Empirical road section-based autonomous driving speed planning method and device, medium

Abstract

The application discloses an automatic driving speed planning method and device based on experience road sections, a medium and equipment, and belongs to the technical field of automatic driving. Mainly includes, the current road section is positioned and identified to obtain the current road section positioning and identification information; from the historical driving speed record library of the automatic driving vehicle pre-established, the record of the current road section historical driving speed corresponding to the road section positioning and identification information is inquired; if the historical road section driving speed record library exists the record of the current road section historical driving speed, then the current planning strategy is obtained according to the record of the current road section historical driving speed, and then the speed of the automatic driving vehicle is planned according to the current planning strategy; and according to the current driving speed of the automatic driving vehicle in the current road section, and the current road section positioning and identification information, the historical driving speed record library is iteratively updated. The application can save the operation resources when planning the speed, improve the system response, and improve the speed planning efficiency.

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, medium and equipment based on experience-based road sections. 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. Current technologies, such as cruise control or adaptive cruise control, rely solely on sensor information for speed planning and require manual setting of the initial speed via levers or buttons, resulting in low planning efficiency. Summary of the Invention

[0003] To address the problems existing in the prior art, this application mainly provides an autonomous driving speed planning method, device, medium, and equipment based on experience-based road sections. By trimming the ground side lines and road edge lines, the available parking space during path planning is increased, the success rate of path planning is improved, the space required for parking is reduced, and the parking efficiency is improved.

[0004] To achieve the above objectives, one technical solution adopted in this application is: providing an autonomous driving speed planning method based on experience-based road segments, which includes:

[0005] The system performs localization and identification on the current road segment where the autonomous vehicle is located, obtaining the current road segment localization and identification information. Based on the current road segment localization and identification information, it queries the historical driving speed record database pre-established by the autonomous vehicle to find the record of the current road segment's historical driving speed corresponding to the previous road segment localization and identification information. If the historical driving speed record database contains a record of the current road segment's historical driving speed, it obtains the current planning strategy based on the record of the current road segment's historical driving speed, and then performs speed planning for the autonomous vehicle based on the current planning strategy. Finally, it iteratively updates the historical driving speed record database based on the current driving speed of the autonomous vehicle on the current road segment and the current road segment localization and identification information.

[0006] One technical solution adopted in this application is: providing an autonomous driving speed planning and prompting method based on experience-based road sections, which includes:

[0007] The system locates and identifies the current road segment where the autonomous vehicle is located, obtaining the current road segment location information. Based on the current road segment location information, it queries the historical driving speed record database pre-established by the autonomous vehicle to find the record of the current road segment's historical driving speed corresponding to the previous road segment location information. If the historical driving speed record database contains a record of the current road segment's historical driving speed, the system obtains the current planning strategy based on this record, and then performs speed planning for the autonomous vehicle according to the current planning strategy. The system also provides a gradual visual display of the real-time speed changes determined by the speed planning, thereby providing corresponding prompts to the driver.

[0008] Another technical solution adopted in this application is: providing an autonomous driving speed planning device based on experience-based road sections, which includes:

[0009] The system comprises the following modules: a positioning and identification module for locating the current road segment where the autonomous vehicle is located, and a query module for querying historical speed records corresponding to the previous road segment positioning and identification information from a pre-established historical speed record database; a speed planning module for determining the current planning strategy based on historical speed records of the current road segment if such records exist in the database, and then performing speed planning for the autonomous vehicle based on these records; and an iterative update module for iteratively updating the historical speed record database based on the current speed of the autonomous vehicle on the current road segment and the current road segment positioning and identification information.

[0010] Another technical solution adopted in this application is to provide a computer-readable storage medium storing computer instructions that are operated to execute the experience-based road segment-based autonomous driving speed planning method in the above solution.

[0011] 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 experience-based road segment-based autonomous driving speed planning method in the above solution.

[0012] The beneficial effects of the technical solution of this application are: a method, device, medium, and equipment for autonomous driving speed planning based on experience-based road segments. This application utilizes a pre-established database of historical driving speeds to directly perform speed planning based on historical driving records when the current driving segment is the same as a historical driving segment. This saves computational resources during speed planning, improves system response, and increases speed planning efficiency. Attached Figure Description

[0013] 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.

[0014] Figure 1 This is a flowchart illustrating a specific implementation of an autonomous driving speed planning method based on experience-based road sections according to this application.

[0015] Figure 2 This is a flowchart illustrating a specific implementation of an experience-based speed planning and prompting method for autonomous driving based on road sections, as proposed in this application.

[0016] Figure 3 This is a schematic diagram of a specific implementation of an autonomous driving speed planning device based on experience road sections according to this application;

[0017] Figure 4 This is a schematic diagram of a specific embodiment of an autonomous driving speed planning and prompting device based on experience road sections according to this application;

[0018] 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

[0019] 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.

[0020] 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.

[0021] Existing autonomous vehicles perform speed planning in two modes: cruise control and following. Speed ​​planning requires data from perceived information and initial speed settings via levers or buttons. The computational demands of utilizing perceived information, coupled with delays caused by manual operation, result in relatively low efficiency for speed planning.

[0022] This application provides a method, apparatus, medium, and equipment for autonomous driving speed planning based on experience-based road segments, which can directly perform speed planning based on historical driving records when the current driving segment is the same as the historical driving segment.

[0023] 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.

[0024] Figure 1 This invention illustrates a specific implementation of an autonomous driving speed planning method based on experience-based road segments.

[0025] exist Figure 1 The specific implementation of the autonomous driving speed planning method based on experience road segments of this application, as shown, includes the following steps: Step S101, locating and identifying the current road segment where the autonomous vehicle is located to obtain the current road segment location identification information; Step S102, querying the historical driving speed record of the current road segment corresponding to the previous road segment location identification information from the historical driving speed record database pre-established by the autonomous vehicle based on the current road segment location identification information; Step S103, if the historical driving speed record of the current road segment exists in the historical driving speed record database, obtaining the current planning strategy based on the historical driving speed record of the current road segment, and then performing speed planning for the autonomous vehicle based on the current planning strategy; and Step S104, iteratively updating the historical driving speed record database based on the current driving speed of the autonomous vehicle in the current road segment and the current road segment location identification information.

[0026] This application utilizes a pre-established database of historical driving speeds to perform speed planning directly based on historical driving records when the current driving segment is the same as a historical driving segment. This saves computational resources during speed planning, improves system response, and increases speed planning efficiency.

[0027] Process S101 represents the process of locating and identifying the current road segment where the autonomous vehicle is located to obtain the current road segment location identification information. This process allows the system to query the historical driving speed of the current road segment from the pre-established historical driving speed records based on the current road segment location identification information.

[0028] In an optional embodiment of this application, the autonomous vehicle's own navigation map or high-precision map is used to locate and identify its current road segment. Typically, the vehicle's location and road segment information can be obtained through a map.

[0029] In an optional embodiment of this application, the perception devices configured on the autonomous vehicle itself are used to identify and locate the current road segment. During vehicle operation, there may be situations where communication between the onboard electronic devices is poor, preventing the use of maps for location identification. In such cases, the vehicle's own perception devices are needed to obtain current environmental information and identify the current road segment accordingly.

[0030] In an optional embodiment of this application, the autonomous vehicle utilizes its own navigation map or high-precision map, along with its onboard sensing devices, to locate and identify the current road segment. By using map positioning and sensing information as complementary elements, the identification of the current road segment becomes more accurate.

[0031] Specifically, the perception devices equipped in the aforementioned autonomous vehicles include AVM (Around View Fisheye Camera) and USS (Ultrasonic Radar).

[0032] Process S102 represents the process of querying the historical driving speed record of the current road segment corresponding to the previous road segment positioning and identification information from the historical driving speed record database pre-established by the autonomous vehicle based on the current road segment positioning and identification information. This facilitates obtaining the current planning strategy for speed planning when driving on the current road segment based on the historical driving speed of the current road segment.

[0033] In optional specific embodiments of this application, the autonomous driving speed planning method based on experience road segments further includes, during the autonomous driving process, performing location identification on the driving road segment traveled by the autonomous driving vehicle to obtain driving road segment location identification information, and storing the driving road segment location identification information and the corresponding driving speed in a one-to-one correspondence to obtain the above-mentioned historical driving speed record library, which can provide a basis for the autonomous driving vehicle to use historical driving speed to set the initial planned speed when driving the same road segment multiple times.

[0034] In an optional specific example of this application, all road segments traversed by the autonomous vehicle are identified and matched with their corresponding driving speeds, and the data is saved by powering down the vehicle controller.

[0035] In an optional specific example of this application, the aforementioned localization and identification process, as well as the process of storing the historical driving speed record database, are only performed when the autonomous vehicle is driving on frequently traveled road sections. Establishing a historical driving speed database for infrequently traveled road sections results in low usage and consumes system resources and memory space. Therefore, considering all factors, the historical driving speed record database is only established for frequently traveled routes to save memory and system resources.

[0036] In an optional specific embodiment of this application, the process of locating and identifying the driving road segment to obtain driving road segment location identification information includes dividing the road traversed by the autonomous vehicle into corresponding driving road segments based on the changes in the driving speed of the autonomous vehicle.

[0037] Specifically, autonomous vehicles cannot maintain a constant low or high speed during operation. For example, at the start of a journey, an autonomous vehicle needs to maintain a low speed on a side road, then a high speed in the middle, slowing down when passing schools, intersections, or traffic lights, then continuing at high speed, and finally reducing speed again to maintain a low speed for a period near the destination. Based on this, the journey can be divided into five segments.

[0038] In an optional specific embodiment of this application, a lookup table method is used to query the record of the historical driving speed of the current road segment corresponding to the previous road segment positioning and identification information from a pre-established historical driving speed record database of the autonomous vehicle.

[0039] Process S103 indicates that if the historical driving speed record of the current road segment exists in the historical driving speed record library, the current planning strategy is obtained based on the historical driving speed record of the current road segment, and then the speed planning process of the autonomous vehicle is performed based on the current planning strategy. The speed planning can be performed based on the corresponding historical driving speed record of the current road segment, which can reduce the amount of computation during speed planning, improve system response, and improve the efficiency of speed planning.

[0040] In an optional embodiment of this application, the process of obtaining the current planning strategy based on the historical driving speed record of the current road segment includes directly initializing the planned speed of the autonomous vehicle on the current road segment to the historical driving speed of the current road segment. Specifically, if there are no obstacles or other environmental changes on the current road segment, speed planning can be performed simply by directly initializing the planned speed to the historical driving speed of that road segment, which can greatly reduce the system's computational load, improve system responsiveness, and increase planning efficiency.

[0041] In an optional embodiment of this application, the process of obtaining the current planning strategy based on the historical driving speed record of the current road segment includes setting the initial planning speed of the autonomous vehicle on the current road segment to the historical driving speed of the current road segment; and obtaining the current planning strategy based on the perception information perceived by the autonomous vehicle and the initial planning speed. The perception information includes at least one of the following: the drivable space ahead of the autonomous vehicle, the driving speed of other relevant vehicles of the autonomous vehicle, the road slope of the current road segment, and the maximum speed limit of the current road segment. Specifically, the initial planning speed is first set to the historical driving speed to avoid the need for manual lever or button adjustment to set the initial planning speed or to perform perception and corresponding planning speed calculations from the beginning. Then, the planning is further adjusted based on the real-time driving environment perception information perceived by the vehicle, which can improve planning efficiency while ensuring driving safety and compliance.

[0042] In one optional specific example of this application, the acceleration of the autonomous vehicle is determined based on the drivable space in front of it, which is the free space in front of the vehicle in the lane and largely determines the upper limit of the vehicle's acceleration.

[0043] In one optional specific example of this application, the speed of the first vehicle in front of the autonomous vehicle is used to determine its planned speed. In order to ensure driving safety, it is necessary to maintain a safe distance between the vehicle and the vehicle in front. Therefore, the speed of the first vehicle in front is determined as the planned speed.

[0044] In one optional specific example of this application, the decision to allow the autonomous vehicle to change lanes and accelerate is determined based on the speed of vehicles in adjacent lanes. In a human driving scenario, if the speed of vehicles in adjacent lanes is significantly faster than that in the current lane, a lane change and acceleration are often sought. Therefore, simulating the human decision-making process involves paying attention to the speed of vehicles in adjacent lanes and making a decision on whether to change lanes and accelerate.

[0045] In one optional specific example of this application, the maximum speed limit of the current road segment is determined as the planned speed of the autonomous vehicle. In order to ensure safety and comply with relevant traffic regulations, it is necessary to ensure that the vehicle speed does not exceed the maximum speed limit of the current road segment. Therefore, the maximum speed limit of the current road segment is used as the planned speed of the vehicle.

[0046] In one optional specific example of this application, adjusting the planned speed of the autonomous vehicle according to the slope of the current road segment can avoid excessive fuel consumption and excessive wear and tear on related components caused by driving at high speeds on uphill sections. Figure 2 This paper illustrates a specific embodiment of an autonomous driving speed planning method based on experience-based road segments, as proposed in this application.

[0047] In one optional embodiment of this application, if there is no record of the historical driving speed for the current road segment in the historical road segment speed record database, the current planning strategy is directly obtained based on the perception information perceived by the autonomous vehicle, and speed planning is performed on the autonomous vehicle according to the current planning strategy. The perception information includes at least one of the following: the drivable space ahead of the autonomous vehicle, the driving speeds of other related vehicles of the autonomous vehicle, the road slope of the current road segment, and the maximum speed limit of the current road segment.

[0048] Process S104 represents the iterative update of the historical driving speed record database based on the current driving speed of the autonomous vehicle on the current road segment and the current road segment positioning and identification information, which facilitates speed planning based on the latest historical driving speed record database.

[0049] Specifically, if the road conditions of a section of road have changed compared to before, such as the addition of speed limits or traffic lights, the historical speed records of that section of road need to be updated iteratively so that speed planning can be carried out based on the latest speed records and a more suitable speed planning strategy can be obtained.

[0050] Figure 2 This paper illustrates a specific implementation of an autonomous driving speed planning prompt method based on experience-based road segments, as proposed in this application.

[0051] exist Figure 2 In the specific implementation shown, the autonomous driving speed planning prompt method based on experience road segments of this application includes the following steps: Step S201, locating and identifying the current road segment where the autonomous vehicle is located to obtain the current road segment location identification information; Step S202, querying the historical driving speed record of the current road segment corresponding to the previous road segment location identification information from the historical driving speed record database pre-established by the autonomous vehicle based on the current road segment location identification information; Step S203, if the historical driving speed record of the current road segment exists in the historical driving speed record database, obtaining the current planning strategy based on the historical driving speed record of the current road segment, and then performing speed planning for the autonomous vehicle based on the current planning strategy; and Step S204, gradually visualizing the real-time speed change process determined by the speed planning to provide corresponding prompts to the driver.

[0052] Process S204 represents the process of gradually visualizing the real-time speed changes determined by the speed planning, thereby providing corresponding prompts to the driver and enabling the driver to be psychologically prepared for changes in vehicle speed.

[0053] Existing autonomous vehicles can only display the vehicle's current speed and the planned speed. Drivers cannot be prepared in time 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 have good 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 status 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.

[0054] In an optional specific embodiment of this application, the process of obtaining the driving state that the autonomous vehicle needs to perform according to the current planning strategy, visually displaying the driving state that the autonomous vehicle needs to perform, and then providing corresponding prompts to the driver includes distinguishing and displaying the acceleration state, deceleration state, and constant speed state of the autonomous vehicle.

[0055] 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.

[0056] 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.

[0057] In an optional embodiment of this application, the process of gradually visually displaying the real-time speed change process determined by the speed planning, thereby providing corresponding prompts to the driver, includes:

[0058] The system compares the actual driving speed of the autonomous vehicle with the current planned speed obtained according to the current planning strategy. If the first speed difference obtained by subtracting the actual driving speed from the current planned speed is less than a preset first speed difference threshold, a first visual alarm prompt is given to the driver. The system also compares the actual driving speed of the autonomous vehicle with the current lane minimum drivable speed calculated based on the current perception information. If the second speed difference obtained by subtracting the current lane minimum drivable speed from the actual driving speed is less than a preset second speed difference threshold, a second visual alarm prompt is given to the driver.

[0059] 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 first speed difference is less than a preset first speed difference threshold, a visual prompt can be given to the driver by flashing a red and green speed progress bar, or a visual prompt can be given to the driver by voice broadcast.

[0061] Optionally, if the second speed difference is less than a preset second speed difference threshold, a visual prompt can be given to the driver by flashing a yellow-green speed progress bar, or a visual prompt can 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 experience-based road sections.

[0063] exist Figure 3The specific implementation of the autonomous driving speed planning device based on experience road segments of this application, as shown, includes a positioning and identification module 301, used to perform positioning and identification on the current road segment where the autonomous vehicle is located to obtain the current road segment positioning and identification information; a query module 302, used to query the historical driving speed record of the current road segment corresponding to the previous road segment positioning and identification information from the historical driving speed record database pre-established by the autonomous vehicle based on the current road segment positioning and identification information; a speed planning module 303, used to obtain the current planning strategy based on the historical driving speed record of the current road segment if there is a record of the historical driving speed of the current road segment in the historical road segment driving speed record database, and then perform speed planning for the autonomous vehicle based on the current planning strategy; and an iterative update module 304, used to iteratively update the historical driving speed record database based on the current driving speed of the autonomous vehicle in the current road segment and the current road segment positioning and identification information.

[0064] The device in this application utilizes a pre-established database of historical driving speeds to perform speed planning directly based on historical driving records when the current driving segment is the same as a historical driving segment. This saves computational resources during speed planning, improves system response, and enhances speed planning efficiency.

[0065] The positioning and identification module 301 is used to locate and identify the current road segment where the autonomous vehicle is located to obtain the current road segment positioning and identification information. It can facilitate the query of the historical driving speed of the current road segment from the pre-established historical driving speed records based on the current road segment positioning and identification information.

[0066] The query module 302 is used to query the historical driving speed record of the current road segment corresponding to the previous road segment positioning and identification information from the historical driving speed record database pre-established by the autonomous vehicle based on the current road segment positioning and identification information. It can facilitate the current planning strategy for speed planning when driving on the current road segment based on the historical driving speed of the current road segment.

[0067] The speed planning module 303 is used to obtain the current planning strategy based on the historical driving speed record of the current road segment if the historical driving speed record of the current road segment exists in the historical driving speed record library, and then perform speed planning for the autonomous vehicle based on the current planning strategy. It can perform speed planning based on the corresponding historical driving speed record of the current road segment, which can reduce the amount of computation during speed planning, improve system responsiveness, and improve the efficiency of speed planning.

[0068] The iterative update module is used to update the historical driving speed record database based on the current driving speed of the autonomous vehicle on the current road segment and the current road segment positioning and identification information. This facilitates speed planning based on the latest historical driving speed record database.

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

[0070] exist Figure 4 In the specific implementation shown, the autonomous driving speed planning prompt device based on experience road segments of this application includes: a positioning and identification module 301, used to perform positioning and identification on the current road segment where the autonomous driving vehicle is located to obtain the current road segment positioning and identification information; a query module 302, used to query the historical driving speed record corresponding to the previous road segment positioning and identification information from the historical driving speed record database pre-established by the autonomous driving vehicle based on the current road segment positioning and identification information; a speed planning module 303, used to obtain the current planning strategy based on the historical driving speed record if there is a record of the current road segment driving speed in the historical road segment driving speed record database, and then perform speed planning for the autonomous driving vehicle based on the current planning strategy; and a display prompt module 404, used to gradually visualize the real-time speed change process determined by the speed planning, thereby providing corresponding prompts to the driver.

[0071] The display prompt module 404 is used to gradually visualize the real-time speed change process determined by the speed plan, thereby providing corresponding prompts to the driver, which helps the driver to be mentally prepared for changes in vehicle speed.

[0072] Existing autonomous vehicles can only display the vehicle's current speed and the planned speed. Drivers cannot be prepared in time 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 experience-based road segment-based autonomous driving speed planning device provided in this application can be used to execute the extended experience-based road segment-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 experience road segments 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 experience-based road segment-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 experience-based road segment-based autonomous driving speed planning method in the above-described scheme.

[0079] In another specific embodiment of this application, an autonomous driving system includes the experience-based road segment 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 speed planning method for autonomous driving based on experience-based road sections, characterized in that, include: The location of the autonomous vehicle on the current road segment is identified to obtain the location identification information of the current road segment; Based on the current road segment location and identification information, the system queries the historical driving speed record of the current road segment corresponding to the previous road segment location and identification information from the historical driving speed record database pre-established by the autonomous vehicle. If the historical road segment speed record database contains a record of the historical driving speed of the current road segment, then the current planning strategy is obtained based on the record of the historical driving speed of the current road segment, and then the speed of the autonomous vehicle is planned according to the current planning strategy. The process of obtaining the current planning strategy based on the record of the historical driving speed of the current road segment includes: The initial planned speed of the autonomous vehicle on the current road segment is set to the historical driving speed of the current road segment; and The current planning strategy is obtained based on the real-time perception information perceived by the autonomous vehicle and the initial planning speed. The perception information includes at least one of the following: the drivable space ahead of the autonomous vehicle, the driving speed of other related vehicles of the autonomous vehicle, the road gradient of the current road segment, and the maximum speed limit of the current road segment. The step of speed planning for the autonomous vehicle according to the current planning strategy includes: adjusting the planned speed of the autonomous vehicle based on the gradient of the current road segment; and The historical driving speed record database is iteratively updated based on the current driving speed of the autonomous vehicle on the current road segment and the positioning and identification information of the current road segment.

2. The autonomous driving speed planning method based on experience-based road segments according to claim 1, characterized in that, The process of establishing the historical driving speed record database includes: During the historical driving process of the autonomous vehicle, the driving route segments traveled by the autonomous vehicle are located and identified in real time to obtain driving route segment location identification information; and The historical driving speed record database is obtained by storing the location and identification information of the driving section and the corresponding driving speed in a one-to-one correspondence.

3. The autonomous driving speed planning method based on experience-based road segments according to claim 2, characterized in that, The process of obtaining real-time location identification information for the driving route segments during the historical driving process of the autonomous vehicle includes: Based on the changes in the driving speed of the autonomous vehicle, the roads traveled by the autonomous vehicle are divided into corresponding driving segments.

4. A method for providing speed planning and prompting for autonomous driving based on experience-based road sections, characterized in that, include: The location of the autonomous vehicle on the current road segment is identified to obtain the location identification information of the current road segment; Based on the current road segment location and identification information, the system queries the historical driving speed record of the current road segment corresponding to the previous road segment location and identification information from the historical driving speed record database pre-established by the autonomous vehicle. If the historical road segment speed record database contains a record of the historical driving speed of the current road segment, then the current planning strategy is obtained based on the record of the historical driving speed of the current road segment, and then the speed of the autonomous vehicle is planned according to the current planning strategy. The process of obtaining the current planning strategy based on the record of the historical driving speed of the current road segment includes: The initial planned speed of the autonomous vehicle on the current road segment is set to the historical driving speed of the current road segment; and The current planning strategy is obtained based on the real-time perception information perceived by the autonomous vehicle and the initial planning speed. The perception information includes at least one of the following: the drivable space ahead of the autonomous vehicle, the driving speed of other related vehicles of the autonomous vehicle, the road gradient of the current road segment, and the maximum speed limit of the current road segment. The step of speed planning for the autonomous vehicle according to the current planning strategy includes: adjusting the planned speed of the autonomous vehicle based on the gradient of the current road segment; and The real-time speed change process determined by the speed planning is gradually visualized to provide corresponding prompts to the driver.

5. The autonomous driving speed planning and prompting method based on experience-based road segments according to claim 4, characterized in that, The process of gradually visualizing the real-time speed changes determined by the speed planning, thereby providing corresponding prompts to the driver, includes: The system distinguishes between accelerating, decelerating, and constant-speed driving states.

6. The autonomous driving speed planning and prompting method based on experience-based road segments according to claim 4, characterized in that, The process of gradually visualizing the real-time speed changes determined by the speed planning, thereby providing corresponding prompts to the driver, includes: The actual driving speed of the autonomous vehicle is compared with the current planned speed obtained according to the current planning strategy. If the first speed difference obtained by subtracting the actual driving speed from the current planned speed is less than a preset first speed difference threshold, a first visual alarm is issued to the driver. The actual driving speed of the autonomous vehicle is compared with the minimum driving speed of the current lane calculated based on the current perception information. If the second speed difference obtained by subtracting the minimum driving speed of the current lane from the actual driving speed is less than a preset second speed difference threshold, a second visual alarm prompt is given to the driver.

7. An autonomous driving speed planning device based on experience-based road sections, characterized in that, include, The positioning and identification module is used to locate and identify the current road segment where the autonomous vehicle is located, and obtain the positioning and identification information of the current road segment; The query module is used to query the historical driving speed record of the current road segment corresponding to the previous road segment positioning and identification information from the historical driving speed record database pre-established by the autonomous vehicle, based on the current road segment positioning and identification information. A speed planning module is used to, if the historical speed record database for the current road segment contains a record of the historical speed of the current road segment, obtain a current planning strategy based on the historical speed record of the current road segment, and then perform speed planning for the autonomous vehicle based on the current planning strategy. The process of obtaining the current planning strategy based on the historical speed record of the current road segment includes: setting the initial planned speed of the autonomous vehicle on the current road segment to the historical speed of the current road segment; and obtaining the current planning strategy based on real-time perception information perceived by the autonomous vehicle and the initial planned speed. The perception information includes at least one of the following: the drivable space ahead of the autonomous vehicle, the speeds of other relevant vehicles, the slope of the current road segment, and the maximum speed limit of the current road segment. The process of performing speed planning for the autonomous vehicle based on the current planning strategy includes: adjusting the planned speed of the autonomous vehicle based on the slope of the current road segment; and... The iterative update module is used to iteratively update the historical driving speed record database based on the current driving speed of the autonomous vehicle on the current road segment and the positioning and identification information of the current road segment.

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 experience road segments 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 automated driving speed planning method based on experience road segments according to any one of claims 1-3.

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