WO2022041869A1 - Procédé et appareil d'invite d'état de route, et dispositif électronique, support de stockage et produit de programme - Google Patents

Procédé et appareil d'invite d'état de route, et dispositif électronique, support de stockage et produit de programme Download PDF

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Publication number
WO2022041869A1
WO2022041869A1 PCT/CN2021/095149 CN2021095149W WO2022041869A1 WO 2022041869 A1 WO2022041869 A1 WO 2022041869A1 CN 2021095149 W CN2021095149 W CN 2021095149W WO 2022041869 A1 WO2022041869 A1 WO 2022041869A1
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WIPO (PCT)
Prior art keywords
target object
type
obstacle avoidance
avoidance device
information
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PCT/CN2021/095149
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English (en)
Chinese (zh)
Inventor
殷卫华
邵巾芮
蔺颖
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北京市商汤科技开发有限公司
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Priority to JP2022520723A priority Critical patent/JP2022550895A/ja
Priority to KR1020227011056A priority patent/KR20220057577A/ko
Publication of WO2022041869A1 publication Critical patent/WO2022041869A1/fr

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/097—Supervising of traffic control systems, e.g. by giving an alarm if two crossing streets have green light simultaneously
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/165—Anti-collision systems for passive traffic, e.g. including static obstacles, trees
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes

Definitions

  • the present disclosure relates to the technical field of blind guidance, and in particular, to a road condition prompting method, device, electronic device, storage medium and program product.
  • the traditional travel of the visually impaired mainly relies on blind canes and guide dogs.
  • the detection range of the blind cane-assisted travel is limited, and the use scenarios of the guide dog-assisted travel are limited.
  • the embodiments of the present disclosure provide at least one road condition prompting solution.
  • an embodiment of the present disclosure provides a road condition prompting method, including:
  • the object attribute information corresponding to the target object within the set distance corresponding to the obstacle avoidance device and the distance information corresponding to the target object can be obtained, and the target can be determined based on the object attribute information and distance information corresponding to the target object at the same time
  • the risk information of the object so that the risk information of the target object can be accurately determined.
  • the obstacle avoidance device can be the obstacle avoidance glasses worn by the visually impaired
  • the target object can be the obstacle on the road for the visually impaired.
  • an embodiment of the present disclosure provides a road condition prompting device, including:
  • an acquisition part configured to acquire object attribute information corresponding to a target object within a distance setting range corresponding to the obstacle avoidance device, and distance information corresponding to the target object;
  • a determining part configured to determine the risk information of the target object based on the object attribute information and the distance information corresponding to the target object;
  • the prompting part is configured to prompt the road condition through the obstacle avoidance device based on the determined risk information.
  • an embodiment of the present disclosure provides an electronic device, including: a processor, a memory, and a bus, where the memory stores machine-readable instructions executable by the processor, and when the electronic device runs, all The processor and the memory communicate through a bus, and when the machine-readable instructions are executed by the processor, the steps of the road condition prompting method according to the first aspect are executed.
  • an embodiment of the present disclosure provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the road conditions described in the first aspect are executed Steps to prompt the method.
  • an embodiment of the present disclosure provides a computer program product, including computer-readable code, and when the computer-readable code is executed in an electronic device, a processor in the electronic device executes the first The steps of the road condition prompting method described in the aspect.
  • FIG. 1 shows a flowchart of a road condition prompting method provided by an embodiment of the present disclosure
  • FIG. 2 shows a flowchart of a method for risk information of a target object provided by an embodiment of the present disclosure
  • FIG. 3 shows a flowchart of a language prompting method for a first type of target object provided by an embodiment of the present disclosure
  • FIG. 4 shows a flowchart of a language prompting method for a second type of target object provided by an embodiment of the present disclosure
  • FIG. 5 shows a flowchart of a first method for determining a road scene type corresponding to the location of an obstacle avoidance device provided by an embodiment of the present disclosure
  • FIG. 6 shows a flowchart of a second method for determining a road scene type corresponding to the location of an obstacle avoidance device provided by an embodiment of the present disclosure
  • FIG. 7 shows a flowchart of a method for voice playback for the first type of voice prompt information and the second type of voice prompt information provided by an embodiment of the present disclosure
  • FIG. 8 shows a schematic diagram of a specific road condition prompting solution provided by an embodiment of the present disclosure
  • FIG. 9 shows a schematic structural diagram of a road condition prompting device provided by an embodiment of the present disclosure.
  • FIG. 10 shows a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure.
  • the accurate prompting of road condition information is of great significance in the field of traffic safety.
  • the travel of the visually impaired mainly relies on blind canes and guide dogs.
  • the usage scenarios of the way of assisted travel by dog guidance are limited. Therefore, it is urgent to provide an effective way of guiding the blind to assist the travel of the visually impaired.
  • the embodiments of the present disclosure provide a road condition prompting method, which can effectively assist the visually impaired to travel.
  • the method can obtain the object attribute information corresponding to the target object within the distance setting range corresponding to the obstacle avoidance device, and the distance information corresponding to the target object, and simultaneously determine the risk information of the target object based on the object attribute information and distance information corresponding to the target object , so that road conditions can be prompted based on the risk information, and the travel safety of the visually impaired can be improved.
  • the equipment includes: terminal equipment or server or other processing equipment
  • the terminal equipment can be one of the following: user equipment (User Equipment, UE), mobile equipment, user terminal, terminal, handheld equipment such as mobile phone (Mobile Phone), tablet computer (Pad), computers with wireless transceiver functions, handheld computers, desktop computers, personal digital assistants, portable media players, smart speakers, navigation devices, smart watches, smart glasses, smart necklaces and other wearable devices, pedometers, Digital TV, Virtual Reality (VR) terminal equipment, Augmented Reality (AR) terminal equipment, wireless terminal in Industrial Control, wireless terminal in Self Driving (Self Driving), remote surgery ( Wireless terminals in Remote Medical Surgery, wireless terminals in Smart Grid, wireless terminals in Transportation Safety, wireless terminals in Smart City, wireless terminals in Smart Home Wireless terminals, vehicles in the Internet of Vehicles system, in-vehicle equipment, in-vehicle modules, etc.
  • the flowchart of the road condition prompting method may include the following S101 to S103:
  • S101 Obtain object attribute information corresponding to a target object within a distance setting range corresponding to an obstacle avoidance device, and distance information corresponding to the target object.
  • the execution subject of the road condition prompting method provided by the embodiment of the present disclosure may be an obstacle avoidance device, or may be other devices listed above that can communicate with the obstacle avoidance device. Generally, other devices may communicate with the obstacle avoidance device.
  • the communication connection is maintained or the communication connection is established when data transmission is required, which is not limited herein.
  • the obstacle avoidance device may include at least one of obstacle avoidance glasses and a mobile device, or may include obstacle avoidance glasses and other devices. At least one of, or may include at least one of obstacle avoidance glasses and cloud devices. In some embodiments, the obstacle avoidance device may refer solely to wearable devices such as obstacle avoidance glasses.
  • the target object may include at least one of a preset obstacle matching the application scenario, an object indicated by road conditions, and a pedestrian.
  • Objects or indication signals such as at least one of traffic lights and pedestrian crossings, that indicate the user's walking style in the road scene, and may also include obstacles that may cause collisions during the user's progress, such as vehicles, pedestrians, steps , at least one of barricades, utility poles, trees, etc.
  • the object attribute information of the target object may include: classifying different target objects included in the application scene based on attributes in advance, and obtaining information used to represent the attribute characteristics of the target object, such as the object corresponding to the target object contained in the road scene.
  • the attribute information may include at least one of a dynamic motor vehicle, a dynamic non-motor vehicle, and a static object. Different object attribute information corresponds to different risk factors, which will be described in detail later.
  • the target detection method can be used here to perform target detection on the scene image captured by the obstacle avoidance device to determine whether it contains a preset target object that matches the application scene. For example, for a road scene, the scene captured by the obstacle avoidance device After the image is imaged, it can be detected based on the pre-trained target detection network whether the scene image contains at least one of vehicles, pedestrians, railings, trees, steps, roadblocks, telephone poles, and the like.
  • an image acquisition component may be provided on the obstacle avoidance device, and the image acquisition component may include one or more cameras installed on the obstacle avoidance device, wherein the camera may be a panoramic camera, or a camera capable of capturing a wide range of Cameras, when the obstacle avoidance device is obstacle avoidance glasses, each camera can be distributed in different positions of the obstacle avoidance glasses, and is used to collect scene images of the road scene where the user is located.
  • the obstacle avoidance device corresponds to the target object within the set distance, which may refer to the target object within the set distance from the obstacle avoidance device.
  • the scene image is collected by the image acquisition component on the obstacle avoidance device
  • the The scene image is used to obtain the target object within the set distance from the obstacle avoidance device.
  • the distance between the boundary of the set range and the obstacle avoidance device is within a preset range
  • the preset range is related to the internal parameters of the image acquisition component on the obstacle avoidance device.
  • the image The farthest distance that the acquisition component can capture may represent the distance corresponding to the preset range.
  • the distance information corresponding to the target object may represent the distance between the target object and the obstacle avoidance device, and the distance may be determined in various ways, for example, by means of laser ranging, or by detecting the flight time of the light pulse. , to determine the distance information between the target object and the obstacle avoidance device, which will be described in detail later.
  • S102 Determine risk information of the target object based on the object attribute information and distance information corresponding to the target object.
  • the distance between the obstacle and the user is close, the possibility of collision is higher.
  • the probability of danger is also high, so the distance information corresponding to the target object can be used as a measure of the target object indicators of risk information.
  • the target objects of different object attribute information have different risks to the user.
  • the object attribute information corresponding to the target object can also be used as an indicator to measure the risk information of the target object, that is, the object attribute information of the target object is
  • the risk level of the target object relative to the user can be determined through attribute information.
  • a road condition prompt is performed through the obstacle avoidance device.
  • a road condition prompt can be provided for the target object.
  • each target object can be The risk information of the user is selected, and the user is selectively prompted, for example, the target object with higher risk is selected to remind the user of the road condition, so as to ensure the user's travel safety.
  • the prompting of road conditions by the obstacle avoidance device may include: prompting in at least one of a voice form and a vibration form.
  • the user is prompted by voice that "there is an obstacle ahead, please pay attention to slow down and avoid", or the user can be reminded that there is an obstacle in front of the user through vibration.
  • the object attribute information corresponding to the target object within the set distance corresponding to the obstacle avoidance device and the distance information corresponding to the target object can be obtained, and the target can be determined based on the object attribute information and distance information corresponding to the target object at the same time
  • the risk information of the object so that the risk information of the target object can be accurately determined.
  • the obstacle avoidance device can be the obstacle avoidance glasses worn by the visually impaired
  • the target object can be the obstacle on the road for the visually impaired.
  • acquiring the object attribute information corresponding to the target object within the distance setting azimuth corresponding to the obstacle avoidance device may include the following S1011-S1012:
  • the image acquisition component of the obstacle avoidance device may include a camera for collecting RGB images, the camera may collect RGB scene images of the target road condition scene, and for the RGB scene images, the target detection neural network can be used for pre-training.
  • the target object contained in the RGB scene image is subjected to target detection, so as to determine the target object contained in the RGB scene image and the object attribute information corresponding to the target object.
  • a neural network capable of detecting a set target object can be trained in advance based on a large number of sample images corresponding to the road condition scene, for example, it can be trained to detect motor vehicles, bicycles, pedestrians, traffic indicating roadblocks (traffic signal lights), A neural network of at least one obstacle such as traffic markings (crosswalks), trees, utility poles, steps, etc.
  • the scene image can be directly captured by the obstacle avoidance device.
  • the scene image corresponding to the user's travel scene can be directly obtained.
  • the scene image can be determined according to the scene image.
  • the target object and the corresponding object attribute information are displayed.
  • the target object can be directly detected on the scene image based on the pre-trained target detection neural network, so that the obstacle avoidance device can be equipped with a camera capable of acquiring the scene image, which can save the volume of the obstacle avoidance device and is convenient for the user to carry.
  • S1013 Acquire a scene image and a depth image obtained by photographing a target road condition scene by an obstacle avoidance device.
  • the obstacle avoidance device may include, in addition to an RGB camera for acquiring an RGB scene image corresponding to a target road condition scene, a camera for acquiring a depth image, and the camera for acquiring a depth image may include a binocular stereo vision camera or a time-of-flight camera. Law (Time Of Flight, TOF) camera.
  • RGB camera for acquiring an RGB scene image corresponding to a target road condition scene
  • the camera for acquiring a depth image may include a binocular stereo vision camera or a time-of-flight camera. Law (Time Of Flight, TOF) camera.
  • TOF Time Of Flight
  • the time-of-flight ranging method can be used to obtain a depth image corresponding to the target road condition scene, for example, according to the time interval from transmitting the light pulse to receiving the light pulse, and The transmission speed of the light pulse generates a depth image corresponding to the target road condition scene.
  • the depth image corresponding to the target road condition scene can be aligned with the scene image, so that the RGB camera and the TOF camera are in the same coordinate system, and then based on the aligned depth image and scene image Determine the distance information between each target object and the obstacle avoidance device.
  • the distance information corresponding to each target object can be quickly determined in combination with the scene image corresponding to the target road condition scene.
  • the above-mentioned process of determining the target object and the object attribute information corresponding to the target object that is, the process of S1011 to S1012, and the process of determining the distance information corresponding to the target object, that is, the sequence of the above-mentioned processes of S1013 to S1014 are not limited, you can first Determine the distance information corresponding to each object included in the scene image, and then determine which objects are target objects, or may first determine the target object, and then determine the distance information corresponding to the target object.
  • the distance information corresponding to the target object is determined, including the following S10141-S10142:
  • some edge position points of the same building contained in both the scene image and the depth image can be selected as the calibration feature points.
  • the scene image contains building A
  • the depth image also contains building A.
  • the feature points of the A contour are used as the calibration feature points, so that the scene image and the depth image are aligned, so that the depth information corresponding to the target object contained in the scene image can be determined in the depth image, and the depth information is used as the distance information corresponding to the target object.
  • a method for aligning the scene image and the depth image is provided, and the alignment of high accuracy.
  • the risk information of the target object is determined based on the object attribute information and distance information corresponding to the target object, as shown in FIG. 2, the following S201-S203 may be included:
  • S202 Determine a second risk coefficient corresponding to the target object according to the distance between the target object and the obstacle avoidance device indicated by the distance information corresponding to the target object.
  • a corresponding first risk coefficient may be pre-set for each type of object attribute information according to the degree of danger of each type of object attribute information, and a corresponding first risk factor may be pre-set for each distance interval according to the degree of risk corresponding to different distance intervals. Two risk factors.
  • the degree of danger of a dynamic motor vehicle to the user is greater than that of a dynamic non-motor vehicle, and the degree of danger of a dynamic non-motor vehicle is greater than the degree of danger of a static object to the user.
  • a risk factor is greater than the first risk factor of dynamic non-motor vehicles such as people and bicycles; the first risk factor of dynamic non-motor vehicles is greater than the first risk factor of static objects such as railings and trees.
  • the second risk factor corresponding to different distance intervals may be preset.
  • the distance interval may include an interval greater than 0.5 meters and less than or equal to 1 meter, greater than 1 meter and less than Or the interval equal to 3 meters, the interval greater than 3 meters, each distance interval corresponds to a different second risk factor.
  • the first risk factor and the second risk factor jointly determine the risk information of the target object.
  • the object attribute information corresponding to the target object and the distance information between the target object and the obstacle avoidance device can be comprehensively considered to jointly determine the target object's impact on the user. to improve the accuracy of the risk information of the determined target object.
  • the risk information of the target object is determined based on the distance information, the first risk factor and the second risk factor, which may include the following S2031-S2032:
  • S2032 Use the product of the difference between the target distance, the first risk coefficient and the second risk coefficient as the risk information of the target object.
  • the farthest distance corresponding to the shooting range of the camera on the obstacle avoidance device is related to the internal parameters of the camera, and the farthest distance is a fixed parameter, which can be determined by the distance indicated by the farthest distance and the distance information corresponding to the target object. The target distance difference between this target object and the furthest distance.
  • the risk value representing the risk information of the target object can be determined by the target distance difference, the first risk coefficient and the second risk coefficient corresponding to the target object.
  • the risk value R i of the target object i can be determined according to the following formula (1):
  • H represents the farthest distance corresponding to the shooting range of the obstacle avoidance device
  • d i represents the distance between the target object i and the obstacle avoidance device
  • w i1 represents the first risk factor corresponding to the target object i
  • w i2 represents the corresponding target object i the second risk factor.
  • the road condition prompting method provided by the embodiment of the present disclosure may further include:
  • category information corresponding to the target object is determined; the category information includes at least one of a traffic instruction category and a non-traffic instruction category.
  • target objects can be divided into target objects of the traffic indication category, target objects of the non-traffic indication category, and target objects of the traffic indication category according to the object attribute information.
  • it contains traffic signal lights and traffic marking lights, such as at least one of traffic lights and crosswalks
  • the target objects of non-traffic indication categories can include dynamic motor vehicles such as cars and motorcycles, dynamic non-motor vehicles such as pedestrians, bicycles, and static non-traffic indicating objects, such as at least one of railings, trees, and steps.
  • the road condition prompting by the obstacle avoidance device may include: based on the category information and risk information corresponding to the target object, the road condition prompting by the obstacle avoidance device.
  • the road condition prompt information in the case of prompting the user of the road condition, can be determined based on the target category information and risk information corresponding to the target object, and then the user is prompted according to the road condition prompt information, so as to improve the travel safety of the user.
  • the target object may be divided into a first type of target object belonging to a traffic indication category and a second type of target object belonging to a non-traffic indication category.
  • the meaning of the target object of the traffic indication category in the road scene that is, it is used to indicate the traffic rules, so that in the prompt sequence of the road condition prompt, the priority of the target object belonging to the first category of the traffic indication category is higher than or equal to that of the non-traffic indication category.
  • the priority of the second class target object of the traffic indication class is used to indicate the traffic rules, so that in the prompt sequence of the road condition prompt, the priority of the target object belonging to the first category of the traffic indication category is higher than or equal to that of the non-traffic indication category.
  • the first type of target object corresponding to the first The class risk coefficient is a negative number
  • the first class risk coefficient corresponding to the second class target object is a positive number
  • the information indicated by the traffic signal indicator can be given priority to the user, and the user can be based on the information. Determine whether to cross the road, and then prompt the target objects of the non-traffic indication category existing on the road. In this way, the user can travel safely in the road scene.
  • the obstacle avoidance device is used to prompt the road condition, as shown in FIG. 3 , which may include the following S301 to S302:
  • the target object includes a first-type target object belonging to a traffic indication category, based on the risk information of the first-type target object, determine the prompting sequence of the first-type target object in the case of prompting the road condition through the obstacle avoidance device .
  • the obstacle avoidance device is used to prompt the road condition for the first type of target object.
  • the risk information of each first-type target object can be determined according to the above formula (1), and then according to the risk descending method, each first-type target object The objects are sorted to obtain the prompt sequence of each first-type target object in the case of prompting the road conditions through the obstacle avoidance device.
  • the prompting sequence of the first type of target object in the case of prompting the road condition through the obstacle avoidance device including the following S3011-S3014:
  • the parameter information corresponding to the obstacle avoidance device may include at least one of internal parameters for converting the image coordinate system to the camera coordinate system, and external parameters for converting the camera coordinate system to the world coordinate system.
  • the first direction information that the obstacle avoidance device points to the first type of target object can be used to represent the directional relationship between the first type of target object and the obstacle avoidance device in the world coordinate system, such as the first type of target object in the world coordinate system.
  • the tie is located in the positive direction of the obstacle avoidance device along the X axis. If the positive direction of the X axis points to the east, the first type of target object is located in the east direction of the obstacle avoidance device.
  • the distance information corresponding to the first type of target object, and the parameter information corresponding to the obstacle avoidance device, to determine the first direction information of the obstacle avoidance device pointing to the first type of target object you may include:
  • the pose information of the obstacle avoidance device in the world coordinate system corresponding to the real scene can be determined based on the scene image captured by the obstacle avoidance device and the pre-established three-dimensional scene map representing the real scene.
  • the 3D scene map representing the real scene can be completely overlapped with the real scene, so the scene image captured by the obstacle avoidance device and the 3D scene map can be used to determine the position of the obstacle avoidance device in the world coordinate system corresponding to the real scene. pose information.
  • the pose information of the obstacle avoidance device in the world coordinate system corresponding to the real scene may include the position coordinate value and/or the orientation angle of the obstacle avoidance device in the world coordinate system, wherein the orientation angle can be determined by comparing with the world coordinate The angle between the coordinate axes of the system is represented.
  • the two-dimensional detection information of the first type of target object in the image coordinate system corresponding to the scene image is determined.
  • a pre-trained target detection neural network can be used to detect the target object contained in the scene image, and the pixel coordinates of the detection frame corresponding to the target object in the image coordinate system.
  • the pixel coordinates are used as the two-dimensional detection information of the first type of target object in the image coordinate system corresponding to the scene image.
  • the first type of target object may be determined based on the two-dimensional detection information of the first type of target object in the image coordinate system corresponding to the scene image and the internal parameters (pre-stored internal parameters) corresponding to the obstacle avoidance device
  • the coordinate values along the X axis and the Y axis of the camera coordinate system can then be determined based on the distance information corresponding to the first type of target object in the obstacle avoidance device.
  • the coordinate value along the Z axis of the camera coordinate system and then combined with the external parameters corresponding to the obstacle avoidance device (which can be determined by the pose information of the obstacle avoidance device in the world coordinate system corresponding to the real scene), determine the first The pose information of the class target object in the world coordinate system.
  • the pose information of the first type of target object in the world coordinate system may include the position coordinate value of the first type of target object in the world coordinate system.
  • the determination may be based on the position coordinate values of the obstacle avoidance device and the first type of target object in the world coordinate system.
  • the change of the position coordinate value of the obstacle avoidance device in the world coordinate system can be determined based on a plurality of scene images, and then the movement direction of the obstacle avoidance device can be obtained.
  • the first-type target objects that tend to be approached by obstacle avoidance settings can be used as the first-type target objects to be prompted.
  • three first-type target objects are detected, which are respectively recorded as The first type of target object A, the first type of target object B and the first type of target object C, if the movement direction of the obstacle avoidance device is towards the first type of target object A, away from the first type of target object B and the first type of target object C , where the first type of target object A can be used as the first type of target object to be prompted.
  • the first-type target objects to be prompted are selected from the plurality of first-type target objects, it can be determined based on the risk information of the first-type target objects to be prompted that the first-type target objects to be prompted are undergoing road conditions through the obstacle avoidance device. Prompt order in case of prompts.
  • the traffic lights correspond to The risk value is greater than the risk value corresponding to the pedestrian crossing, and it can be determined that the prompting order of the traffic lights takes precedence over the prompting order of the pedestrian crossing.
  • the obstacle avoidance device is used to prompt the target object of the first type of road conditions, which may include:
  • the distance between the first type of target object to be prompted and the obstacle avoidance device indicated by the distance information corresponding to the first type of target object to be prompted is less than the distance between the first type of target object to be prompted and the obstacle avoidance device.
  • the obstacle avoidance device will prompt the road condition for the first type of target object to be prompted.
  • the embodiment of the present disclosure proposes that when the obstacle avoidance device prompts the user about the road condition for the target object of the first category to be prompted, the distance between the user and the target object of the first category to be prompted can be adjusted.
  • the prompt will be given again, wherein the distance required for the user to be able to adjust the walking state urgently in the event of an emergency can be used as the first preset distance threshold here, and the first preset distance
  • the setting of the threshold can be obtained by pre-statistics based on big data.
  • the first-type target object that is close to the obstacle avoidance device may be preferentially selected as the target object to be prompted, and after determining that the obstacle avoidance device and the first-type target object are When the distance between them is smaller than the first preset distance threshold, prompting is performed again to reduce the situation of invalid prompting, thereby improving the accuracy of the road condition prompting during the road condition prompting process for the user.
  • the obstacle avoidance device is used to prompt the road condition, as shown in FIG. 4 , which may include the following S401 to S402:
  • the target object includes a second type of target object belonging to a non-traffic indication category, based on risk information of the second type of target object, determine a second type of target to be prompted that meets a preset condition from the second type of target object object.
  • the second type of target objects that are likely to cause danger to the user's travel can be screened out according to the risk information of the second type of target objects as the second type of target objects to be prompted.
  • the second preset distance threshold and the above-mentioned first preset distance threshold may be the same or different. Similar to the above-mentioned prompting process for the first type of target object to be prompted, when the second type of target object is to be prompted.
  • the obstacle avoidance device can be used to target the second type of target object to be prompted when it is determined that the distance between the second type of target object to be prompted and the obstacle avoidance device is less than the second preset distance threshold. Carrying out road condition prompts can also reduce the situation of invalid prompts, thereby improving the accuracy of road condition prompts during the process of road condition prompting.
  • determining the second type of target object to be prompted that meets the preset condition from the second type of target object may include S4011 to S4014:
  • the manner of determining the second direction information of the obstacle avoidance device pointing to the second type of target object is similar to the above-mentioned manner of determining the first direction information of the obstacle avoidance device pointing to the first type of target object.
  • S4013 Determine a second angle between the second direction indicated by the second direction information and the movement direction of the obstacle avoidance device based on the second direction information corresponding to the second type of target object and the movement direction of the obstacle avoidance device.
  • whether the obstacle avoidance device moves toward the second type of target object can be determined through the second angle, for example, the smaller the second angle, the higher the probability of the obstacle avoidance device to move toward the second type of target object.
  • the target objects of the second type to be prompted can be selected based on the second angle and the risk information corresponding to the target objects of the second type at the same time.
  • the second type of target object with higher risk indicated by the risk information is regarded as the second type of target object to be prompted.
  • the second type of target object to be prompted is screened in combination with the moving direction of the obstacle avoidance device and the distance between the second type of target object and the obstacle avoidance device, so that the second type of target object that is likely to be dangerous to the user can be selected.
  • the class target object is prompted to improve the user's travel safety.
  • the types of road scenes encountered by the user in the road scene may also be considered, such as pedestrian road scene types, intersection scene types, and overpass tunnel scene types. , station scene type, etc.
  • the road condition prompting method provided by the embodiment of the present disclosure further includes:
  • the road scene type can be obtained in different ways.
  • the road scene type that the user is currently in can be determined based on the navigation component and the pre-selected navigation route, or the obstacle avoidance device can The type of road scene the user is currently in is determined by the scene sign captured by the device, and the method of determining the type of road scene the user is currently in will be described later.
  • the obstacle avoidance device may include: based on the determined risk information and road scene type, the obstacle avoidance device is used to prompt the road condition.
  • the prompting may be performed for the target object first, and then for the road scene type, or the prompting may be performed for the road scene type first, and then the target object is prompted.
  • acquiring the road scene type corresponding to the location of the obstacle avoidance device may include the following S501-S502:
  • the location information of the obstacle avoidance device may be obtained through a navigation component on the obstacle avoidance device, or the location information of the obstacle avoidance device may be determined based on a scene image captured by the obstacle avoidance device, as described above for details.
  • the obstacle avoidance device may include a mobile device, such as a mobile phone or a tablet, and the navigation component is a navigation component on the mobile phone or tablet.
  • the user can select a navigation path to the destination through the obstacle avoidance device.
  • the navigation path can include various road scenarios and the location information corresponding to each road scene.
  • the road scene type corresponding to the location of the obstacle avoidance device can be determined.
  • S602 Perform scene sign recognition on the stop sign image to determine the road scene type corresponding to the area where the obstacle avoidance device is located.
  • the stop sign image can be acquired by an image acquisition component on the obstacle avoidance device, and the stop sign image can be recognized based on a pre-trained sign recognition neural network to determine the road scene type corresponding to the area where the obstacle avoidance device is located.
  • the road scene type corresponding to the area where the obstacle avoidance device is located is the station scene type.
  • the obstacle avoidance device performs road condition prompting, which may include the following S701 to S703:
  • the obstacle avoidance device performs road condition prompting for the first type of prompt information and the second type of prompt information.
  • the method for generating the first type of prompt information for the obstacle avoidance device based on the determined risk information is described in the above.
  • the target object category information, the object attribute information, and the relationship with the obstacle avoidance device can be used for the target object. distance to generate the first type of prompt information for obstacle avoidance equipment.
  • the second type of prompt information for the obstacle avoidance device may be used to prompt the type of road scene where the user is located, so as to facilitate the user to determine the type of road scene where he is located, so as to determine whether to adjust the driving speed to improve travel safety.
  • the preset prompt sequence between the first type of prompt information and the second type of prompt information is that the second type of prompt information is prior to the first type of prompt information
  • the second type of prompt information is broadcast first
  • the first type of prompt information is broadcast again, so that users can first determine the type of road scene they are in, and then determine the obstacles encountered in the road scene type, so that the walking speed and direction can be adjusted in time to improve travel safety.
  • the obstacle avoidance equipment used mainly uses ultrasonic technology, laser ranging technology, binocular vision technology, and global positioning system technology, and these technologies are only for object and human body recognition, and cannot be judged. Which object is the first to arrive, and it is impossible to judge whether this object will endanger the walking of the blind.
  • the embodiment of the present disclosure adopts an automatic screening method that can help the blind.
  • the first object, the second object, the third object, etc. that arrive first are screened out, and the danger level of the object is judged at the same time.
  • the road condition prompting method provided by the embodiment of the present disclosure can screen the information of obstacles ahead, reduce the interference caused by a large number of information broadcasts, perform object risk assessment combined with different weights of objects at different distances, and broadcast only the most dangerous object.
  • the user is a visually impaired user
  • the obstacle avoidance equipment includes obstacle avoidance glasses and terminal equipment as an example.
  • video capture is performed through the RGB camera set on the obstacle avoidance glasses.
  • the terminal device to collect the scene image corresponding to the road scene, and then use the terminal device to perform target detection on the scene image to determine the target objects contained in the scene image, such as sidewalks/blind lanes, motor vehicles/non-motor vehicles, subway stations/buses Identify at least one target object of stations, pedestrians/animals, overpasses/underpasses, ramps/steps/elevators, station signs, telephone poles/trees, slopes/puddles, etc., and determine the target objects contained in the scene image, At the same time, distance collection can also be performed based on the TOF camera to collect depth images corresponding to the road scene.
  • target objects contained in the scene image such as sidewalks/blind lanes, motor vehicles/non-motor vehicles, subway stations/buses Identify at least one target object of stations, pedestrians/animals, overpasses/underpasses, ramps/steps/elevators, station signs, telephone poles/trees, slopes/puddles, etc.
  • Obtaining the distance information of the target object may include: determining the distance information corresponding to the target object, that is, determining the distance information between the detected target object and the obstacle avoidance glasses.
  • the position coordinate value of the target object in the world coordinate system can be determined based on the above-mentioned scene image and depth image, and then the spatial position of the target object can be determined.
  • the terminal device can determine the navigation route guidance according to the map location.
  • the current location can be determined based on the navigation route, and then scene perception can be performed based on the current location. For example, it can be based on the user's location information and preset
  • the navigation route determines the type of road scene where the user is located, for example, it can identify the type of sidewalk walking scene, the scene type of crossing the intersection, the scene type of the overpass tunnel, the scene type of bus and subway, etc., or the road where the user is located can be determined based on the stop sign. At least one of the scene types.
  • a navigation path plan may be determined based on the navigation route, and voice prompt information may be generated based on the navigation path plan.
  • the type of road scene where the user is located After determining the type of road scene where the user is located, the type of road scene where the user is located and the distance information of the target object can be obtained based on the scene perception, the potential risk level of each target object to the user can be judged, and then the voice prompt information can be generated based on the risk level.
  • the voice prompt information for the user can be generated by combining the road scene type, the object attribute information corresponding to the target object, and the distance information between the target object and the obstacle avoidance device. After the voice prompt information is obtained, a voice prompt can be given to the user based on the language prompt information, thereby improving the travel safety of the user.
  • the user can be given a voice prompt through the obstacle avoidance device.
  • a voice prompt may be given to the user through the terminal device.
  • the embodiment of the present disclosure also provides a road condition prompting device corresponding to the road condition prompting method. See implementation of the method.
  • the road condition prompting apparatus 800 includes:
  • the obtaining part 801 is configured to obtain the object attribute information corresponding to the target object within the distance setting range corresponding to the obstacle avoidance device, and the distance information corresponding to the target object;
  • the determining part 802 is configured to determine the risk information of the target object based on the object attribute information and distance information corresponding to the target object;
  • the prompting part 803 is configured to prompt the road condition through the obstacle avoidance device based on the determined risk information.
  • the acquisition part 801 when configured to acquire the object attribute information corresponding to the target object within the set distance corresponding to the obstacle avoidance device, it includes:
  • the target object contained in the scene image and the object attribute information corresponding to the target object are determined.
  • the obtaining part 801 when configured to obtain the distance information corresponding to the target object, it includes:
  • the distance information corresponding to the target object is determined, and the distance information includes the distance between the target object and the obstacle avoidance device.
  • the acquisition part 801 when configured to determine the distance information corresponding to the target object based on the scene image and the depth image, it includes:
  • the scene image and the depth image are aligned, and the depth information of the target object contained in the scene image is extracted from the depth image, and the distance information corresponding to the target object is obtained.
  • the method includes:
  • risk information of the target object is determined.
  • the method when the determining part 802 is configured to determine the risk information of the target object based on the distance information, the first risk factor and the second risk factor, the method includes:
  • the product of the target distance difference, the first risk coefficient and the second risk coefficient is used as risk information of the target object.
  • the determining part 802 is further configured to:
  • the category information includes at least one of a traffic indication category and a non-traffic indication category;
  • the prompting part 803, when configured to prompt the road condition through the obstacle avoidance device based on the determined risk information, includes:
  • the priority of the first type of target objects belonging to the traffic indication category is higher than or equal to the priority of the second type of target objects belonging to the non-traffic indication category.
  • the prompting part 803 when the prompting part 803 is configured to perform road condition prompting through the obstacle avoidance device based on the category information and risk information corresponding to the target object, the prompting part 803 includes:
  • the target object includes the first type of target object belonging to the traffic indication category, based on the risk information of the first type of target object, determine the prompting sequence of the first type of target object when the obstacle avoidance device is used to prompt the road condition;
  • the obstacle avoidance equipment is used to prompt the road condition for the first type of target object.
  • the prompting part 803 when the prompting part 803 is configured to determine, based on the risk information of the first-type target object, the prompting sequence of the first-type target object in the case of prompting the road condition through the obstacle avoidance device, the prompting part 803 includes: :
  • the distance information corresponding to the first type of target object, and the parameter information corresponding to the obstacle avoidance device determine the first direction information that the obstacle avoidance device points to the first type of target object;
  • the first-type target objects to be prompted are determined from the first-type target objects based on the first direction information corresponding to the first-type target objects and the movement direction of the obstacle avoidance device,
  • the first angle between the direction indicated by the first direction information corresponding to the first type of target object to be prompted and the movement direction of the obstacle avoidance device is smaller than the set angle threshold;
  • the prompting part 803 is configured to perform road condition prompting for the first type of target object through the obstacle avoidance device according to the determined prompting sequence, it includes:
  • the distance between the first type of target object to be prompted and the obstacle avoidance device indicated by the distance information corresponding to the first type of target object to be prompted is less than the distance between the first type of target object to be prompted and the obstacle avoidance device.
  • the obstacle avoidance device will prompt the road condition for the first type of target object to be prompted.
  • the prompting part 803 is configured to determine that the obstacle avoidance device points to the first type based on the scene image captured by the obstacle avoidance device, the distance information corresponding to the first type of target object, and the parameter information corresponding to the obstacle avoidance device.
  • the first direction information of the target object it includes:
  • the two-dimensional detection information of the first type of target object in the image coordinate system corresponding to the scene image is determined;
  • the first direction information of the obstacle avoidance device pointing to the first type of target object is determined.
  • the prompting part 803 when the prompting part 803 is configured to perform road condition prompting through the obstacle avoidance device based on the category information and risk information corresponding to the target object, the prompting part 803 includes:
  • the target object includes a second type of target object belonging to a non-traffic indication category, based on the risk information of the second type of target object, determine the second type of target object to be prompted that meets the preset condition from the second type of target object;
  • the obstacle avoidance device When the distance information corresponding to the target object of the second type to be prompted indicates that the distance between the target object of the second type to be prompted and the obstacle avoidance device is less than the second preset distance threshold, the obstacle avoidance device will use the obstacle avoidance device for the target object to be prompted.
  • the second type of target object is prompted for road conditions.
  • the prompting part 803 is configured to, based on the risk information of the second type of target objects, determine from the second type of target objects to be prompted the second type of target objects that meet the preset conditions, include:
  • the distance information corresponding to the second type of target object, and the parameter information corresponding to the obstacle avoidance device determine the second direction information that the obstacle avoidance device points to the second type of target object;
  • At least one second-type target object whose second angle is less than the preset angle threshold determined from the second-type target objects is taken as the second-type target object to be prompted, at least The risk degree indicated by the risk information corresponding to a target object of the second type is higher than the risk degree indicated by the risk information corresponding to other target objects of the second type target object except the target object of the second type to be prompted.
  • the obtaining part 801 is further configured to:
  • the prompting part 803 is configured to perform road condition prompting through the obstacle avoidance device based on the determined risk information, it includes:
  • the obtaining part 801 when configured to obtain the road scene type corresponding to the location of the obstacle avoidance device, it includes:
  • the obtaining part 801 when configured to obtain the road scene type corresponding to the location of the obstacle avoidance device, it includes:
  • the scene sign recognition is performed on the stop sign image, and the road scene type corresponding to the location of the obstacle avoidance equipment is determined.
  • the prompting part 803 when configured to prompt the road condition through the obstacle avoidance device based on the determined risk information and the road scene type, it includes:
  • the first type of prompt information is generated
  • the obstacle avoidance device is used to prompt the road conditions for the first prompt information and the second type of prompt information.
  • an embodiment of the present disclosure further provides an electronic device 900 .
  • a schematic structural diagram of the electronic device 900 provided in an embodiment of the present disclosure includes:
  • the communication between the processor 91 and the memory 92 is through the bus 93, and the machine-readable instructions
  • the instruction is executed by the processor 91, the steps of the road condition prompting method in the above method embodiment are executed.
  • the memory 92 is configured to store execution instructions, including the memory 921 and the external memory 922; the memory 921 here is also called internal memory, and is configured to temporarily store the operation data in the processor 91 and the data exchanged with the external memory 922 such as the hard disk. 91 performs data exchange with the external memory 922 through the memory 921.
  • the processor 91 and the memory 92 communicate through the bus 93, so that the processor 91 executes the following instructions: Obtain the distance setting corresponding to the obstacle avoidance device Object attribute information corresponding to the target object within the range, and distance information corresponding to the target object; based on the object attribute information and distance information corresponding to the target object, determine the risk information of the target object; hint.
  • the electronic device 900 may also execute the steps of the road condition prompting method provided by any of the foregoing embodiments.
  • Embodiments of the present disclosure further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the steps of the road condition prompting method described in the foregoing method embodiments are executed.
  • the storage medium may be a volatile or non-volatile computer-readable storage medium.
  • the computer program product of the road condition prompting method provided by the embodiments of the present disclosure includes computer-readable codes, and when the computer-readable codes are executed in an electronic device, the processor in the electronic device executes the foregoing method embodiments
  • the steps of the road condition prompting method described in reference may be made to the above method embodiments.
  • Embodiments of the present disclosure also provide a computer program, which implements any one of the methods in the foregoing embodiments when the computer program is executed by a processor.
  • the computer program product can be implemented in hardware, software or a combination thereof.
  • the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK) and the like.
  • the units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the functions, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a processor-executable non-volatile computer-readable storage medium.
  • the computer software products are stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present disclosure.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk and other media that can store program codes .
  • the embodiments of the present disclosure disclose a road condition prompting method, device, electronic device, storage medium and program product, wherein the road condition prompting method includes: acquiring object attribute information corresponding to a target object within a distance setting range corresponding to an obstacle avoidance device, and the distance information corresponding to the target object; based on the object attribute information and the distance information corresponding to the target object, determine the risk information of the target object; based on the determined risk information, through the obstacle avoidance
  • the device provides traffic alerts.
  • the above solution can accurately determine the risk information of obstacles for the visually impaired person, so that the road condition can be prompted based on the risk information, and the travel safety of the visually impaired person can be improved.

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Abstract

La présente invention concerne un procédé et un appareil d'invite d'état de route, et un dispositif électronique, un support de stockage et un produit de programme. Le procédé d'invite d'état de route consiste à : acquérir des informations d'attribut d'objet correspondant à un objet cible dans une plage de distance définie correspondant à un dispositif d'évitement d'obstacle, et des informations de distance correspondant à l'objet cible (S101) ; déterminer des informations de risque de l'objet cible sur la base des informations d'attribut d'objet et des informations de distance correspondant à l'objet cible (S102) ; et sur la base des informations de risque déterminées, donnant une invite d'état de route au moyen du dispositif d'évitement d'obstacle (S103).
PCT/CN2021/095149 2020-08-28 2021-05-21 Procédé et appareil d'invite d'état de route, et dispositif électronique, support de stockage et produit de programme WO2022041869A1 (fr)

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CN112489460A (zh) * 2020-12-03 2021-03-12 百度国际科技（深圳）有限公司 信号灯信息的输出方法和装置
CN112906625A (zh) * 2021-03-12 2021-06-04 北京市商汤科技开发有限公司 一种避障提示方法、装置、电子设备及存储介质
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