Driving route identification system and method, electronic equipment and computer readable medium

Abstract

The invention provides a driving route recognition system and method, electronic equipment and a readable medium, and belongs to the field of intelligent driving. According to the processed original image and preset navigation information, navigation and road condition information guidance are provided for a driver or intelligent driving is provided for the driver, and according to the intelligent driving technology provided by the patent, an intelligent driving auxiliary system with the core target of solving driver navigation confusion under complex road conditions is constructed. Through deep fusion of high-precision visual perception and map navigation information, strong road identification judgment logic is utilized, when a driver actively requests or a system pre-judges needs, an intelligent driving module provides accurate vehicle control assistance, and clear navigation prompts are combined to jointly ensure that a vehicle safely and correctly passes through a complex road scene, so that the driving safety of the vehicle is improved. And the driving convenience and safety are obviously improved. Voice input is a key link of man-machine cooperation.

Description

Technical Field

[0001] This invention relates to the field of intelligent driving technology, and in particular to a driving route recognition system, method, electronic device, and computer-readable medium. Background Technology

[0002] With the rapid development of the automotive industry, cars are no longer an unattainable means of transportation, and ordinary families can now own one. Driving is no longer the exclusive domain of experienced drivers; novice drivers can also enjoy daily commutes. However, due to complex road conditions and intersections, it's easy to take the wrong turn, miss exits, or even worse, drive against traffic. Currently, most people use map software for navigation, which can indeed help drivers plan routes. However, for complex intersections, drivers still need to make their own judgments. Even experienced drivers sometimes make mistakes at these complex intersections or forks in the road, let alone novice drivers.

[0003] As a tool for image acquisition and recognition, dashcams can only perform simple traffic sign and road recognition. They provide insufficient key information to the driver and may also have limitations in chip processing power, resulting in delays and lags in information delivery. Furthermore, they only provide basic intersection and road information without voice or intelligent driving intervention. In extremely complex road conditions where even with key information, proper driving is impossible, and the vehicle cannot replace the driver for correct driving. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art, and proposes a driving route recognition system, method, electronic device and computer-readable medium.

[0005] In a first aspect, embodiments of the present invention provide a driving route recognition system, comprising:

[0006] The visual image acquisition module is used to capture raw images of the front of the vehicle in real time.

[0007] A visual image processing module is used to process the original image;

[0008] The navigation information collection module is used to provide preset navigation information;

[0009] The road recognition and judgment module is used to determine whether to execute the navigation prompt module or the intelligent driving module based on the processed original image and the navigation information.

[0010] The navigation prompt module is used to provide the driver with navigation and road condition information guidance according to the instructions of the road recognition and judgment module;

[0011] The intelligent driving module is used to provide intelligent driving to the driver according to the instructions of the road recognition and judgment module.

[0012] In some embodiments, the visual image acquisition module is used to convert optical information of the vehicle's surrounding environment into digital images.

[0013] In some embodiments, the visual image acquisition module includes multiple cameras and multiple sensors, the multiple cameras including a front-view camera, a side-view camera and a rear-view camera, and the multiple sensors including radar.

[0014] In some embodiments, the visual image processing module performs the following processing on the original image:

[0015] The original image is preprocessed;

[0016] Image correction is performed on the preprocessed original image;

[0017] The corrected image is then processed using image enhancement techniques.

[0018] Extracting key features from images processed by image enhancement techniques;

[0019] Target recognition and classification are performed on images from which key features have been extracted;

[0020] Image recognition and classification of targets are analyzed and predicted through behavior analysis;

[0021] The image data is fused with behavioral analysis and prediction to generate panoramic images.

[0022] In some embodiments, the navigation information collection module integrates an in-vehicle navigation system or connects to a mobile phone / cloud navigation service to provide preset navigation information, including planned routes, information on upcoming intersections / ramp, suggested turning directions, number of lanes, speed limit information, and road classification.

[0023] In some embodiments, when the road recognition and judgment module determines that the road conditions are simple and clear and consistent with the navigation information based on the processed original image and the navigation information, the navigation prompt module is triggered to provide regular voice / image prompts.

[0024] When the road recognition and judgment module determines that the road conditions are complex and conflict with the navigation information based on the processed original image and the navigation information, it triggers the intelligent driving module to prepare for assisted decision-making or vehicle control.

[0025] In some embodiments, a voice input module is also included, which is used to receive voice commands from the driver, and the intelligent driving module is also used to make auxiliary decisions or control the vehicle based on the driver's voice requests.

[0026] Secondly, the present invention also provides a method for identifying the driving route of the driving route identification system, comprising the following steps:

[0027] Capture raw images of the area in front of the vehicle in real time;

[0028] The original image is processed;

[0029] Provides preset navigation information;

[0030] Based on the processed original image and the navigation information, it is determined whether to provide the driver with navigation and road condition information guidance or to provide the driver with intelligent driving.

[0031] Thirdly, embodiments of the present invention provide an electronic device, including:

[0032] One or more processors;

[0033] Memory, used to store one or more programs;

[0034] When the one or more programs are executed by the one or more processors, the one or more processors implement any of the methods.

[0035] Fourthly, embodiments of the present invention also provide a computer-readable medium storing a computer program, which, when executed by a processor, implements the steps of any of the methods described.

[0036] The driving route recognition system provided by this invention captures raw images of the road ahead in real time, processes these images, and determines whether to provide the driver with navigation and road condition guidance or intelligent driving assistance based on the processed raw images and preset navigation information. The intelligent driving technology provided by this patent constructs an intelligent driving assistance system with the core objective of solving driver navigation confusion in complex road conditions. Through deep fusion of high-precision visual perception and map navigation information, and utilizing powerful road recognition and judgment logic, the intelligent driving module provides precise vehicle control assistance when the driver actively requests it or the system anticipates the need. Combined with clear navigation prompts, this ensures the vehicle safely and correctly navigates complex road scenarios, significantly improving driving convenience and safety. Voice input is a key link in human-machine collaboration. Attached Figure Description

[0037] Figure 1This is a flowchart illustrating the steps of an embodiment of the vehicle route recognition system of the present invention;

[0038] Figure 2 This is a flowchart of the steps of the visual image processing module of the vehicle route recognition system of the present invention;

[0039] Figure 3 This is a flowchart of the driving route recognition method of the present invention;

[0040] Figure 4 This is a schematic diagram of the structure of an embodiment of the electronic device of the present invention. Detailed Implementation

[0041] To enable those skilled in the art to better understand the technical solutions of the present invention, exemplary embodiments of the present invention are described below in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0042] Where there is no conflict, the various embodiments of the present invention and the features thereof may be combined with each other.

[0043] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0044] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Terms such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0045] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having the meaning consistent with their meaning in the context of the relevant art and the invention, and will not be interpreted as having an idealized or overly formal meaning unless expressly so defined herein.

[0046] In the technical solution of this invention, the collection, storage, use, processing, transmission, provision, and disclosure of user personal information all comply with relevant laws and regulations and do not violate public order and good morals. The use of user data in this technical solution follows relevant national laws and regulations (e.g., the "Information Security Technology - Personal Information Security Specification"). For example: appropriate measures are taken for personal information access control; restrictions are imposed on the display of personal information; the purpose of using personal information does not exceed the scope of direct or reasonable association; and explicit identity targeting is eliminated when using personal information to avoid precisely locating a specific individual.

[0047] In related technologies, dashcams, as tools for image acquisition and recognition, can only perform simple traffic sign and road recognition. They provide insufficient key information to the driver and may also have limitations in chip computing power, leading to delays and lags in information prompts. Furthermore, they only provide simple intersection and road information without voice or intelligent driving intervention. In extremely complex road conditions where even with key information, proper driving is impossible, and the vehicle cannot replace the driver for correct driving. It also cannot provide route planning and operational prompts for complex road conditions, nor can it replace the driver, allowing intelligent driving systems to navigate complex road sections based on image and map data.

[0048] To address at least one of the technical problems existing in the aforementioned related technologies, the present invention provides a driving route recognition system. Figure 1 This is a schematic diagram of a driving route recognition system provided in an embodiment of the present invention.

[0049] like Figure 1 As shown, the driving route recognition system includes: a visual image acquisition module 10, a visual image processing module 20, a navigation information collection module 30, a voice input module 40, a road recognition and judgment module 50, a navigation prompt module 60, and an intelligent driving module. The specific implementation methods of each component are described in detail below.

[0050] The visual image acquisition module 10 is used to capture raw images of the front of the vehicle in real time.

[0051] As can be understood, the visual image acquisition module 10 acts as the system's "eyes," responsible for capturing raw image / video data of the road environment in front of the vehicle in real time. This primarily relies on a high-resolution camera (monocular or multi-view) mounted at the front of the vehicle (usually behind the windshield). Its field of view covers a certain range directly in front of and to the sides of the vehicle, ensuring the capture of crucial information such as road signs, lane lines, traffic lights, vehicles, pedestrians, obstacles, and intersection structures.

[0052] Specifically, visual acquisition is a crucial component of the vehicle vision system, responsible for converting optical information about the vehicle's surroundings into digital images. First, by configuring multiple cameras (such as front-view, side-view, and rear-view cameras) and multi-sensor fusion (such as radar and lidar), comprehensive environmental perception is achieved. Cameras capture images at predetermined time intervals or triggered by specific events. Image data is transmitted to the processing unit via a high-speed interface and temporarily stored in a high-speed cache, with data compression and persistent storage performed as needed.

[0053] The visual image processing module 20 is used to process the original image.

[0054] In this embodiment, the visual image processing module 20 acts as the "visual brain" of the system, responsible for real-time analysis and understanding of the acquired raw images.

[0055] Specifically, it relies on powerful image processing chips (such as GPUs and dedicated AI accelerators) for high-speed computing and applies advanced computer vision (CV) and deep learning (DL) algorithms to perform real-time analysis of the acquired raw images.

[0056] Please see Figure 2 The visual image processing module 20 is a core component of the vehicle vision system, responsible for performing a series of processing steps on the acquired images to extract useful information and improve image quality. First, preprocessing steps such as denoising, grayscale conversion, contrast adjustment, image cropping, and color correction remove noise, reduce computational load, enhance contrast, preserve key areas, and correct color deviations. Next, image correction is performed, including lens distortion correction and perspective transformation, to eliminate distortion and adjust the viewing angle. Then, image enhancement techniques such as brightness adjustment, sharpening, and histogram equalization improve the overall image quality and detail. Next, feature extraction is performed, using edge detection, texture analysis, color segmentation, shape recognition, and depth estimation to extract key features from the image. Subsequently, target recognition and classification are performed, identifying traffic signs, lane lines, pedestrians, vehicles, and obstacles, and predicting traffic lights. Furthermore, through behavior analysis and prediction, the movement trajectories of other vehicles and pedestrians are predicted, and driving intentions are identified. Finally, through multi-sensor fusion and multi-view image fusion, image data is combined with other sensor data to generate a panoramic image. Image annotation (manual or automatic) is also an important step in training the machine learning model. The entire image processing process ensures the efficient and accurate extraction and processing of key information from the image.

[0057] Through the above analysis, target detection and recognition can be achieved, such as: recognizing road signs (speed limit, turn indicators, prohibition, etc.), traffic light status, lane line types (solid lines, dashed lines, disappearing lines, etc.), pedestrians, vehicles, cones, and other objects; and analyzing the current road type (highway, urban road, rural road), intersection structure (cross, T, roundabout, multi-way intersection), and lane topology.

[0058] It is understandable that the visual image processing module 20 is used to transform the raw pixel data into structured data with semantic information (such as: "There is a five-way intersection 100 meters ahead", "The current lane is a left-turn lane", "Stop sign detected", "Red light is on").

[0059] The navigation information collection module 30 is used to provide preset navigation information.

[0060] The navigation information collection module 30 acts as the system's "predictive map," providing preset route planning and road information.

[0061] In this embodiment, the navigation information collection module 30 integrates an in-vehicle navigation system (such as GPS + inertial navigation) or connects to a mobile phone / cloud navigation service. It acquires high-precision map data (or standard navigation maps), including planned routes, information on upcoming intersections / ramp points, suggested turning directions, number of lanes, speed limits, road classification, etc.

[0062] It is understood that this embodiment utilizes road condition information provided by navigation, such as road speed limits and road signs, combined with in-vehicle / external cameras and machine vision technology, to proactively assess the driving difficulty of road sections from multiple dimensions, such as pedestrians, actual road vehicles, and congestion. Such comprehensive analysis will help to design the optimal route more accurately and take over the driving work of the driver at any time.

[0063] The voice input module 40 is used to receive the driver's voice commands.

[0064] The voice input module 40 serves as the system's start switch and human-machine interface, receiving the driver's voice commands to activate specific functions (mainly intelligent driving assistance).

[0065] For example, the system collects the driver's voice through an in-vehicle microphone array. Automatic speech recognition (ASR) technology is used to convert the speech into text. Natural language understanding (NLU) technology is used to interpret the intent of the commands. The driver can actively request the system to intervene in complex road conditions or take over control through specific voice commands (such as "Activate intelligent driving assistance to pass the intersection" or "Help me see how to get there").

[0066] It is understood that the voice-activated intelligent interaction function provided in this embodiment enables more natural and efficient information exchange between the driver and the vehicle through natural language interaction. Compared with existing voice interaction systems, the voice recognition technology in this technical solution can better understand the driver's needs, reduce response time, and improve the interactive experience.

[0067] The road recognition and judgment module 50 is used to determine whether to execute the navigation prompt module or the intelligent driving module based on the processed original image and the navigation information.

[0068] The road recognition and judgment module 50 serves as the system's decision center and information fusion unit, responsible for comparison, analysis, and decision-making.

[0069] It is understandable that the road recognition and judgment module 50 receives real-time perception results from the visual image processing module and planned route / map information from the navigation information collection module.

[0070] Does the road condition information recognized by the vision ahead (such as intersection type, lane indication, and signs) match the next action prompted by the navigation (such as "turn right in 300 meters ahead")? Is the current road condition complex (such as multiple forks, irregular intersections, unclear signs, and chaotic lane lines) or conflicting (such as seeing a no-entry sign but the navigation prompts you to go straight)? Will the driver be confused? Has a clear assistance request been received from the "voice input module"?

[0071] If the road conditions are simple, clear, and consistent with the navigation: the navigation prompt module is triggered, providing standard voice / image prompts. If the road conditions are complex, contain conflicting information, or a voice request is received from the driver: the intelligent driving module is triggered, preparing to make assisted decisions or control the vehicle.

[0072] This embodiment provides more intelligent driving operation prompts, tailored to different road conditions, such as speed control, steering wheel maneuvers, and light operation. The driver operates according to the vehicle's prompts, and the system can also correct any missed actions. If the driver explicitly requests the vehicle's intelligent driving system to take over, it will immediately activate and match visual and map navigation data to help the driver navigate complex road conditions correctly. After the driver exits the system via voice, it enters the monitoring state described in section 1 above, providing voice prompts for vehicle operation.

[0073] It is understood that the intelligent driving technology provided in this embodiment can calculate the optimal driving route based on map navigation data and real-time traffic information, and control the vehicle to travel along the predetermined route. Compared with existing intelligent driving systems, this technical solution can better cope with complex traffic conditions, improve traffic efficiency, and reduce traffic congestion.

[0074] The navigation prompt module 60 is used to provide the driver with navigation and road condition information guidance according to the instructions of the road recognition and judgment module.

[0075] It is understood that the navigation prompt module 60 acts as the system's "information broadcaster," providing the driver with navigation and road condition information guidance.

[0076] Standard prompts: In simple road conditions, standard voice prompts (such as "Go straight at the intersection ahead" or "Keep to the left") and / or display turn arrows and lane guidance maps on the instrument panel / center console screen.

[0077] Enhanced prompts for complex road conditions: When the "Road Recognition and Judgment Module" deems it necessary, more detailed and emphasized voice prompts will be provided (such as "Attention, there is a complex five-way intersection ahead, please take the second right turn lane", "You are about to enter a roundabout, please exit at the third exit"), and clearer guide lines or enlarged intersection diagrams may be superimposed on the screen.

[0078] Potential interaction: When the system is uncertain or needs confirmation, it can ask the driver via voice (e.g., "Construction detected, please confirm whether to detour along the original route?").

[0079] The intelligent driving module 70 is used to provide intelligent driving to the driver according to the instructions of the road recognition and judgment module.

[0080] The intelligent driving module 70 acts as the "executor" of the system, providing direct vehicle control assistance to help the vehicle pass through correctly when the driver needs assistance or when the system judges the road conditions to be too complex and prone to errors.

[0081] The intelligent driving module 70 receives the start command from the "road recognition and judgment module" and comprehensively utilizes the real-time perception data from the "visual image processing module" and the map information from the "navigation information collection module". Based on the fused information, it generates a locally optimal path through the current complex road conditions (such as selecting the correct lane and determining the timing of the roundabout exit).

[0082] For example, through the vehicle's drive-by-wire system (steering, accelerator, brake), the driver can take over briefly under supervision or upon request to control the vehicle to travel along a planned path (such as automatically steering through complex curves, automatically selecting lanes and exits in roundabouts).

[0083] This module intervenes when the driver is unable to match the visual scene (output of the vision module) with the navigation prompts (output of the navigation module) due to complex road conditions. It utilizes the system's powerful fusion perception and decision-making capabilities to complete the "seeing," "thinking," and "doing" parts on behalf of the driver, ensuring that the vehicle travels along the correct path.

[0084] It is understood that this embodiment, through its autonomous driving function, allows the driver to relax and reduce driving burden during driving. Especially during long drives or in complex road conditions, it significantly improves driving comfort and safety. Furthermore, the intelligent driving technology provided in this embodiment can automatically adjust driving strategies according to different road conditions and environments, improving the system's adaptability. Compared to existing intelligent driving systems, it can better cope with various complex driving environments, improving driving safety and reliability.

[0085] The driving route recognition system provided in this embodiment constructs an intelligent driving assistance system with the core objective of solving driver navigation confusion in complex road conditions. Through deep fusion of high-precision visual perception and map navigation information, and utilizing powerful road recognition and judgment logic, the intelligent driving module provides precise vehicle control assistance when the driver actively requests it or the system anticipates the need. Combined with clear navigation prompts, this ensures the vehicle safely and correctly navigates complex road scenarios, significantly improving driving convenience and safety.

[0086] like Figure 3 As shown, based on the same inventive concept, embodiments of the present invention also provide a driving route recognition method for executing the above-described driving route recognition system, comprising:

[0087] Capture raw images of the area in front of the vehicle in real time.

[0088] Specifically, visual acquisition is a crucial component of the vehicle vision system, responsible for converting optical information about the vehicle's surroundings into digital images. First, by configuring multiple cameras (such as front-view, side-view, and rear-view cameras) and multi-sensor fusion (such as radar and lidar), comprehensive environmental perception is achieved. Cameras capture images at predetermined time intervals or triggered by specific events. Image data is transmitted to the processing unit via a high-speed interface and temporarily stored in a high-speed cache, with data compression and persistent storage performed as needed.

[0089] The original image is then processed.

[0090] In this embodiment, firstly, preprocessing steps such as denoising, grayscale conversion, contrast adjustment, image cropping, and color correction are performed to remove noise, reduce computational load, enhance contrast, preserve key areas, and correct color deviations. Next, image correction is performed, including lens distortion correction and perspective transformation, to eliminate distortion and adjust the viewing angle. Then, image enhancement techniques such as brightness adjustment, sharpening, and histogram equalization are used to improve the overall image quality and detail. Next, feature extraction is performed using edge detection, texture analysis, color segmentation, shape recognition, and depth estimation to extract key features from the image. Subsequently, target recognition and classification are performed to identify traffic signs, lane lines, pedestrians, vehicles, and obstacles, and traffic lights are predicted. Furthermore, through behavior analysis and prediction, the movement trajectories of other vehicles and pedestrians are predicted, and driving intentions are identified. Finally, through multi-sensor fusion and multi-view image fusion, image data is combined with other sensor data to generate a panoramic image. Image annotation (manual or automatic) is also an important step in training the machine learning model. The entire image processing process ensures efficient and accurate extraction and processing of key information in the image.

[0091] Provides preset navigation information.

[0092] In this embodiment, high-precision map data (or standard navigation map) is acquired, including planned routes, information on upcoming intersections / ramp, suggested turning directions, number of lanes, speed limit information, road grade, etc.

[0093] Receives voice commands from the driver.

[0094] For example, the system collects the driver's voice through an in-vehicle microphone array. Automatic speech recognition (ASR) technology is used to convert the speech into text. Natural language understanding (NLU) technology is used to interpret the intent of the commands. The driver can actively request the system to intervene in complex road conditions or take over control through specific voice commands (such as "Activate intelligent driving assistance to pass the intersection" or "Help me see how to get there").

[0095] Based on the processed original image and the navigation information, it is determined whether to provide the driver with navigation and road condition information guidance or to provide the driver with intelligent driving.

[0096] Does the road condition information recognized by the vision ahead (such as intersection type, lane indication, and signs) match the next action prompted by the navigation (such as "turn right in 300 meters ahead")? Is the current road condition complex (such as multiple forks, irregular intersections, unclear signs, and chaotic lane lines) or conflicting (such as seeing a no-entry sign but the navigation prompts you to go straight)? Will the driver be confused? Has a clear assistance request been received from the "voice input module"?

[0097] If the road conditions are simple, clear, and consistent with the navigation: the navigation prompt module is triggered, providing standard voice / image prompts. If the road conditions are complex, contain conflicting information, or a voice request is received from the driver: the intelligent driving module is triggered, preparing to make assisted decisions or control the vehicle.

[0098] Standard prompts: In simple road conditions, standard voice prompts (such as "Go straight at the intersection ahead" or "Keep to the left") and / or display turn arrows and lane guidance maps on the instrument panel / center console screen.

[0099] Enhanced prompts for complex road conditions: When the "Road Recognition and Judgment Module" deems it necessary, more detailed and emphasized voice prompts will be provided (such as "Attention, there is a complex five-way intersection ahead, please take the second right turn lane", "You are about to enter a roundabout, please exit at the third exit"), and clearer guide lines or enlarged intersection diagrams may be superimposed on the screen.

[0100] Potential interaction: When the system is uncertain or needs confirmation, it can ask the driver via voice (e.g., "Construction detected, please confirm whether to detour along the original route?").

[0101] It is understood that this embodiment, through its autonomous driving function, allows the driver to relax and reduce driving burden during driving. Especially during long drives or in complex road conditions, it significantly improves driving comfort and safety. Furthermore, the intelligent driving technology provided in this embodiment can automatically adjust driving strategies according to different road conditions and environments, improving the system's adaptability. Compared to existing intelligent driving systems, it can better cope with various complex driving environments, improving driving safety and reliability.

[0102] The driving route recognition method provided in this embodiment constructs an intelligent driving assistance system with the core objective of resolving driver navigation confusion in complex road conditions. Through deep fusion of high-precision visual perception and map navigation information, and utilizing powerful road recognition and judgment logic, the intelligent driving module provides precise vehicle control assistance when the driver actively requests it or the system anticipates the need. Combined with clear navigation prompts, this ensures the vehicle safely and correctly navigates complex road scenarios, significantly improving driving convenience and safety.

[0103] Based on the same inventive concept, embodiments of the present invention also provide an electronic device. Figure 4 This is a structural block diagram of an electronic device provided in an embodiment of the present invention. Figure 4As shown, an embodiment of the present invention provides an electronic device including: one or more processors 101, a memory 102, and one or more I / O interfaces 103. The memory 102 stores one or more programs, which, when executed by the one or more processors, enable the one or more processors to implement any of the driving route recognition systems described in the above embodiments; the one or more I / O interfaces 103 are connected between the processor and the memory, configured to enable information interaction between the processor and the memory.

[0104] The processor 101 is a device with data processing capabilities, including but not limited to a central processing unit (CPU); the memory 102 is a device with data storage capabilities, including but not limited to random access memory (RAM, more specifically SDRAM, DDR, etc.), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), and flash memory (FLASH); the I / O interface (read / write interface) 103 is connected between the processor 101 and the memory 102, and can realize information interaction between the processor 101 and the memory 102, including but not limited to a data bus (Bus).

[0105] In some embodiments, the processor 101, memory 102, and I / O interface 103 are interconnected via bus 104, and thus connected to other components of the computing device.

[0106] In some embodiments, the one or more processors 101 include a field-programmable gate array.

[0107] This invention also provides a computer-readable medium. The computer-readable medium stores a computer program, which, when executed by a processor, implements the steps of any of the driving route recognition systems described in the above embodiments. The computer-readable storage medium can be volatile or non-volatile.

[0108] This invention also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code. When the computer-readable code is run in the processor of an electronic device, the processor in the electronic device executes the above-described intelligent driving assistance method.

[0109] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0110] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0111] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0112] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0113] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0114] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0115] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0116] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0118] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in conjunction with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in conjunction with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of the invention as set forth in the appended claims.

Claims

1. A driving route recognition system, characterized in that, It includes: The visual image acquisition module is used to capture raw images of the vehicle's surrounding environment in real time. A visual image processing module is used to process the original image; The navigation information collection module is used to provide preset navigation information; The road recognition and judgment module is used to determine whether to execute the navigation prompt module or the intelligent driving module based on the processed original image and the navigation information. The navigation prompt module is used to provide the driver with navigation and road condition information guidance according to the instructions of the road recognition and judgment module; The intelligent driving module is used to provide intelligent driving to the driver according to the instructions of the road recognition and judgment module.

2. The driving route recognition system according to claim 1, characterized in that, The visual image acquisition module is used to convert optical information of the vehicle's surrounding environment into digital images.

3. The driving route recognition system according to claim 2, characterized in that, The visual image acquisition module includes multiple cameras and multiple sensors. The multiple cameras include a front-view camera, a side-view camera, and a rear-view camera. The multiple sensors include radar.

4. The driving route recognition system according to claim 1, characterized in that, The visual image processing module performs the following processing on the original image: The original image is preprocessed; Image correction is performed on the preprocessed original image; The corrected image is then processed using image enhancement techniques. Extracting key features from images processed by image enhancement techniques; Target recognition and classification are performed on images from which key features have been extracted; Image recognition and classification of targets are analyzed and predicted through behavior analysis; The image data is fused with behavioral analysis and prediction to generate panoramic images.

5. The driving route recognition system according to claim 1, characterized in that, The navigation information collection module integrates an in-vehicle navigation system or connects to a mobile phone / cloud navigation service to provide preset navigation information, including planned routes, information on upcoming intersections / ramp, suggested turning directions, number of lanes, speed limit information, and road classification.

6. The driving route recognition system according to claim 1, characterized in that, When the road recognition and judgment module determines that the road conditions are simple and clear and consistent with the navigation information based on the processed original image and the navigation information, it triggers the navigation prompt module to provide regular voice / image prompts. When the road recognition and judgment module determines that the road conditions are complex and conflict with the navigation information based on the processed original image and the navigation information, it triggers the intelligent driving module to prepare for assisted decision-making or vehicle control.

7. The driving route recognition system according to claim 1, characterized in that, It also includes a voice input module, which is used to receive the driver's voice commands. The intelligent driving module is also used to make auxiliary decisions or control the vehicle based on the driver's voice requests.

8. A method for implementing the route recognition system according to any one of claims 1-7, characterized in that, Includes the following steps: Capture raw images of the area in front of the vehicle in real time; The original image is processed; Provides preset navigation information; Based on the processed original image and the navigation information, it is determined whether to provide the driver with navigation and road condition information guidance or to provide the driver with intelligent driving.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in claim 8.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in claim 8.

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