the Gap reduces the driving parameters of a large number of calibrated vehicles during the lane-changing process, and improves the efficiency of the target vehicle in selecting the lane-changing Gap. Secondly, according to the Gap attributes of the lane-changing Gap, the most suitable lane-changing Gap template (target lane-changing Gap template) is selected from multiple lane-changing Gap templates. This lane-changing Gap template can make the vehicle have more suitable and refined Under the premise of advanced driving information (such as preset Gap attributes), passengers have a higher comfort and smooth ride experience. For example, the target vehicle can have a more precise adjustment range when adjusting the speed of the vehicle during the lane change process according to the preset Gap attributes.

In a possible implementation manner, the acquiring the target lane changing gap and the target lane changing gap template from the N lane changing gaps and the M lane changing gap templates includes: calculating the N lane changing gaps The similarity between the Gap attribute of each lane-changing Gap in the Gap and the preset Gap attribute of each lane-changing Gap template in the M lane-changing Gap templates; after sorting the similarities, the pair with the highest similarity is obtained The lane change Gap and lane change Gap templates are the target lane change Gap and the target lane change Gap template. To implement the embodiment of this application, the preset Gap attributes corresponding to the M lane-changing Gap templates are compared with the Gap attributes corresponding to the N lane-changing Gaps. When the similarity is higher, the Gap attribute corresponding to the lane-changing Gap is proved The more similar the preset Gap attributes of the lane-changing Gap template are, the more suitable the road conditions of the lane-changing Gap are to the lane-changing Gap template. Therefore, after the similarity is sorted, the pair of lane-changing Gap templates and lane-changing Gaps with the highest similarity are determined as the target lane-changing Gap and the target lane-changing Gap template respectively, which is conducive to the accuracy of the target vehicle based on the existing lane-changing Gap template. Efficiently choose a safer and more comfortable lane-changing Gap for lane-changing driving.

In a possible implementation manner, according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, after obtaining M lane-changing Gap templates matching the current speed from the Gap template set, It also includes: according to the current speed, respectively determining the probability that the target vehicle matches each lane change Gap template of the M lane change Gap templates; and calculating each lane change of the N lane change Gap templates The similarity between the Gap attributes of the Gap and the preset Gap attributes of each lane-changing Gap template in the M lane-changing Gap templates includes: according to the target vehicle and each of the M lane-changing Gap templates The matching probability of the lane-changing Gap template is calculated based on the standardized Euclidean distance evaluation method to calculate the Gap attribute of each lane-changing Gap in the N lane-changing Gap and the prediction of each lane-changing Gap template in the M lane-changing Gap templates. Let the similarity between Gap attributes. In the implementation of the embodiment of this application, because the same speed may correspond to different lane-changing gap templates, it is necessary to first determine that each lane-changing gap template matches each of the M lane-changing gap templates at the current speed of the target vehicle. For example, the probability that the target vehicle at 21.5km/h matches the lane-change Gap template corresponding to 20km/h-22km/h is greater than the probability that the lane-change Gap template corresponding to 21km/h-24km/h matches. Then calculate the similarity with each template according to the matching probability, which is beneficial to the target vehicle to more accurately screen out the target lane-changing gap, so as to make lane-changing driving safer and more comfortable.

In a possible implementation manner, the target lane-changing Gap template further includes a preset lane-changing trajectory; the controlling the target vehicle to change lanes to the target lane-changing Gap through the target lane-changing Gap template includes : Determine the lane change time and lane change trajectory of the target vehicle according to the Gap attribute of the target lane change Gap and the preset lane change trajectory; control the lane change time and lane change trajectory of the target vehicle according to the lane change time and the lane change trajectory The target vehicle changes lanes from the current lane to the target lane change Gap. In the implementation of the embodiment of this application, after the target lane-changing Gap and target lane-changing Gap template are filtered out, the target vehicle can determine the specific lane-changing time and lane-changing trajectory of the target vehicle according to the Gap attribute and the preset lane-changing trajectory, so that the target The vehicle changes lanes accurately and efficiently.

In a possible implementation manner, the Gap template set sent by the service device is received and saved. In this embodiment of the present application, the Gap template set directly obtained can be used to directly filter out M lane-changing Gap templates matching the current speed of the target vehicle, and then the target lane-changing Gap template can be determined through the M lane-changing Gap templates. It can further improve the efficiency of vehicles actively selecting target lane-changing gaps in autonomous driving, and enhance the user's riding experience.

In the second aspect, an embodiment of the present application provides a vehicle lane changing method, including:

Send a Gap template set to the target vehicle, where the Gap template set is used for the target vehicle to obtain from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed M lane-changing gap templates matching the current speed of the target vehicle, each lane-changing gap template of the M lane-changing gap templates includes a preset lane-changing gap and a preset gap attribute, the preset gap attribute Is the Gap attribute corresponding to the preset lane-changing Gap, and the Gap attribute includes the Gap length corresponding to the preset lane-changing Gap, the distance between the corresponding preset lane-changing Gap and the lane-changing vehicle, and the corresponding preset One or more of the speed difference between the lane-changing Gap and the lane-changing vehicle, the distance between the lane-changing vehicle and the first vehicle, and the speed difference between the lane-changing vehicle and the first vehicle The first vehicle is the previous vehicle in the lane where the lane-changing vehicle is currently located, and the target vehicle belongs to the lane-changing vehicle, where M is an integer greater than or equal to 1; the M lane-changing vehicles The Gap template is used by the target vehicle to obtain the target lane-changing Gap template and the target lane-changing Gap from the M lane-changing Gap templates and N lane-changing Gaps on the target lane, wherein the target lane-changing Gap template corresponds to The preset Gap attribute is the highest similarity with the Gap attribute corresponding to the target lane-changing Gap, the target lane is the lane to which the target vehicle will change lanes, and the lane-changing Gap is two phases on the target lane. The gap between adjacent vehicles.

With the method provided in the second aspect, after sending the Gap template set to the target vehicle, the target vehicle may select the Gap template set from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed. Obtain M lane-changing Gap templates that match the current speed of the target vehicle, and then determine the target lane-changing Gap template through the M lane-changing Gap templates, which can further improve the comfort and stability of vehicle traffic in automatic driving , Enhance the user's ride experience. Secondly, when the vehicle actively selects the target lane-changing gap, it compares the preset Gap attributes corresponding to multiple lane-changing gap templates with the Gap attributes corresponding to multiple lane-changing gaps, and then selects the pair with the highest similarity as the target. The lane-changing Gap template and the target lane-changing Gap, so that the target vehicle can pass the target lane-changing Gap template to safely and efficiently insert the vehicle to the target lane-changing Gap. Moreover, it can be ensured that the vehicle does not need to detect the driving state of the vehicle in the target lane for a long time during the lane change process. It only needs to determine multiple lane change gaps, and directly compare the lane change gap template to determine the target lane change gap among multiple lane change gaps. , It reduces the driving parameters of a large number of calibration vehicles during the lane change process, and improves the efficiency of the target vehicle in selecting the lane change gap.

In a possible implementation manner, before sending the Gap template set to the target vehicle, the method further includes: acquiring a plurality of lane-changing sample data, wherein each lane-changing sample data corresponds to a vehicle speed, and each The lane change sample data includes the sample lane change Gap and the sample Gap attribute, the sample Gap attribute is the Gap attribute corresponding to the sample lane change Gap; according to the size of the vehicle speed corresponding to each lane change sample data, the The multiple lane changing sample data are respectively divided into multiple data sets of different speed sections, wherein the data sets of each speed section in the multiple data sets of different speed sections are the same as the data sets of two adjacent speed sections. There is intersection; calculate the average value of sample Gap attributes corresponding to one or more lane-changing sample data contained in the data set of each speed section, and obtain the lane-changing Gap template corresponding to the data set of each speed section; The lane-changing Gap template corresponding to the data set of the speed segment is obtained, and the Gap template set corresponding to the multiple lane-changing sample data and the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed are obtained. In the embodiment of this application, after sending the Gap template set to the target vehicle, the target vehicle can obtain multiple lane change sample data and then determine the Gap template set, which can better enable the target vehicle to determine a more suitable set during the subsequent lane change process. A collection of Gap templates for self-cars. Among them, when the vehicle lane changing device determines the lane changing Gap template corresponding to each speed segment in the Gap template set, it can first count the sample Gap attributes contained in all lane changing sample data corresponding to each speed segment, and according to the speed range The sample Gap attribute determines the preset lane change information within the speed range. Based on more sample data of lane changing, statistically calculate the Gap attributes of the lane changing Gap, and give the coarse-grained preset Gap attributes of the passing vehicles under different speed ranges, which further improves the comfort of the vehicle changing lanes in automatic driving. The flexibility and stability have improved the user’s ride experience.

In a possible implementation manner, after said dividing the multiple lane-changing sample data into multiple data sets of different speed segments according to the magnitude of the vehicle speed corresponding to each lane-changing sample data, further Including: deleting the sample lane change Gap corresponding to one or more lane change sample data contained in each data set of the multiple data sets of different speed segments and the lane change samples that do not meet the three sigma 3sigma criterion among the sample Gap attributes data. In the embodiments of this application, the three sigma criterion is to assume that a set of test data contains only random errors, and calculate and process them to obtain the standard deviation, and determine an interval with a certain probability. It is considered that any error that exceeds this interval is not random. The error is a gross error, and the data containing the error should be eliminated. Therefore, by deleting the sample road data that does not meet the three sigma criterion in each data set in the multiple data sets of different speed segments, each data can be obtained The collection of corresponding Gap templates for lane changing more accurately helps the target vehicle to accurately and efficiently select a safer and more comfortable lane changing Gap when changing lanes.

In a third aspect, an embodiment of the present application provides a vehicle lane changing device, including:

The first acquiring unit is used to acquire the current speed of the target vehicle, the N lane-changing gaps on the target lane, and the Gap attribute corresponding to each lane-changing gap, where the target lane is the target vehicle to which the target vehicle will change lanes. Lane, the lane-changing Gap is the gap between two adjacent vehicles on the target lane, and the Gap attribute includes the Gap length of the corresponding lane-changing Gap, and the distance between the corresponding lane-changing Gap and the target vehicle Or Multiple, the first vehicle is the previous vehicle in the lane where the target vehicle is currently located, and N is an integer greater than or equal to 1;

The template unit is used to obtain M lane-changing Gap templates matching the current speed from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed. Each lane change Gap template in the lane change Gap template includes a preset lane change Gap and a preset Gap attribute, the preset Gap attribute is the Gap attribute corresponding to the preset lane change Gap, where M is greater than or equal to 1 Integer

The second acquiring unit is configured to acquire a target lane-changing Gap and a target lane-changing Gap template from the N lane-changing Gap and the M lane-changing Gap templates, wherein the Gap attribute corresponding to the target lane-changing Gap is the same as The preset Gap attribute corresponding to the target lane change Gap template has the highest similarity;

The control unit is configured to control the target vehicle to change lanes to the target lane change Gap according to the target lane change Gap template.

In a possible implementation manner, the second acquiring unit is specifically configured to: calculate the Gap attribute of each lane-changing gap in the N lane-changing gaps and each lane-changing gap template in the M lane-changing gaps. The similarity between the preset Gap attributes of the lane Gap template; after sorting the similarities, the pair of lane-changing Gap and lane-changing Gap templates with the highest similarity are obtained as the target lane-changing Gap and the target lane-changing Gap template .

In a possible implementation manner, the device further includes: a first calculation unit, configured to obtain the data from the Gap template set according to the mapping relationship between each lane-changing Gap template and the vehicle speed in the Gap template set. After the M lane-changing Gap templates matched by the current speed, determine the probability that the target vehicle matches each lane-changing Gap template of the M lane-changing Gap templates according to the current speed; the second acquisition The unit is further specifically configured to: calculate each of the N lane-changing gaps based on the standardized Euclidean distance evaluation method based on the probability that the target vehicle matches each lane-changing gap template of the M lane-changing gap templates The similarity between the Gap attribute of the lane-changing Gap and the preset Gap attribute of each lane-changing Gap template in the M lane-changing Gap templates.

In a possible implementation manner, the target lane-changing Gap template further includes a preset lane-changing trajectory; the control unit is specifically configured to according to the Gap attribute of the target lane-changing Gap and the preset lane-changing trajectory , Determining the lane-changing time and lane-changing trajectory of the target vehicle; controlling the target vehicle to change lanes from the current lane to the target lane-changing Gap according to the lane-changing time and the lane-changing trajectory.

In a possible implementation manner, the apparatus further includes: a receiving unit, configured to receive and save the set of Gap templates sent by the service device.

In a fourth aspect, an embodiment of the present application provides a vehicle lane changing device, including:

The sending unit is configured to send a set of Gap templates to a target vehicle, where the set of Gap templates is used by the target vehicle according to the mapping relationship between each lane-changing Gap template in the set of Gap templates and the vehicle speed, from the Obtain M lane-changing Gap templates matching the current speed of the target vehicle from the Gap template set. Each lane-changing Gap template in the M lane-changing Gap templates includes preset lane-changing gaps and preset Gap attributes, so The preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, and the Gap attribute includes the Gap length corresponding to the preset lane-changing Gap, the distance between the corresponding preset lane-changing Gap and the lane-changing vehicle, The speed difference between the corresponding preset lane-changing Gap and the lane-changing vehicle, the distance between the lane-changing vehicle and the first vehicle, and the speed difference between the lane-changing vehicle and the first vehicle The first vehicle is the previous vehicle in the lane where the lane-changing vehicle is currently located, and the target vehicle belongs to the lane-changing vehicle, where M is an integer greater than or equal to 1;

The M lane-changing Gap templates are used for the target vehicle to obtain the target lane-changing Gap template and the target lane-changing Gap from the M lane-changing Gap templates and the N lane-changing Gaps in the target lane, wherein the The preset Gap attribute corresponding to the target lane-changing Gap template has the highest similarity with the Gap attribute corresponding to the target lane-changing Gap. The target lane is the lane to which the target vehicle will change lanes, and the lane-changing Gap is the The gap between two adjacent vehicles on the target lane.

In a possible implementation, the device further includes: a third acquiring unit, configured to acquire multiple lane-changing sample data before sending the Gap template set to the target vehicle, wherein each lane-changing sample data is associated with one Corresponding to the vehicle speed, each lane change sample data includes a sample lane change Gap and a sample Gap attribute, the sample Gap attribute is the Gap attribute corresponding to the sample lane change Gap; The size of the vehicle speed corresponding to the lane sample data, the multiple lane-changing sample data are respectively divided into multiple data sets of different speed segments, wherein the data of each speed segment in the multiple data sets of different speed segments The set has an intersection with the data sets of two adjacent speed sections; the second calculation unit is used to calculate the average value of the sample Gap attribute corresponding to one or more lane-changing sample data contained in the data set of each speed section, Obtain the lane-changing Gap template corresponding to the data set of each speed section; the fourth obtaining unit is configured to obtain the lane-changing Gap template corresponding to the data set of each speed section to obtain the lane-changing Gap template corresponding to the multiple lane-changing sample data. The Gap template set and the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed.

In a possible implementation manner, the device further includes: a deleting unit configured to divide the multiple lane change sample data into multiple lane change sample data according to the magnitude of the vehicle speed corresponding to each lane change sample data. After the data sets of different speed sections are deleted, the sample lane change gap corresponding to one or more lane change sample data contained in each data set of the multiple different speed section data sets and the sample gap attributes do not satisfy the three requirements. Lane change sample data based on Sigma 3sigma criterion.

In a fifth aspect, an intelligent vehicle is characterized by comprising a processor, a memory, and a communication interface, wherein the memory is used to store information sending program code, and the processor is used to call the vehicle driving control program code to execute The method described in the first aspect.

In a sixth aspect, an embodiment of the present application provides a service device, the service device includes a processor, and the processor is configured to support the service device to implement corresponding functions in the vehicle driving control method provided in the second aspect. The service device may also include a memory, which is used for coupling with the processor, and stores the necessary program instructions and data of the service device. The service device may also include a communication interface for the service device to communicate with other devices or a communication network.

In a seventh aspect, the present application provides a chip system that includes a processor for supporting the service device to implement the functions involved in the above-mentioned first aspect, for example, generating or processing the vehicle lane changing method in the above-mentioned first aspect The information involved. In a possible design, the chip system further includes a memory, and the memory is used to store program instructions and data necessary for the data sending device. The chip system can be composed of chips, or include chips and other discrete devices.

In an eighth aspect, the present application provides a chip system that includes a processor for supporting a service device to implement the functions involved in the second aspect, for example, generating or processing the vehicle lane change method in the second aspect The information involved. In a possible design, the chip system further includes a memory, and the memory is used to store program instructions and data necessary for the data sending device. The chip system can be composed of chips, or include chips and other discrete devices.

In a ninth aspect, an embodiment of the present application provides a computer-readable storage medium for storing computer software instructions used for the vehicle driving control device provided in the above-mentioned first aspect, which includes instructions for executing the design in the above-mentioned first aspect program of.

In a tenth aspect, an embodiment of the present application provides a computer-readable storage medium for storing computer software instructions used in a service device provided in the above second aspect, which includes instructions for executing the design in the above second aspect program.

In an eleventh aspect, an embodiment of the present application provides a computer program, the computer program including instructions, when the computer program is executed by a computer, the computer can execute the process executed by the vehicle lane changing device in the first aspect.

In a twelfth aspect, embodiments of the present application provide a computer program, the computer program including instructions, when the computer program is executed by a computer, the computer can execute the process executed by the service device in the second aspect.

Description of the drawings

In order to more clearly describe the technical solutions in the embodiments of the present application or the background art, the following will describe the drawings that need to be used in the embodiments of the present application or the background art.

FIG. 1A is a schematic diagram of the architecture of a vehicle driving control system provided by an embodiment of the present application.

Fig. 1B is a schematic structural diagram of another vehicle driving control system provided by an embodiment of the present application.

Fig. 2A is a functional block diagram of a smart vehicle 002 provided by an embodiment of the present application.

Fig. 2B is a schematic structural diagram of a vehicle lane changing device provided by an embodiment of the present application.

FIG. 2C is a functional block diagram of another smart vehicle 002 provided by an embodiment of the present application.

Fig. 2D is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application.

FIG. 3A is a schematic flowchart of a vehicle lane changing method provided by an embodiment of the present application.

FIG. 3B is a schematic diagram of a scenario in which a service device monitors a certain road section according to an embodiment of the present application.

Fig. 3C is a schematic diagram of a process for screening sample lane change data provided by an embodiment of the present application.

FIG. 3D is a schematic flowchart of a data set for dividing different speed segments based on vehicle speed according to an embodiment of the present application.

FIG. 3E is a schematic diagram of a data set that divides different speed segments based on vehicle speed according to an embodiment of the present application.

FIG. 3F is a schematic diagram of a data set of different speed segments after screening provided by an embodiment of the present application.

FIG. 3G is a schematic diagram of a process for acquiring N lane-changing gaps on a target lane according to an embodiment of the present application.

FIG. 3H is a schematic diagram of Gap attributes of a lane-changing Gap provided in an embodiment of the present application.

FIG. 3I is a schematic diagram of a vehicle-mounted screen for controlling a target vehicle to change lanes from a current lane to a target lane-changing Gap in an application scenario according to an embodiment of the present application.

FIG. 3J is a schematic diagram of a scene that is applied to the vehicle lane changing to the target lane changing Gap of FIG. 3I according to an embodiment of the present application.

Fig. 4A is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application.

FIG. 4B is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application.

Fig. 5A is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application.

Fig. 5B is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application.

Detailed ways

The embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

The terms "first" and "second" in the specification and claims of the application and the drawings are used to distinguish different objects, rather than to describe a specific sequence. In addition, the terms "including" and "having" and any variations of them are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes unlisted steps or units, or optionally also includes Other steps or units inherent to these processes, methods, products or equipment.

The reference to "embodiments" herein means that a specific feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art clearly and implicitly understand that the embodiments described herein can be combined with other embodiments.

The terms "component", "module", "system", etc. used in this specification are used to denote computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, the component may be, but is not limited to, a process, a processor, an object, an executable file, an execution thread, a program, and/or a computer running on a processor. Through the illustration, both the application running on the computing device and the computing device can be components. One or more components may reside in processes and/or threads of execution, and components may be located on one computer and/or distributed among two or more computers. In addition, these components can be executed from various computer readable media having various data structures stored thereon. The component may be based on, for example, data having one or more data packets (for example, data from two components interacting with another component in a local system, a distributed system, and/or a network, for example, the Internet that interacts with other systems through signals) Signals are communicated through local and/or remote processes.

First of all, some terms in this application are explained to facilitate the understanding of those skilled in the art.

(1) Electronic Control Unit (ECU), which is the abbreviation of Electronic Control Unit. The function of the electronic control unit is to calculate, process, and judge the information input by the air flow meter and various sensors according to the programs and data in its memory, and then output instructions to provide a certain width of electrical pulse signal to the fuel injector to control fuel injection quantity. The electronic control unit is composed of a microcomputer, input, output and control circuits.

(2) The world coordinate system is the absolute coordinate system of the system. Before the user coordinate system is established, the coordinates of all points on the screen are determined by the origin of the coordinate system.

(3) The Ackerman principle. The basic point of the Ackerman principle is: when a car is driving (straight driving and turning), the trajectory of each wheel must fully conform to its natural trajectory, so as to ensure that the tires and The ground is in pure rolling without slipping.

(4) Three sigma (3sigma) criterion, also known as Laida criterion, is to first assume that a set of test data contains only random errors, calculate and process them to obtain the standard deviation, and determine an interval according to a certain probability. The error in this interval is not a random error but a gross error, and the data containing this error should be eliminated.

(5) Road Side Unit (RSU), which can be composed of a high-gain directional beam control read-write antenna and a radio frequency controller. The high-gain directional beam control read-write antenna is a microwave transceiver module, responsible for signal and data transmission/reception, modulation/demodulation, encoding/decoding, encryption/decryption; the radio frequency controller controls the transmission and reception of data and processes the upper computer Module for sending and receiving information.

(6) && can be used as a logical AND operator, which means logical and (and). When the results of the expressions on both sides of the operator are true, the entire operation result is true. Otherwise, as long as one of them is false, then The result is false.

Secondly, based on the corresponding application scenarios in this application, and also in order to facilitate the understanding of the embodiments of this application,

In order to facilitate the understanding of the embodiments of the present application, one of the vehicle driving control system architectures based on the embodiments of the present application will be described below. Please refer to FIG. 1A. FIG. 1A is a schematic structural diagram of a vehicle driving control system provided by an embodiment of the present application. The architecture of the vehicle driving control system in this application may include the service device 001 and the smart vehicle 002 in FIG. 1A, where the service device 001 and the smart vehicle 002 can communicate through the network, so that the service device 001 monitors that the smart vehicle 002 changes from the current lane. Road to the target lane. It is understandable that please refer to FIG. 1B, which is a schematic diagram of the architecture of another vehicle driving control system provided by an embodiment of the present application. The service device 001 can simultaneously monitor multiple smart vehicles 002 in the coverage area of the service device 001.

Service equipment 001, the service equipment 001 can be installed on the roadside, using dedicated short-range communication technology (Dedicated Short Range Communication, DSRC) to communicate with the onboard unit (OBU, On Board Unit) to realize vehicle identification, speed detection, etc. The service device; the service device 001 can also be used to quickly acquire, process, analyze, and extract data, based on interactive data, to bring various conveniences to third parties. For example: backend server, cloud server, roadside unit, etc. In this application, the service device 001 can send a collection of Gap templates to the target vehicle, and can also provide the target vehicle with a road distribution map around the target vehicle. The road distribution map can include high-precision coordinates of the road distribution, as well as accurate road shapes. , And the slope, curvature, heading, elevation, roll and other data of each lane can also include the vehicle data in each lane. For example: The lane line between each lane and the lane provided by the road distribution map is a dashed line, a solid line or a double yellow line, the color of the line, the isolation zone of the road, the material of the isolation zone and even the arrow and text on the road The content and location will be described.

The intelligent vehicle 002 is a car that senses the road environment through the on-board sensor system, automatically plans the driving route and controls the vehicle to reach the predetermined target. Smart cars focus on the use of technologies such as computers, modern sensing, information fusion, communications, artificial intelligence, and automatic control. It is a high-tech complex integrating environmental perception, planning and decision-making, and multi-level assisted driving. Among them, the intelligent vehicle in this application may be a vehicle that mainly relies on a computer system-based intelligent driver in the vehicle to automatically change lanes, it may be an intelligent vehicle with an assisted driving system or a fully automatic driving system, or it may be Wheeled mobile robots, etc. When the smart vehicle 002 is driving on a road section within the coverage area of the service device, the electronic control unit in the smart vehicle can receive the Gap template set sent by the service device 001, and can also obtain the current speed of the target vehicle and the N number of lane changes on the target lane Gap and the Gap attribute corresponding to each lane-changing Gap, where the target lane is the lane to which the target vehicle will change lanes, and the lane-changing Gap is the gap between two adjacent vehicles on the target lane The Gap attribute includes the Gap length of the corresponding lane-changing Gap, the distance between the corresponding lane-changing Gap and the target vehicle, the speed difference between the corresponding lane-changing Gap and the target vehicle, and the target vehicle. One or more of the distance between the vehicle and the first vehicle and the speed difference between the target vehicle and the first vehicle, the first vehicle being the previous vehicle in the lane where the target vehicle is currently located , N is an integer greater than or equal to 1; According to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, obtain M lane-changing Gap templates matching the current speed from the Gap template set, Each lane-changing Gap template of the M lane-changing Gap templates includes a preset lane-changing Gap and a preset Gap attribute, the preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, where M is An integer greater than or equal to 1; the target lane-changing Gap and the target lane-changing Gap template are obtained from the N lane-changing Gap and the M lane-changing Gap templates, wherein the Gap attribute corresponding to the target lane-changing Gap is the same as The preset Gap attribute similarity corresponding to the target lane-changing Gap template is the highest; through the target lane-changing Gap template, the target vehicle is controlled to change lanes to the target lane-changing Gap.

It is understandable that the vehicle travel control system architecture in FIG. 1A and FIG. 1B is only an exemplary implementation in the embodiment of the present application, and the vehicle travel control system architecture in the embodiment of the present application includes but is not limited to the above vehicle travel Control system architecture.

Based on the foregoing vehicle travel control system architecture, an embodiment of the present application provides a smart vehicle 002 applied to the foregoing vehicle travel control system architecture. Please refer to FIG. 2A. Functional block diagram. In one embodiment, the smart vehicle 002 can be configured in a fully or partially autonomous driving mode. For example, the smart vehicle 002 can control itself while in the automatic driving mode, and can determine the current state of the vehicle and its surrounding environment through human operation, determine the possible behavior of at least one other vehicle in the surrounding environment, and determine the other The confidence level corresponding to the likelihood of the vehicle performing possible behaviors is used to control the smart vehicle 002 based on the determined information. When the smart vehicle 002 is in the automatic driving mode, the smart vehicle 002 can be set to operate without human interaction.

The smart vehicle 002 may include various subsystems, such as a travel system 202, a sensor system 204, a control system 206, one or more peripheral devices 208 and a power supply 210, a computer system 212, and a user interface 216. Optionally, the smart vehicle 002 may include more or fewer subsystems, and each subsystem may include multiple elements. In addition, each of the subsystems and components of the smart vehicle 002 can be wired or wirelessly interconnected.

The travel system 202 may include components that provide power to the smart vehicle 002. In one embodiment, the travel system 202 may include an engine 218, an energy source 219, a transmission 220, and wheels/tires 221. The engine 218 may be an internal combustion engine, an electric motor, an air compression engine, or a combination of other types of engines, such as a hybrid engine composed of a gas oil engine and an electric motor, or a hybrid engine composed of an internal combustion engine and an air compression engine. The engine 218 converts the energy source 219 into mechanical energy.

Examples of energy sources 219 include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electricity. The energy source 219 can also provide energy for other systems of the smart vehicle 002.

The transmission 220 can transmit the mechanical power from the engine 218 to the wheels 221. The transmission 220 may include a gearbox, a differential, and a drive shaft. In an embodiment, the transmission device 220 may also include other devices, such as a clutch. Among them, the drive shaft may include one or more shafts that can be coupled to one or more wheels 221.

The sensor system 204 may include several sensors that sense information about the environment around the smart vehicle 002. For example, the sensor system 204 may include a positioning system 222 (the positioning system may be a GPS system, a Beidou system or other positioning systems), an inertial measurement unit (IMU) 224, a radar 226, a laser rangefinder 228, and Camera 230. The sensor system 204 may also include sensors of the internal system of the smart vehicle 002 to be monitored (for example, an in-vehicle air quality monitor, a fuel gauge, an oil temperature gauge, etc.). Sensor data from one or more of these sensors can be used to detect objects and their corresponding characteristics (position, shape, direction, speed, etc.). Such detection and identification are the key functions for the safe operation of the autonomous intelligent vehicle 002.

The positioning system 222 can be used to estimate the geographic location of the smart vehicle 002. The IMU 224 is used to sense the position and orientation changes of the smart vehicle 002 based on inertial acceleration. In one embodiment, the IMU 224 may be a combination of an accelerometer and a gyroscope. For example: IMU 224 can be used to measure the curvature of smart vehicle 002.

The radar 226 can use radio signals to sense objects in the surrounding environment of the smart vehicle 002. In some embodiments, in addition to sensing the object, the radar 226 may also be used to sense the speed and/or heading direction of the object.

The laser rangefinder 228 can use laser light to sense objects in the environment where the smart vehicle 002 is located. In some embodiments, the laser rangefinder 228 may include one or more laser sources, laser scanners, and one or more detectors, as well as other system components.

The camera 230 can be used to capture multiple images of the surrounding environment of the smart vehicle 002. The camera 230 may be a still camera or a video camera.

The control system 206 controls the operation of the intelligent vehicle 002 and its components. The control system 206 may include various components, including a steering system 232, a throttle 234, a braking unit 236, a sensor fusion algorithm 238, a computer vision system 240, a route control system 242, and an obstacle avoidance system 244.

The steering system 232 is operable to adjust the forward direction of the smart vehicle 002. For example, in one embodiment, it may be a steering wheel system.

The throttle 234 is used to control the operating speed of the engine 218 and thereby control the speed of the smart vehicle 002.

The braking unit 236 is used to control the smart vehicle 002 to decelerate. The braking unit 236 may use friction to slow down the wheels 221. In other embodiments, the braking unit 236 may convert the kinetic energy of the wheels 221 into electric current. The braking unit 236 may also take other forms to slow down the rotation speed of the wheels 221 so as to control the speed of the smart vehicle 002.

The computer vision system 240 may be operable to process and analyze the images captured by the camera 230 in order to identify objects and/or features in the surrounding environment of the smart vehicle 002. The objects and/or features may include traffic signals, road boundaries and obstacles. The computer vision system 240 may use object recognition algorithms, Structure from Motion (SFM) algorithms, video tracking, and other computer vision technologies. In some embodiments, the computer vision system 240 may be used to map the environment, track objects, estimate the speed of objects, and so on.

The route control system 242 is used to determine the driving route of the smart vehicle 002. In some embodiments, the route control system 242 may combine data from the sensor 238, the GPS 222, and one or more predetermined maps to determine the driving route for the smart vehicle 002.

The obstacle avoidance system 244 is used to identify, evaluate and avoid or otherwise cross over potential obstacles in the environment of the smart vehicle 002.

Of course, in one example, the control system 206 may additionally or alternatively include components other than those shown and described. Alternatively, a part of the components shown above may be reduced.

The smart vehicle 002 interacts with external sensors, other vehicles, other computer systems, or users through peripheral devices 208. The peripheral device 208 may include a wireless communication system 246, an onboard computer 248, a microphone 250, and/or a speaker 252.

In some embodiments, the peripheral device 208 provides a means for the user of the smart vehicle 002 to interact with the user interface 216. For example, the onboard computer 248 can provide information to the user of the smart vehicle 002. The user interface 216 can also operate the onboard computer 248 to receive user input. The on-board computer 248 can be operated via a touch screen. In other cases, the peripheral device 208 may provide a means for the smart vehicle 002 to communicate with other devices located in the vehicle. For example, the microphone 250 may receive audio (eg, voice commands or other audio input) from the user of the smart vehicle 002. Similarly, the speaker 252 may output audio to the user of the smart vehicle 002.

The wireless communication system 246 may wirelessly communicate with one or more devices directly or via a communication network. For example, the wireless communication system 246 may use 3G cellular communication, such as CDMA, EVDO, GSM/GPRS, or 4G cellular communication, such as LTE. Or 5G cellular communication. The wireless communication system 246 may use WiFi to communicate with a wireless local area network (WLAN). In some embodiments, the wireless communication system 246 may directly communicate with the device using an infrared link, Bluetooth, or ZigBee. Other wireless protocols, such as: various vehicle communication systems. For example, the wireless communication system 246 may include one or more dedicated short-range communications (DSRC) devices, which may include vehicles and/or roadside stations. Public and/or private data communication between.

The power supply 210 can provide power to various components of the smart vehicle 002. In one embodiment, the power source 210 may be a rechargeable lithium ion or lead-acid battery. One or more battery packs of such batteries can be configured as a power source to provide power to various components of the smart vehicle 002. In some embodiments, the power source 210 and the energy source 219 may be implemented together, such as in some all-electric vehicles.

Part or all of the functions of the smart vehicle 002 are controlled by the computer system 212. The computer system 212 may include at least one processor 213 that executes instructions 215 stored in a non-transitory computer readable medium such as a data storage device 214. The computer system 212 may also be multiple computing devices that control individual components or subsystems of the smart vehicle 002 in a distributed manner.

The processor 213 may be any conventional processor, such as a commercially available CPU. Alternatively, the processor may be a dedicated device such as an ASIC or other hardware-based processor. Although FIG. 2A functionally illustrates the processor, memory, and other elements of the computer 120 in the same block, those of ordinary skill in the art should understand that the processor, computer, or memory may actually include Multiple processors, computers, or memories stored in the same physical enclosure. For example, the memory may be a hard disk drive or other storage medium located in a housing other than the computer 120. Therefore, a reference to a processor or computer will be understood to include a reference to a collection of processors or computers or memories that may or may not operate in parallel. Rather than using a single processor to perform the steps described here, some components such as steering components and deceleration components may each have its own processor that only performs calculations related to component-specific functions .

In the various aspects described herein, the processor may be located away from the vehicle and wirelessly communicate with the vehicle. In other aspects, some of the processes described herein are executed on a processor disposed in the vehicle and others are executed by a remote processor, including taking the necessary steps to perform a single manipulation.

In some embodiments, the data storage device 214 may include instructions 215 (eg, program logic), which may be executed by the processor 213 to perform various functions of the smart vehicle 002, including those described above. The data storage device 224 may also contain additional instructions, including sending data to, receiving data from, interacting with, and/or performing data on one or more of the propulsion system 202, the sensor system 204, the control system 206, and the peripheral device 208. Control instructions.

In addition to the instructions 215, the data storage device 214 may also store data, such as road maps, route information, the location, direction, and speed of the vehicle, and other such vehicle data, as well as other information. Such information may be used by the smart vehicle 002 and the computer system 212 during operation of the smart vehicle 002 in autonomous, semi-autonomous, and/or manual modes. For example: according to the Gap attributes corresponding to each of the N lane changing Gaps and the preset Gap attributes corresponding to each lane changing Gap template of the M lane changing Gap templates, the target lane changing Gap template and target are determined Change lanes Gap to enable smart vehicles to change lanes efficiently and safely.

The user interface 216 is used to provide information to or receive information from the user of the smart vehicle 002. Optionally, the user interface 216 may include one or more input/output devices in the set of peripheral devices 208, such as a wireless communication system 246, an in-vehicle computer 248, a microphone 250, and a speaker 252.

The computer system 212 may control the functions of the smart vehicle 002 based on inputs received from various subsystems (eg, the travel system 202, the sensor system 204, and the control system 206) and from the user interface 216. For example, the computer system 212 may utilize input from the control system 206 in order to control the steering unit 232 to avoid obstacles detected by the sensor system 204 and the obstacle avoidance system 244. In some embodiments, the computer system 212 is operable to provide control of many aspects of the smart vehicle 002 and its subsystems.

Optionally, one or more of the above-mentioned components may be installed or associated with the smart vehicle 002 separately. For example, the data storage device 214 may exist partially or completely separately from the smart vehicle 002. The above-mentioned components may be communicatively coupled together in a wired and/or wireless manner.

Optionally, the above-mentioned component is only an example. In actual applications, the components in each of the above-mentioned modules may be added or deleted according to actual needs. FIG. 2A should not be construed as a limitation to the embodiment of the present application.

A self-driving car traveling on the road, such as the smart vehicle 002 above, can recognize objects in its surrounding environment to determine the current speed adjustment. The object may be other vehicles, traffic control equipment, or other types of objects. In some examples, each recognized object can be considered independently, and based on the respective characteristics of the object, such as its current speed, acceleration, distance from the vehicle, etc., can be used to determine the speed to be adjusted by the self-driving car.

Optionally, the self-driving car smart vehicle 002 or the computing device associated with the self-driving smart vehicle 002 (such as the computer system 212, computer vision system 240, and data storage device 214 in FIG. 2A) may be based on the characteristics of the recognized object and The state of the surrounding environment (for example, traffic, rain, ice on the road, etc.) predicts the behavior of the identified object. Optionally, each recognized object depends on each other's behavior, so all recognized objects can also be considered together to predict the behavior of a single recognized object. The smart vehicle 002 can adjust its speed based on the predicted behavior of the identified object. In other words, an autonomous vehicle can determine what stable state the vehicle will need to adjust to (for example, accelerate, decelerate, or stop) based on the predicted behavior of the object. In this process, other factors may also be considered to determine the speed of the smart vehicle 002, such as the lateral position of the smart vehicle 002 on the road, the curvature of the road, the proximity of static and dynamic objects, and so on.

In addition to providing instructions to adjust the speed of the self-driving car, the computing device can also provide instructions to modify the steering angle of the smart vehicle 002 so that the self-driving car follows a given trajectory and/or maintains an object near the self-driving car ( For example, the safe horizontal and vertical distances of cars in adjacent lanes on the road.

The above-mentioned smart vehicle 002 can be a car, truck, motorcycle, bus, boat, airplane, helicopter, lawn mower, recreational vehicle, playground vehicle, construction equipment, tram, golf cart, train, and trolley, etc., The embodiments of this application do not make any special limitations.

It is understandable that the functional diagram of the smart vehicle in FIG. 2A is only an exemplary implementation in the embodiment of the present application, and the smart vehicle in the embodiment of the present application includes but is not limited to the above structure.

Please refer to Figure 2B. Figure 2B is a schematic structural diagram of a vehicle lane changing device provided by an embodiment of the present application. 203 is coupled with the system bus 205. The processor 203 may be one or more processors, where each processor may include one or more processor cores. The memory 235 can store related data information, and the memory 235 is coupled to the system bus 205. A display adapter (video adapter) 207, the display adapter can drive the display 209, and the display 209 is coupled to the system bus 205. The system bus 205 is coupled with an input/output (I/O) bus 213 through a bus bridge 201. The I/O interface 215 is coupled to the I/O bus. The I/O interface 215 communicates with various I/O devices, such as an input device 217 (such as a keyboard, a mouse, a touch screen, etc.), a media tray 221 (such as a CD-ROM, a multimedia interface, etc.). Transceiver 223 (can send and/or receive radio communication signals), camera 255 (can capture scene and dynamic digital video images) and external USB interface 225. Wherein, optionally, the interface connected to the I/O interface 215 may be a USB interface.

The processor 203 may be any conventional processor, including a reduced instruction set computing ("RISC") processor, a complex instruction set computing ("CISC") processor, or a combination of the foregoing. Alternatively, the processor may be a dedicated device such as an application specific integrated circuit ("ASIC"). Optionally, the processor 203 may be a neural network processor or a combination of a neural network processor and the foregoing traditional processors. For example, the processor 203 may determine the target lane change according to the Gap attribute corresponding to each lane-changing Gap of the N lane-changing gaps and the preset Gap attributes corresponding to each lane-changing Gap template of the M lane-changing Gap templates. The Gap template and the target lane-changing Gap calculate the appropriate refined lane-changing data (ie, lane-changing time and lane-changing trajectory) of the smart vehicle 002.

Optionally, in various embodiments described herein, the computer system 212 may be located far away from the autonomous driving vehicle, and may perform wireless communication with the autonomous driving vehicle. In other respects, some of the processes described herein are executed on a processor provided in an autonomous vehicle, and others are executed by a remote processor, including taking actions required to perform a single manipulation.

The computer system 212 can communicate with the software deployment server 249 through the network interface 229. The network interface 229 is a hardware network interface, such as a network card. The network 227 may be an external network, such as the Internet, or an internal network, such as an Ethernet or a virtual private network (VPN). Optionally, the network 227 may also be a wireless network, such as a WiFi network, a cellular network, and so on.

The transceiver 223 (which can send and/or receive radio communication signals) can pass various wireless communication methods such as not limited to the second generation mobile networks (2G), 3G, 4G, and 5G, or DSRC Technology, or Long Term Evolution-Vehicle (LTE-V), etc. Its main function is to receive information and data sent by external equipment, and send the information and data back to the external equipment when the vehicle is driving on the target road section Perform storage analysis.

The hard disk drive interface 231 is coupled to the system bus 205. The hardware drive interface 231 and the hard disk drive 233 are connected. The system memory 235 is coupled to the system bus 205. The data running in the system memory 235 may include the operating system 237 and application programs 243 of the computer system 212.

The memory 235 is coupled to the system bus 205. For example, the memory 235 in the present application may be used to store the driving information of vehicles on the target road section in the memory in a certain format.

The operating system includes Shell 239 and kernel 241. Shell 239 is an interface between the user and the kernel of the operating system. The shell is the outermost layer of the operating system. The shell manages the interaction between the user and the operating system: waiting for the user's input; interpreting the user's input to the operating system; and processing the output of various operating systems.

The kernel 241 is composed of those parts of the operating system that are used to manage memory, files, peripherals, and system resources. Directly interact with the hardware. The operating system kernel usually runs processes and provides inter-process communication, providing CPU time slice management, interrupts, memory management, IO management, and so on.

Application programs 243 include programs that control auto-driving cars, such as programs that manage the interaction between autonomous vehicles and obstacles on the road, programs that control the route or speed of autonomous vehicles, and programs that control interaction between autonomous vehicles and other autonomous vehicles on the road. . The application 243 also exists on the deploying server 249 system. In one embodiment, when the application 247 needs to be executed, the computer system 212 may download the application 243 from the deploying server 249. For example, the application 243 can determine the lane-changing time and lane-changing trajectory of the intelligent vehicle according to the target lane-changing Gap and the target lane-changing Gap template, and convert it into a dynamic model of vehicle engineering, such as a bicycle model or Ackerman model. Control the vehicle's line control command, that is, convert speed information and curvature information into accelerator pedal opening, and the angular speed information of the steering wheel controls the vehicle to change lanes from the current lane to the target lane change gap.

The sensor 253 is associated with the computer system 212. The sensor 253 is used to detect the environment around the computer system 212. For example, the sensor 253 can detect animals, cars, obstacles, and crosswalks. Further, the sensor can also detect the surrounding environment of the above-mentioned animals, cars, obstacles, and crosswalks, such as: the environment around the animals, for example, when the animals appear around them. Other animals, weather conditions, the brightness of the surrounding environment, etc. Optionally, if the computer system 212 is located on a self-driving car, the sensor may be a camera, an infrared sensor, a chemical detector, a microphone, etc.

Please refer to FIG. 2C, which is a functional block diagram of another smart vehicle 002 provided by an embodiment of the present application.

Among them, the functional block diagram of the smart vehicle 002 as shown in FIG. 2C mainly includes a sensor system 0021, a central computer system 0022, and a controller system 0023. in,

The sensor system 0021 is equivalent to the sensor system 204 shown in FIG. 2A, and is mainly used to load relevant data collected by related equipment such as monocular/binocular cameras, lidar/millimeter wave radar, GPS positioning, etc., to obtain environmental information, including vehicles Information (e.g., vehicle speed, vehicle location, vehicle distance, etc. on the target lane), road structure information, and vehicle status information (e.g., vehicle speed, vehicle location, etc.) of the vehicle. For example: the sensor system 0021 is responsible for the acquisition of camera data, radar data, high-precision positioning data and chassis information, which will not be repeated here.

The central computer system 0022 is equivalent to the computer system 212 shown in FIG. 2A, and includes: a perception fusion module, a prediction module, a decision-making module, a planning module, and a control module. Among them, the perception fusion module is mainly responsible for the recognition of lane lines, pedestrians, vehicles or other obstacles, etc.; the prediction module is mainly responsible for predicting the behavioral intention and future behavior of vehicles or obstacles around the target vehicle based on the obstacle information given by the perception fusion. Trajectory, such as: vehicle behavior intention prediction, vehicle trajectory prediction, road structure reasoning, etc.; the decision-making module is mainly responsible for horizontal behavior decision-making and vertical behavior decision-making based on the behavior intention and trajectory of obstacles around the self-vehicle, combined with the motion state of the self-vehicle, this application The active lane change Gap selection involved belongs to this module; the planning module is responsible for horizontal trajectory planning and longitudinal speed planning based on the obstacle information around the vehicle and the results of the decision module; the control module outputs control actuators based on the results of the planning module instruction. Therefore, the related description of each function in the central computer system 0022 may refer to the related description of the embodiment shown in FIG. 2A and the related description of the following embodiment shown in FIG. 3A, which will not be repeated here.

The controller system 0023 is equivalent to the control system 206 shown in FIG. 2A, and is responsible for controlling the steering, braking, and accelerator of the vehicle based on the results of the control module. Therefore, the related description of each function in the controller system 0023 may refer to the related description of the embodiment shown in FIG. 2A and the related description of the following embodiment shown in FIG. 3A, which will not be repeated here.

It is understandable that the functional diagrams of the smart vehicle in FIG. 2A and FIG. 2C are only two exemplary implementations in the embodiment of the present application, and the smart vehicle in the embodiment of the present application includes but is not limited to the above structure.

Optionally, the selection of the lane change gap in this application is implemented in the decision-making module of the central computer system. Please refer to Figure 2D. Figure 2D is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application. The central computer system shown is 0022,

Among them, the decision-making module block in the vehicle lane changing device is mainly used to solve the problem of how to select the target lane changing gap in the autonomous driving vehicle in the active lane changing scene. As shown in Figure 2D, the decision-making module receives the environmental information provided by the perception fusion module and the prediction module, including vehicle or obstacle information (eg, vehicle speed, vehicle position, vehicle distance, etc. on the target lane), road structure information, and self-vehicle State information (such as vehicle speed, vehicle position, etc.) of the self-vehicle, and then control the longitudinal and lateral behavior of the self-vehicle through longitudinal and lateral decisions.

The decision-making module includes a vertical decision-making module and a horizontal decision-making module. Among them, the horizontal decision includes four functional modules: lane change intention, target lane selection, lane change gap selection, and lane change time. Lane change intention is to decide whether the vehicle has the intention to change lanes based on the received information; target lane selection is to select the target lane based on the lane change intention and road structure information; lane change gap is to select the appropriate lane change and insert on the target lane Car clearance; lane change time decides the time to start the lane change and the time to cancel the lane change to ensure the safety of the lane change process. Longitudinal decision-making is used to determine the longitudinal behavior of the vehicle, such as the acceleration or deceleration of the vehicle.

It is understandable that the structural schematic diagrams of the vehicle lane changing device in FIGS. 2B and 2D are only two exemplary implementations in the embodiments of the present application, and the vehicle lane changing device structure in the embodiments of the present application includes but is not limited to the above structures .

Based on the vehicle lane-changing system architecture provided in Figure 1A, the smart vehicle provided in Figure 2A or Figure 2C and the vehicle lane-changing device for smart vehicles provided in Figure 2B or Figure 2D, combined with the vehicle lane-changing method provided in this application, The technical issues raised in the application are analyzed and resolved in detail.

Please refer to FIG. 3A. FIG. 3A is a schematic flowchart of a vehicle lane changing method provided by an embodiment of the present application. The method can be applied to the vehicle lane changing system architecture shown in FIG. 1A and the intelligence provided in FIG. 2A or FIG. 2C. In the vehicle and the vehicle lane changing device provided in FIG. 2B or FIG. 2D, the service device 001 shown in FIG. 1A can be used to support and execute steps S301-step S305 of the method flow shown in FIG. The vehicle lane-changing device 10 can be used to support and execute steps S306 to S309 of the method flow shown in FIG. 3A.

Step S301: Obtain multiple lane change sample data.

Specifically, the service device acquires multiple lane changing sample data, where each lane changing sample data corresponds to a vehicle speed, and each lane changing sample data includes the sample lane changing gap and the sample gap attribute, and the sample gap The attribute is the Gap attribute corresponding to the sample change Gap. Among them, the service device can be a roadside unit next to the lane, which is used to monitor the driving status of vehicles on a certain road segment or monitor the driving status of vehicles in all road segments in an area, and then statistically process the driving data of the vehicles to obtain the Gap template set. ; It can also be a cloud server, which is used to receive a large amount of vehicle lane change data and then statistically process the vehicle lane change data to obtain a collection of Gap templates and so on.

Please refer to FIG. 3B. FIG. 3B is a schematic diagram of a scenario in which a service device monitors a certain road section according to an embodiment of the present application. It is understandable that, as shown in Figure 3B, a schematic diagram of a service device monitoring the vehicle to change lanes, when the service device monitors the target vehicle to change lanes (for example, when the vehicle is monitored to turn on the turn signal, the lateral displacement is When within the preset distance range), the service device can obtain the lane-changing sample data when the vehicle changes lanes, and save the lane-changing sample data, so as to obtain the Gap template set according to the multiple lane-changing sample data. Wherein, it should be noted that the sample change Gap is the lane change Gap to which the vehicle changes, and the sample Gap attribute is the Gap attribute corresponding to the lane change Gap, where the Gap attribute includes the Gap length corresponding to the lane change Gap, the The distance between the corresponding lane-changing Gap and the lane-changing vehicle, the speed difference between the corresponding lane-changing Gap and the lane-changing vehicle, the distance between the lane-changing vehicle and the vehicle before the lane-changing vehicle, and the One or more of the speed difference between the target vehicle and the previous vehicle, where the Gap attribute can also refer to the description of step 306 below.

It should also be noted that when acquiring multiple lane-changing sample data, since the vehicle will send a turn signal during the lane-changing process, and the vehicle will have a lateral displacement, it can be used as a judgment condition for judging whether it is a lane-changing. Please refer to FIG. 3C. FIG. 3C is a schematic diagram of a process for screening sample lane change data provided by an embodiment of the present application. As shown in Figure 3C, first, the service equipment screens out possible lane change time points and sample lane change data from the driving data within the monitoring range; then calculates the lateral displacement of vehicles near that point in time; finally judges the magnitude of the lateral displacement Whether it’s a lane change, if it is, record the data at that time point as the sample lane change data, and save the sample Gap attribute of the sample lane change data (using the information of the front and rear cars of the lane change gap selected for this lane change, etc., calculate The sample Gap attribute of the selected lane-changing Gap at the time of the lane-changing time); otherwise, the lane-changing data is discarded. It is understandable that by making a lateral displacement judgment at all time points when the turn signal signal appears, the data set related to the lane change can be obtained.

Step S302: According to the size of the vehicle speed corresponding to each lane change sample data, the multiple lane change sample data are respectively divided into multiple data sets of different speed segments.

Specifically, the service device divides the multiple lane change sample data into multiple data sets of different speed segments according to the size of the vehicle speed corresponding to each lane change sample data in the multiple lane change sample data. In the multiple data sets of different speed sections, the data set of each speed section has an intersection with the data sets of two adjacent speed sections. For example, please refer to FIG. 3D. FIG. 3D is a schematic flowchart of a data set for dividing different speed segments based on vehicle speed according to an embodiment of the present application. As shown in Figure 3D, based on the set initial speed v ₀ and the speed difference △v, the vehicle speed of multiple lane-changing sample data is divided into: v ₀ , v ₀ +△v with the speed difference △v as the arithmetic difference , V ₀ +2△v, v ₀ +3△v,...v ₀ +n△v, where n is the number of divided data sets and also the number of corresponding Gap templates for lane change.

Please refer to FIG. 3E. FIG. 3E is a schematic diagram of a data set that divides different speed segments based on vehicle speed according to an embodiment of the present application. As shown in Figure 3E, each lane-changing sample data of multiple lane-changing sample data whose vehicle speed _{is within the range of v 0} ±Δv can be divided into a data set of the same speed section. The data set contains all sample data. Among them, when dividing the data set, the constructed lane change Gap template needs to cover all speeds within the speed range, so it is judged that the two adjacent data sets after screening need to have an intersection, that is, the following conditions need to be met:

This holds true for n greater than 0. in,

Is the average value of vehicle speed corresponding to all lane-changing sample data in the nth data set,

All lane-changing sample data corresponding to the vehicle speed standard deviation in the nth data set. If the above conditions are not met, you can re-divide, reduce the speed difference Δv, and continue to cycle until the above conditions are met. Satisfying this condition can divide the speed range more reasonably, so that the target vehicle can obtain the most similar change to the template, which improves the safety of the target vehicle when changing lanes.

Optionally, each data subset can be filtered based on the 3sigma criterion. That is, the sample lane change gap corresponding to one or more lane change sample data contained in each data set in the multiple data sets of different speed segments and the lane change samples that do not meet the three sigma 3sigma criterion in the sample Gap attribute are deleted data. Among them, the three sigma criterion is to assume that a set of test data contains only random errors, calculate and process them to obtain the standard deviation, and determine an interval with a certain probability. It is believed that any error exceeding this interval is not a random error but a gross error. , The data containing this error should be eliminated.

Please refer to FIG. 3F. FIG. 3F is a schematic diagram of a data set of different speed segments after screening according to an embodiment of the present application. As shown in Figure 3F, the preliminary classification and screening of each data set, the vehicle speed according to the 3sigma criterion (the 3sigma criterion screening process is not repeated here), the data is filtered, and a new average speed in the data set is obtained.

Divide the data set of points, and get the average value of the vehicle speed in each new data set

Standard deviation from vehicle speed

(As shown in Figure 3G). Therefore, delete the sample Gap attribute corresponding to one or more lane change sample data contained in each data set of the multiple data sets of different speed segments, and the lane change sample corresponding to the sample road data that does not meet the three sigma criterion. According to the data, a more accurate lane-changing gap template corresponding to each data set can be obtained, which helps the target vehicle to accurately and efficiently select a safer and more comfortable lane-changing gap when changing lanes.

Step S303: Calculate the average value of the sample Gap attributes corresponding to one or more lane-changing sample data contained in the data set of each speed section, and obtain the lane-changing Gap template corresponding to the data set of each speed section.

Specifically, the service device calculates the average value of the sample Gap attributes corresponding to one or more lane-changing sample data included in the data set of each speed section, and obtains the lane-changing Gap template corresponding to the data set of each speed section. Perform statistical calculations on the sample Gap attribute corresponding to one or more lane-changing sample data contained in the data set of each speed section, and determine the preset lane-changing Gap corresponding to the data set of each speed section, and the corresponding The preset Gap attribute, wherein the preset lane-changing Gap corresponding to the data set of each speed segment is the Gap to which the lane-changing vehicle in the speed segment will change lanes, and the preset Gap attribute is the preset lane-changing Gap The corresponding Gap attribute, the Gap attribute includes the Gap length corresponding to the preset lane-changing Gap, the distance between the corresponding preset lane-changing Gap and the lane-changing vehicle, the corresponding preset lane-changing Gap and the lane-changing One or more of the speed difference between the vehicles, the distance between the lane-changing vehicle and the first vehicle, and the speed difference between the lane-changing vehicle and the first vehicle, the first vehicle is The previous vehicle in the lane where the lane-changing vehicle is currently located, wherein the target vehicle belongs to the lane-changing vehicle. The preset Gap attribute corresponding to the data set of each speed segment may include the average value or the average value and the standard deviation determined by the sample Gap attribute of one or more lane-changing sample data contained in the data set of each speed segment, so as to obtain The lane-changing Gap template Mn corresponding to the data set Sn of each speed segment, and the mapping relationship between each lane-changing Gap template and the vehicle speed. Among them, the mapping relationship between each lane-changing Gap template and the vehicle speed includes the applicable speed range of the lane-changing Gap template Mn and the speed range of the data set Sn of each speed segment.

Step S304: Obtain the Gap template set corresponding to multiple lane-changing sample data and the mapping relationship between each lane-changing Gap template and the vehicle speed in the Gap template set according to the lane-changing Gap template corresponding to the data set of each speed section.

Specifically, the service device obtains the Gap template set corresponding to multiple lane-changing sample data and the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed according to the lane-changing Gap template corresponding to the data set of each speed section. After obtaining the lane-changing Gap template corresponding to the data set of each speed section, the lane-changing Gap template corresponding to the data set of each speed section is assembled into a Gap template set. Each lane-changing Gap template in the Gap template set is different from The speed segment corresponds, that is, each vehicle speed has at least one lane change Gap template corresponding to it.

Step S305: Send a collection of Gap templates to the target vehicle

Specifically, the service device sends a Gap template set to the target vehicle according to the Gap template set, which is used by the target vehicle to determine a target lane-changing Gap template according to the Gap template set, so as to pass the target lane-changing Gap template , Controlling the target vehicle to change lanes to the target lane.

Step S306: Obtain the current speed of the target vehicle, the N lane-changing gaps on the target lane, and the Gap attribute corresponding to each lane-changing gap.

Specifically, the vehicle lane-changing device on the target vehicle acquires the current speed of the target vehicle, the N lane-changing gaps on the target lane, and the Gap attributes corresponding to each lane-changing gap, where the target lane is the target vehicle The lane to be changed, the lane change Gap is the gap between two adjacent vehicles on the target lane, the Gap attribute includes the Gap length of the corresponding lane change Gap, the corresponding lane change Gap and the target The distance between vehicles, the speed difference between the corresponding lane-changing Gap and the target vehicle, the distance between the target vehicle and the first vehicle, and the speed difference between the target vehicle and the first vehicle In one or more of them, the first vehicle is the previous vehicle in the lane where the target vehicle is currently located, and N is an integer greater than or equal to 1. When the target vehicle needs to change lanes from the current lane to the target lane, the target vehicle needs to first determine the N lane change gaps in the target lane on the target lane. The lane change gaps are used for the target vehicle to perform the lane change operation. For example: please refer to FIG. 3G, which is a schematic diagram of a process for acquiring N lane-changing gaps on a target lane provided by an embodiment of the present application. First, the vehicle lane-changing device determines the target lane selected for lane-changing according to the turn signal or indicator signal of the target vehicle, and then, as shown in Fig. 3G, according to the obstacle information on the target lane and the current road information, Filter out all the vehicles in the target lane from the vehicle conditions around the vehicle; secondly, based on the selected vehicles in the target lane, determine the N lane change gaps and each of the N lane change gaps in the target lane. Gap attribute corresponding to Gap. Optionally, the N lane changing gaps may constitute an optional lane changing gap set. Among them, the optional lane-changing gap set consisting of N lane-changing gaps is available:

Means, where,

Gap is the Gap attribute of the Nth lane-changing gap, and G _list is a set of optional lane-changing gaps.

Please refer to FIG. 3H. FIG. 3H is a schematic diagram of Gap attributes of a lane-changing Gap provided in an embodiment of the present application. In this embodiment of the application, data can be processed according to the Gap attributes (such as Gap speed, Gap position, etc.) corresponding to each of the N lane-changing gaps to obtain the corresponding Gap of each lane-changing Gap in the N lane-changing gaps. Gap attributes. For example: as shown in Figure 3H, the Gap attribute of the j-th lane-changing Gap among the N lane-changing gaps can be used

Express,

Where j = 1, 2, 3...N, l _g represents the Gap length of the n-th lane-changing Gap, that is, the distance between the preceding and following Gap; d _g represents the corresponding lane-changing Gap and the The distance between the target vehicles, that is, the distance between the target vehicle and the vehicle in front of the j-th lane-changing Gap; Δv _gb and Δv _gf represent the speed difference between the corresponding lane-changing Gap and the target vehicle, that is, the current speed of the target vehicle v _e j-th lane change Gap vehicle in front of the vehicle speed v _gf speed difference Δv _gf, the current speed of the target vehicle v _e j-th lane change Gap rear vehicle vehicle speed v _gb speed difference Δv _gb; d represents a distance between the target vehicle and the first vehicle; Δv _f represents the first vehicle and the target vehicle speed v _f of the speed difference Δv _f; v _e represents the current target vehicle speed, the The first vehicle is the previous vehicle in the lane where the target vehicle is currently located.

From the related description of the above steps S302-S303, it can be seen that the lane change Gap template Mn of the data set Sn of each speed segment includes the preset Gap attribute, which may be the value of all lane change sample data in the speed segment. The average and/or standard deviation of the Gap attribute of the sample, therefore, according to

The representation of Mn, one of the representations of Mn can be expressed as:

And the applicable speed range of the Gap template Mn corresponding to the data set of each speed section is:

Among them, && can be used as a logical AND operator, which means logical and (and). When the results of the expressions on both sides of the operator are true, the entire operation result is true, otherwise, as long as one of the two sides is false, the result is Is false.

in,

Is the average value _{of l g} of the sample Gap attributes in the lane change data of all samples in the data set Sn;

Is the standard deviation _{of l g} of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the average value _{of the d g} of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the standard deviation _{of the d g} of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the average value _{of the Δv gf} of the sample Gap attributes in the lane change data of all samples in the data set Sn;

Is the standard deviation _{of the Δv gf} of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the average value _{of Δv gb} of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the standard deviation _{of the Δv gb} of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the average value of d of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the standard deviation of d of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the average value _{of Δv f} of the sample Gap attributes in the lane change data of all samples in the data set Sn;

Is the standard deviation _{of the Δv f} of the sample Gap attribute in the lane change data of all samples in the data set Sn;

Is the average value _{of v e} of the sample Gap attributes in the lane change data of all samples in the data set Sn;

All data sets Sn for the samples v _e Gap sample standard deviation lane change attribute data.

Optionally, another way of expressing Mn may also be to include only the average value of the sample Gap attributes in the sample lane change data, and the corresponding similarity calculation method is only determined by comparing the average value.

Optionally, before acquiring the current speed of the target vehicle, the N lane-changing gaps on the target lane, and the Gap attribute corresponding to each lane-changing gap, the vehicle lane-changing device may also obtain a lane-changing signal, which is used When instructing the target vehicle to start a lane change operation, including a lane change request signal or a driving obstacle signal, the lane change request signal is used to request a lane change operation, and the driving obstacle signal is used to indicate that it is impossible to continue driving in the current lane Perform a lane change operation. For example: when the driving speed of the first vehicle is much lower than the driving speed of the target vehicle, the lane can be changed to a side lane for driving experience. Another example: when receiving a driving obstacle signal, when acquiring the current speed of the target vehicle and N lane-changing gaps on the target lane, the obstacles on the target lane (such as pedestrians, construction areas, etc.) can also be correspondingly determined Based on the current road information (such as: location information, speed information, etc.), select N lane changing gaps without obstacles to prevent the vehicle from colliding with obstacles when changing lanes and causing safety accidents.

Step S307: According to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, obtain M lane-changing Gap templates matching the current speed from the Gap template set.

Specifically, the vehicle lane changing device obtains M lane changing Gap templates matching the current speed from the Gap template set according to the mapping relationship between each lane changing Gap template in the Gap template set and the vehicle speed. Each lane-changing Gap template in the two lane-changing Gap templates includes a preset lane-changing Gap and a preset Gap attribute, the preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, where M is greater than or equal to An integer of 1. Among them, the Gap template set contains lane-changing Gap templates corresponding to different speed sections, and the data set of each speed section in the data sets of multiple different speed sections has an intersection with the data sets of two adjacent speed sections, so , The same vehicle speed corresponds to at least one lane-changing gap template, the target vehicle can filter out M lane-changing gaps matching the current speed from the Gap template set according to the current speed and the mapping relationship between each lane-changing gap template and the vehicle speed template.

Optionally, the vehicle lane-changing device can receive the transmission from the service device before obtaining M lane-changing Gap templates matching the current speed from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed Gap template collection. It is possible to directly filter out M lane changing Gap templates that match the current speed of the target vehicle through the directly obtained Gap template collection. Among them, because the lane-changing Gap template is determined based on multiple lane-changing sample data in the speed section corresponding to the lane-changing Gap template, the Gap template set gives the situation of multiple lane-changing Gap templates corresponding to different speed sections. Next, the preset Gap attributes included in the lane-changing Gap template can further improve the comfort and stability of vehicle traffic in autonomous driving, and enhance the user's riding experience.

Optionally, the target vehicle can re-update the Gap template set after autonomously acquiring multiple lane change data of its own vehicle, which can better enable the target vehicle to determine a Gap template set more suitable for its own vehicle during subsequent lane changes. . Further improve the comfort and stability of vehicle traffic in autonomous driving, and enhance the user's riding experience.

Optionally, the smart vehicle can also receive a collection of Gap templates corresponding to the model information of the smart vehicle sent by the service device, so that different vehicle models can correspond to different lane changing Gap templates, which improves the safety of the vehicle when changing lanes. For example: Even when a large truck and a small car are running at the same speed, the corresponding Gap template for lane change is different.

Step S308: Obtain a target lane change Gap and a target lane change Gap template from the N lane change Gap and the M lane change Gap templates.

Specifically, the vehicle lane changing device may obtain a target lane changing gap and a target lane changing gap template from the N lane changing gaps and the M lane changing gap templates, wherein the Gap attribute corresponding to the target lane changing gap The preset Gap attribute corresponding to the target lane change Gap template has the highest similarity. For example, during driving, in order to prevent the target vehicle from colliding with other vehicles, the target vehicle needs to maintain a certain safe distance from other surrounding vehicles. Therefore, according to the Gap attribute of the lane-changing gap, the most efficient one is selected from multiple lane-changing gap templates. A suitable lane-changing Gap template (target lane-changing Gap template), the lane-changing Gap template can enable the vehicle to have more appropriate and more refined driving prior information (such as: preset Gap attributes), so that passengers have Higher comfort and smooth ride experience. For example, the target vehicle can have a more precise adjustment range when adjusting the speed of the vehicle during the lane change process according to the preset Gap attributes.

In a possible implementation manner, according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, after obtaining M lane-changing Gap templates matching the current speed from the Gap template set, It also includes: according to the current speed, respectively determining the probability that the target vehicle matches each lane change Gap template of the M lane change Gap templates; and calculating each lane change of the N lane change Gap templates The similarity between the Gap attributes of the Gap and the preset Gap attributes of each lane-changing Gap template in the M lane-changing Gap templates includes: according to the target vehicle and each of the M lane-changing Gap templates The matching probability of the lane-changing Gap template is calculated based on the standardized Euclidean distance evaluation method to calculate the Gap attribute of each lane-changing Gap in the N lane-changing Gap and the prediction of each lane-changing Gap template in the M lane-changing Gap templates. Let the similarity between Gap attributes. For example, the probability of a target vehicle at 21.5km/h matching the lane-changing Gap template corresponding to 20km/h-22km/h is greater than the probability of matching the lane-changing Gap template corresponding to 21km/h-24km/h. Therefore, it is necessary to first determine the probability that the target vehicle matches each of the lane-changing Gap templates in the lane-changing Gap templates, and then calculate the similarity with each template based on the matching probability, which is beneficial to the target vehicle to more accurately screen out the target. Change lanes Gap to make lane change driving safer and more comfortable.

Among them, all the optional N lane-changing gaps and M lane-changing gap templates matching the current speed are calculated based on the standardized Euler distance. For example, the following standardized Euler distance formula can be used to reduce The influence between different dimensions.

Above

Is the similarity between the j-th lane-changing Gap and the i-th lane-changing Gap template determined according to the standardized Euler distance formula, where j is the j-th lane-changing Gap among the N lane-changing Gaps, and i represents the M lane-changing Gap. The i-th Gap template in the Gap template.

It should be noted that the data set of each speed section in multiple data sets of different speed sections has an intersection with the data sets of two adjacent speed sections. If the vehicle speed is in the data set of the minimum speed section and the maximum speed section For the speed at both ends, there is only one Gap template selected for lane change, so it only needs to calculate the similarity with the Gap template for lane change once, and it is the final similarity, namely

In the case that there are two selected Gap templates for changing lanes, similarity calculations need to be performed with both templates, and the final similarity is the weight of the two. The probability that the speed of the vehicle belongs to the two templates is different. The 3sigma criterion is used in the above screening process. Therefore, based on the normal distribution, the probability of belonging to the two Gap templates for changing lanes can be calculated as:

Therefore, for example, when there are two selected Gap templates for changing lanes, the similarities can be respectively

and

The similarity between the j-th lane-changing Gap and the two lane-changing Gap templates is as follows:

Among them, p _i is the probability that the target vehicle belongs to the i-th lane-changing Gap template among the M lane-changing Gap templates. Through the sorting method (there are many sorting methods, and will not be repeated here), it is easy to find the highest similarity from the similarity of all N lane-changing gaps and M lane-changing gap templates, and then obtain the target lane-changing gap.

Optionally, a target lane change gap with the highest similarity to all lane change Gap templates of M lane change Gap templates can be determined from N lane change Gap templates, and then all lane change Gap templates from M lane change Gap templates A target lane-changing Gap template with the highest similarity to the target lane-changing Gap is determined, which is not specifically limited in the embodiment of the present application.

Optionally, when the two lane-changing gaps have the same similarity as the lane-changing gap template, the lane change with the smallest speed change rate when the target vehicle changes from the current lane to the target lane can be determined according to the Gap attributes of the lane-changing gap Gap changes to Gap for the goal.

Step S309: Control the target vehicle to change lanes to the target lane-changing Gap through the target lane-changing Gap template.

Specifically, the vehicle lane-changing device can control the target vehicle to change lanes to the target lane-changing Gap through the target lane-changing Gap template.

Optionally, the target lane-changing Gap template further includes a preset lane-changing trajectory; the controlling the target vehicle to change lanes to the target lane-changing Gap through the target lane-changing Gap template includes: according to the target The Gap attribute of the lane-changing Gap and the preset lane-changing trajectory determine the lane-changing time and lane-changing trajectory of the target vehicle; according to the lane-changing time and the lane-changing trajectory, the target vehicle is controlled to be controlled by the The current lane changes to the target lane change Gap. In the implementation of the embodiment of this application, after the target lane-changing Gap and target lane-changing Gap template are filtered out, the target vehicle can determine the specific lane-changing time and lane-changing trajectory of the target vehicle according to the Gap attribute and the preset lane-changing trajectory, so that the target The vehicle changes lanes accurately and efficiently.

Optionally, the vehicle lane change device may send the lane change trajectory and the Gap attribute of the target lane change Gap to a service device, so that the service device updates lane change Gap templates corresponding to multiple data sets of different speed segments.

Optionally, the lane-changing time and lane-changing trajectory of the target vehicle can be planned directly according to the Gap attribute of the target lane-changing Gap; according to the lane-changing time and the lane-changing trajectory, the target vehicle is controlled to be routed by The current lane changes to the target lane change Gap.

Through the embodiments of the present application, when the vehicle changes from the current lane to the target lane, the vehicle can actively select the appropriate insertion gap Gap (ie, the lane change gap) in the target lane, and change lanes to the target lane through the insertion gap to ensure In the course of the target vehicle changing lanes, the active selection of the road section where the vehicle is about to change lanes can better meet the driving needs of the target vehicle, and avoid the default selection of the nearest lane change gap to the target vehicle, and the target cannot be guaranteed. The vehicle changes lanes safely and comfortably. Among them, when the vehicle insertion gap is actively selected, the preset Gap attributes corresponding to multiple lane-changing gap templates are compared with the Gap attributes corresponding to multiple lane-changing gaps, and the pair with the highest similarity is selected as the target lane-changing gap. Template and target lane-changing Gap, so that the target vehicle can pass the target lane-changing Gap template to safely and efficiently insert the vehicle to the target lane-changing Gap. For example, the target vehicle can select the front or rear lane change gap according to the lane change gap template to realize the acceleration or deceleration of the vehicle and merge into the target lane to ensure that the target vehicle can safely change lanes on the road without overspeeding or The collision caused a safety accident and improved the driving safety of the vehicle. Moreover, by comparing the Gap attribute similarity between the lane-changing Gap template and the lane-changing Gap, the lane-changing Gap with the highest similarity among the existing lane-changing Gap templates is selected from multiple lane-changing Gaps. The lane-changing gap for the target vehicle can ensure that the vehicle does not need to detect the driving state of the vehicle in the target lane for a long time during the lane-changing process. It only needs to determine multiple lane-changing gaps and directly compare the lane-changing gap template to determine multiple lane-changes. The target lane-changing Gap in the Gap reduces the driving parameters of a large number of calibrated vehicles during the lane-changing process, and improves the efficiency of the target vehicle in selecting the lane-changing Gap. Secondly, according to the Gap attributes of the lane-changing Gap, the most suitable lane-changing Gap template (target lane-changing Gap template) is selected from multiple lane-changing Gap templates. This lane-changing Gap template can make the vehicle have more suitable and refined Under the premise of advanced driving information (such as preset Gap attributes), passengers have a higher comfort and smooth ride experience. For example, the target vehicle can have a more precise adjustment range when adjusting the speed of the vehicle during the lane change process according to the preset Gap attributes.

Please refer to FIG. 3I and FIG. 3J. FIG. 3I is a schematic diagram of an on-board screen for controlling a target vehicle to change lanes from a current lane to a target lane change gap in an application scenario according to an embodiment of the present application. FIG. 3J is a schematic diagram of a scene that is applied to the vehicle lane changing to the target lane changing Gap of FIG. 3I according to an embodiment of the present application.

Application scenario: When the target vehicle is driving along four lanes, there is no vehicle in front of the target vehicle. If it is determined that the target vehicle needs to change lanes, the following steps are taken:

1. Obtain the current driving state of the target vehicle. The driving state includes: the speed of the target vehicle, the target lane to which the target vehicle is to be changed, and the four lane-changing gaps on the target lane and the Gap attribute corresponding to each lane-changing gap. As shown in Figure 3I (1), there are four lane-changing Gaps (Gap1, Gap2, Gap3, Gap4) in the target lane, which can be used for lane-changing by the target vehicle. In the road condition display diagram, the five-pointed star represents Target vehicle.

2. The target vehicle matches the current speed of its own vehicle with the pre-obtained Gap template set, and obtains two matching Gap templates from the Gap template set. As shown in (1) in Figure 3I, there are two Gap template sets. Two lane-changing Gap templates (template 1 and template 2) match the speed of the target vehicle.

3. Perform similarity matching between the two lane-changing Gap templates obtained above and the four lane-changing Gaps, and obtain the pair of lane-changing Gap templates and lane-changing Gaps with the highest similarity, as shown in (2) in Figure 3I, Gap2 The highest similarity with template 2 is 89%.

4. Through the obtained target lane-changing Gap template (template 2), control the target vehicle to change lanes to the target lane-changing Gap (Gap2). As shown in Figure 3J, the target vehicle is controlled to accelerate from the current lane to Gap2.

The foregoing describes the method of the embodiment of the present application in detail, and the relevant device of the embodiment of the present application is provided below.

Please refer to FIG. 4A, which is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application. The vehicle lane changing device 30 may include a first acquiring unit 401, a template unit 402, a second acquiring unit 403, and a control The unit 404 may also include a first calculating unit 405 and a receiving unit 406. Among them, the detailed description of each unit is as follows.

The first acquiring unit 401 is configured to acquire the current speed of the target vehicle, the N lane-changing gaps on the target lane, and the Gap attribute corresponding to each lane-changing gap, where the target lane is where the target vehicle will change lanes The lane change Gap is the gap between two adjacent vehicles on the target lane, and the Gap attribute includes the Gap length of the corresponding lane change Gap, and the distance between the corresponding lane change Gap and the target vehicle One of the distance between the corresponding lane change Gap and the target vehicle, the distance between the target vehicle and the first vehicle, and the speed difference between the target vehicle and the first vehicle Or more, the first vehicle is the previous vehicle in the lane where the target vehicle is currently located, and N is an integer greater than or equal to 1;

The template unit 402 is configured to obtain M lane-changing Gap templates matching the current speed from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, and the M Each lane-changing Gap template in the lane-changing Gap template includes a preset lane-changing Gap and a preset Gap attribute. The preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, where M is greater than or equal to 1. Integer

The second acquiring unit 403 is configured to acquire a target lane-changing Gap and a target lane-changing Gap template from the N lane-changing Gap and the M lane-changing Gap templates, wherein the Gap attribute corresponding to the target lane-changing Gap The preset Gap attribute corresponding to the target lane change Gap template has the highest similarity;

The control unit 404 is configured to control the target vehicle to change lanes to the target lane change Gap according to the target lane change Gap template.

In a possible implementation manner, the second acquiring unit 403 is specifically configured to: calculate the Gap attribute of each lane-changing gap in the N lane-changing gaps and each of the M lane-changing gap templates The similarity between the preset Gap attributes of the lane-changing Gap template; after sorting the similarities, the pair of lane-changing Gap and lane-changing Gap templates with the highest similarity are obtained as the target lane-changing Gap and the target lane-changing Gap template.

In a possible implementation manner, the device further includes: a first calculation unit 405, configured to obtain and from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed After the M lane-changing Gap templates matched by the current speed, determine the probability that the target vehicle matches each lane-changing Gap template of the M lane-changing Gap templates according to the current speed; the second The acquiring unit 403 is further specifically configured to: according to the probability that the target vehicle matches each lane-changing gap template of the M lane-changing gap templates, and based on a standardized Euclidean distance evaluation method, calculate the number of lane-changing gaps. The similarity between the Gap attribute of each lane-changing Gap and the preset Gap attribute of each lane-changing Gap template in the M lane-changing Gap templates.

In a possible implementation manner, the target lane-changing Gap template further includes a preset lane-changing trajectory; the control unit 404 is specifically configured to change according to the Gap attribute of the target lane-changing Gap and the preset lane-changing Trajectory, determining the lane-changing time and lane-changing trajectory of the target vehicle; according to the lane-changing time and the lane-changing trajectory, controlling the target vehicle to change lanes from the current lane to the target lane-changing gap.

In a possible implementation manner, the apparatus further includes: a receiving unit 406, configured to receive and save the Gap template set sent by the service device.

It should be noted that the functions of each functional unit in the vehicle lane changing device 20 described in the embodiment of the present application can refer to the related description of step S306 to step S309 in the method embodiment described in FIG. 3A, and will not be omitted here. Go into details.

Please refer to FIG. 4B. FIG. 4B is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application. The vehicle lane changing device 40 may be applied to the service equipment 001 described in FIG. 1A and FIG. 1B, and includes a sending unit 410 may further include a third acquiring unit 420, a dividing unit 430, a second calculating unit 440, a fourth acquiring unit 450, and a deleting unit 460. Among them, the detailed description of each unit is as follows.

The sending unit 410 is configured to send a set of Gap templates to a target vehicle, where the set of Gap templates is used by the target vehicle according to the mapping relationship between each lane-changing Gap template in the set of Gap templates and the speed of the vehicle. Acquiring M lane-changing Gap templates matching the current speed of the target vehicle from the Gap template set, each lane-changing Gap template in the M lane-changing Gap templates includes a preset lane-changing gap and preset Gap attributes, The preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, and the Gap attribute includes the Gap length corresponding to the preset lane-changing Gap, and the distance between the corresponding preset lane-changing Gap and the lane-changing vehicle , The speed difference between the corresponding preset lane-changing Gap and the lane-changing vehicle, the distance between the lane-changing vehicle and the first vehicle, and the speed difference between the lane-changing vehicle and the first vehicle The first vehicle is the previous vehicle in the lane where the lane-changing vehicle is currently located, and the target vehicle belongs to the lane-changing vehicle, where M is an integer greater than or equal to 1;

In a possible implementation, the device further includes: a third acquiring unit 420, configured to acquire multiple lane change sample data before sending the Gap template set to the target vehicle, wherein each lane change sample data is Corresponds to a vehicle speed, each lane change sample data includes a sample lane change Gap and a sample Gap attribute, the sample Gap attribute is the Gap attribute corresponding to the sample lane change Gap; the dividing unit 430 is configured to Each lane-changing sample data corresponds to the size of the vehicle speed, the multiple lane-changing sample data are respectively divided into a plurality of data sets of different speed sections, wherein each speed section in the plurality of data sets of different speed sections The data sets of both have an intersection with the data sets of two adjacent speed sections; the second calculation unit 440 is used to calculate the sample Gap attribute corresponding to one or more lane-changing sample data contained in the data set of each speed section The average value is used to obtain the lane change Gap template corresponding to the data set of each speed section; the fourth obtaining unit 450 is configured to obtain the multiple lane change Gap templates corresponding to the data set of each speed section. The Gap template set corresponding to the sample data and the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed.

In a possible implementation manner, the device further includes: a deleting unit 460, configured to divide the plurality of lane-changing sample data at most according to the magnitude of the vehicle speed corresponding to each lane-changing sample data. After the data sets of different speed sections are deleted, the sample lane change gap corresponding to one or more lane change sample data contained in each data set of the multiple different speed section data sets and the sample gap attributes are not satisfied The sample data of lane change based on the 3sigma criterion.

It should be noted that the functions of each functional unit in the vehicle lane changing device 20 described in the embodiment of the present application can refer to the related description of step S301 to step S305 in the method embodiment described in FIG. 3A, and will not be omitted here. Go into details.

As shown in FIG. 5A, FIG. 5A is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application. The device 50 includes at least one processor 501, at least one memory 502, and at least one communication interface 503. In addition, the device may also include general components such as antennas, which will not be described in detail here.

The processor 501 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of the above program programs.

The communication interface 503 is used to communicate with other devices or communication networks, such as Ethernet, wireless access network (RAN), core network, wireless local area networks (WLAN), etc.

The memory 502 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (RAM), or other types that can store information and instructions The dynamic storage device can also be electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), CD-ROM (Compact Disc Read-Only Memory, CD-ROM) or other optical disc storage, optical disc storage (Including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or can be used to carry or store desired program codes in the form of instructions or data structures and can be used by a computer Any other media accessed, but not limited to this. The memory can exist independently and is connected to the processor through a bus. The memory can also be integrated with the processor.

Wherein, the memory 502 is used to store application program codes for executing the above solutions, and the processor 501 controls the execution. The processor 501 is configured to execute application program codes stored in the memory 502.

The code stored in the memory 502 can execute the vehicle driving control method provided in FIG. 3A, such as obtaining the current speed of the target vehicle, the N lane-changing gaps on the target lane, and the Gap attribute corresponding to each lane-changing gap, where the target The lane is the lane to which the target vehicle will change lanes, the lane change Gap is the gap between two adjacent vehicles on the target lane, and the Gap attribute includes the Gap length of the corresponding lane change Gap, and the corresponding The distance between the lane-changing Gap and the target vehicle, the speed difference between the corresponding lane-changing Gap and the target vehicle, the distance between the target vehicle and the first vehicle, and the distance between the target vehicle and the first vehicle One or more of the speed difference between a vehicle, the first vehicle is the previous vehicle in the lane where the target vehicle is currently located, and N is an integer greater than or equal to 1; according to each of the Gap template sets The mapping relationship between lane-changing Gap templates and vehicle speeds, M lane-changing Gap templates matching the current speed are obtained from the Gap template set, and each lane-changing Gap template of the M lane-changing Gap templates includes a preset Set lane-changing Gap and preset Gap attributes, the preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, where M is an integer greater than or equal to 1; Obtaining the target lane-changing Gap and the target lane-changing Gap template from the M lane-changing Gap templates, wherein the Gap attribute corresponding to the target lane-changing Gap and the preset Gap attribute corresponding to the target lane-changing Gap template have the highest similarity; Through the target lane-changing Gap template, the target vehicle is controlled to change lanes to the target lane-changing Gap.

It should be noted that the function of each functional unit in the vehicle lane changing device 30 described in the embodiment of the present application can refer to the related description of step S306 to step S309 in the method embodiment described in FIG. 3A, which will not be omitted here. Go into details.

As shown in FIG. 5B, FIG. 5B is a schematic structural diagram of another vehicle lane changing device provided by an embodiment of the present application. The device 60 includes at least one processor 511, at least one memory 512, and at least one communication interface 513. In addition, the device may also include general components such as antennas, which will not be described in detail here.

The processor 511 may be a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the programs in the above scheme.

The communication interface 513 is used to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), core network, wireless local area networks (WLAN), etc.

The memory 512 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (RAM), or other types that can store information and instructions The dynamic storage device can also be electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), CD-ROM (Compact Disc Read-Only Memory, CD-ROM) or other optical disc storage, optical disc storage (Including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or can be used to carry or store desired program codes in the form of instructions or data structures and can be used by a computer Any other media accessed, but not limited to this. The memory can exist independently and is connected to the processor through a bus. The memory can also be integrated with the processor.

Wherein, the memory 512 is used to store application program codes for executing the above solutions, and the processor 511 controls the execution. The processor 511 is configured to execute the application program code stored in the memory 512.

The code stored in the memory 512 can execute the vehicle driving control method provided in FIG. 3A, such as sending a set of Gap templates to a target vehicle, where the set of Gap templates is used for the target vehicle to change according to each of the set of Gap templates. The mapping relationship between lane Gap templates and vehicle speeds, obtaining M lane-changing Gap templates matching the current speed of the target vehicle from the Gap template set, and each lane-changing Gap template of the M lane-changing Gap templates Including a preset lane changing gap and a preset gap attribute, the preset gap attribute being the Gap attribute corresponding to the preset lane changing gap, the gap attribute including the gap length corresponding to the preset lane changing gap, the corresponding preset gap Set the distance between the lane-changing Gap and the lane-changing vehicle, the speed difference between the corresponding preset lane-changing Gap and the lane-changing vehicle, the distance between the lane-changing vehicle and the first vehicle, and the lane-changing One or more of the speed difference between the vehicle and the first vehicle, where the first vehicle is the previous vehicle in the lane where the lane-changing vehicle is currently located, and the target vehicle belongs to the lane-changing vehicle , Where M is an integer greater than or equal to 1; the M lane-changing gap templates are used by the target vehicle to obtain the target lane-changing gap from the M lane-changing gap templates and the N lane-changing gaps on the target lane Gap template and target lane-changing Gap, wherein the preset Gap attribute corresponding to the target lane-changing Gap template has the highest similarity with the Gap attribute corresponding to the target lane-changing Gap, and the target lane is that the target vehicle will change lanes To the lane, the lane change Gap is the gap between two adjacent vehicles on the target lane.

In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in an embodiment, reference may be made to related descriptions of other embodiments.

It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited by the described sequence of actions. Because according to this application, some steps may be performed in other order or at the same time. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

In the several embodiments provided in this application, it should be understood that the disclosed device may be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the above-mentioned units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components can be combined or integrated. To another system, or some features can be ignored, or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical or other forms.

The units described above as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.

In addition, the functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.

If the above integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present application essentially or the part that contributes to the existing technology or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , Including several instructions to enable a computer device (which may be a personal computer, a server or a network device, etc., specifically a processor in a computer device) to execute all or part of the steps of the above methods of the various embodiments of the present application. Among them, the aforementioned storage media may include: U disk, mobile hard disk, magnetic disk, optical disk, read-only memory (Read-Only Memory, abbreviation: ROM) or Random Access Memory (Random Access Memory, abbreviation: RAM), etc. A medium that can store program codes.

As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions recorded in the embodiments are modified, or some of the technical features are equivalently replaced; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

A method for changing lanes of a vehicle, which is characterized in that it includes:

Acquire the current speed of the target vehicle, the N lane-changing gaps in the target lane, and the Gap attribute corresponding to each lane-changing gap, where the target lane is the lane to which the target vehicle will change lanes, and the lane-changing gap Is the gap between two adjacent vehicles on the target lane, and the Gap attributes include the Gap length of the corresponding lane-changing Gap, the distance between the corresponding lane-changing Gap and the target vehicle, and the corresponding lane-changing Gap. One or more of the speed difference between the Gap and the target vehicle, the distance between the target vehicle and the first vehicle, and the speed difference between the target vehicle and the first vehicle, the first The vehicle is the previous vehicle in the lane where the target vehicle is currently located, and N is an integer greater than or equal to 1;

According to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, obtain M lane-changing Gap templates matching the current speed from the Gap template set, and each lane-changing Gap template in the M lane-changing Gap templates A lane-changing gap template includes a preset lane-changing Gap and preset Gap attributes, where the preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, where M is an integer greater than or equal to 1;

Obtain a target lane change Gap and a target lane change Gap template from the N lane change Gap and the M lane change Gap templates, wherein the Gap attribute corresponding to the target lane change Gap is the same as the target lane change Gap template The corresponding preset Gap attribute has the highest similarity;

Through the target lane-changing Gap template, the target vehicle is controlled to change lanes to the target lane-changing Gap.
The method according to claim 1, wherein the acquiring a target lane changing Gap and a target lane changing Gap template from the N lane changing Gap and the M lane changing Gap templates comprises:

Calculating the similarity between the Gap attribute of each lane-changing Gap in the N lane-changing gaps and the preset Gap attribute of each lane-changing Gap template in the M lane-changing Gap templates;

After sorting the similarities, a pair of lane-changing Gap and lane-changing Gap templates with the highest similarity are obtained as the target lane-changing Gap and the target lane-changing Gap template.
The method according to claim 1 or 2, characterized in that, according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed, the M that matches the current speed is obtained from the Gap template set. After a Gap template for changing lanes, it also includes:

According to the current speed, respectively determine the probability that the target vehicle matches each lane-changing Gap template of the M lane-changing Gap templates;

The calculating the similarity between the Gap attribute of each lane-changing Gap in the N lane-changing gaps and the preset Gap attribute of each lane-changing Gap template in the M lane-changing Gap templates includes:

According to the probability that the target vehicle matches each lane-changing gap template in the M lane-changing gap templates, and based on the standardized Euclidean distance evaluation method, calculate the Gap attribute of each lane-changing gap in the N lane-changing gaps and The similarity between the preset Gap attributes of each lane-changing Gap template in the M lane-changing Gap templates.
The method according to any one of claims 1-3, wherein the target lane-changing Gap template further comprises a preset lane-changing trajectory; and the target vehicle is controlled to change lanes through the target lane-changing Gap template Gap to the target lane change includes:

Determining the lane-changing time and lane-changing trajectory of the target vehicle according to the Gap attribute of the target lane-changing Gap and the preset lane-changing trajectory;

According to the lane change time and the lane change trajectory, the target vehicle is controlled to change lanes from the current lane to the target lane change Gap.
The method according to any one of claims 1-4, wherein the method further comprises:

Receive and save the Gap template set sent by the service device.
A method for changing lanes of a vehicle, which is characterized in that it includes:

Send a Gap template set to the target vehicle, where the Gap template set is used for the target vehicle to obtain from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed M lane-changing gap templates matching the current speed of the target vehicle, each lane-changing gap template of the M lane-changing gap templates includes a preset lane-changing gap and a preset gap attribute, the preset gap attribute Is the Gap attribute corresponding to the preset lane-changing Gap, and the Gap attribute includes the Gap length corresponding to the preset lane-changing Gap, the distance between the corresponding preset lane-changing Gap and the lane-changing vehicle, and the corresponding preset One or more of the speed difference between the lane-changing Gap and the lane-changing vehicle, the distance between the lane-changing vehicle and the first vehicle, and the speed difference between the lane-changing vehicle and the first vehicle The first vehicle is the previous vehicle in the lane where the lane-changing vehicle is currently located, and the target vehicle belongs to the lane-changing vehicle, where M is an integer greater than or equal to 1;

The M lane-changing Gap templates are used for the target vehicle to obtain the target lane-changing Gap template and the target lane-changing Gap from the M lane-changing Gap templates and the N lane-changing Gaps in the target lane, wherein the The preset Gap attribute corresponding to the target lane-changing Gap template has the highest similarity with the Gap attribute corresponding to the target lane-changing Gap. The target lane is the lane to which the target vehicle will change lanes, and the lane-changing Gap is the The gap between two adjacent vehicles on the target lane.
The method according to claim 6, characterized in that, before sending the Gap template set to the target vehicle, the method further comprises:

Acquire multiple lane changing sample data, where each lane changing sample data corresponds to a vehicle speed, and each lane changing sample data includes a sample lane changing gap and a sample gap attribute, and the sample gap attribute is the sample The Gap attribute corresponding to the Gap when changing lanes;

According to the size of the vehicle speed corresponding to each of the lane-changing sample data, the multiple lane-changing sample data are respectively divided into a plurality of data sets of different speed sections, wherein the data sets of the multiple different speed sections are The data set of each speed section has an intersection with the data sets of two adjacent speed sections;

Calculate the average value of the sample Gap attributes corresponding to one or more lane-changing sample data contained in the data set of each speed section, and obtain the lane-changing Gap template corresponding to the data set of each speed section;

According to the lane-changing Gap template corresponding to the data set of each speed segment, the Gap template set corresponding to the multiple lane-changing sample data and the relationship between each lane-changing Gap template and the vehicle speed in the Gap template set are obtained. Mapping relations.
The method according to claim 7, wherein the plurality of lane-changing sample data are respectively divided into a plurality of data sets of different speed segments according to the size of the vehicle speed corresponding to each of the lane-changing sample data After that, it also includes:

The sample lane change Gap corresponding to one or more lane change sample data contained in each data set in the multiple data sets of different speed segments and the lane change sample data that do not meet the three sigma and 3 sigma criteria in the sample Gap attribute are deleted.
A vehicle lane changing device is characterized in that it comprises:

The first acquiring unit is used to acquire the current speed of the target vehicle, the N lane-changing gaps on the target lane, and the Gap attribute corresponding to each lane-changing gap, where the target lane is the target vehicle to which the target vehicle will change lanes. Lane, the lane-changing Gap is the gap between two adjacent vehicles on the target lane, and the Gap attribute includes the Gap length of the corresponding lane-changing Gap, and the distance between the corresponding lane-changing Gap and the target vehicle Or Multiple, the first vehicle is the previous vehicle in the lane where the target vehicle is currently located, and N is an integer greater than or equal to 1;

The template unit is used to obtain M lane-changing Gap templates matching the current speed from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed. Each lane change Gap template in the lane change Gap template includes a preset lane change Gap and a preset Gap attribute, the preset Gap attribute is the Gap attribute corresponding to the preset lane change Gap, where M is greater than or equal to 1 Integer

The second acquiring unit is configured to acquire a target lane-changing Gap and a target lane-changing Gap template from the N lane-changing Gap and the M lane-changing Gap templates, wherein the Gap attribute corresponding to the target lane-changing Gap is the same as The preset Gap attribute corresponding to the target lane change Gap template has the highest similarity;

The control unit is configured to control the target vehicle to change lanes to the target lane change Gap according to the target lane change Gap template.
The device according to claim 9, wherein the second acquiring unit is specifically configured to:

Calculating the similarity between the Gap attribute of each lane-changing Gap in the N lane-changing gaps and the preset Gap attribute of each lane-changing Gap template in the M lane-changing Gap templates;

After sorting the similarities, a pair of lane-changing Gap and lane-changing Gap templates with the highest similarity are obtained as the target lane-changing Gap and the target lane-changing Gap template.
The device according to claim 9 or 10, wherein the device further comprises:

The first calculation unit is configured to obtain the M lane-changing Gap templates matching the current speed from the Gap template set according to the mapping relationship between each lane-changing Gap template in the Gap template set and the vehicle speed. The current speed, respectively determining the probability that the target vehicle matches each lane-changing Gap template of the M lane-changing Gap templates;

The second acquiring unit is further specifically configured to: according to the probability that the target vehicle matches each lane-changing Gap template of the M lane-changing Gap templates, and based on a standardized Euclidean distance evaluation method, calculate the N conversions The degree of similarity between the Gap attribute of each lane-changing Gap in the lane Gap and the preset Gap attributes of each lane-changing Gap template in the M lane-changing Gap templates.
The device according to any one of claims 9-11, wherein the target lane-changing Gap template further comprises a preset lane-changing trajectory;

The control unit is specifically configured to determine the lane-changing time and lane-changing trajectory of the target vehicle according to the Gap attribute of the target lane-changing Gap and the preset lane-changing trajectory;

According to the lane change time and the lane change trajectory, the target vehicle is controlled to change lanes from the current lane to the target lane change Gap.
The device according to any one of claims 9-12, wherein the device further comprises:

The receiving unit is configured to receive and save the Gap template set sent by the service device.
A vehicle lane changing device is characterized in that it comprises:

The sending unit is configured to send a set of Gap templates to a target vehicle, where the set of Gap templates is used by the target vehicle according to the mapping relationship between each lane-changing Gap template in the set of Gap templates and the vehicle speed, from the Obtain M lane-changing Gap templates matching the current speed of the target vehicle from the Gap template set. Each lane-changing Gap template in the M lane-changing Gap templates includes preset lane-changing gaps and preset Gap attributes, so The preset Gap attribute is the Gap attribute corresponding to the preset lane-changing Gap, and the Gap attribute includes the Gap length corresponding to the preset lane-changing Gap, the distance between the corresponding preset lane-changing Gap and the lane-changing vehicle, The speed difference between the corresponding preset lane-changing Gap and the lane-changing vehicle, the distance between the lane-changing vehicle and the first vehicle, and the speed difference between the lane-changing vehicle and the first vehicle The first vehicle is the previous vehicle in the lane where the lane-changing vehicle is currently located, and the target vehicle belongs to the lane-changing vehicle, where M is an integer greater than or equal to 1;

The M lane-changing Gap templates are used for the target vehicle to obtain the target lane-changing Gap template and the target lane-changing Gap from the M lane-changing Gap templates and the N lane-changing Gaps in the target lane, wherein the The preset Gap attribute corresponding to the target lane-changing Gap template has the highest similarity with the Gap attribute corresponding to the target lane-changing Gap. The target lane is the lane to which the target vehicle will change lanes, and the lane-changing Gap is the The gap between two adjacent vehicles on the target lane.
The device according to claim 14, wherein the device further comprises:

The third acquiring unit is used to acquire multiple lane change sample data before sending the Gap template set to the target vehicle, wherein each lane change sample data corresponds to a vehicle speed, and each lane change sample data includes sample change Gap and a sample Gap attribute, where the sample Gap attribute is the Gap attribute corresponding to the sample change Gap;

The dividing unit is configured to divide the multiple lane change sample data into multiple data sets of different speed segments according to the magnitude of the vehicle speed corresponding to each lane change sample data, wherein the multiple different speeds The data collection of each speed segment in the data collection of the segments has an intersection with the data collections of two adjacent speed segments;

The second calculation unit is used to calculate the average value of sample Gap attributes corresponding to one or more lane-changing sample data contained in the data set of each speed section, and obtain the lane-changing Gap template corresponding to the data set of each speed section;

The fourth obtaining unit is configured to obtain the Gap template set corresponding to the multiple lane change sample data and each change in the Gap template set according to the lane change Gap template corresponding to the data set of each speed section. The mapping relationship between road Gap template and vehicle speed.
The device according to claim 15, wherein the device further comprises:

The deleting unit is configured to delete the plurality of different lane change sample data after dividing the plurality of lane change sample data into a plurality of data sets of different speed segments according to the magnitude of the vehicle speed corresponding to each lane change sample data. The sample lane change Gap corresponding to one or more lane change sample data contained in each data set of the speed segment data set and the lane change sample data that does not meet the three sigma criterion in the sample Gap attribute.
A computer storage medium, wherein the computer storage medium stores a computer program, which when executed by a processor implements the method according to any one of claims 1-8.
A computer program, characterized in that the computer program includes instructions, which when the computer program is executed by a computer, cause the computer to execute the method according to any one of claims 1-8.