Vehicle driving control method and device based on lane changing prediction, equipment and medium
By obtaining the position information of the vehicle ahead and predicting the lane change time point, and controlling the driving status of the vehicle, the problem of low accuracy of lane change prediction in the prior art is solved, and driving safety is improved.
Patent Information
- Application Number
- CN202411977622.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-31
- Publication Date
- 2025-03-18
AI Technical Summary
The existing automatic connected vehicle technology has low accuracy in lane change prediction and decision-making, resulting in limited driving safety.
By obtaining the position information of the car in front, determining the starting point and end point of the lane change prediction time, and predicting the lane change prediction time point of the car in front frame by frame within this time interval, thereby controlling the driving state of the car.
It effectively improves the accuracy of lane change prediction and decision-making, and thus improves driving safety.
Smart Images
Figure CN119636801A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of intelligent transportation technology, and in particular to a vehicle driving control method and device, equipment and medium based on lane change prediction. Background Art
[0002] In related technologies, automatic networked vehicles are not only believed to significantly improve road traffic safety, but also to effectively alleviate traffic congestion, improve traffic flow stability, and reduce environmental pollution caused by exhaust emissions. Especially in terms of traffic safety, automatic networked vehicles can reduce traffic accidents caused by human errors. In order to reduce problems such as reaction delays and information asymmetry in human driving, the advanced driver assistance system (ADAS) in autonomous driving technology significantly improves the driving safety of the vehicle by sensing, processing and responding to surrounding environmental information. However, the existing technology only focuses on the perception data of the vehicle itself, resulting in low accuracy in lane change prediction and decision-making.
[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the invention
[0004] The main purpose of the embodiments of the present application is to propose a vehicle driving control method and device, equipment and medium based on lane change prediction, which can effectively improve the accuracy of lane change prediction and decision-making, thereby improving driving safety.
[0005] To achieve the above object, one aspect of an embodiment of the present application provides a vehicle driving control method based on lane change prediction, the method comprising the following steps:
[0006] Obtaining the first position information of the preceding vehicle;
[0007] Determining, according to the first position information, that the preceding vehicle satisfies a first change state, and generating a lane change prediction time starting point of the preceding vehicle;
[0008] Acquire second position information of the preceding vehicle after the starting point of the lane change prediction time;
[0009] Determining, according to the second position information, that the preceding vehicle satisfies a second change state, and generating a predicted lane change time end point of the preceding vehicle;
[0010] Predicting the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time ending point;
[0011] The driving state of the vehicle is controlled according to the lane change prediction time point.
[0012] In some embodiments, determining, according to the first position information, that the preceding vehicle satisfies a first change state and generating a lane change prediction start time of the preceding vehicle includes:
[0013] When it is determined according to the first position information that the front vehicle has both a lateral position greater than the lane line and a lateral position less than the lane line in a continuous time sequence, a lane change prediction time starting point of the front vehicle is generated according to the continuous time sequence.
[0014] In some embodiments, the lane change prediction starting time of the preceding vehicle is as follows:
[0015]
[0016] In the formula, T lc1 Indicates the lane change prediction starting point of the preceding vehicle; t1 and t2 represent T lc1 x(t1) and x(t2) are the horizontal coordinates of the t1th frame and the t2th frame; x lane is the lateral position of the current lane line.
[0017] In some embodiments, determining that the preceding vehicle satisfies the second change state according to the second position information and generating a predicted lane change time end point of the preceding vehicle includes:
[0018] It is determined according to the second position information that the lateral displacement direction of the leading vehicle is different from the lane-changing direction for the first time, and a predicted lane-changing time end point of the leading vehicle is generated according to a corresponding moment of the second position information.
[0019] In some embodiments, the lane change prediction time end point is as follows:
[0020]
[0021] In the formula, T lc2 Indicates the end point of lane change prediction time when the lane change prediction point is detected; t3 and t4 respectively represent T lc2 x(t3) and x(t4) are the horizontal coordinates of the t3th frame and the t4th frame; x lane is the horizontal coordinate of the current lane line; x Tlc1 The vehicle lateral coordinate of the starting point of the lane change prediction time.
[0022] In some embodiments, the predicting the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time end point includes:
[0023] Calculating the first lateral displacement change value of the leading vehicle frame by frame within the long time window according to the leading vehicle position information corresponding to the lane change prediction time starting point, until the calculation time point reaches the lane change prediction time end point and the calculation is terminated;
[0024] Calculating the second lateral displacement change value of the leading vehicle frame by frame within a short time window according to the leading vehicle position information corresponding to the lane change prediction time starting point, until the calculation time point reaches the lane change prediction time end point and the calculation is terminated;
[0025] A lane-changing prediction time point of the leading vehicle is predicted according to the first lateral displacement change value and the second lateral displacement change value.
[0026] In some embodiments, the lane change prediction time point is as follows:
[0027]
[0028] In the formula, T lc3 represents the lane change prediction point that meets the judgment for the first time; TW1 represents the long time window; TW2 represents the short time window; x(t+TW1) and x(t+TW2) are the lateral positions of the vehicle at time t after the long time window TW1 and the short time window TW2, respectively; C1 is the lateral change threshold; x Tlc1 x is the vehicle lateral coordinate of the starting point of the lane change prediction time; lane is the lateral coordinate of the current lane line; T range ={T lc1 ≤t <T lc2}, T lc2 Indicates the end of the lane change prediction time when detection of the lane change prediction point begins.
[0029] To achieve the above object, another aspect of an embodiment of the present application provides a vehicle driving control device based on lane change prediction, the device comprising:
[0030] The first module is used to obtain the first position information of the preceding vehicle;
[0031] A second module is used to determine, based on the first position information, that the preceding vehicle satisfies a first change state, and generate a lane change prediction time starting point of the preceding vehicle;
[0032] The third module is used to obtain the second position information of the preceding vehicle after the starting point of the lane change prediction time;
[0033] A fourth module is used to determine that the front vehicle satisfies a second change state according to the second position information, and generate a lane change prediction time end point of the front vehicle;
[0034] A fifth module is used to predict the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time end point;
[0035] The sixth module is used to control the driving state of the vehicle according to the lane change prediction time point.
[0036] To achieve the above object, another aspect of an embodiment of the present application provides an electronic device, including:
[0037] at least one processor;
[0038] at least one memory for storing at least one program;
[0039] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.
[0040] To achieve the above objective, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.
[0041] To achieve the above objectives, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.
[0042] The embodiments of the present application include at least the following beneficial effects: The present application provides a vehicle driving control method and apparatus, device and medium based on lane change prediction. The scheme obtains the first position information of the leading vehicle, determines the lane change prediction time starting point of the leading vehicle according to the first position information when the leading vehicle satisfies the first change state, then obtains the second position information of the leading vehicle after the lane change prediction time starting point, determines the lane change prediction time ending point of the leading vehicle according to the second position information when the leading vehicle satisfies the second change state, predicts the lane change prediction time point of the leading vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time ending point, and controls the driving state of the vehicle according to the lane change prediction time point, thereby effectively improving the accuracy of lane change prediction and decision-making, and thus improving driving safety. BRIEF DESCRIPTION OF THE DRAWINGS
[0043] Figure 1 is a flow chart of a vehicle driving control method based on lane change prediction provided in an embodiment of the present application;
[0044] Figure 2 It is provided by the embodiments of the present application;
[0045] Figure 3 is a structural schematic diagram of a vehicle driving control device based on lane change prediction provided in an embodiment of the present application;
[0046] Figure 4 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION
[0047] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application, they are only examples of devices and methods consistent with some aspects of the embodiments of the present application.
[0048] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".
[0049] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.
[0050] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.
[0051] In related technologies, automatic networked vehicles are not only believed to significantly improve road traffic safety, but also to effectively alleviate traffic congestion, improve traffic flow stability, and reduce environmental pollution caused by exhaust emissions. Especially in terms of traffic safety, automatic networked vehicles can reduce traffic accidents caused by human errors. In order to reduce problems such as reaction delays and information asymmetry in human driving, the advanced driver assistance system (ADAS) in autonomous driving technology significantly improves the driving safety of the vehicle by sensing, processing and responding to surrounding environmental information. However, the existing technology only focuses on the perception data of the vehicle itself, resulting in low accuracy in lane change prediction and decision-making.
[0052] In view of this, a vehicle driving control method and apparatus, equipment and medium based on lane change prediction are provided in an embodiment of the present application. After obtaining the first position information of the leading vehicle, the present application determines the lane change prediction time starting point of the leading vehicle when the leading vehicle satisfies the first change state according to the first position information, and then obtains the second position information of the leading vehicle after the lane change prediction time starting point, and determines the lane change prediction time ending point of the leading vehicle when the leading vehicle satisfies the second change state according to the second position information. The lane change prediction time point of the leading vehicle is predicted frame by frame within the lane change prediction time starting point and the lane change prediction time ending point, and the driving state of the vehicle is controlled according to the lane change prediction time point, thereby effectively improving the accuracy of lane change prediction and decision-making, thereby improving driving safety.
[0053] The vehicle driving control method based on lane change prediction provided in the embodiment of the present application relates to the field of intelligent transportation technology. The vehicle driving control method based on lane change prediction provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a vehicle-mounted terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or it can be configured as a server cluster or a distributed system composed of multiple physical servers, and can also be configured to provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms and other basic cloud computing services. The server can also be a node server in a blockchain network; the software can be an application that implements a vehicle driving control method based on lane change prediction, etc., but is not limited to the above forms.
[0054] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.
[0055] Figure 1is an optional flowchart of a vehicle driving control method based on lane change prediction provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S110 to S160:
[0056] Step S110, obtaining first position information of the preceding vehicle;
[0057] Step S120, determining that the preceding vehicle satisfies a first change state according to the first position information, and generating a lane change prediction start time of the preceding vehicle;
[0058] Step S130, obtaining second position information of the preceding vehicle after the starting point of the lane change prediction time;
[0059] Step S140, determining that the preceding vehicle satisfies a second change state according to the second position information, and generating a predicted lane change time end point of the preceding vehicle;
[0060] Step S150, predicting the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time ending point;
[0061] Step S160: Control the driving state of the vehicle according to the predicted lane change time point.
[0062] It is understood that the vehicle's location information can be uploaded in real time via the GPS installed on the vehicle chassis. Specifically, the vehicle's corresponding location information can be determined based on the uploaded latitude and longitude information. The vehicle's location information can be located (x i ,y i ), i∈[1,N], N=1024 represents the number of acquisition moments, x i represents the lateral coordinate of the vehicle at the i-th acquisition moment, y i Represents the longitudinal coordinate of the vehicle at the i-th acquisition moment.
[0063] In the embodiment of the present application, the process of generating the lane change prediction starting point of the preceding vehicle when the preceding vehicle satisfies the first change state according to the first position information may be to generate the lane change prediction starting point of the preceding vehicle according to the continuous time sequence when the preceding vehicle has both a lateral position greater than the lane line and a lateral position less than the lane line in the continuous time sequence according to the first position information. The lane change prediction starting point of the preceding vehicle is as follows:
[0064]
[0065] In the formula, T lc1 Indicates the lane change prediction starting point of the preceding vehicle; t1 and t2 represent T lc1 x(t1) and x(t2) are the horizontal coordinates of the t1th frame and the t2th frame; x lane is the lateral position of the current lane line.
[0066] For example, in the continuous time series, when it is determined that the front vehicle has a left-right swaying trajectory according to the first position information of the front vehicle, it can be determined that the front vehicle has the possibility of changing lanes. Therefore, the instantaneous continuous time series is used as the lane change prediction time starting point of the front vehicle, and the lane change prediction of the front vehicle begins from this time starting point.
[0067] In the embodiment of the present application, the process of generating the lane change prediction end point of the preceding vehicle when the preceding vehicle satisfies the second change state according to the second position information may be to determine that the lateral displacement direction of the preceding vehicle is different from the lane change direction for the first time according to the second position information, and to generate the lane change prediction end point of the preceding vehicle according to the corresponding moment of the second position information. The lane change prediction end point is as follows:
[0068]
[0069] In the formula, T lc2 Indicates the end point of lane change prediction time when the lane change prediction point is detected; t3 and t4 respectively represent T lc2 x(t3) and x(t4) are the horizontal coordinates (second position information) of the t3th frame and the t4th frame; x lane is the horizontal coordinate of the current lane line; The vehicle lateral coordinate of the starting point of the lane change prediction time.
[0070] Exemplarily, after the lane change prediction of the leading vehicle is turned on, if it is determined that the lane change directions of the vehicles corresponding to the previous and next time points at a certain time point are inconsistent, it means that the leading vehicle has not changed lanes or its lane change direction is irrelevant to the driving direction of this vehicle. This time point is taken as the end point of the lane change prediction time, that is, the lane change prediction process of the leading vehicle is ended at this time point.
[0071] From the above content, it can be seen that this embodiment starts the lane change prediction process of the leading vehicle according to the driving status of the leading vehicle, and ends the lane change prediction process according to the driving status of the leading vehicle, thereby effectively saving the data processing amount of the lane change prediction and improving the data processing effect.
[0072] In the embodiment of the present application, the lane change prediction time interval T is formed by the lane change prediction time start point and the lane change prediction time end point. range ={T lc1 ≤t <T lc2}, T lc2Indicates the end of the lane change prediction time when the lane change prediction point is detected. The lane change prediction time point of the front vehicle is predicted frame by frame within the lane change prediction time interval. Specifically, this embodiment calculates the first lateral displacement change value of the front vehicle frame by frame within the long time window according to the front vehicle position information corresponding to the lane change prediction time start point, until the calculation time point reaches the lane change prediction time end point and the calculation ends; calculates the second lateral displacement change value of the front vehicle frame by frame within the short time window according to the front vehicle position information corresponding to the lane change prediction time start point, until the calculation time point reaches the lane change prediction time end point and the calculation ends; then predicts the lane change prediction time point of the front vehicle based on the first lateral displacement change value and the second lateral displacement change value. In the judgment process, if the lateral displacement change value within the long time window is greater than the threshold value at a certain moment and the lateral displacement within the short time window is consistent with the lane change direction, the lane change behavior of the front vehicle is determined at this moment. If no moment that meets the conditions occurs until the end of the interval, there is no lane change prediction point in the time interval, and the lane change prediction in the time interval ends.
[0073] It is understandable that the lane change prediction time point is as follows:
[0074]
[0075] In the formula, T lc3 represents the lane change prediction point that meets the judgment for the first time; TW1 represents the long time window; TW2 represents the short time window; x(t+TW1) and x(t+TW2) are the lateral positions of the vehicle at time t after the long time window TW1 and the short time window TW2 respectively; C1 is the lateral change threshold; x is the vehicle lateral coordinate of the starting point of lane change prediction time; lane is the lateral coordinate of the current lane line; T range ={T lc1 ≤t <T lc2}, T lc2 Indicates the end of the lane change prediction time when detection of the lane change prediction point begins.
[0076] In the embodiment of the present application, when it is determined that the front vehicle has a lane change prediction time point, the driving state of the vehicle is controlled according to the lane change prediction time point. Specifically, the following formula can be used to determine whether the vehicle needs to perform deceleration avoidance:
[0077]
[0078] In the formula, is the decision at each time t within the time interval of detecting the lane change prediction point.
[0079] For example, Figure 2In the lane driving direction (Flow Direction) shown in the figure, when the host vehicle EV (Egovehicle, EV for short) is suspected of overtaking the preceding vehicle (Initial Preceding Vehicle, IPV for short) at the lane changing prediction point of the preceding vehicle, that is, the time when the host vehicle EV travels to the position corresponding to the lane changing prediction point is before the time when the preceding vehicle IPV changes lanes from the initial lane (Initial lane) to the target lane (Target lane), it is judged that the host vehicle EV may have a risk of collision with the preceding vehicle IPV when changing lanes, so the host vehicle EV is controlled to slow down; when the host vehicle EV does not have a suspicion of overtaking the preceding vehicle at the lane changing prediction point of the preceding vehicle, that is, the time when the host vehicle EV travels to the position corresponding to the lane changing prediction point is after the time when the preceding vehicle IPV changes lanes from the initial lane to the target lane, it is judged that there is no risk of collision between the host vehicle EV and the preceding vehicle IPV during the lane changing process, so the host vehicle EV can be controlled to maintain the current vehicle speed.
[0080] From the above content, it can be seen that the method provided in the embodiment of the present application controls the vehicle's state by predicting the lane change prediction time point of the leading vehicle and the position relationship between the vehicle and the leading vehicle at the lane change prediction time point, thereby effectively improving the driving safety of the vehicle.
[0081] Reference Figure 3 , an embodiment of the present application provides a vehicle driving control device based on lane change prediction, the device comprising:
[0082] The first module 310 is used to obtain first position information of a preceding vehicle;
[0083] The second module 320 is used to determine that the front vehicle meets the first change state according to the first position information, and generate a lane change prediction time starting point of the front vehicle;
[0084] The third module 330 is used to obtain the second position information of the preceding vehicle after the starting point of the lane change prediction time;
[0085] A fourth module 340 is used to determine that the front vehicle meets the second change state according to the second position information, and generate a lane change prediction time end point of the front vehicle;
[0086] A fifth module 350 is used to predict the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time start point and the lane change prediction time end point;
[0087] The sixth module 360 is used to control the driving state of the vehicle according to the lane change prediction time point.
[0088] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0089] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.
[0090] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0091] See also Figure 4 , Figure 4 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:
[0092] The processor 410 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;
[0093] The memory 420 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 420 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 420, and the processor 410 calls and executes the above-mentioned method of the embodiments of this application;
[0094] Input / output interface 430, used to implement information input and output;
[0095] Communication interface 440, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);
[0096] bus 450 , which transmits information between the various components of the device (e.g., processor 410 , memory 420 , input / output interface 430 , and communication interface 440 );
[0097] The processor 410 , the memory 420 , the input / output interface 430 , and the communication interface 440 are connected to each other in communication within the device via the bus 450 .
[0098] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program, and the computer program implements the above method when executed by a processor.
[0099] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.
[0100] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0101] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.
[0102] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.
[0103] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0104] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.
[0105] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0106] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.
[0107] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.
[0108] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0109] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0110] If the 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, or the part that contributes to the prior art, 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 multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.
[0111] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.
Claims
1. A vehicle driving control method based on lane change prediction, characterized in that: The method comprises the following steps: Obtaining the first position information of the preceding vehicle; Determining, according to the first position information, that the preceding vehicle satisfies a first change state, and generating a lane change prediction time starting point of the preceding vehicle; Acquire second position information of the preceding vehicle after the starting point of the lane change prediction time; Determining, according to the second position information, that the preceding vehicle satisfies a second change state, and generating a predicted lane change time end point of the preceding vehicle; Predicting the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time ending point; The driving state of the vehicle is controlled according to the lane change prediction time point.
2. The method according to claim 1, characterized in that The determining, according to the first position information, that the preceding vehicle satisfies a first change state and generating a lane change prediction time starting point of the preceding vehicle includes: When it is determined according to the first position information that the front vehicle has both a lateral position greater than the lane line and a lateral position less than the lane line in a continuous time sequence, a lane change prediction time starting point of the front vehicle is generated according to the continuous time sequence.
3. The method according to claim 2, characterized in that The lane change prediction starting point of the preceding vehicle is as follows: In the formula, T lc1 Indicates the starting point of the lane change prediction time of the preceding vehicle; t1 and t2 represent T lc1 x(t1) and x(t2) are the horizontal coordinates of the t1th frame and the t2th frame; x lane is the lateral position of the current lane line.
4. The method according to claim 1, characterized in that The determining, according to the second position information, that the preceding vehicle satisfies the second change state and generating a predicted lane change time end point of the preceding vehicle includes: It is determined according to the second position information that the lateral displacement direction of the leading vehicle is different from the lane-changing direction for the first time, and a predicted lane-changing time end point of the leading vehicle is generated according to a corresponding moment of the second position information.
5. The method according to claim 4, characterized in that The lane change prediction time end point is as follows: In the formula, T lc2 Indicates the end point of the lane change prediction time when the lane change prediction point detection starts; t3 and t4 represent T lc2 x(t3) and x(t4) are the horizontal coordinates of the t3th frame and the t4th frame; x lane is the horizontal coordinate of the current lane line; The vehicle lateral coordinate of the starting point of the lane change prediction time.
6. The method according to claim 1, characterized in that The predicting the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time ending point comprises: Calculating the first lateral displacement change value of the leading vehicle frame by frame within the long time window according to the leading vehicle position information corresponding to the lane change prediction time starting point, until the calculation time point reaches the lane change prediction time end point and the calculation is terminated; Calculating the second lateral displacement change value of the leading vehicle frame by frame within a short time window according to the leading vehicle position information corresponding to the lane change prediction time starting point, until the calculation time point reaches the lane change prediction time end point and the calculation is terminated; A lane-changing prediction time point of the leading vehicle is predicted according to the first lateral displacement change value and the second lateral displacement change value.
7. The method according to claim 6, characterized in that The lane change prediction time point is as follows: In the formula, T lc3 represents the lane change prediction point that meets the judgment for the first time; TW1 represents the long time window; TW2 represents the short time window; x(t+TW1) and x(t+TW2) are the lateral positions of the vehicle at time t after the long time window TW1 and the short time window TW2 respectively; C1 is the lateral change threshold; x is the vehicle lateral coordinate of the starting point of the lane change prediction time; lane is the lateral coordinate of the current lane line; T range ={T lc1 ≤t <T lc2 }, T lc2 Indicates the end of the lane change prediction time when detection of the lane change prediction point begins.
8. A vehicle driving control device based on lane change prediction, characterized in that: The device comprises: The first module is used to obtain the first position information of the preceding vehicle; A second module is used to determine, based on the first position information, that the preceding vehicle satisfies a first change state, and generate a lane change prediction time starting point of the preceding vehicle; The third module is used to obtain the second position information of the preceding vehicle after the starting point of the lane change prediction time; A fourth module is used to determine that the front vehicle satisfies a second change state according to the second position information, and generate a lane change prediction time end point of the front vehicle; A fifth module is used to predict the lane change prediction time point of the preceding vehicle frame by frame within the lane change prediction time starting point and the lane change prediction time end point; The sixth module is used to control the driving state of the vehicle according to the lane change prediction time point.
9. An electronic device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.