An automatic driving speed planning method and device based on adjacent lanes and a medium

Abstract

The application discloses a kind of adjacent lane-based automatic driving speed planning method, device and medium, belong to the field of automatic driving. Mainly include, calculate the maximum drivable speed of current lane;Determine whether the maximum drivable speed of adjacent lane needs to be calculated;If it is determined that the maximum drivable speed of adjacent lane needs to be calculated, then calculate the maximum drivable speed of adjacent lane;Make a decision on whether to change lanes;And if the result of the decision is to change lanes, then change the driving lane to the adjacent lane, and obtain the current first planning strategy according to the maximum drivable speed of adjacent lane, and then plan the speed, if the result of the decision is not to change lanes, then continue driving in the current lane, and obtain the current second planning strategy according to the maximum drivable speed of current lane, and then plan the speed. The application seeks to change lanes to plan the speed, so that the automatic driving speed planning process is more human-like intelligent.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to an autonomous driving speed planning method, device and medium based on adjacent lanes. Background Technology

[0002] As autonomous driving technology matures, it is attracting increasing market attention, which in turn places new and higher demands on it. Speed ​​planning, a key technology in autonomous driving, also faces continuous improvement and enhancement requirements.

[0003] In existing technologies, speed planning, for example through automatic cruise control and highway mode, simply executes preset speed adjustment methods or speed planning based on obstacles or potential obstacles in the driving lane, and cannot actively seek speed change planning like manual driving. Summary of the Invention

[0004] To address the problems existing in the prior art, this application mainly provides an autonomous driving speed planning method, device and medium based on adjacent lanes. By focusing on the driving speed of vehicles in adjacent lanes, it seeks to perform speed planning by changing lanes, making autonomous driving speed planning more human-like and intelligent.

[0005] To achieve the above objectives, one technical solution adopted in this application is: providing an autonomous driving speed planning method based on adjacent lanes, which includes:

[0006] Based on the first driving environment information acquired in real time during the autonomous vehicle's operation, the maximum permissible speed in the current lane is calculated. Based on the first driving environment information, it is determined whether the maximum permissible speed of adjacent lanes needs to be calculated. If it is determined that the maximum permissible speed of adjacent lanes needs to be calculated, then the maximum permissible speed of adjacent lanes is calculated. Based on the current maximum permissible speed, the maximum permissible speed of adjacent lanes, and the second driving environment information acquired in real time, a decision is made regarding whether to change lanes. If the decision is to change lanes, the autonomous vehicle's driving lane is changed to the adjacent lane, and a current first planning strategy is obtained based on the maximum permissible speed of the adjacent lane. Speed ​​planning for the autonomous vehicle is then performed based on the current first planning strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and a current second planning strategy is obtained based on the current maximum permissible speed of the current lane. Speed ​​planning for the autonomous vehicle is then performed based on the current second planning strategy.

[0007] Another technical solution adopted in this application is: providing an autonomous driving speed planning and prompting method based on adjacent lanes, which includes,

[0008] Based on the first driving environment information acquired in real time during the autonomous vehicle's operation, the maximum permissible speed in the current lane is calculated. Based on the first driving environment information, it is determined whether the maximum permissible speed of adjacent lanes needs to be calculated. If it is determined that the maximum permissible speed of adjacent lanes needs to be calculated, then the maximum permissible speed of adjacent lanes is calculated. Based on the current lane's maximum permissible speed, the adjacent lane's maximum permissible speed, and the second driving environment information acquired in real time, a decision is made regarding whether to change lanes. If the decision is to change lanes, the autonomous vehicle's driving lane is changed to the adjacent lane, and a current first planning strategy is obtained based on the adjacent lane's maximum permissible speed. Speed ​​planning for the autonomous vehicle is then performed according to the current first planning strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and a current second planning strategy is obtained based on the current lane's maximum permissible speed. Speed ​​planning for the autonomous vehicle is then performed according to the current second planning strategy.

[0009] Specifically, during the lane change process, the progress of the change is displayed in a first gradual visual display to provide the driver with corresponding prompts. During the continued driving in the current lane, the real-time speed change process determined according to the corresponding speed plan is displayed in a second gradual visual display to provide the driver with corresponding prompts.

[0010] Another technical solution adopted in this application is: providing an autonomous driving speed planning device based on adjacent lanes, which includes:

[0011] The system includes the following modules: a module for calculating the maximum permissible speed in the current lane based on first driving environment information acquired in real time during the autonomous vehicle's operation; a module for determining whether to calculate the maximum permissible speed in adjacent lanes based on the first driving environment information; a module for calculating the maximum permissible speed in adjacent lanes if it is determined that such calculation is necessary; a module for deciding whether to change lanes based on the maximum permissible speed in the current lane, the maximum permissible speed in adjacent lanes, and second driving environment information acquired in real time; and a module for changing the autonomous vehicle's lane to the adjacent lane if the decision is to change lanes, obtaining a current first planning strategy based on the maximum permissible speed in the adjacent lane, and then planning the speed of the autonomous vehicle based on the current first planning strategy; and a module for continuing to drive in the current lane if the decision is not to change lanes, obtaining a current second planning strategy based on the current maximum permissible speed in the current lane, and then planning the speed of the autonomous vehicle based on the current second planning strategy.

[0012] Another technical solution adopted in this application is to provide a computer-readable storage medium storing computer instructions that are operated to execute the autonomous driving speed planning method based on adjacent lanes in the above solution.

[0013] Another technical solution adopted in this application is: providing a computer device, which includes a processor and a memory, the memory storing computer instructions, which are operated to execute the autonomous driving speed planning method based on adjacent lanes in the above solution.

[0014] The beneficial effects achievable by the technical solution of this application are: a method, device, and medium for autonomous driving speed planning based on adjacent lanes. This application focuses on the driving speed of vehicles in adjacent lanes and seeks to perform speed planning by changing lanes, making the autonomous driving speed planning process more human-like and intelligent, thereby adapting to more vehicle driving scenarios and improving driving efficiency. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating a specific implementation of an autonomous driving speed planning method based on adjacent lanes according to this application;

[0017] Figure 2 This is a flowchart illustrating a specific implementation of an autonomous driving speed planning and prompting method based on adjacent lanes according to this application;

[0018] Figure 3 This is a schematic diagram of a specific implementation of an autonomous driving speed planning device based on adjacent lanes according to this application;

[0019] Figure 4 This is a schematic diagram of a specific embodiment of an autonomous driving speed planning and prompting device based on adjacent lanes according to this application;

[0020] The accompanying drawings have illustrated specific embodiments of this disclosure, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this disclosure to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0021] The preferred embodiments of this application will now be described in detail with reference to the accompanying drawings, so that the advantages and features of this application can be more easily understood by those skilled in the art, thereby providing a clearer and more definite definition of the scope of protection of this application.

[0022] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0023] Existing autonomous vehicles employ two speed planning modes: cruise control and following mode. Activating these modes is typically done by the driver using a lever or pressing a button. Furthermore, once in cruise control or following mode, the vehicle can only mechanically execute pre-set driving patterns or focus solely on obstacles and potential obstacles within its own lane. Unlike manual driving, it cannot proactively adjust speed by changing lanes based on the movement of vehicles in adjacent lanes, thus failing to achieve human-like and intelligent speed planning.

[0024] To address the aforementioned issues, this application provides a method, apparatus, and medium for autonomous driving speed planning based on adjacent lanes.

[0025] The technical solutions of this application will now be described in detail with reference to specific embodiments and accompanying drawings. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0026] Figure 1 This application illustrates a specific implementation of an autonomous driving speed planning method based on adjacent lanes.

[0027] exist Figure 1The specific implementation of the autonomous driving speed planning method based on adjacent lanes shown in this application includes the following steps: Step S101: Calculate the maximum drivable speed of the current lane based on the first driving environment information acquired in real time during the autonomous driving process; Step S102: Determine whether it is necessary to calculate the maximum drivable speed of the adjacent lane based on the first driving environment information; Step S103: If it is determined that the maximum drivable speed of the adjacent lane needs to be calculated, then calculate the maximum drivable speed of the adjacent lane; Step S104: Make a decision on whether to change lanes based on the maximum drivable speed of the current lane, the maximum drivable speed of the adjacent lane, and the second driving environment information acquired in real time; Step S105: If the decision is to change lanes, then change the autonomous driving vehicle's driving lane to the adjacent lane, and obtain the current first planning strategy based on the maximum drivable speed of the adjacent lane, and then perform speed planning for the autonomous driving vehicle based on the current first planning strategy; if the decision is not to change lanes, then allow the autonomous driving vehicle to continue driving in the current lane, and obtain the current second planning strategy based on the current maximum drivable speed of the current lane, and then perform speed planning for the autonomous driving vehicle based on the current second planning strategy.

[0028] This application seeks to plan speed by paying attention to the speed of vehicles in adjacent lanes and changing lanes, making the speed planning process of autonomous driving more human-like and intelligent, thereby adapting to more vehicle driving scenarios and improving driving efficiency.

[0029] Process S101 indicates that the maximum driving speed of the current lane is calculated based on the first driving environment information obtained in real time during the driving of the autonomous vehicle, which can facilitate the decision of whether to seek a lane change for speed planning based on the maximum driving speed of the current lane.

[0030] In an optional embodiment of this application, during operation, the autonomous vehicle utilizes its own sensing devices to acquire perception information and obtains the aforementioned first driving environment information based on map information obtained from a high-precision map and the aforementioned perception information. This allows for the calculation of the maximum permissible speed in the current lane and the maximum permissible speed in adjacent lanes based on the current environment information. Specifically, the aforementioned sensing devices can be AVM (Around View Monitor) and USS (Ultrasonic Radar), among other sensing devices.

[0031] In an optional specific embodiment of this application, the process of sensing the current driving environment using its own configured sensing device includes sensing information such as obstacles in front of the autonomous vehicle in the current driving lane and obstacles in adjacent lanes, including the vehicle's driving speed information, to obtain sensing information.

[0032] In an optional embodiment of this application, map information obtained from a high-precision map, such as the road segment where the autonomous vehicle is located and the maximum speed limit of the road segment, is used.

[0033] Process S102 represents the process of determining whether it is necessary to calculate the maximum driving speed of adjacent lanes based on the first driving environment information. Paying attention to adjacent lanes makes it easier to make a decision on whether to plan speed by changing lanes.

[0034] In an optional specific embodiment of this application, the process of determining whether it is necessary to calculate the maximum driving speed of the adjacent lane includes: calculating the number of target vehicles that drive in the adjacent lane and overtake autonomous vehicles within a predetermined historical period based on the first driving environment information; if the number of target vehicles exceeds a preset overtaking number threshold, it is determined that it is necessary to calculate the maximum driving speed of the adjacent lane; otherwise, it is determined that it is not necessary to calculate the maximum driving speed of the adjacent lane.

[0035] In real-world driving scenarios, if a lane's speed cannot be too high due to various factors, such as a lane for passing oncoming vehicles, the vehicle speed is often slower than in other lanes. When driving manually, the driver will seek to change lanes and accelerate based on the current situation. To simulate manual driving scenarios and determine whether the speed of vehicles in adjacent lanes is greater than that of the current vehicle, it is necessary to exclude the situation where the speed of vehicles in adjacent lanes is necessarily greater than the current vehicle's speed during the initial acceleration phase.

[0036] If a target vehicle exceeding the aforementioned vehicle number threshold passes this vehicle within the predetermined time period, it indicates that the speed of vehicles in the adjacent lane is faster than the speed of this vehicle in its current lane. Therefore, the program for calculating the maximum speed of the adjacent lane is initiated. Optionally, the predetermined time period is 1 minute, and the aforementioned vehicle number threshold is 5 vehicles. That is, if more than 5 vehicles in the adjacent lane pass this vehicle within the previous predetermined time period, it indicates that the speed of vehicles in the adjacent lane is faster than the current lane, and the program for calculating the maximum speed of the adjacent lane is initiated. If the number of target vehicles passing this vehicle within the previous predetermined time period is less than the aforementioned vehicle number threshold, it indicates that the passing of the target vehicle is an isolated incident. In this case, not calculating the maximum speed of the adjacent lane can save the computing resources of this vehicle's system.

[0037] Process S103 represents the process of calculating the maximum permissible speed of adjacent lanes if it is determined that it is necessary to calculate the maximum permissible speed of adjacent lanes. This process facilitates the decision of whether to seek lane change for speed planning based on the maximum permissible speed of adjacent lanes.

[0038] In an optional embodiment of this application, the process of calculating the maximum permissible speed of adjacent lanes includes,

[0039] Based on the first driving environment information, the driving speed of the target vehicle that travels in the adjacent lane and overtakes the autonomous vehicle during the predetermined historical period is calculated; and based on the driving speed of each target vehicle, the maximum driving speed of the adjacent lane is calculated.

[0040] The maximum speed that can be driven on a segment of each lane is necessarily related to the speed of all vehicles traveling on that segment. Therefore, based on the speed of the target vehicles that exceed this vehicle within a predetermined time period, it is possible to calculate the maximum speed that can be driven in the adjacent lanes corresponding to the segment where this vehicle is located.

[0041] Optionally, the process of calculating the maximum permissible speed of adjacent lanes based on the driving speed of each target vehicle includes calculating the average speed of all target vehicles based on the driving speed of each target vehicle, as the maximum permissible speed of adjacent lanes.

[0042] Process S104 represents the process of making a decision on whether to change lanes based on the maximum drivable speed of the current lane, the maximum drivable speed of the adjacent lane, and the real-time acquired second driving environment information. This process can facilitate speed planning by changing lanes based on the decision result, or by continuing to maintain the current lane for speed planning.

[0043] In an optional embodiment of this application, the process of determining whether to change lanes based on the current maximum drivable speed of the lane, the maximum drivable speed of the adjacent lane, and the real-time acquired second driving environment information includes:

[0044] If the first speed difference obtained by subtracting the maximum speed of the current lane from the maximum speed of the adjacent lane is not less than the first speed difference threshold, and if it is determined that it is safe to change lanes based on the second driving environment information, then a lane change is decided to proceed; if the first speed difference is less than the first speed difference threshold, or if it is determined that it is not safe to change lanes based on the second driving environment information, then a lane change is not decided to proceed.

[0045] In manual driving scenarios, lane changing is only considered worthwhile when the speed of vehicles in adjacent lanes significantly exceeds that of vehicles in the current lane. Therefore, to simulate manual driving scenarios, a lane change decision is only made when the difference between the maximum permissible speed of the adjacent lane and the current lane exceeds a predetermined threshold.

[0046] Optionally, the aforementioned first speed difference threshold is 10% of the maximum drivable speed of the current lane.

[0047] In a specific embodiment of this application, the aforementioned second driving environment information includes whether the distance between the following vehicle and the preceding vehicle in the adjacent lane meets the distance requirement for lane change acceleration, whether there is a vehicle in a third lane changing lanes into the adjacent lane, whether there are obstacles between the two lanes in the current road segment, and whether lane change is permitted. When determining whether lane change acceleration is worthwhile based on the maximum drivable speed of the adjacent lane and the maximum drivable speed of the current lane, it is also necessary to ensure that environmental safety conditions are met and relevant traffic regulations are followed.

[0048] Process S105 indicates that if the decision is to change lanes, the autonomous vehicle's driving lane is changed to an adjacent lane, and a current first planning strategy is obtained based on the maximum driving speed of the adjacent lane. Then, speed planning is performed on the autonomous vehicle based on the current first planning strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and a current second planning strategy is obtained based on the maximum driving speed of the current lane. Then, speed planning is performed on the autonomous vehicle based on the current second planning strategy. Ultimately, based on the decision, the autonomous vehicle can intelligently and human-like complete the lane change and acceleration or continue driving in the current lane.

[0049] In an optional specific embodiment of this application, if the decision is to change lanes, the autonomous vehicle will change lanes and the previously calculated maximum drivable speed of the adjacent lane will be used as the planning speed to obtain the current planning strategy.

[0050] Specifically, the planning strategy mentioned above includes the driving states that the autonomous vehicle needs to enter. In the lane change and acceleration driving scenario of this application, the planning strategy mentioned above refers to the need to enable the autonomous vehicle to enter the acceleration driving state. The planning strategy mentioned above also includes acceleration information in the acceleration driving state.

[0051] Figure 2 This paper illustrates a specific implementation of an autonomous driving speed planning prompt method based on adjacent lanes, as proposed in this application.

[0052] exist Figure 2In the specific implementation shown, the autonomous driving speed planning and prompting method based on adjacent lanes of this application includes: process S201 calculating the maximum drivable speed of the current lane based on the first driving environment information acquired in real time during the autonomous driving process; process S202 determining whether it is necessary to calculate the maximum drivable speed of adjacent lanes based on the first driving environment information; process S203 calculating the maximum drivable speed of adjacent lanes if it is determined that it is necessary to calculate the maximum drivable speed of adjacent lanes; process S204 deciding whether to change lanes based on the maximum drivable speed of the current lane, the maximum drivable speed of adjacent lanes, and the second driving environment information acquired in real time; and process S205 adjusting the driving speed of the autonomous driving vehicle if the decision is to change lanes. The vehicle changes lanes to adjacent lanes, and a first planning strategy is obtained based on the maximum drivable speed of the adjacent lane. Then, speed planning is performed on the autonomous vehicle based on the first planning strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and a second planning strategy is obtained based on the maximum drivable speed of the current lane. Then, speed planning is performed on the autonomous vehicle based on the second planning strategy. In process S206, during the lane change process, the progress of the change process is displayed in a first gradual visual display to provide corresponding prompts to the driver. During the continued driving in the current lane, the real-time speed change process determined according to the corresponding speed planning is displayed in a second gradual visual display to provide corresponding prompts to the driver.

[0053] Process S206 represents the process of displaying the progress of the lane change process in a first gradual visual display to provide the driver with corresponding prompts, and the process of displaying the real-time speed change process determined according to the corresponding speed plan in a second gradual visual display to provide the driver with corresponding prompts during the continued driving in the current lane. This process helps the driver to be mentally prepared for changes in the vehicle's driving status in a timely manner.

[0054] Existing autonomous vehicles can only display the vehicle's current speed and the planned speed, leaving the driver unprepared for changes in the vehicle's driving status. In contrast, in real-world human driving scenarios, drivers adjust the vehicle's driving status by adjusting the accelerator and decelerator, allowing for better psychological anticipation. This application aims to display the required driving states of the vehicle and provide prompts to the driver, simulating the perception of driving states in human driving. This helps drivers prepare for changes in the vehicle's driving status in a timely manner, thereby improving the driver's experience during autonomous vehicle operation.

[0055] In an optional embodiment of this application, the process of displaying the progress of the lane change process in a first gradual visual display to provide corresponding prompts to the driver, and the process of displaying the real-time speed change process determined according to the corresponding speed plan in a second gradual visual display to provide corresponding prompts to the driver during the continued driving in the current lane, includes distinguishing between the acceleration state, deceleration state, and constant speed state of the autonomous vehicle.

[0056] Optionally, the current speed of the autonomous vehicle can be displayed as a progress bar instead of a number. The progress bar is displayed in red when the autonomous vehicle needs to accelerate, in yellow when it needs to decelerate, and in green when it needs to maintain a constant speed. This way, the driver can know the vehicle's upcoming driving status as long as they see the corresponding color of the progress bar, thus making timely psychological preparations and improving the driver's riding experience.

[0057] Preferably, when the acceleration required for the autonomous vehicle to accelerate or the deceleration required to decelerate exceeds a preset acceleration threshold, an alarm is issued to the driver by flashing the color of the speed progress bar, or an alarm is issued to the driver by voice broadcast.

[0058] In an optional embodiment of this application, the first and second gradient visualization processes include: comparing the actual driving speed of the autonomous vehicle with the corresponding current planned speed obtained according to one of the current first planning strategy and the current second planning strategy; if the second speed difference obtained by subtracting the actual driving speed from the current planned speed is less than a preset second speed difference threshold, then providing a first visual alarm prompt to the driver; and comparing the actual driving speed of the autonomous vehicle with the current lane minimum drivable speed calculated according to the first driving environment information; if the third speed difference obtained by subtracting the current lane minimum drivable speed from the actual driving speed is less than a preset third speed difference threshold, then providing a second visual alarm prompt to the driver.

[0059] Specifically, if the current speed of an autonomous vehicle is close to the planned speed or the minimum drivable speed, it means that the vehicle will transition from one driving state to another, such as from accelerating to constant speed, from decelerating to constant speed, or from decelerating to accelerating. Providing appropriate prompts at this time can help the driver have a correct psychological expectation of the vehicle's next driving state and improve the riding experience.

[0060] Optionally, if the second speed difference obtained by subtracting the actual driving speed from the current planned speed is less than the preset second speed difference threshold, a visual prompt will be given to the driver by flashing red and green speed progress bars, or a visual prompt will be given to the driver by voice broadcast.

[0061] If the third speed difference obtained by subtracting the minimum permissible speed of the current lane from the actual driving speed is less than the preset third speed difference threshold, a visual prompt will be given to the driver by flashing a yellow-green speed progress bar, or a visual prompt will be given to the driver by voice broadcast.

[0062] Figure 3 This application illustrates a specific embodiment of an autonomous driving speed planning device based on adjacent lanes.

[0063] exist Figure 3 The specific implementation of the autonomous driving speed planning device based on adjacent lanes shown in this application includes: a module 301 for calculating the maximum drivable speed of the current lane based on first driving environment information acquired in real time during the autonomous driving process; a module 302 for determining whether it is necessary to calculate the maximum drivable speed of adjacent lanes based on the first driving environment information; a module 303 for calculating the maximum drivable speed of adjacent lanes if it is determined that it is necessary to calculate the maximum drivable speed of adjacent lanes; a module 304 for making a decision on whether to change lanes based on the maximum drivable speed of the current lane, the maximum drivable speed of adjacent lanes, and second driving environment information acquired in real time; and a module 305 for changing the driving lane of the autonomous driving vehicle to the adjacent lane if the decision is to change lanes, obtaining a current first planning strategy based on the maximum drivable speed of the adjacent lane, and then planning the speed of the autonomous driving vehicle based on the current first planning strategy; and for continuing to drive in the current lane if the decision is not to change lanes, obtaining a current second planning strategy based on the current maximum drivable speed of the current lane, and then planning the speed of the autonomous driving vehicle based on the current second planning strategy.

[0064] This application proposes an autonomous driving speed planning device based on adjacent lanes. By paying attention to the driving speed of vehicles in adjacent lanes, it seeks to plan speed by changing lanes, making the autonomous driving speed planning process more human-like and intelligent, thereby adapting to more vehicle driving scenarios and improving driving efficiency.

[0065] Module 301, which calculates the maximum permissible speed in the current lane based on the first driving environment information obtained in real time during the autonomous vehicle's operation, can facilitate speed planning decisions on whether to seek a lane change based on the maximum permissible speed in the current lane.

[0066] Module 303, which calculates the maximum permissible speed of adjacent lanes if it is determined that it is necessary to calculate the maximum permissible speed of adjacent lanes, can facilitate the decision of whether to seek a lane change for speed planning based on the maximum permissible speed of adjacent lanes.

[0067] Module 304, which determines whether to change lanes based on the maximum permissible speed of the current lane, the maximum permissible speed of the adjacent lane, and real-time second driving environment information, can facilitate lane changing for speed planning based on the decision result, or continue driving in the current lane for speed planning.

[0068] Module 305, which is used to change the driving lane of the autonomous vehicle to the adjacent lane if the decision is to change lanes, and obtain the current first planning strategy based on the maximum driving speed of the adjacent lane, and then plan the speed of the autonomous vehicle according to the current first planning strategy, and if the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and obtains the current second planning strategy based on the maximum driving speed of the current lane, and then plans the speed of the autonomous vehicle according to the current second planning strategy, can ultimately complete the lane change acceleration or continue driving in the current lane in a human-like intelligent manner according to the decision.

[0069] Figure 4 This paper illustrates a specific embodiment of an autonomous driving speed planning prompt device based on adjacent lanes, as described in this application.

[0070] exist Figure 4In the specific embodiment shown, the autonomous driving speed planning prompt device based on adjacent lanes of this application includes: a module 401 for calculating the maximum drivable speed of the current lane based on first driving environment information acquired in real time during the autonomous driving process; a module 402 for determining whether it is necessary to calculate the maximum drivable speed of adjacent lanes based on the first driving environment information; a module 403 for calculating the maximum drivable speed of adjacent lanes if it is determined that it is necessary to calculate the maximum drivable speed of adjacent lanes; a module 404 for making a decision on whether to change lanes based on the maximum drivable speed of the current lane, the maximum drivable speed of adjacent lanes, and the second driving environment information acquired in real time; and a module 405 for changing the driving lane of the autonomous driving vehicle to the lane specified by the decision if the decision is to change lanes. The system includes a module 405 that determines the speed of an autonomous vehicle based on the maximum permissible speed of the adjacent lanes and then performs speed planning based on the current first planning strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane. The system also includes a module 406 that performs speed planning based on the current second planning strategy, based on the current maximum permissible speed of the current lane. The module 405 further includes a module 406 that provides a first gradual visual display of the progress of lane change to provide corresponding prompts to the driver, and a second gradual visual display of the real-time speed change determined by the corresponding speed planning to provide corresponding prompts to the driver during continued driving in the current lane.

[0071] Module 406 helps drivers prepare mentally for changes in the vehicle's driving status in a timely manner.

[0072] Existing autonomous vehicles can only display the vehicle's current speed and the planned speed, leaving the driver unprepared for changes in the vehicle's driving status. This application, by displaying the necessary driving states and providing prompts to the driver, helps the driver prepare for changes in the vehicle's driving status in a timely manner, thereby improving the driver's experience during autonomous vehicle operation.

[0073] The extended adjacent lane-based autonomous driving speed planning device provided in this application can be used to execute the extended adjacent lane-based autonomous driving speed planning method described in any of the above embodiments. Its implementation principle and technical effect are similar, and will not be repeated here.

[0074] In one specific embodiment of this application, the functional modules of the autonomous driving speed planning device based on adjacent lanes can be directly in hardware, in software modules executed by a processor, or in a combination of both.

[0075] Software modules may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium known in this art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium.

[0076] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor can be a microprocessor, but alternatively, it can be any conventional processor, controller, microcontroller, or state machine. The processor can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors incorporating a DSP core, or any other such configuration. Alternatively, the storage medium can be integrated with the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in the user terminal. Alternatively, the processor and storage medium can reside as discrete components in the user terminal.

[0077] In another specific embodiment of this application, a computer-readable storage medium stores computer instructions that are operated to perform the extended adjacent lane-based autonomous driving speed planning method described above.

[0078] In another specific embodiment of this application, a computer device includes a processor and a memory, the memory storing computer instructions that are operated to execute the adjacent lane-based autonomous driving speed planning method in the above scheme.

[0079] In another specific embodiment of this application, an autonomous driving system includes the adjacent lane-based autonomous driving speed planning device described above.

[0080] In another specific embodiment of this application, an autonomous vehicle includes the autonomous driving system described above.

[0081] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0082] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0083] The above are merely embodiments of this application and do not limit the scope of this patent application. Any equivalent structural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of this application.

Claims

1. A method for autonomous driving speed planning based on adjacent lanes, characterized in that, include: Calculate the maximum permissible speed in the current lane based on the first driving environment information obtained in real time during the autonomous vehicle's operation; Based on the first driving environment information, it is determined whether it is necessary to calculate the maximum driving speed of adjacent lanes. The process of determining whether it is necessary to calculate the maximum driving speed of adjacent lanes based on the first driving environment information includes: Based on the first driving environment information, the number of target vehicles that drove in the adjacent lanes and overtook the autonomous driving vehicle within a predetermined historical period is calculated. If the number of target vehicles exceeds a preset overtaking threshold, it is determined that the maximum driving speed of the adjacent lane needs to be calculated; otherwise, it is determined that the maximum driving speed of the adjacent lane does not need to be calculated. If it is determined that the maximum driving speed of the adjacent lanes needs to be calculated, then the maximum driving speed of the adjacent lanes is calculated. Based on the current maximum permissible speed in the lane, the maximum permissible speed in the adjacent lane, and the real-time acquired second driving environment information, a decision is made regarding whether to change lanes; and If the decision results in a lane change, the autonomous vehicle's driving lane is changed to the adjacent lane. A current first planning strategy is then derived based on the maximum permissible speed of the adjacent lane, and speed planning for the autonomous vehicle is performed according to this strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and a current second planning strategy is obtained based on the maximum drivable speed of the current lane. Then, speed planning is performed on the autonomous vehicle based on the current second planning strategy.

2. The autonomous driving speed planning method based on adjacent lanes according to claim 1, characterized in that, The process of calculating the maximum permissible speed of the adjacent lanes includes: Based on the first driving environment information, the speed of the target vehicle that travels in the adjacent lane and overtakes the autonomous driving vehicle within the predetermined historical time period is calculated; and The maximum permissible speed in the adjacent lanes is calculated based on the driving speed of each target vehicle.

3. The autonomous driving speed planning method based on adjacent lanes according to claim 1, characterized in that, The process of determining whether to change lanes based on the maximum permissible speed of the current lane, the maximum permissible speed of the adjacent lane, and the real-time acquired second driving environment information includes: If the first speed difference obtained by subtracting the maximum drivable speed of the current lane from the maximum drivable speed of the adjacent lane is not less than the first speed difference threshold, and if it is determined that it is safe to change lanes based on the second driving environment information, then a lane change is decided to be performed. If the first speed difference is less than the first speed difference threshold, or if it is determined from the second driving environment information that it is not safe to change lanes, then the decision is made not to change lanes.

4. A method for providing speed planning and prompting for autonomous driving based on adjacent lanes, characterized in that, include: Calculate the maximum permissible speed in the current lane based on the first driving environment information obtained in real time during the autonomous vehicle's operation; Based on the first driving environment information, it is determined whether it is necessary to calculate the maximum driving speed of adjacent lanes. The process of determining whether it is necessary to calculate the maximum driving speed of adjacent lanes based on the first driving environment information includes: Based on the first driving environment information, the number of target vehicles that drove in the adjacent lanes and overtook the autonomous driving vehicle within a predetermined historical period is calculated. If the number of target vehicles exceeds a preset overtaking threshold, it is determined that the maximum driving speed of the adjacent lane needs to be calculated; otherwise, it is determined that the maximum driving speed of the adjacent lane does not need to be calculated. If it is determined that the maximum driving speed of adjacent lanes needs to be calculated, then the maximum driving speed of the adjacent lanes is calculated. Based on the current maximum permissible speed in the lane, the maximum permissible speed in the adjacent lane, and the real-time acquired second driving environment information, a decision is made regarding whether to change lanes; and If the decision results in a lane change, the autonomous vehicle's driving lane is changed to the adjacent lane. A current first planning strategy is then derived based on the maximum permissible speed of the adjacent lane, and speed planning for the autonomous vehicle is performed according to this strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and a current second planning strategy is obtained based on the maximum permissible speed of the current lane. Then, speed planning is performed on the autonomous vehicle based on the current second planning strategy. During the lane change process, the progress of the lane change is displayed in a first gradual visual manner to provide corresponding prompts to the driver. During the continued driving in the current lane, the real-time speed change process determined according to the corresponding speed plan is displayed in a second gradual visual display to provide corresponding prompts to the driver.

5. The autonomous driving speed planning and prompting method based on adjacent lanes according to claim 4, characterized in that, The processes of the first gradient visualization and the second gradient visualization include: The system distinguishes between accelerating, decelerating, and constant-speed driving states.

6. The autonomous driving speed planning and prompting method based on adjacent lanes according to claim 4, characterized in that, The processes of the first gradient visualization and the second gradient visualization include: The actual driving speed of the autonomous vehicle is compared with the corresponding currently planned speed obtained according to either the current first planning strategy or the current second planning strategy. If the second speed difference obtained by subtracting the actual driving speed from the current planned speed is less than a preset second speed difference threshold, a first visual alarm is issued to the driver; and The actual driving speed of the autonomous vehicle is compared with the minimum drivable speed of the current lane calculated based on the first driving environment information. If the third speed difference obtained by subtracting the minimum drivable speed of the current lane from the actual driving speed is less than a preset third speed difference threshold, a second visual alarm prompt is given to the driver.

7. An autonomous driving speed planning device based on adjacent lanes, characterized in that, include, This module is used to calculate the maximum permissible speed in the current lane based on the first driving environment information obtained in real time during the autonomous vehicle's operation. A module for determining whether to calculate the maximum drivable speed of adjacent lanes based on the first driving environment information, wherein the process of determining whether to calculate the maximum drivable speed of adjacent lanes based on the first driving environment information includes: calculating the number of target vehicles that travel in the adjacent lanes and overtake the autonomous driving vehicle within a predetermined historical period based on the first driving environment information; if the number of target vehicles exceeds a preset overtaking number threshold, then it is determined that the maximum drivable speed of the adjacent lanes needs to be calculated; otherwise, it is determined that the maximum drivable speed of the adjacent lanes does not need to be calculated. A module for calculating the maximum driving speed of adjacent lanes if it is determined that it is necessary to calculate the maximum driving speed of adjacent lanes; A module for determining whether to change lanes based on the current maximum drivable speed of the lane, the maximum drivable speed of the adjacent lane, and real-time acquired second driving environment information; and If the decision is to change lanes, the autonomous vehicle's driving lane is changed to the adjacent lane. A current first planning strategy is obtained based on the maximum permissible speed of the adjacent lane, and then speed planning is performed on the autonomous vehicle according to the current first planning strategy. If the decision is not to change lanes, the autonomous vehicle continues to drive in the current lane, and a current second planning strategy is obtained based on the maximum drivable speed of the current lane. Then, the autonomous vehicle performs speed planning based on the current second planning strategy.

8. A computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are operated to perform the autonomous driving speed planning method based on adjacent lanes as described in any one of claims 1-3.

9. A computer device comprising a processor and a memory storing computer instructions, wherein the processor operates the computer instructions to perform the autonomous driving speed planning method based on adjacent lanes as described in any one of claims 1-3.

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