An automatic driving assistance method, device, equipment and storage medium

Abstract

The application discloses an automatic driving assistance method and device, equipment and a storage medium. The method comprises the following steps: acquiring vehicle driving parameters and road marking information corresponding to a target vehicle; determining a theoretical driving track space corresponding to the target vehicle based on the vehicle driving parameters, and determining obstacle space position information in the theoretical driving track space; determining a vehicle passing state of the target vehicle according to the obstacle space position information, the road marking information and the theoretical driving track space; in the case that the vehicle passing state is a safe passing state, performing type identification processing on the obstacle, and in the case that the obstacle type is a preset type obstacle, controlling the target vehicle to continue driving according to the current vehicle driving parameters, so that a runnable track space of the target vehicle can be obtained, more reasonable obstacle avoidance options are provided, and the driving experience is improved.

Description

Technical Field

[0001] This invention relates to the field of driver assistance technology, and in particular to an autonomous driving assistance method, device, equipment, and storage medium. Background Technology

[0002] Assisted driving technology is constantly evolving and is expected to further improve traffic safety and convenience in the future. Currently, obstacle recognition systems equipped on autonomous vehicles often simply identify and confirm obstacles before braking or changing lanes.

[0003] However, this approach can sometimes cause vehicles to overreact to even the slightest obstacle (such as plastic bags and sponges), leading to safety hazards and a poor driving experience. Summary of the Invention

[0004] This invention provides an autonomous driving assistance method, device, equipment, and storage medium to obtain the operational trajectory space of a target vehicle, thereby providing more reasonable obstacle avoidance options and improving the driving experience.

[0005] According to one aspect of the present invention, an autonomous driving assistance method is provided. The method includes:

[0006] Obtain the vehicle driving parameters and road marking information corresponding to the target vehicle;

[0007] Based on the vehicle driving parameters, the theoretical driving trajectory space corresponding to the target vehicle is determined, and the spatial location information of obstacles in the theoretical driving trajectory space is determined.

[0008] Based on the spatial location information of the obstacle, the road marking information, and the theoretical driving trajectory space, the vehicle passage status of the target vehicle is determined, wherein the vehicle passage status includes a safe passage status and a risky passage status.

[0009] When the vehicle passage status is a safe passage status, the obstacle type is identified, and if the obstacle type is a preset type obstacle, the target vehicle is controlled to continue driving according to the current vehicle driving parameters.

[0010] According to another aspect of the present invention, an autonomous driving assistance device is provided. The device includes:

[0011] The data acquisition module is used to acquire the vehicle driving parameters and road marking information corresponding to the target vehicle;

[0012] The trajectory space determination module is used to determine the theoretical driving trajectory space corresponding to the target vehicle based on the vehicle driving parameters, and to determine the spatial location information of obstacles in the theoretical driving trajectory space.

[0013] The traffic status determination module is used to determine the traffic status of the target vehicle based on the spatial location information of the obstacle, the road marking information and the theoretical driving trajectory space, wherein the traffic status includes a safe traffic status and a risky traffic status.

[0014] The vehicle driving control module is used to identify the type of obstacle when the vehicle passage status is a safe passage status, and to control the target vehicle to continue driving according to the current vehicle driving parameters when the obstacle type is a preset type obstacle.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the autonomous driving assistance method according to any embodiment of the present invention.

[0019] The technical solution of this invention involves acquiring vehicle driving parameters and road marking information corresponding to a target vehicle. Based on the vehicle driving parameters, a theoretical driving trajectory space corresponding to the target vehicle is determined, and the spatial location information of obstacles within the theoretical driving trajectory space is also determined. According to the obstacle spatial location information, the road marking information, and the theoretical driving trajectory space, the vehicle's traffic status is determined, wherein the vehicle traffic status includes a safe traffic status and a risky traffic status. When the vehicle traffic status is safe, obstacle type identification processing is performed, and if the obstacle type is a preset type obstacle, the target vehicle is controlled to continue driving according to the current vehicle driving parameters. This solves the technical problem of simply braking or changing lanes, providing more reasonable driving options and thus improving the driving experience.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of an autonomous driving assistance method provided according to Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart of an autonomous driving assistance method provided according to Embodiment 2 of the present invention;

[0024] Figure 3 This is a structural diagram of an autonomous driving assistance device according to Embodiment 3 of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the autonomous driving assistance method of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] Example 1

[0029] Figure 1This is a flowchart of an autonomous driving assistance method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations where autonomous vehicles intelligently select driving strategies in response to obstacles. This method can be executed by an autonomous driving assistance device, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0030] S101. Obtain the vehicle driving parameters and road marking information corresponding to the target vehicle.

[0031] The vehicle driving parameters include at least position information, speed information, acceleration information, steering angle information, and direction information. Road marking information includes at least the road marking type, which includes at least solid line types and dashed line types.

[0032] Specifically, obtaining vehicle driving parameters and road marking information for a target vehicle requires the use of specific technologies and equipment, such as in-vehicle GPS, radar, and cameras. These devices can acquire vehicle driving parameters such as position, speed, and direction in real time, and obtain road marking information through technologies such as image recognition.

[0033] Specifically, in-vehicle GPS can acquire real-time information such as the vehicle's latitude, longitude, speed, and direction. By matching this information with map data, the vehicle's current location and direction of travel can be determined. Radar can acquire real-time information about obstacles around the vehicle. Cameras can acquire information about road markings ahead of the vehicle. Through image recognition technology, they can automatically identify lane lines, stop lines, road signs, and other information, helping drivers better understand road conditions.

[0034] These devices and technologies can be integrated into the vehicle's onboard system, exchanging data with cloud servers through the vehicle's communication module to obtain more comprehensive driving parameters and road marking information. Furthermore, data sharing and collaborative computing can improve the accuracy and real-time nature of the information.

[0035] S102. Based on the vehicle driving parameters, determine the theoretical driving trajectory space corresponding to the target vehicle, and determine the spatial location information of obstacles in the theoretical driving trajectory space.

[0036] The theoretical driving trajectory space refers to the maximum driving trajectory space of the target vehicle under the current vehicle driving parameters. The obstacle spatial location information refers to the location information of the obstacle in the theoretical driving trajectory space.

[0037] Specifically, based on vehicle driving parameters, the maximum operating capacity of the target vehicle is calculated, and the theoretical driving trajectory space of the target vehicle is determined based on the maximum operating capacity of the target vehicle. At the same time, the spatial position of obstacles in the theoretical driving trajectory space is determined by the target vehicle's sensors.

[0038] For example, determining the theoretical driving trajectory space corresponding to the target vehicle based on the vehicle driving parameters includes:

[0039] Based on the vehicle driving parameters, determine the target vehicle's corresponding driving speed range, driving acceleration range, driving speed threshold corresponding to the shortest braking distance, and the current vehicle spatial position at the current moment;

[0040] Based on the driving speed range, the driving acceleration range, the driving speed threshold, and the current vehicle spatial position, the theoretical driving trajectory space corresponding to the target vehicle is determined.

[0041] Specifically, the theoretical driving trajectory space is constructed by the following three motion constraints, wherein:

[0042] The first type of motion restriction is the target vehicle's maximum speed and the speed range V of its maximum angular velocity. k That is, considering only the motor performance, the velocity space formed by the upper and lower limits of the car's linear velocity v and angular velocity w is calculated as follows:

[0043] V k ={(v,ω)v∈[v min ,v max ],ω∈[ω min ,ω max ]}

[0044] The second type of motion limitation is that, due to torque limitations, the robot has a range of maximum acceleration and maximum angular acceleration, V. d This refers to the velocity space that a vehicle can reach within time dt under the constraint of driving force, based on its acceleration and angular acceleration. The calculation formula is as follows:

[0045]

[0046] Where v c With ω c Given the vehicle's current linear velocity and angular velocity, represents the upper and lower limits of vehicle acceleration and angular acceleration, respectively, and (v,ω) represents the range of vehicle linear velocity and angular velocity.

[0047] The final motion restriction is that the vehicle must not collide with obstacles during its trajectory. This is because when the vehicle detects an obstacle, it should have sufficient braking distance to decelerate and prevent a collision. The speed space satisfies the formula, which is the driving speed threshold corresponding to the shortest braking distance. The calculation formula is as follows:

[0048]

[0049] Where d(v,ω) is the braking distance function between the robot and the obstacle. represents the upper and lower limits of vehicle acceleration and angular acceleration, respectively, and (v,ω) represents the range of vehicle linear velocity and angular velocity.

[0050] The above three sets of equations yield the actual possible trajectories for the car. The worst-case scenario for this trajectory is a speed of 0, meaning the vehicle comes to a complete stop. However, sudden stopping reduces comfort, and can create driving hazards, especially on highways.

[0051] The theoretical driving trajectory space is:

[0052]

[0053] Among them, [x t y t θ t ]′ represents the vehicle's current spatial position in the coordinate system at the current moment, [x t+dt y t+dt θ t+dt ]′ represents the theoretical driving trajectory space of the vehicle at the next moment, and [dx dy dθ]′ represents the change in the vehicle's coordinates and orientation during time dt.

[0054] S103. Determine the vehicle passage status of the target vehicle based on the obstacle spatial location information, the road marking information, and the theoretical driving trajectory space.

[0055] The vehicle traffic status includes safe traffic status and risky traffic status. For different types of vehicle traffic status, the target vehicle adopts a vehicle control strategy corresponding to the status type.

[0056] Specifically, based on road marking information and the theoretical driving trajectory space, the actual driving trajectory space of the target vehicle under the current road conditions is determined. Combining this actual driving trajectory space with obstacle location information, it is determined whether the target vehicle can safely avoid obstacles within the actual driving trajectory space. If the target vehicle can safely avoid obstacles, the vehicle's traffic status is determined to be a safe traffic status. If not, the vehicle's traffic status is determined to be a risky traffic status.

[0057] S104. When the vehicle passage status is a safe passage status, the obstacle type is identified, and if the obstacle type is a preset type, the target vehicle is controlled to continue driving according to the current vehicle driving parameters.

[0058] The preset type can refer to the type of obstacle that the target vehicle does not need to avoid, such as soft or fluid obstacles.

[0059] Specifically, when the vehicle's passage status is determined to be safe, the type of obstacle is identified and determined. If the obstacle type is a preset type, there is no need to avoid the obstacle; the target vehicle is controlled to continue driving according to the current vehicle driving parameters, thereby improving the driving experience without causing danger.

[0060] For example, the obstacle type identification process includes: acquiring obstacle point cloud data corresponding to the obstacle; simulating the simulated deformation value of the obstacle under the action of road wind based on the obstacle point cloud data; and determining the obstacle as a preset type obstacle if the simulated deformation value is greater than or equal to the simulated deformation threshold.

[0061] Specifically, using obstacle point cloud data, a 5mm*5mm grid is divided on the obstacle (the value can be adjusted, but 5mm is optimal). Marking points are generated at each grid point, and continuous time recording is performed. The collected data is then analyzed to determine if the obstacle changes over time. The image processing portion can be uploaded to the cloud for processing, employing the YOLOv5 image processing method proposed by Mosaic. This reduces geometric and optical distortion, thereby simulating the deformation of the obstacle under road wind conditions. If the simulated deformation value is greater than or equal to a simulated deformation threshold, the obstacle is determined to be a preset type of obstacle. The simulated deformation threshold can be set according to actual conditions, and this invention does not specifically limit it.

[0062] The technical solution of this invention involves acquiring vehicle driving parameters and road marking information corresponding to a target vehicle. Based on the vehicle driving parameters, a theoretical driving trajectory space corresponding to the target vehicle is determined, and the spatial location information of obstacles within the theoretical driving trajectory space is also determined. According to the obstacle spatial location information, the road marking information, and the theoretical driving trajectory space, the vehicle's traffic status is determined, wherein the vehicle traffic status includes a safe traffic status and a risky traffic status. When the vehicle traffic status is safe, obstacle type identification processing is performed, and if the obstacle type is a preset type obstacle, the target vehicle is controlled to continue driving according to the current vehicle driving parameters. This solves the technical problem of simply braking or changing lanes, providing more reasonable driving options and thus improving the driving experience.

[0063] Based on the above embodiments, the method further includes: when it is determined that the vehicle passage status is a risky passage status, acquiring obstacle point cloud data corresponding to the obstacle; determining whether the obstacle height exceeds the chassis safety height of the target vehicle based on the obstacle point cloud data; and controlling the target vehicle to continue driving according to the current vehicle driving parameters when it is determined that the obstacle height is lower than the chassis safety height of the target vehicle.

[0064] Specifically, when the vehicle passage status is determined to be a risky passage status, it can be further determined whether the height of the obstacle exceeds the chassis safety height of the target vehicle. If the height of the obstacle is lower than the chassis safety height of the target vehicle, there is no need to avoid the obstacle, and the target vehicle can be controlled to continue driving according to the current vehicle driving parameters, thereby improving the driving experience without causing danger.

[0065] Example 2

[0066] Figure 2 This is a flowchart of an autonomous driving assistance method provided in Embodiment 2 of the present invention. Based on the above embodiments, the road marking information in this embodiment includes at least road marking types, wherein the road marking types include at least solid line types and dashed line types. Specific discussions are conducted based on the road marking types, and the determination of the vehicle traffic status of the target vehicle is further refined. For example... Figure 2 As shown, the method includes:

[0067] S201. Obtain the vehicle driving parameters and road marking information corresponding to the target vehicle.

[0068] S202. Based on the vehicle driving parameters, determine the theoretical driving trajectory space corresponding to the target vehicle, and determine the spatial location information of obstacles in the theoretical driving trajectory space.

[0069] S203. When the road marking type is solid line, determine the solid line driving trajectory space corresponding to the target vehicle based on the theoretical driving trajectory space and the road marking information, and determine the vehicle passage status of the target vehicle based on the solid line driving trajectory space and the obstacle spatial position information.

[0070] Among them, the solid line driving trajectory space can refer to the actual driving trajectory space of the target vehicle in the theoretical driving trajectory space when lane changing is restricted by the solid line.

[0071] Specifically, when the road marking is a solid line, the target vehicle cannot change lanes. Under these prohibited lane-changing conditions, the target vehicle's solid line travel trajectory space is determined. Then, based on the solid line travel trajectory space and the spatial location information of obstacles, the target vehicle's traffic status is determined.

[0072] For example, determining the vehicle passage status of the target vehicle based on the solid line driving trajectory space and the obstacle spatial location information includes: determining the solid line safe driving range of the current road marking based on the solid line driving trajectory space and the obstacle spatial location information; determining the vehicle passage status of the target vehicle as a safe passage status when the solid line safe driving range is greater than the target vehicle range occupied by the target vehicle; and determining the vehicle passage status of the target vehicle as a risky passage status when the solid line safe driving range is less than or equal to the target vehicle range.

[0073] The safe driving range along the solid line can refer to the maximum width of the driving trajectory space along the solid line, excluding the width of obstacles. The target vehicle range can refer to the spatial range occupied by the target vehicle.

[0074] Specifically, based on the spatial information of the solid line driving trajectory and the spatial location of obstacles, the remaining driving width space after the obstacle is occupied in the solid line driving trajectory space is calculated, and the maximum driving width space is determined as the safe driving range of the current road marking solid line. If the safe driving range of the solid line is greater than the target vehicle range occupied by the target vehicle, the vehicle's driving status is determined to be a safe driving status. If the safe driving range of the solid line is less than or equal to the target vehicle range, the vehicle's driving status is determined to be a risky driving status.

[0075] S204. When the road marking type is dashed, determine the dashed driving trajectory space corresponding to the target vehicle based on the theoretical driving trajectory space and the road marking information, and determine the vehicle passage status of the target vehicle based on the dashed driving trajectory space and the obstacle spatial location information.

[0076] Among them, the dashed line driving trajectory space can refer to the actual driving trajectory space of the target vehicle in the theoretical driving trajectory space when lane changing is allowed.

[0077] Specifically, when the road marking type is dashed, the target vehicle is allowed to change lanes to avoid obstacles. Given this permission, the target vehicle's dashed line trajectory space is determined. Then, based on the dashed line trajectory space and the obstacle's spatial location information, the target vehicle's traffic status is determined.

[0078] For example, determining the vehicle passage status of the target vehicle based on the dashed line driving trajectory space and the obstacle spatial location information includes: determining the safe driving range of the current road marking dashed line based on the dashed line driving trajectory space and the obstacle spatial location information; determining the vehicle passage status of the target vehicle as a safe passage status when the safe driving range of the dashed line is greater than the target vehicle range occupied by the target vehicle; and obtaining the adjacent lane vehicle information of the adjacent lane when the safe driving range of the dashed line is less than or equal to the target vehicle range, and determining the vehicle passage status of the target vehicle based on the adjacent lane vehicle information.

[0079] The safe driving range of the dashed line can refer to the maximum width of the driving trajectory space within the dashed line, excluding the width of obstacles. The target vehicle range can refer to the spatial range occupied by the target vehicle.

[0080] Specifically, based on the spatial information of the dashed line travel trajectory and the spatial location of obstacles, the remaining travel width space after the obstacle is occupied in the dashed line travel trajectory space is calculated, and the maximum travel width space is determined as the safe travel range of the current road marking. If the safe travel range of the dashed line is greater than the target vehicle range occupied by the target vehicle, the vehicle's traffic status is determined to be a safe traffic status. If the safe travel range of the dashed line is less than or equal to the target vehicle range, the vehicle's traffic status needs to be determined based on the vehicle information of adjacent lanes.

[0081] For example, determining the vehicle traffic status of the target vehicle based on the adjacent lane vehicle information includes: analyzing and processing the adjacent lane vehicle information to determine whether the target vehicle meets the lane-changing driving conditions; if the target vehicle meets the lane-changing driving conditions, determining the vehicle traffic status of the target vehicle as a safe traffic status; if the target vehicle does not meet the lane-changing driving conditions, determining the vehicle traffic status of the target vehicle as a risky traffic status.

[0082] Specifically, the information on vehicles in adjacent lanes is analyzed and processed to determine whether the target vehicle can change lanes. If the target vehicle can change lanes, its traffic status is determined to be a safe traffic status. Otherwise, its traffic status is determined to be a risky traffic status.

[0083] S205. When the vehicle passage status is a safe passage status, the obstacle type is identified, and if the obstacle type is a preset type obstacle, the target vehicle is controlled to continue driving according to the current vehicle driving parameters.

[0084] The technical solution of this invention, when the road marking type is solid line, determines the solid line driving trajectory space corresponding to the target vehicle based on the theoretical driving trajectory space and the road marking information, and determines the vehicle's traffic status based on the solid line driving trajectory space and the obstacle spatial position information; when the road marking type is dashed line, it determines the dashed line driving trajectory space corresponding to the target vehicle based on the theoretical driving trajectory space and the road marking information, and determines the vehicle's traffic status based on the dashed line driving trajectory space and the obstacle spatial position information. This specific discussion of road marking types allows for more reasonable obstacle avoidance options, solves the technical problem of relying solely on braking or lane changing, and thus improves the driving experience.

[0085] Example 3

[0086] Figure 3 This is a schematic diagram of the structure of an autonomous driving assistance device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes:

[0087] The data information acquisition module 301 is used to acquire the vehicle driving parameters and road marking information corresponding to the target vehicle;

[0088] The trajectory space determination module 302 is used to determine the theoretical driving trajectory space corresponding to the target vehicle based on the vehicle driving parameters, and to determine the spatial location information of obstacles in the theoretical driving trajectory space;

[0089] The passage status determination module 303 is used to determine the vehicle passage status of the target vehicle based on the obstacle spatial location information, the road marking information and the theoretical driving trajectory space, wherein the vehicle passage status includes a safe passage status and a risky passage status.

[0090] The vehicle driving control module 304 is used to identify the type of obstacle when the vehicle passage status is a safe passage status, and to control the target vehicle to continue driving according to the current vehicle driving parameters when the obstacle type is a preset type obstacle.

[0091] The technical solution of this invention involves acquiring vehicle driving parameters and road marking information corresponding to a target vehicle. Based on the vehicle driving parameters, a theoretical driving trajectory space corresponding to the target vehicle is determined, and the spatial location information of obstacles within the theoretical driving trajectory space is also determined. According to the obstacle spatial location information, the road marking information, and the theoretical driving trajectory space, the vehicle's traffic status is determined, wherein the vehicle traffic status includes a safe traffic status and a risky traffic status. When the vehicle traffic status is safe, obstacle type identification processing is performed, and if the obstacle type is a preset type obstacle, the target vehicle is controlled to continue driving according to the current vehicle driving parameters. This solves the technical problem of simply braking or changing lanes, providing more reasonable driving options and thus improving the driving experience.

[0092] Optionally, the trajectory space determination module 302 is specifically used for:

[0093] Based on the vehicle driving parameters, determine the target vehicle's corresponding driving speed range, driving acceleration range, driving speed threshold corresponding to the shortest braking distance, and the current vehicle spatial position at the current moment;

[0094] Based on the driving speed range, the driving acceleration range, the driving speed threshold, and the current vehicle spatial position, the theoretical driving trajectory space corresponding to the target vehicle is determined.

[0095] Optionally, the road marking information includes at least road marking types, and the road marking types include at least solid line types and dashed line types;

[0096] Accordingly, the passage status determination module 303 may include:

[0097] The first traffic status determination unit is used to determine the solid line driving trajectory space corresponding to the target vehicle based on the theoretical driving trajectory space and the road marking information when the road marking type is solid line type, and to determine the vehicle traffic status of the target vehicle based on the solid line driving trajectory space and the obstacle spatial position information.

[0098] The second traffic status determination unit is used to determine the dashed line travel trajectory space corresponding to the target vehicle based on the theoretical travel trajectory space and the road marking information when the road marking type is dashed line, and to determine the vehicle traffic status of the target vehicle based on the dashed line travel trajectory space and the obstacle spatial location information.

[0099] Optionally, the first passage state determination unit is specifically used for:

[0100] Based on the solid line driving trajectory space and the obstacle spatial location information, determine the safe driving range of the current road marking solid line;

[0101] If the safe driving range of the solid line is greater than the target vehicle range occupied by the target vehicle, the vehicle passage status of the target vehicle is determined to be a safe passage status.

[0102] If the safe driving range of the solid line is less than or equal to the range of the target vehicle, the vehicle traffic status of the target vehicle is determined to be a risky traffic status.

[0103] Optionally, the second passage state determination unit includes:

[0104] The safe driving range determination subunit is used to determine the safe driving range of the current road marking based on the space of the dashed driving trajectory and the spatial position information of the obstacle.

[0105] The first traffic status determination subunit is used to determine the traffic status of the target vehicle as a safe traffic status when the safe driving range of the dashed line is greater than the target vehicle range occupied by the target vehicle.

[0106] The second traffic status determination subunit is used to obtain adjacent lane vehicle information in adjacent lanes when the safe driving range of the dashed line is less than or equal to the target vehicle range, and to determine the vehicle traffic status of the target vehicle based on the adjacent lane vehicle information.

[0107] Optionally, the second passage state determination subunit is specifically used for:

[0108] The adjacent lane vehicle information is analyzed and processed to determine whether the target vehicle meets the lane change conditions.

[0109] If it is determined that the target vehicle meets the conditions for lane changing, the vehicle's traffic status is determined to be a safe traffic status.

[0110] If it is determined that the target vehicle does not meet the conditions for changing lanes, the vehicle's traffic status is determined to be a risky traffic status.

[0111] Optionally, the device further includes: an obstacle type determination module, used for:

[0112] Obtain the obstacle point cloud data corresponding to the obstacle;

[0113] Based on the obstacle point cloud data, simulated deformation values ​​of the obstacle under the action of road wind were generated.

[0114] If the simulated deformation value is greater than or equal to the simulated deformation threshold, the obstacle is determined to be a preset type of obstacle.

[0115] Optionally, the vehicle driving control module 304 is also used for:

[0116] If the vehicle passage status is determined to be a risky passage status, obtain the obstacle point cloud data corresponding to the obstacle;

[0117] Based on the obstacle point cloud data, determine whether the height of the obstacle exceeds the safe chassis height of the target vehicle;

[0118] If it is determined that the height of the obstacle is lower than the safe chassis height of the target vehicle,

[0119] Control the target vehicle to continue driving according to the current vehicle driving parameters.

[0120] The autonomous driving assistance device provided in the embodiments of the present invention can execute the autonomous driving assistance method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method execution.

[0121] Example 4

[0122] Figure 4 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0123] like Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0124] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0125] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as methods for autonomous driving assistance.

[0126] In some embodiments, the method of autonomous driving assistance may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method of autonomous driving assistance described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the method of autonomous driving assistance by any other suitable means (e.g., by means of firmware).

[0127] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0128] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0129] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0130] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0131] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0132] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0133] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0134] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. An autonomous driving assistance method, characterized in that, include: Obtain the vehicle driving parameters and road marking information corresponding to the target vehicle; Based on the vehicle driving parameters, the theoretical driving trajectory space corresponding to the target vehicle is determined, and the spatial location information of obstacles in the theoretical driving trajectory space is determined. Based on the spatial location information of the obstacle, the road marking information, and the theoretical driving trajectory space, the vehicle passage status of the target vehicle is determined, wherein the vehicle passage status includes a safe passage status and a risky passage status. When the vehicle passage status is a safe passage status, the obstacle type is identified, and if the obstacle type is a preset type, the target vehicle is controlled to continue driving according to the current vehicle driving parameters; If the vehicle passage status is determined to be a risky passage status, obtain the obstacle point cloud data corresponding to the obstacle; Based on the obstacle point cloud data, determine whether the height of the obstacle exceeds the safe chassis height of the target vehicle; If it is determined that the height of the obstacle is lower than the safe chassis height of the target vehicle, Control the target vehicle to continue driving according to the current vehicle driving parameters.

2. The method according to claim 1, characterized in that, The step of determining the theoretical driving trajectory space corresponding to the target vehicle based on the vehicle driving parameters includes: Based on the vehicle driving parameters, determine the target vehicle's corresponding driving speed range, driving acceleration range, driving speed threshold corresponding to the shortest braking distance, and the current vehicle spatial position at the current moment; Based on the driving speed range, the driving acceleration range, the driving speed threshold, and the current vehicle spatial position, the theoretical driving trajectory space corresponding to the target vehicle is determined.

3. The method according to claim 1, characterized in that, The road marking information includes at least road marking types, and the road marking types include at least solid line types and dashed line types; determining the vehicle passage status of the target vehicle based on the obstacle spatial location information, the road marking information, and the theoretical driving trajectory space includes: When the road marking type is solid line, the solid line driving trajectory space corresponding to the target vehicle is determined according to the theoretical driving trajectory space and the road marking information, and the vehicle passage status of the target vehicle is determined according to the solid line driving trajectory space and the obstacle spatial position information. When the road marking type is dashed, the dashed driving trajectory space corresponding to the target vehicle is determined based on the theoretical driving trajectory space and the road marking information, and the vehicle passage status of the target vehicle is determined based on the dashed driving trajectory space and the obstacle spatial location information.

4. The method according to claim 3, characterized in that, Determining the vehicle passage status of the target vehicle based on the solid line driving trajectory space and the obstacle spatial position information includes: Based on the solid line driving trajectory space and the obstacle spatial location information, determine the safe driving range of the current road marking solid line; If the safe driving range of the solid line is greater than the target vehicle range occupied by the target vehicle, the vehicle passage status of the target vehicle is determined to be a safe passage status. If the safe driving range of the solid line is less than or equal to the range of the target vehicle, the vehicle traffic status of the target vehicle is determined to be a risky traffic status.

5. The method according to claim 3, characterized in that, Determining the vehicle passage status of the target vehicle based on the dashed driving trajectory space and the spatial position information of the obstacles includes: Based on the space of the dashed line driving trajectory and the spatial location information of the obstacle, determine the safe driving range of the current road marking dashed line; If the safe driving range of the dashed line is greater than the target vehicle range occupied by the target vehicle, the vehicle passage status of the target vehicle is determined to be a safe passage status. If the safe driving range of the dashed line is less than or equal to the range of the target vehicle, obtain the vehicle information of the adjacent lanes, and determine the vehicle traffic status of the target vehicle based on the vehicle information of the adjacent lanes.

6. The method according to claim 5, characterized in that, Determining the vehicle traffic status of the target vehicle based on the adjacent lane vehicle information includes: The adjacent lane vehicle information is analyzed and processed to determine whether the target vehicle meets the lane change conditions. If it is determined that the target vehicle meets the conditions for lane changing, the vehicle's traffic status is determined to be a safe traffic status. If it is determined that the target vehicle does not meet the conditions for changing lanes, the vehicle's traffic status is determined to be a risky traffic status.

7. The method according to claim 1, characterized in that, The obstacle type identification process includes: Obtain the obstacle point cloud data corresponding to the obstacle; Based on the obstacle point cloud data, simulated deformation values ​​of the obstacle under the action of road wind were generated. If the simulated deformation value is greater than or equal to the simulated deformation threshold, the obstacle is determined to be a preset type of obstacle.

8. An autonomous driving assistance device, characterized in that, include: The data acquisition module is used to acquire the vehicle driving parameters and road marking information corresponding to the target vehicle; The trajectory space determination module is used to determine the theoretical driving trajectory space corresponding to the target vehicle based on the vehicle driving parameters, and to determine the spatial location information of obstacles in the theoretical driving trajectory space. The traffic status determination module is used to determine the traffic status of the target vehicle based on the spatial location information of the obstacle, the road marking information and the theoretical driving trajectory space, wherein the traffic status includes a safe traffic status and a risky traffic status. The vehicle driving control module is used to identify the type of obstacle when the vehicle passage status is a safe passage status, and to control the target vehicle to continue driving according to the current vehicle driving parameters when the obstacle type is a preset type obstacle. The vehicle driving control module is also used for: If the vehicle passage status is determined to be a risky passage status, obtain the obstacle point cloud data corresponding to the obstacle; Based on the obstacle point cloud data, determine whether the height of the obstacle exceeds the safe chassis height of the target vehicle; If it is determined that the height of the obstacle is lower than the safe chassis height of the target vehicle, Control the target vehicle to continue driving according to the current vehicle driving parameters.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the autonomous driving assistance method according to any one of claims 1-7.

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