WO2022183415A1 - 一种积水深度确定方法及装置 - Google Patents

一种积水深度确定方法及装置 Download PDF

Info

Publication number
WO2022183415A1
WO2022183415A1 PCT/CN2021/078931 CN2021078931W WO2022183415A1 WO 2022183415 A1 WO2022183415 A1 WO 2022183415A1 CN 2021078931 W CN2021078931 W CN 2021078931W WO 2022183415 A1 WO2022183415 A1 WO 2022183415A1
Authority
WO
WIPO (PCT)
Prior art keywords
road
water
depth
maximum
area
Prior art date
Application number
PCT/CN2021/078931
Other languages
English (en)
French (fr)
Inventor
高鲁涛
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN202180000406.8A priority Critical patent/CN113168535A/zh
Priority to PCT/CN2021/078931 priority patent/WO2022183415A1/zh
Publication of WO2022183415A1 publication Critical patent/WO2022183415A1/zh

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00Scenes; Scene-specific elements
    • G06V20/50Context or environment of the image
    • G06V20/56Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/588Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/21Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214Generating training patterns; Bootstrap methods, e.g. bagging or boosting

Definitions

  • the present application relates to the field of intelligent driving, and in particular, to a method and device for determining the depth of accumulated water.
  • ADAS Advanced Driving Assist System
  • Driving assistance or unmanned driving needs to use the vehicle's own sensors to perceive the surrounding environment.
  • the output of the sensor directly determines the formulation of the vehicle's driving strategy. Therefore, it is particularly important whether the output of the sensor can accurately describe the real environment.
  • During the driving process of the vehicle it is inevitable to encounter low-lying road sections. For example, the road sections under the road bridges in urban roads, these places are prone to accumulation of water after rain, which is easily caused by human drivers wading in the wrong estimation of the depth of the accumulation of water. Vehicle broke down. Therefore, how to determine the depth of water accumulation is also a very important problem for autonomous vehicles.
  • a method for determining the depth of water accumulation is shown in Figure 1. After the vehicle enters the water accumulation area, use the camera to take pictures of the side of the vehicle to detect the position where the water surface does not pass the vehicle tires, and then pass the known vehicle tires. Size, judge the depth of standing water through the proportional relationship.
  • the prior art is to detect the depth of the water after the vehicle wades into the water, and it is difficult to ensure that the vehicle will not encounter a deep water area in front of the vehicle, so that the vehicle may easily drive into the deep water area without knowing it, thereby causing the vehicle to break down.
  • the embodiments of the present application provide a method and device for determining the water accumulation depth, which solves the problem of measuring the water accumulation depth of the road ahead before the vehicle enters the water accumulation area.
  • an embodiment of the present application provides a method for determining the depth of stagnant water, including: acquiring image information of a stagnant road; and determining spatial position information of a first edge in an edge of stagnant water based on the image information of the stagnant road ; wherein, the first edge is any edge of the two edges of the stagnant area in the extending direction of the stagnant road; obtain road slope angle information, the road slope angle information includes the first the slope angle of the road where the edge is located; determine the road position information corresponding to the maximum water depth of the water accumulation area/water surface position information corresponding to the maximum water depth of the water accumulation area; based on the spatial position information of the first edge, The road slope angle information, the road position information corresponding to the maximum water depth/the water surface position information corresponding to the maximum water depth of the water accumulation area are used to determine the maximum water accumulation depth of the water accumulation area.
  • the image information of the stagnant road is obtained, and then the image information is analyzed and processed to obtain the spatial position of the stagnant water edge, and then the road slope angle and the road corresponding to the maximum water depth of the stagnant area are determined by certain strategies.
  • Position/the position of the water surface corresponding to the maximum water depth of the water accumulation area, and finally determined according to the spatial position of the water accumulation edge, the slope angle of the road, the road position corresponding to the maximum water depth/the water surface position corresponding to the maximum water depth of the water accumulation area The maximum ponding depth of the ponded area. It realizes the measurement of the water depth of the road ahead before the vehicle enters the water accumulation area, and avoids the risk of anchoring caused by the vehicle wading too deep.
  • the maximum water accumulation depth of the water accumulation area is determined based on the spatial position information of the first edge, the road slope angle information, and the road position information corresponding to the maximum water depth
  • the method includes: determining a first distance based on the spatial position information of the first edge and the road position information corresponding to the maximum water depth, where the first distance represents the spatial position of the first edge corresponding to the maximum water depth The distance of the road location; based on the product of the first distance and the sine value of the road slope angle, determine the maximum water accumulation depth of the water accumulation area.
  • the method before the determining the road location information corresponding to the maximum water depth of the stagnant area, the method further includes: acquiring slope aspect information of the stagnant road, where the slope aspect information includes the stagnant road The position at the change of the slope aspect of the stagnant road; the determining the road position information corresponding to the maximum water depth of the stagnant water area includes: based on the position of the slope aspect change of the stagnant road, determining the maximum value of the stagnant water area.
  • Road location information corresponding to water depth before the determining the road location information corresponding to the maximum water depth of the stagnant area, the method further includes: acquiring slope aspect information of the stagnant road, where the slope aspect information includes the stagnant road The position at the change of the slope aspect of the stagnant road; the determining the road position information corresponding to the maximum water depth of the stagnant water area includes: based on the position of the slope aspect change of the stagnant road, determining the maximum value of the stagnant water area.
  • Road location information corresponding to water depth before the determining the road location information
  • the road position corresponding to the maximum water depth of the stagnant water area is determined by the change of the road slope aspect, without obtaining relatively sensitive road elevation information, which increases the application scope of the solution.
  • the determining the road location information corresponding to the maximum water depth of the stagnant area includes: based on the first road The orthographic projection of the center line of , on the stagnant road, to determine the road position information corresponding to the maximum water depth of the stagnant area.
  • the embodiment of the present application solves the problem of determining the road position corresponding to the maximum water depth of the stagnant water area in a bridge-hole scenario.
  • the maximum area of the water accumulation area is determined based on the spatial position information of the first edge, the road slope angle information, and the water surface position information corresponding to the maximum water depth of the water accumulation area.
  • Water depth including: determining a second distance based on the spatial position information of the first edge and the water surface position information corresponding to the maximum water depth, where the second distance represents the spatial position of the first edge to the maximum water depth The distance of the water surface position corresponding to the water depth; based on the product of the second distance and the tangent of the road slope angle, the maximum water accumulation depth of the water accumulation area is determined.
  • the stagnant road is a tunnel bridge
  • the image information of the stagnant road includes a bridge hole area image and a road area image
  • the determining the water surface position corresponding to the maximum water depth of the stagnant area information including: determining the bridge hole area image and the road area image based on the image information of the stagnant road; based on the junction position of the bridge hole area image and the road area image, determining the water surface position corresponding to the maximum water depth of the stagnant water area information.
  • the embodiment of the present application provides a solution for determining the depth of water accumulation in tunnel bridge water accumulation scenarios. Without a high-precision map, the water surface position corresponding to the maximum water depth in the water accumulation area can be determined by means of image analysis, without relying on high-precision maps. Map, in the absence of high-precision maps, the implementation of the solution is still guaranteed.
  • the determining the water surface position information corresponding to the maximum water depth of the water accumulation area includes: determining the road position coordinates corresponding to the maximum water depth of the water accumulation area, where the road position coordinates are: Two-dimensional coordinates; based on the road position coordinates, determine the water surface position information corresponding to the maximum water depth of the water accumulation area.
  • the method further includes: when a height limit device is set on the road in the stagnant water area; acquiring a height limit value of the height limit device; based on the height limit value and the current location of the terminal location information, and determine the first height difference, where the first height difference represents the difference between the current location of the terminal and the height of the height-limiting device; based on the current location information of the terminal, the first edge
  • the spatial position information, road slope angle information, height limit value and first height difference are obtained to determine the maximum water accumulation depth of the water accumulation area.
  • the spatial location information of the first edge, the road slope angle information, the height limit value and the first height difference determine the maximum value of the water accumulation area
  • the depth of water accumulation includes: determining a third distance based on the current location information of the terminal and the spatial location information of the first edge, where the third distance represents the current location of the terminal to the first edge
  • the distance of the spatial position based on the product of the third distance and the sine value of the road slope angle and the first height difference, determine the second height difference, and the second height difference represents the height limit device and the height difference.
  • the height difference of the water surface of the ponding area based on the difference between the limit height value and the second height difference, determine the maximum ponding depth of the ponding area.
  • the embodiment of the present application provides a solution for determining the depth of ponding water in a height-limited scenario, by obtaining the height-limited value obtained from the vehicle sensor, the height difference between the vehicle and the highest point of the height-limiting device, and the spatial position of the ponding water edge, road slope
  • the maximum water depth of the water accumulation area can be determined by the angle, and it is not strongly dependent on the high-precision map.
  • the embodiments of the present application provide another method for determining the depth of stagnant water, including: acquiring image information of a stagnant road; determining a spatial position of a first edge in the stagnant water edge based on the image information of the stagnant road information, and determine the elevation information of the first edge according to the spatial position information of the first edge; wherein, the first edge is any one of the two edges of the stagnant area in the extending direction of the stagnant road edge; determine the elevation information of the road corresponding to the maximum water depth of the water accumulation area; determine the water accumulation area based on the elevation information of the first edge and the road elevation information corresponding to the maximum water depth of the water accumulation area The maximum water depth of the area.
  • the maximum water depth of the water accumulation area can be determined based on the difference between the elevations of the two elevations by obtaining the elevation of the water accumulation edge and the elevation of the road corresponding to the maximum water depth of the water accumulation area. It greatly simplifies the algorithm, reduces the computing power requirements for the terminal, and improves the efficiency of water depth determination.
  • the acquiring the elevation information of the road corresponding to the maximum water depth of the water accumulation area includes: acquiring map information of the road where the water accumulation area is located, where the map information includes the elevation of the road where the water accumulation area is located information; based on the minimum elevation value in the elevation information of the road where the water accumulation area is located, determine the elevation information of the road corresponding to the maximum water depth of the water accumulation area.
  • the elevation of the road corresponding to the maximum water depth of the stagnant water area can be determined only by obtaining the elevation value of the road and then comparing, without analyzing other information of the road, and the algorithm is simple and efficient.
  • an embodiment of the present application further provides a method for controlling a terminal, including: a terminal at a preset distance from a water accumulation area, detecting and determining the maximum water accumulation depth of the water accumulation area, and determining the maximum accumulation depth of the water accumulation area according to the The maximum water depth controls the terminal.
  • the controlling the terminal according to the maximum water accumulation depth of the water accumulation area includes: if the maximum accumulation water depth of the water accumulation area is greater than or equal to a preset threshold, sending a warning message and /or control the terminal to stop and/or exit the automatic driving mode and/or re-plan the driving route.
  • the terminal is a vehicle. It realizes the measurement of the water depth of the road ahead before the vehicle enters the water accumulation area, and avoids the risk of breaking down caused by the vehicle wading too deep.
  • the detecting and determining the maximum ponding depth of the ponding area is determined based on the method of the first aspect or the second aspect.
  • an embodiment of the present application further provides an information transmission method, comprising: a terminal at a preset distance from a water accumulation area, determining the location of the water accumulation area and/or the maximum accumulation of water in the water accumulation area Depth, send the location information of the stagnant area and/or the maximum stagnant depth of the stagnant area to other vehicles and/or upload the dynamic information to the high-precision map.
  • the maximum ponding depth is determined based on the method described in the first aspect or the second aspect.
  • an embodiment of the present application further provides a device for determining the depth of stagnant water, comprising: an acquisition module configured to acquire image information and road slope angle information of a stagnant road; wherein the road slope angle information includes the the slope angle of the road where the first edge is located; the determination module is configured to determine the spatial position information of the first edge in the stagnant water based on the image information of the stagnant road; wherein, the first edge is the stagnant water any one of the two edges of the area in the extending direction of the water-filled road; used to obtain road slope angle information, the road slope angle information includes the road slope angle where the first edge is located; the second determination A module for determining the road position information corresponding to the maximum water depth of the water accumulation area/water surface position information corresponding to the maximum water depth of the water accumulation area; for determining the spatial position information based on the first edge, the road slope Angle information, road position information corresponding to the maximum water depth/water surface position information corresponding to the maximum water depth of the water accumulation area, to determine the maximum
  • the determining module is specifically configured to: determine a first distance based on the spatial location information of the first edge and the road location information corresponding to the maximum water depth, where the first distance represents the The distance from the spatial position of the first edge to the road position corresponding to the maximum water depth; based on the product of the first distance and the sine value of the road slope angle, the maximum water accumulation depth of the water accumulation area is determined.
  • the obtaining module is further configured to obtain the slope aspect information of the stagnant road, where the slope aspect information includes a position where the slope aspect of the stagnant road changes; the determining module is specifically used for: Based on the position where the slope aspect of the stagnant road changes, road location information corresponding to the maximum water depth of the stagnant area is determined.
  • the determining module is specifically configured to: based on the positive value of the center line of the first road on the stagnant road Projection is performed to determine the road location information corresponding to the maximum water depth of the water accumulation area.
  • the determining module is specifically configured to: determine a second distance based on the spatial position information of the first edge and the water surface position information corresponding to the maximum water depth, where the second distance represents the The distance from the spatial position of the first edge to the water surface position corresponding to the maximum water depth; based on the product of the second distance and the tangent of the road slope angle, the maximum water depth of the water accumulation area is determined.
  • the stagnant road is a tunnel bridge
  • the image information of the stagnant road includes a bridge hole area image and a road area image
  • the determining module is specifically configured to: based on the image of the stagnant road The information determines the bridge hole area image and the road area image; based on the junction position of the bridge hole area image and the road area image, the water surface position information corresponding to the maximum water depth of the water accumulation area is determined.
  • the determining module is specifically configured to: determine the road position coordinates corresponding to the maximum water depth of the water accumulation area, where the road position coordinates are two-dimensional coordinates; based on the road position coordinates, determine The water surface position information corresponding to the maximum water depth of the water accumulation area.
  • the first obtaining module is further configured to obtain the height limiting value of the height limiting device
  • the determining module is further configured to Determine a first height difference based on the height limit value and the current location information of the terminal, where the first height difference represents the difference between the current location of the terminal and the height of the height limiting device
  • the current position information of the terminal, the spatial position information of the first edge, the road slope angle information, the height limit value and the first height difference are used to determine the maximum water accumulation depth of the water accumulation area.
  • the determining module is specifically configured to: determine a third distance based on the current location information of the terminal and the spatial location information of the first edge, where the third distance represents the terminal The distance from the current position to the spatial position of the first edge; the second height difference is determined based on the product of the third distance and the sine of the road slope angle and the first height difference, and the first height difference is determined.
  • the second height difference represents the height difference between the height limit device and the water surface of the water accumulation area; based on the difference between the height limit value and the second height difference, the maximum water accumulation depth of the water accumulation area is determined.
  • an embodiment of the present application further provides a vehicle, including the device for determining the depth of ponding water described in the fifth aspect or any possible implementation manner of the fifth aspect.
  • an embodiment of the present application further provides a chip system, including a processor and a memory, the memory stores program instructions, and the first aspect is implemented when the program instructions stored in the memory are called and executed by the processor Or the method described in the second aspect or the third aspect or the fourth aspect.
  • an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed in a computer, the computer is made to execute the first aspect or the second aspect or the third aspect The method of aspect or the fourth aspect.
  • the present application may further combine to provide more implementation manners.
  • Fig. 1 is the application scene diagram of water depth determination in the prior art
  • FIG. 2 is an application scenario diagram provided by an embodiment of the present application
  • Fig. 3 is a flow chart of a method for determining the depth of ponding water provided for the implementation of this application;
  • Figure 4 is a schematic diagram of the principle of the similar triangle ranging method at the landing point
  • 5 is a schematic diagram of a calculation method for a road slope angle
  • Fig. 6 is another kind of calculation method schematic diagram of road slope angle
  • Fig. 7 is a kind of road water accumulation scene diagram
  • Figure 8 is a schematic diagram of the calculation of the maximum ponding depth of a ponding area
  • FIG. 9 is a flowchart of another method for determining the depth of ponding water provided by the implementation of this application.
  • FIG. 10 is a schematic diagram of the principle of determining the water surface position corresponding to the maximum water depth of the ponding area provided for the implementation of the application;
  • Figure 11 is a schematic diagram of the calculation of the maximum ponding depth of another ponding area
  • FIG. 13 is a scene diagram of a height-limited road
  • Fig. 14 The principle diagram of calculation of the maximum water depth of another water accumulation area
  • 15 is a flowchart of another method for determining the depth of ponding water provided by the implementation of this application.
  • 16 is a flowchart of a vehicle control method provided by an embodiment of the application.
  • 17 is a flowchart of an information transmission method provided by an embodiment of the present application.
  • FIG. 18 is a schematic structural diagram of a device for determining the depth of ponding water provided by an embodiment of the present application.
  • FIG. 19 is a schematic structural diagram of a terminal control apparatus provided by an embodiment of the application.
  • FIG. 20 is a schematic structural diagram of a communication device according to an embodiment of the present application.
  • FIG. 21 is a schematic structural diagram of an apparatus for determining the depth of ponding water provided by an embodiment of the present application.
  • FIG. 2 is a diagram of an application scenario provided by an embodiment of the present application.
  • the terminal can collect the image information of the water accumulation area through the camera, obtain the road information of the water accumulation area, and then determine the water accumulation area based on the image information and the road information. Maximum water depth.
  • the terminal can realize the detection of the water depth without wading in the water.
  • the terminal may be a vehicle, a traffic device (eg, a traffic camera), a drone, a rail car, a bathymetry device, a handheld device (eg, a smart phone with bathymetry software installed) and other devices with cameras.
  • the following describes the solution for determining the depth of accumulated water provided by the embodiment of the present application by taking the terminal as a vehicle as an example.
  • FIG. 3 is a flowchart of a method for determining the depth of ponding water provided in the implementation of the present application. The method can be applied to the terminal shown in FIG. 2 , such as a vehicle.
  • a method for determining the depth of ponding includes at least steps S301-S305.
  • step S301 the image information of the flooded road collected by the camera is acquired.
  • the vehicle perceives the environment around the vehicle in real time through the sensor system, and if it perceives that there is a water accumulation area at the preset distance in front of the vehicle, the processor of the vehicle calls the water accumulation depth determination program stored in the memory, and starts to execute the accumulation water area.
  • the water depth determination program obtains the image information of the water-filled road ahead collected by the camera of the vehicle.
  • the preset distance may be set by a user or by a technician, and may also be related to the sensing distance of the sensor of the vehicle, which is not limited in this application.
  • the driver or passenger when the vehicle is in a non-autonomous driving mode, the driver or passenger observes that there is water standing in front of the vehicle, and can interact with the vehicle through the vehicle's interaction system to issue an instruction to the vehicle to measure the water depth of the road ahead , the processor of the vehicle executes a program for determining the depth of stagnant water according to the user's instruction, and acquires the image information of the stagnant road ahead collected by the camera of the vehicle.
  • step S302 based on the image information of the stagnant road, the spatial position information of the first edge in the stagnant water edge is determined.
  • the first edge is any one of the two edges of the water accumulation area in the extending direction of the water accumulation road.
  • the first edge is a water-retaining edge on the side close to the vehicle.
  • the processor of the vehicle recognizes the image area of the stagnant water area in the stagnant road image according to the image recognition technology, and then determines the edge of the image area of the stagnant area close to the vehicle side as the first edge.
  • the image area of the water accumulation area is determined by segmentation according to the semantic segmentation model in deep learning, and then the edge of the image area of the water accumulation area that is close to the vehicle side is determined as the first edge.
  • the distance between the vehicle and the first edge is calculated, and then the position information of the first edge is determined according to the position information of the vehicle and the distance between the vehicle and the first edge.
  • the position information of the vehicle can be determined by positioning a positioning system (such as GPS, Beidou, etc.), and the distance between the vehicle and the first edge can be determined by the landing point similarity triangle ranging method, the landing point coordinate transformation ranging method and the scale. It can be obtained by various methods such as ranging method.
  • a positioning system such as GPS, Beidou, etc.
  • the distance between the vehicle and the first edge can be determined by the landing point similarity triangle ranging method, the landing point coordinate transformation ranging method and the scale. It can be obtained by various methods such as ranging method.
  • the target distance Z is the distance between the vehicle and the first edge.
  • y is the distance between the projected point of the water edge in the image and the optical center of the image, in pixels, f is the focal length, in pixels, H is the height of the camera from the ground, in m, and Z is the distance between the water edge and the camera Distance, in m.
  • step S303 the road slope angle information of the location of the first edge is obtained.
  • the road slope angle can be obtained by measuring the IMU of the vehicle.
  • the IMU will be equipped with a three-axis gyroscope and three-direction accelerometer to measure the three-axis attitude angle and acceleration of the object.
  • the attitude angle of the vehicle can also determine the slope angle of the road where the vehicle is located.
  • the vehicle first determines the position of the vehicle through the positioning system, and then obtains the road slope angle of the road where the vehicle position is located through the high-precision map.
  • the slope angle information in the high-precision map can be explicitly stored in the high-precision map, and each road corresponds to a slope angle value, or the road can be calculated from the elevation information of the vertical dimension of the road and the road length in the high-precision map. Curvature, as shown in Figure 5, the elevation information of the two ends of the road is H1 and H2, and the road length information is L, then the road slope angle value is arcsin((H2-H1)/L).
  • the curvature of the road can be obtained by derivation of the shape information of the vertical dimension of the road.
  • the present application does not limit the way of acquiring road slope angle information.
  • step S304 the road position information corresponding to the maximum water depth of the water accumulation area is determined.
  • the position of the road slope aspect change can be determined by acquiring the slope aspect information of the road with water accumulation, and the position is the road position corresponding to the maximum water depth of the water accumulation area. That is to say, the slope bottom of the flooded road is determined by the change of the slope aspect of the flooded road, and the bottom of the slope is the road position corresponding to the maximum water depth.
  • the slope aspect of the road may be obtained from a high-precision map, and the obtaining method is similar to the obtaining method of the road slope angle, which is not repeated here for brevity.
  • the stagnant road often appears under the bridge, and the intersection of the stagnant road and the road above the stagnant road (ie, the first road) is often the position where the stagnant water is deepest. Therefore, the location information of the stagnant road and the location information of the first road can be obtained through the high-precision map, and then the position of the center line of the first road can be determined.
  • the orthographic projection of the line on the stagnant road is the road position corresponding to the maximum water depth.
  • the intersection of the first road centerline and the stagnant road represents the position where the abscissa and ordinate in the position coordinates of the first road centerline are the same as the abscissas in the position coordinates of the stagnant road.
  • the position coordinates corresponding to the abscissa and ordinate coordinates in the position coordinates of the stagnant road and the abscissa and ordinate coordinates in the position coordinates of the first road center line are taken as the road position corresponding to the maximum water depth.
  • step S305 the maximum water accumulation depth of the water accumulation area is determined based on the spatial position information of the first edge, the road slope angle information, and the road position information corresponding to the maximum water depth.
  • the image information of the stagnant road collected by the camera that is relatively easy to obtain and the road information obtained from the high-precision map or the sensor system are used to realize the depth of the stagnant road ahead. It can avoid the risk of breaking down caused by the vehicle wading too deep.
  • the embodiments of the present application further provide another method for determining the depth of ponding water.
  • FIG. 9 provides another method for determining the depth of ponding water provided by the embodiment of the present application.
  • the method can be applied to the terminal shown in FIG. 2 , such as a vehicle.
  • the method includes at least steps S901-S905.
  • steps S901-S903 is similar to the implementation of steps S301-S303 in FIG. 3 , and reference may be made to the above description, which is not repeated here for brevity.
  • step S904 the water surface position information corresponding to the maximum water depth of the water accumulation area is determined.
  • a common stagnant road scene is a tunnel bridge scene, and the stagnant road image includes a bridge hole area image and a road area image.
  • the front bridge hole boundary can be detected by the target detection model in deep learning according to the image of the waterlogged road collected by the camera, and the intersection line between the bridge hole detection frame and the waterlogged area can be determined. Then, the coordinates of the intersection line in the vehicle coordinate system are determined by the camera landing point ranging algorithm or other algorithms, and the coordinates are the water surface position coordinates corresponding to the maximum water depth of the water accumulation area.
  • the sensor system of the vehicle is used to perceive the distance between the bridge opening and the vehicle.
  • radar or lidar measures the distance between the bridge opening and the vehicle in front. Combined with the position of the edge of the water accumulation, the maximum water depth of the water accumulation area can be obtained. The coordinates of the water surface position.
  • the road position corresponding to the maximum water depth in the stagnant area is represented by two-dimensional coordinates, and the road position corresponding to the maximum water depth in the stagnant area is the water surface position corresponding to the maximum water depth in the stagnant area.
  • the method for determining the position of the road corresponding to the maximum water depth of the water accumulation area is referred to above, and will not be repeated here.
  • the above two-dimensional coordinates only include two-dimensional coordinates (x, y) representing the plane position of the road (eg, longitude and latitude determine the geographic location), but not the coordinate z representing the height of the road.
  • step S905 the maximum water depth of the water accumulation area is determined based on the spatial position information of the first edge, the road slope angle information, and the water surface position information corresponding to the maximum water depth of the water accumulation area.
  • the embodiment of the present application provides a solution for determining the depth of water accumulation in tunnel bridge water accumulation scenarios. Without a high-precision map, the water surface position corresponding to the maximum water depth in the water accumulation area can be determined by means of image analysis, without relying on high-precision maps. Map, in the absence of high-precision maps, the implementation of the solution is still guaranteed.
  • the embodiments of the present application further provide another method for determining the depth of ponding water.
  • FIG. 12 provides another method for determining the depth of ponding water provided by the embodiment of the present application. This method is suitable for scenarios with limited height, and this method can be applied to the terminal shown in Figure 2, such as a vehicle.
  • the method includes at least steps S1201-S1206.
  • steps S1201-S1203 is similar to the implementation of steps S301-S303 in FIG. 3 , and reference may be made to the above description, which is not repeated here for brevity.
  • step S1204 the height limit value of the height limit device is obtained.
  • the height limit device is generally marked with a limit height value by means of camera recognition. Therefore, the height limit value h3 of the height limit device can be obtained by directly identifying the height limit value by the camera of the vehicle. The value is the height of the height-limiting device from the lowest point of the road, or the height-limiting value of the height-limiting device can be directly obtained through the high-precision map. This application does not limit the method by which the height limit value is obtained.
  • the first height difference h1 is determined based on the height limit value and the current position information of the vehicle.
  • the first height difference h1h represents the difference between the current position of the vehicle and the height of the height-limiting device.
  • the first height difference h1 may be sensed by a sensor system of the vehicle.
  • the height h1 of the height limit relative to the horizontal plane where the vehicle is located is determined according to millimeter-wave radar or lidar.
  • the rotation matrix is obtained according to the road slope angle, and the height of the height limit relative to the horizontal plane where the vehicle is located, that is, the first height difference h1, can be obtained according to the coordinates and rotation matrix of the height limit in the radar coordinate system.
  • step S1206 based on the current position of the vehicle, the spatial position of the first edge, the road slope angle, the height limit value and the first height difference, the maximum ponding depth of the ponding area is determined.
  • the embodiment of the present application provides a solution for determining the depth of ponding water in a height-limited scenario, by obtaining the height-limited value obtained from the vehicle sensor, the height difference between the vehicle and the highest point of the height-limiting device, and the spatial position of the ponding water edge, road slope
  • the maximum water depth of the water accumulation area can be determined by the angle, and it is not strongly dependent on the high-precision map.
  • the embodiments of the present application further provide another method for determining the depth of ponding water.
  • FIG. 15 is another method for determining the depth of ponding water provided by the embodiment of the present application. This method is suitable for scenarios where road elevation information is provided in high-precision maps, and this method can be applied to the terminal shown in Figure 2, such as a vehicle.
  • the method includes at least steps S1501-S1504.
  • steps S1501-S1502 is similar to the implementation of steps S301-S302 in FIG. 3 , and reference may be made to the above description, which is not repeated here for brevity.
  • step S1503 based on the spatial position information of the stagnant water edge, the elevation information of the stagnant water edge is determined.
  • the water accumulation edge is any one of the two edges of the water accumulation area in the extending direction of the water accumulation road.
  • the water accumulation edge is the water accumulation edge on the side close to the vehicle.
  • the elevation information of the pond edge can be obtained through a high-precision map. For example, if the elevation information corresponding to each location is explicitly marked in the high-precision map, the corresponding elevation information in the high-precision map can be directly determined according to the location information, that is, the elevation information of the edge of the stagnant water.
  • step S1504 the elevation information of the road corresponding to the maximum water depth of the water accumulation area is acquired.
  • the vehicle locates the current position of the vehicle through the positioning system, and then searches the high-precision map for the elevation information of the road segment according to the segment of the road corresponding to the location, and finds the minimum elevation in the elevation information (that is, the minimum elevation in the elevation information).
  • the elevation at the lowest point of the road), and the minimum elevation is determined as the elevation of the road corresponding to the maximum water depth of the water accumulation area.
  • step S1505 the maximum water accumulation depth of the water accumulation area is determined based on the elevation information of the water accumulation edge and the elevation information of the road corresponding to the maximum water depth of the water accumulation area.
  • the maximum water accumulation depth of the water accumulation area can be determined.
  • the maximum water depth of the water accumulation area can be determined based on the difference between the elevations of the two elevations by obtaining the elevation of the water accumulation edge and the elevation of the road corresponding to the maximum water depth of the water accumulation area. It greatly simplifies the algorithm, reduces the computing power requirements for the terminal, and improves the efficiency of water depth determination.
  • the method for determining the depth of ponding water provided in Figure 9 is suitable for the tunnel bridge scene, and this solution is only enabled when the vehicle travels to the tunnel bridge scene.
  • the method for determining the ponding water depth provided in Figure 12 is suitable for height-limited roads. This solution is only enabled when the vehicle travels to a road with a height limit.
  • the method for determining the water depth provided in Figure 15 is applicable to the scene when the high-precision map has road elevation information, that is, only when the vehicle can obtain the road elevation information. Enable this scheme. Therefore, the step of judging the road scene can be added before the method of FIG. 3 or FIG. 9 or FIG. 12 or FIG. 15 .
  • the solution in FIG. 9 is executed.
  • the solution in FIG. 12 is implemented, and when the high-precision map corresponding to the road section ahead of the vehicle has road elevation information, the solution in FIG. 15 is implemented.
  • the road scene ahead can be sensed through the sensor system of the vehicle to determine what kind of scene the road ahead is, and the method for determining the water depth corresponding to the scene can be automatically activated according to the corresponding scene.
  • the corresponding method can also be activated according to the instruction issued by the user by receiving an instruction from the user. For example, if a driver or a passenger in the vehicle observes that the road ahead is an underpass, the solution shown in FIG. 9 can be activated by instructing the vehicle to detect the maximum water depth of the water accumulation area on the road ahead.
  • S303 may be executed before step S301, that is, firstly obtain road slope angle information, and then obtain image information of the road with stagnant water.
  • the embodiments of the present application also provide a method for controlling a terminal, and the terminal is used as an example for a vehicle to be described.
  • FIG. 16 is a flowchart of a vehicle control method provided by an embodiment of the application. As shown in FIG. 16, the method includes steps S1601-S1602.
  • step S1601 the maximum ponding depth of the ponding area at a preset distance from the vehicle is detected and determined.
  • the preset distance may be set for a user or a technician, and may also be related to the sensing distance of the sensor of the vehicle, which is not limited in this application.
  • the detection and determination of the maximum ponding depth of the ponding area may be determined by any of the methods described above in FIGS. 3-15 , or may be determined by other methods, which are not limited in this application.
  • step S1602 the vehicle is controlled according to the maximum water accumulation depth of the water accumulation area.
  • a warning message is issued to warn the driver that the water depth in front of the vehicle exceeds the maximum water depth of the vehicle, or directly control the vehicle to stop, Either exit self-driving mode and notify the driver to take over, or reroute the drive to bypass the flooded area.
  • a warning message is issued and the vehicle is controlled to stop, or a warning message is issued and the automatic driving mode is exited, or a warning message is issued and the driving route is re-planned, or the vehicle is controlled.
  • Stop and exit autopilot mode or control the vehicle to stop and reroute, or exit autopilot mode and reroute.
  • a warning message is issued and the vehicle is controlled to stop and exit the automatic driving mode, or a warning message is issued and the vehicle is controlled to stop and re-plan the driving route, or, the automatic driving is exited. mode and control the vehicle to stop and re-route.
  • a warning message is issued and the vehicle is controlled to stop and exit the automatic driving mode and re-plan the driving route.
  • both the warning information and the prompt information can be used for warning or prompting by means of video, audio or a combination of video and audio.
  • the embodiment of the present application also provides an information transmission method, and the method can be applied to a terminal with a camera function, and the terminal is taken as an example of a vehicle for illustration.
  • FIG. 17 is a flowchart of an information transmission method provided by an embodiment of the present application. As shown in Figure 17, the method includes steps S1701-S1702.
  • step S1701 the location information of the water accumulation area and/or the maximum water accumulation depth of the water accumulation area at a preset distance from the vehicle is detected and determined.
  • the preset distance may be set for a user or a technician, and may also be related to the sensing distance of the sensor of the vehicle, which is not limited in this application.
  • the detection and determination of the maximum ponding depth of the ponding area may be determined by any of the methods described above in FIGS. 3-15 , or may be determined by other methods, which are not limited in this application.
  • the method for obtaining the position information of the stagnant water area is similar to the method for determining the spatial position of the first edge, and reference may be made to the above description. For brevity, details are not repeated here.
  • step S1702 the location information of the ponding area detected by the vehicle and/or the maximum ponding depth of the ponding area is sent to other vehicles and/or uploaded to the cloud server.
  • the location information of the ponding area detected by the vehicle and/or the maximum ponding depth of the ponding area are sent to other vehicles through the Internet of Vehicles, so that other vehicles can know the condition of the road section and plan the route in advance.
  • the location information of the ponding area and/or the maximum ponding depth of the ponding area detected by the vehicle are uploaded to a cloud server, for example, a cloud server that stores dynamic messages of high-precision maps.
  • the embodiments of the present application also provide a device for determining the depth of water accumulation.
  • FIG. 18 is a schematic structural diagram of an apparatus for determining the depth of ponding water provided by an embodiment of the present application.
  • the apparatus 1800 has a camera. As shown in FIG. 18 , the apparatus 1800 includes at least:
  • an acquisition module 1801, configured to acquire image information and road slope angle information of the water-filled road collected by the camera, where the road slope angle information includes the road slope angle at the location of the first edge;
  • a determination module 1802 configured to determine the spatial position information of a first edge in the stagnant water edge based on the image information of the stagnant road; wherein, the first edge is the extension direction of the stagnant area in the stagnant road either of the two edges on the
  • the determining module 1802 is specifically configured to:
  • a first distance is determined, where the first distance represents the spatial position of the first edge to the road corresponding to the maximum water depth.
  • the distance of the position based on the product of the first distance and the sine value of the road slope angle, determine the maximum water accumulation depth of the water accumulation area.
  • the obtaining module 1801 is further configured to obtain the slope aspect information of the stagnant road, where the slope aspect information includes the position where the slope aspect of the stagnant road changes;
  • the determining module 1802 is specifically configured to: determine the road location information corresponding to the maximum water depth of the water accumulation area based on the position where the slope aspect of the water accumulation road changes.
  • the determining module 1802 is specifically configured to: based on the orthographic projection of the center line of the first road on the stagnant road, to determine the road location information corresponding to the maximum water depth of the stagnant area.
  • the determining module 1802 is specifically configured to:
  • a second distance is determined based on the spatial position information of the first edge and the water surface position information corresponding to the maximum water depth, where the second distance represents the spatial position of the first edge to the water surface corresponding to the maximum water depth the distance of the location;
  • the maximum ponding depth of the ponding area is determined.
  • the stagnant road is a tunnel bridge
  • the image information of the stagnant road includes a bridge hole area image and a road area image
  • the determining module 1802 is specifically configured to: determine the bridge hole area image and the road area image based on the image information of the stagnant road;
  • the water surface position information corresponding to the maximum water depth of the water accumulation area is determined.
  • the determining module 1802 is specifically configured to: determine the road position coordinates corresponding to the maximum water depth of the water accumulation area, and the road position coordinates are two-dimensional coordinates;
  • the water surface position information corresponding to the maximum water depth of the water accumulation area is determined.
  • the obtaining module 1801 is further configured to obtain the height limit value of the height limit device
  • the determining module 1802 is configured to determine a first height difference based on the height limit value and the current location information of the terminal, where the first height difference represents the difference between the current location of the terminal and the height of the height limiting device. difference;
  • the maximum water accumulation depth of the water accumulation area is determined.
  • the determining module 1802 is specifically configured to:
  • the third distance represents the distance from the current location of the terminal to the spatial location of the first edge
  • a second height difference is determined based on the product of the third distance and the sine of the road slope angle and the first height difference, where the second height difference represents the difference between the height limiting device and the water accumulation area the height difference of the water surface;
  • the maximum ponding depth of the ponding area is determined.
  • the apparatus 1800 for determining the ponding depth according to the embodiment of the present application may correspond to executing the method described in the embodiment of the present application, and the above and other operations and/or functions of the various modules in the apparatus 1800 for determining the ponding water depth are for the purpose of realizing FIG. 3 , respectively.
  • the corresponding processes of each method in -15 are not repeated here for brevity.
  • the present application also provides a terminal control device.
  • FIG. 19 is a schematic structural diagram of a terminal control apparatus provided by an embodiment of the present application.
  • the apparatus 1900 has a camera. As shown in FIG. 19 , the apparatus 1900 at least includes:
  • the detection module 1901 is configured to detect and determine the maximum ponding depth of the ponding area at a preset distance from the vehicle.
  • the control module 1902 is configured to control the vehicle according to the maximum water accumulation depth of the water accumulation area.
  • the apparatus 1900 for determining the ponding depth may correspond to executing the method described in the embodiment of the present application, and the above-mentioned and other operations and/or functions of the various modules in the apparatus 1900 for determining the ponding water depth are in order to realize FIG. 16 , respectively.
  • the corresponding processes of each method in the above will not be repeated here.
  • the present application also provides a communication device.
  • FIG. 20 is a schematic structural diagram of a communication apparatus according to an embodiment of the present application. As shown in Figure 20, the device 2000 at least includes:
  • the water accumulation detection module 2001 is configured to detect and determine the location information of the water accumulation area and/or the maximum accumulation water depth of the water accumulation area at a preset distance from the vehicle.
  • the communication module 2002 sends the location information of the stagnant area detected by the vehicle and/or the maximum stagnant depth of the stagnant area to other vehicles and/or uploads it to the cloud server.
  • the communication device 2000 may correspond to executing the methods described in the embodiments of the present application, and the above-mentioned and other operations and/or functions of the various modules in the communication device 2000 are to implement the corresponding methods of the respective methods in FIG. 17 , respectively.
  • the process, for the sake of brevity, will not be repeated here.
  • connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines.
  • the present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed in a computer, the computer is made to execute any one of the above methods.
  • the present application also provides a computer program or computer program product, the computer program or computer program product including instructions, when the instructions are executed, make a computer perform any one of the above methods.
  • the present application further provides a chip system, including a processor and a memory, wherein the memory stores program instructions, and when the program instructions stored in the memory are called and executed by the processor, any one of the above methods is implemented.
  • FIG. 21 is a schematic structural diagram of an apparatus for determining the depth of ponding water provided by an embodiment of the present application.
  • the apparatus 2100 for determining the depth of stagnant water includes a processor 2101 , a memory 2102 and a communication interface 2103 .
  • the processor 2101 and the communication interface 2103 of the memory 2102 are communicatively connected, and the communication can also be realized by other means such as wireless transmission.
  • the communication interface 2103 is used to communicate with other communication devices, such as obtaining road information, including road slope angle, road slope aspect, road elevation, etc., and, for example, sending information to other vehicles or sending information to a cloud server, etc.; the memory 2102 Executable program codes are stored, and the processor 2101 can call the program codes stored in the memory 2102 to execute the method for determining the water depth and/or the terminal control method and/or the information transmission method in the foregoing method embodiments.
  • the processor 2101 may be a central processing unit (CPU), and the processor 2101 may also be other general-purpose processors, digital signal processors (digital signal processors, DSP), application-specific integrated circuits (application-specific integrated circuits). specific integrated circuit, ASIC), field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general purpose processor may be a microprocessor or any conventional processor or the like.
  • the memory 2102 may include read only memory and random access memory, and provides instructions and data to the processor 2101 .
  • Memory 2102 may also include non-volatile random access memory.
  • memory 2102 may also store training data sets.
  • the memory 2102 may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
  • the non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (erasable PROM, EPROM), electrically programmable Erase programmable read-only memory (electrically EPROM, EEPROM) or flash memory.
  • Volatile memory may be random access memory (RAM), which acts as an external cache.
  • RAM static random access memory
  • DRAM dynamic random access memory
  • SDRAM synchronous dynamic random access memory
  • Double data rate synchronous dynamic random access memory double data date SDRAM, DDR SDRAM
  • enhanced synchronous dynamic random access memory enhanced SDRAM, ESDRAM
  • synchronous link dynamic random access memory direct rambus RAM, DR RAM
  • the device 2100 for determining the depth of water according to the embodiment of the present application may correspond to the device for determining the depth of water in the embodiment of the present application, and may correspond to performing the method according to the method shown in FIGS. 3-15 in the embodiment of the present application.
  • the above-mentioned and other operations and/or functions of each device in the apparatus 2100 for determining the depth of accumulation of water are corresponding to the main body, respectively, in order to realize the corresponding flow of each method in FIGS. 3-15, and are not repeated here for brevity.
  • non-transitory English: non-transitory
  • the storage medium is non-transitory ( English: non-transitory) media, such as random access memory, read only memory, flash memory, hard disk, solid state disk, magnetic tape (English: magnetic tape), floppy disk (English: floppy disk), optical disc (English: optical disc) and any combination thereof.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • General Physics & Mathematics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Multimedia (AREA)
  • Traffic Control Systems (AREA)
  • Navigation (AREA)

Abstract

本申请实施例提供了一种积水深度确定方法,该方法包括:在积水区域的预设距离,获取积水道路的图像信息,然后对该图像信息进行分析处理得到积水边缘的空间位置,再获取道路坡角和通过一定策略判断确定积水区域的最大水深处对应的道路位置,最后根据积水边缘的空间位置、道路坡角、最大水深处对应的道路位置,确定积水区域的最大积水深度。实现终端无需涉水,对积水区域的积水深度进行测量,避免了终端涉水带来的风险。该方法可用于辅助驾驶和自动驾驶。进一步,该方法提升了终端在自动驾驶或者辅助驾驶中的高级驾驶辅助系统ADAS能力,可应用于车联网,如车辆外联V2X、车间通信长期演进技术LTE-V、车辆-车辆V2V等。

Description

一种积水深度确定方法及装置 技术领域
本申请涉及智能驾驶领域,尤其涉及积水深度确定方法及装置。
背景技术
随着社会的发展,现代生活中越来越多的机器向自动化、智能化发展,移动出行用的汽车也不例外,智能汽车正在逐步进入人们的日常生活中。近些年,高级驾驶辅助系统(Advanced Driving Assistant System,ADAS)在智能汽车中发挥着十分重要的作用,它是利用安装在车上的各式各样传感器,在汽车行驶过程中随时来感应周围的环境,收集数据,进行静止、移动物体的辨识、侦测与追踪,并结合导航仪地图数据,进行系统的运算与分析,从而预先让驾驶者察觉到可能发生的危险,有效增加汽车驾驶的舒适性和安全性。
驾驶辅助或无人驾驶需要借助车辆本身的传感器对周围环境做感知,传感器的输出结果直接决定了车辆驾驶策略的制定,所以传感器的输出结果是否能精确刻画真实环境显得尤为重要。在车辆行驶过程中,不可避免的会遇到低洼路段例如,城区道路中道路桥下的路段,下雨后这些地方容易出现积水,人类驾驶员在错误估计积水深度涉水后极易引发车辆抛锚。因此,如何确定积水深度对于自动驾驶汽车来说同样是个十分重要的问题。
一种确定积水深度的方法如图1所示,是在车辆进入积水区域后,利用摄像头对车辆侧面拍摄的图片,检测积水水面没过车辆轮胎的位置,再通过已知的车辆轮胎尺寸,通过比例关系判断积水水深。现有技术是在车辆涉水后对积水深度的检测,很难保证在车辆行驶前方不会遇到深水区域,使得车辆容易在不知情的条件下驶入深水区域,从而引发车辆抛锚。
发明内容
本申请实施例提供了一种积水深度确定方法及装置,解决了车辆在进入积水区域之前,实现对前方道路积水深度的测量的问题。
第一方面,本申请实施例提供了一种积水深度确定方法,包括:获取积水道路的图像信息;基于所述积水道路的图像信息,确定积水边缘中第一边缘的空间位置信息;其中,所述第一边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘;获取道路坡角信息,所述道路坡角信息包括所述第一边缘所在位置的道路坡角;确定所述积水区域的最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息;基于所述第一边缘的空间位置信息、道路坡角信息、所述最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息,确定所述积水区域的最大积水深度。
本申请实施例通过获取积水道路的图像信息,然后对该图像信息进行分析处理得到积水边缘的空间位置,再获取道路坡角和通过一定策略判断确定积水区域的最大水深处对应的道路位置/所述积水区域的最大水深处对应的水面位置,最后根据积水边缘的 空间位置、道路坡角、最大水深处对应的道路位置/积水区域的最大水深处对应的水面位置,确定积水区域的最大积水深度。实现车辆在进入积水区域之前,对前方道路积水深度的测量,避免了车辆涉水过深带来的抛锚风险。
在一个可能的实现中,所述基于所述第一边缘的空间位置信息、所述道路坡角信息和所述最大水深处对应的道路位置信息,确定所述积水区域的最大积水深度,包括:基于所述第一边缘的空间位置信息和所述最大水深处对应的道路位置信息,确定第一距离,所述第一距离表征所述第一边缘的空间位置至所述最大水深处对应的道路位置的距离;基于所述第一距离和所述道路坡角的正弦值的乘积,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述确定所述积水区域的最大水深处对应的道路位置信息,之前还包括:获取所述积水道路的坡向信息,所述坡向信息包括积水道路的坡向变化处的位置;所述确定所述积水区域的最大水深处对应的道路位置信息,包括:基于所述积水道路的坡向变化处的位置,确定所述积水区域的最大水深处对应的道路位置信息。
本申请实施例通过道路坡向的变化确定积水区域的最大水深处对应的道路位置,无需获取较为敏感的道路高程信息,增大了方案的适用范围。
在另一个可能的实现中,所述积水道路上方具有与其延伸方向不同的第一道路;所述确定所述积水区域的最大水深处对应的道路位置信息,包括:基于所述第一道路的中心线在所述积水道路上的正投影,确定所述积水区域的最大水深处对应的道路位置信息。
本申请实施例解决了在桥洞场景下,确定积水区域的最大水深处对应的道路位置的问题。
在另一个可能的实现中,所述基于所述第一边缘的空间位置信息、道路坡角信息、所述积水区域的最大水深处对应的水面位置信息,确定所述积水区域的最大积水深度,包括:基于所述第一边缘的空间位置信息和所述最大水深处对应的水面位置信息,确定第二距离,所述第二距离表征所述第一边缘的空间位置至所述最大水深处对应的水面位置的距离;基于所述第二距离和所述道路坡角的正切值的乘积,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述积水道路为地道桥,所述积水道路的图像信息包括桥洞区域图像和道路区域图像;所述确定所述积水区域的最大水深处对应的水面位置信息,包括:基于所述积水道路的图像信息确定桥洞区域图像和道路区域图像;基于所述桥洞区域图像和道路区域图像的交界位置,确定所述积水区域的最大水深处对应的水面位置信息。
本申请实施例提供了针对地道桥积水场景下的积水深度确定方案,无需高精地图,通过图像分析的方法即可确定积水区域的最大水深处对应的水面位置,不依赖于高精地图,在高精地图缺失的情况下依然保证方案的实现。
在另一个可能的实现中,所述确定所述积水区域的最大水深处对应的水面位置信息,包括:确定所述积水区域的最大水深处对应的道路位置坐标,所述道路位置坐标为二维坐标;基于所述道路位置坐标,确定所述积水区域的最大水深处对应的水面位置信息。
在另一个可能的实现中,所述方法还包括:当所述积水区域道路设置限高装置时;获取所述限高装置的限高值;基于所述限高值与所述终端当前所处位置信息,确定第一高差,所述第一高差表征所述终端当前所处位置和所述限高装置高度的差值;基于所述终端当前所处位置信息、所述第一边缘的空间位置信息、道路坡角信息、限高值和第一高差,确定所述积水区域的最大积水深度。
在另一个可能的实现中,基于所述终端当前所处位置信息、所述第一边缘的空间位置信息、道路坡角信息、限高值和第一高差,确定所述积水区域的最大积水深度,包括:基于所述终端当前所处位置信息和所述第一边缘的空间位置信息,确定第三距离,所述第三距离表征所述终端当前所处位置至所述第一边缘的空间位置的距离;基于所述第三距离和所述道路坡角的正弦值的乘积与所述第一高差,确定第二高差,所述第二高差表征所述限高装置与所述积水区域的水面的高差;基于所述限高值与所述第二高差的差值,确定所述积水区域的最大积水深度。
本申请实施例提供了针对限高场景下的积水深度确定方案,通过根据车辆传感器获取的限高值、车辆与限高装置最高点的高度差值、和积水边缘的空间位置、道路坡角即可确定积水区域的最大积水深度,不强依赖于高精地图。
第二方面,本申请实施例提供了另一种积水深度确定方法,包括:获取积水道路的图像信息;基于所述积水道路的图像信息,确定积水边缘中第一边缘的空间位置信息,根据所述第一边缘的空间位置信息确定第一边缘的高程信息;其中,所述第一边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘;确定所述积水区域的最大水深处对应的道路的高程信息;基于所述第一边缘的高程信息和所述积水区域的最大水深处对应的道路的高程信息,确定所述积水区域的最大积水深度。
本申请实施例通过获取的积水边缘的高程和积水区域的最大水深处对应的道路的高程,基于两个高程的高程差即可确定积水区域的最大积水深度。大大简化了算法,降低了对终端的算力要求,提高了积水水深确定的效率。
在一个可能的实现中,所述获取所述积水区域的最大水深处对应的道路的高程信息,包括:获取积水区域所在道路的地图信息,所述地图信息包括积水区域所在道路的高程信息;基于所述积水区域所在道路的高程信息中的最小高程值,确定所述积水区域的最大水深处对应的道路的高程信息。
本申请实施例,只需获取道路的高程值,然后进行比较即可确定积水区域的最大水深处对应的道路的高程,无需对道路其他信息的分析,算法简单高效。
第三方面,本申请实施例还提供了一种终端的控制方法,包括:终端在距离积水区域预设距离,检测确定所述积水区域的最大积水深度,根据所述积水区域的最大积水深度控制所述终端。
在一个可能的实现中,所述根据所述积水区域的最大积水深度控制所述终端,包括:若所述积水区域的最大积水深度大于或等于预设阈值,则发出警示信息和/或控制所述终端停止和/或退出自动驾驶模式和/或重新规划行驶路线。
可选的,所述终端为车辆。实现在车辆在进入积水区域之前,对前方道路积水深度的测量,避免了车辆涉水过深带来的抛锚风险。
在一个可能的实现中,所述检测确定所述积水区域的最大积水深度基于第一方面或第二方面的方法确定。
第四方面,本申请实施例还提供了一种信息传输方法,包括:终端在距离积水区域的预设距离,确定所述积水区域的位置和/或所述积水区域的最大积水深度,将所述积水区域的位置信息和/或所述积水区域的最大积水深度,发送给其他车辆和/或上传至高精地图的动态信息。
在一个可能的实现中,所述最大积水深度是基于第一方面或第二方面所述的方法确定。
第五方面,本申请实施例还提供了一种积水深度确定装置,包括:获取模块,用于获取积水道路的图像信息和道路坡角信息;其中,所述道路坡角信息包括所述第一边缘所在位置的道路坡角;确定模块,用于基于所述积水道路的图像信息,确定积水边缘中第一边缘的空间位置信息;其中,所述第一边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘;用于获取道路坡角信息,所述道路坡角信息包括所述第一边缘所在位置的道路坡角;第二确定模块,用于确定所述积水区域的最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息;用于基于所述第一边缘的空间位置信息、道路坡角信息、所述最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述确定模块具体用于:基于所述第一边缘的空间位置信息和所述最大水深处对应的道路位置信息,确定第一距离,所述第一距离表征所述第一边缘的空间位置至所述最大水深处对应的道路位置的距离;基于所述第一距离和所述道路坡角的正弦值的乘积,确定所述积水区域的最大积水深度。
在另一个可能的实现中,获取模块还用于,获取所述积水道路的坡向信息,所述坡向信息包括积水道路的坡向变化处的位置;所述确定模块具体用于:基于所述积水道路的坡向变化处的位置,确定所述积水区域的最大水深处对应的道路位置信息。
在另一个可能的实现中,所述积水道路上方具有与其延伸方向不同的第一道路;所述确定模块具体用于:基于所述第一道路的中心线在所述积水道路上的正投影,确定所述积水区域的最大水深处对应的道路位置信息。
在另一个可能的实现中,所述确定模块具体用于:基于所述第一边缘的空间位置信息和所述最大水深处对应的水面位置信息,确定第二距离,所述第二距离表征所述第一边缘的空间位置至所述最大水深处对应的水面位置的距离;基于所述第二距离和所述道路坡角的正切值的乘积,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述积水道路为地道桥,所述积水道路的图像信息包括桥洞区域图像和道路区域图像;所述确定模块具体用于:基于所述积水道路的图像信息确定桥洞区域图像和道路区域图像;基于所述桥洞区域图像和道路区域图像的交界位置,确定所述积水区域的最大水深处对应的水面位置信息。
在另一个可能的实现中,所述确定模块具体用于:确定所述积水区域的最大水深处对应的道路位置坐标,所述道路位置坐标为二维坐标;基于所述道路位置坐标,确定所述积水区域的最大水深处对应的水面位置信息。
在另一个可能的实现中,当所述积水区域道路设置限高装置时;第一获取模块还用于,用于获取所述限高装置的限高值;所述确定模块,还用于基于所述限高值与所述终端当前所处位置信息,确定第一高差,所述第一高差表征所述终端当前所处位置和所述限高装置高度的差值;基于所述终端当前所处位置信息、所述第一边缘的空间位置信息、道路坡角信息、限高值和第一高差,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述确定模块具体用于:基于所述终端当前所处位置信息和所述第一边缘的空间位置信息,确定第三距离,所述第三距离表征所述终端当前所处位置至所述第一边缘的空间位置的距离;基于所述第三距离和所述道路坡角的正弦值的乘积与 所述第一高差,确定第二高差,所述第二高差表征所述限高装置与所述积水区域的水面的高差;基于所述限高值与所述第二高差的差值,确定所述积水区域的最大积水深度。
第六方面,本申请实施例还提供了一种车辆,包括第五方面或第五方面任一种可能实现方式中所述的积水深度确定装置。
第七方面,本申请实施例还提供了一种芯片系统,包括处理器和存储器,所述存储器存储有程序指令,当所述存储器存储的程序指令被所述处理器调用执行时实现第一方面或第二方面或第三方面或第四方面所述的方法。
第八方面,本申请实施例还提供了一种计算机可读存储介质,其上存储有计算机程序,当所述计算机程序在计算机中执行时,令计算机执行第一方面或第二方面或第三方面或第四方面所述的方法。
本申请在上述各方面提供的实现方式的基础上,还可以进行进一步组合以提供更多实现方式。
附图说明
图1为现有技术中积水深度确定的应用场景图;
图2为本申请实施例提供的一种应用场景图;
图3为本申请实施提供的一种积水深度确定方法的流程图;
图4为落地点相似三角形测距法原理示意图;
图5为一种道路坡角的计算方法原理图;
图6为另一种道路坡角的计算方法原理图;
图7为一种道路积水场景图;
图8为一种积水区域的最大积水深度计算原理图;
图9为本申请实施提供的另一种积水深度确定方法的流程图;
图10为本申请实施提供的积水区域的最大水深处对应的水面位置确定原理示意图;
图11为另一种积水区域的最大积水深度计算原理图;
图12为本申请实施提供的另一种积水深度确定方法的流程图;
图13为一种限高道路场景图;
图14另一种积水区域的最大积水深度计算原理图;
图15为本申请实施提供的另一种积水深度确定方法的流程图;
图16为本申请实施例提供的一种车辆的控制方法的流程图;
图17为本申请实施例提供的一种信息传输方法的流程图;
图18为本申请实施例提供的一种积水深度确定装置的结构示意图;
图19为本申请实施例提供的一种终端控制装置的结构示意图;
图20为本申请实施例提供的一种通信装置的结构示意图;
图21为本申请实施例提供的一种积水深度确定设备的结构示意图。
具体实施方式
下面将结合本申请实施例中的附图,对本申请实施例中的技术方案进行描述。
图2为本申请实施例提供的一种应用场景图。如图2所示,在道路积水区域的预设距离,终端可通过摄像头采集积水区域的图像信息,获取该积水区域的道路信息,然后基于该图像信息和道路信息确定积水区域的最大积水水深。实现终端无需涉水即可实现对积水水深的检测。其中,终端可以是车辆、交通设备(例如交通摄像头)、无人机、轨道车、水深测量设备、手持设备(例如,安装有水深测量软件的智能手机)等具有摄像头的设备。
下面以终端为车辆为例进行说明本申请实施例提供的积水深度确定方案。
图3为本申请实施提供的一种积水深度确定方法的流程图。该方法可以应用于图2所示的终端,例如车辆。
如图3所示,本申请实施例提供的一种积水深度确定方法至少包括步骤S301-S305。
在步骤S301中,获取摄像头采集的积水道路的图像信息。
在本实施例中,车辆通过传感器系统实时感知车辆周围的环境,若感知到车辆前方预设距离具有积水区域,则车辆的处理器调取存储器中存储的积水深度确定程序,开始执行积水深度确定程序,获取车辆的摄像头采集的前方积水道路图像信息。其中,预设距离可以为用户设置,也可以为技术人员设置,还可以与本车传感器感应距离有关,本申请不做限定。
在另一个示例中,车辆在非自动驾驶模式下,驾驶员或乘客观察到行驶前方具有积水,则可通过车辆的交互系统与车辆进行交互,向车辆下达测量前方道路的积水深度的指令,车辆的处理器根据用户指令执行积水深度确定程序,获取车辆的摄像头采集的前方积水道路图像信息。
在步骤S302中,基于积水道路的图像信息,确定积水边缘中第一边缘的空间位置信息。其中,第一边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘。例如第一边缘为靠近车辆一侧的积水边缘。
在本实施例中,车辆的处理器根据图像识别技术识别出积水道路图像中的积水区域的图像区域,进而将积水区域的图像区域中靠近车辆一侧的边缘确定为第一边缘。例如,根据深度学习中的语义分割模型分割确定积水区域的图像区域,再将积水区域的图像区域中靠近车辆一侧的边缘确定为第一边缘。
然后,计算车辆距离第一边缘的距离,再根据车辆的位置信息和车辆与第一边缘的距离确定第一边缘的位置信息。
示例性的,车辆的位置信息可以通过定位系统(例如GPS、北斗等定位系统)定位确定,车辆和第一边缘的距离可以通过落地点相似三角形测距法、落地点坐标变换测距法和比例测距法等多种方法测量获得。以落地点相似三角形测距法举例说明,如图4所示,摄像头位于P点,摄像头光轴方向与路面平行,I为摄像头的成像平面。那么根据三角形相似关系可得关系:y/f=H/Z。进而可得到目标距离Z=fH/y。目标距离Z即为车辆与第一边缘的距离。
其中y为积水边缘在图像中的投影点距离图像光心的距离,单位为pixel,f为焦距,单位为pixel,H为摄像头离地高度,单位为m,Z为积水边缘距离摄像头的距离,单位为m。
回到图3,在步骤S303中,获取第一边缘所在位置的道路坡角信息。
获取道路坡角的方法有多种方式,例如,通过车辆的IMU测量获得,IMU内会装有三轴的陀螺仪和三个方向的加速度计,用于测量物体三轴姿态角以及加速度,根据物体的姿态角也就能确定出车辆所在位置的道路的坡角等信息。
再例如,通过高精地图获取。例如,车辆首先通过定位系统定位确定车辆的位置,在通过高精地图获取车辆位置所在道路的道路坡角。高精地图中的坡角信息可以是显式存贮于高精地图中,每一段道路均对应一坡角值,或者可以通过高精地图中道路的垂直维度的高程信息和道路长度计算得到道路曲率,如图5所示,道路两端点的高程信息为H1和H2,道路长度信息为L,则道路坡角值为arcsin((H2-H1)/L)。
或者,可通过对道路垂直维度的形状信息求导得到道路的曲率,如图6所示,道路的形状通过多项式表达,如F (x)=ax 3+bx 2+cx+d,其中F为道路高程信息,x为道路方向的位置信息,a,b,c,d为多项式系数,代表曲线的形状,则道路上每一点的坡角值为3ax 2+2bx+c。本申请对道路坡角信息的获取方式不做限定。
在步骤S304中,确定积水区域的最大水深处对应的道路位置信息。
在一个示例中,可通过获取积水道路的坡向信息,确定道路坡向变化处的位置,该位置即为积水区域的最大水深处对应的道路位置。也就是说,通过积水道路的坡向变化确定积水道路的坡底处,坡底处就是最大水深处对应的道路位置。
示例性的,道路的坡向可从高精地图中获取,获取方法与道路坡角的获取方法类似,为了简洁,这里不再赘述。
在另一个示例中,如图7所示,积水道路往往出现在桥下,积水道路和积水道路之上的道路(即第一道路)的交叉位置往往为积水最深的位置。因此,可通过高精地图获取积水道路的位置信息和第一道路的位置信息,再确定第一道路的中心线的位置,第一道路中心线与积水道路相交位置(即第一道路中心线在积水道路上的正投影),即为最大水深对应的道路位置。其中,第一道路中心线与积水道路相交位置表征,第一道路中心线的位置坐标中的横纵坐标与积水道路的位置坐标中的横纵坐标相同的位置。将积水道路的位置坐标中的横纵坐标与第一道路中心线的位置坐标中的横纵坐标相同的横纵坐标对应的位置坐标作为最大水深对应的道路位置。
继续参见图3,在步骤S305中,基于第一边缘的空间位置信息、道路坡角信息、最大水深处对应的道路位置信息,确定积水区域的最大积水深度。
如图8所示,根据第一边缘的空间位置和最大水深处对应的道路位置,容易计算得到第一边缘至最大水深处的距离s,而步骤S303中已得到道路坡角为α,则根据三角函数关系得到最大积水深度h=s×sinα。
如此,本申请实施例在车辆无需涉水的情况下,利用较为容易获取的摄像头采集的积水道路图像信息和从高精地图获取或传感器系统感知获取的道路信息,实现对前方道路积水深度的测量,避免了车辆涉水过深带来的抛锚风险。
本申请实施例还提供另一种积水深度确定方法。
图9为本申请实施例提供的另一种积水深度确定方法。该方法可以应用于图2所示的终端,例如车辆。
如图9所示,该方法至少包括步骤S901-S905。
在本实施例中,步骤S901-S903的实现与图3中的步骤S301-S303的实现类似, 可参考上文描述,为了简洁,这里不再赘述。
在步骤S904中,确定积水区域的最大水深处对应的水面位置信息。
参见图7,常见的积水道路场景为地道桥场景,积水道路图像包括桥洞区域图像和道路区域图像。
在一个示例中,如图10所示,可以根据摄像头采集的积水道路的图像,通过深度学习中的目标检测模型检测前方桥洞边界,确定桥洞检测框与积水区域的交汇线。然后通过摄像头落地点测距算法或其他算法确定上述交汇线在车辆坐标系下的坐标,该坐标即为积水区域的最大水深处对应的水面位置坐标。
在另一个示例中,利用车辆的传感器系统感知桥洞距离车辆的距离,例如雷达或激光雷达测量前方桥洞距离本车的距离,再结合积水边缘位置即可以得到积水区域的最大水深处对应的水面位置坐标。
在另一示例中,积水区域的最大水深处对应的道路位置为二维坐标表示,则积水区域的最大水深处对应的道路位置为积水区域的最大水深处对应的水面位置。积水区域的最大水深处对应的道路位置的确定方法参见上文,此处不再赘述。
容易理解的,上文的二维坐标仅包括表示道路的平面位置的二维坐标(x,y)(例如,经度和维度确定地理位置),而没有表示道路的高度的坐标z。
在步骤S905中,基于第一边缘的空间位置信息、道路坡角信息、积水区域的最大水深处对应的水面位置信息,确定积水区域的最大积水深度。
如图11所示,根据第一边缘的空间位置和最大水深处对应的水面位置,容易计算得到第一边缘至最大水深处的距离l,而步骤S903中已得到道路坡角为α,则根据三角函数关系得到最大积水深度h=l×tanα。
本申请实施例提供了针对地道桥积水场景下的积水深度确定方案,无需高精地图,通过图像分析的方法即可确定积水区域的最大水深处对应的水面位置,不依赖于高精地图,在高精地图缺失的情况下依然保证方案的实现。
本申请实施例还提供另一种积水深度确定方法。
图12为本申请实施例提供的另一种积水深度确定方法。该方法适用于具有限高的场景,该方法可以应用于图2所示的终端,例如车辆。
如图12所示,该方法至少包括步骤S1201-S1206。
在本实施例中,步骤S1201-S1203的实现与图3中的步骤S301-S303的实现类似,可参考上文描述,为了简洁,这里不再赘述。
在步骤S1204中,获取限高装置的限高值。
本实施例中,获取限高装置的限高值的方式有多种。例如,如图13所示,通过摄像头识别的方式,一般限高装置都会标有限高值,因此可通过车辆的摄像头直接识别限高值的方式获取限高装置的限高值h3,该限高值为限高装置距离道路最低点的高度,或者,可通过高精地图直接获取该限高装置的限高值。对通过何种方式获取限高值,本申请不做限定。
在步骤S1205中,基于限高值与车辆当前位置信息,确定第一高差h1。其中,第一高差h1h表征,车辆当前所处位置和限高装置高度的差值。
在一种示例中,可通过车辆的传感器系统感测得到第一高差h1。例如,根据毫米 波雷达或激光雷达确定限高处相对于车辆所在水平面的高度h1。具体的,根据道路坡角获得旋转矩阵,根据限高处在雷达坐标系下的坐标与旋转矩阵即可得到限高处相对于车辆所在水平面的高度,即第一高差h1。
在步骤S1206中,基于车辆当前所处位置、第一边缘的空间位置、道路坡角、限高值和第一高差,确定积水区域的最大积水深度。
如图14所示,根据第一边缘的空间位置和车辆当前所处位置,容易计算得到第一边缘至车辆的距离,即第三距离s1,限高处距离水面高度h2=h1+s1×sinα,则根据数学关系得到最大积水深度h=h3-h2=h3-(h1+s1×sinα)。
本申请实施例提供了针对限高场景下的积水深度确定方案,通过根据车辆传感器获取的限高值、车辆与限高装置最高点的高度差值、和积水边缘的空间位置、道路坡角即可确定积水区域的最大积水深度,不强依赖于高精地图。
本申请实施例还提供另一种积水深度确定方法。
图15为本申请实施例提供的另一种积水深度确定方法。该方法适用于高精地图中提供道路高程信息的场景,该方法可以应用于图2所示的终端,例如车辆。
如图15所示,该方法至少包括步骤S1501-S1504。
在本实施例中,步骤S1501-S1502的实现与图3中的步骤S301-S302的实现类似,可参考上文描述,为了简洁,这里不再赘述。
在步骤S1503中,基于所述积水边缘的空间位置信息,确定积水边缘的高程信息。其中,积水边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘。例如积水边缘为靠近车辆一侧的积水边缘。
在一个示例中,可通过高精地图获取积水边缘的高程信息。例如,高精地图中显性标注了每个位置对应的高程信息,则可直接根据该位置信息确定高精地图中对应的高程信息,即为积水边缘的高程信息。
或者,在高精地图中,道路的形状通过多项式表达,如F (x)=ax 3+bx 2+cx+d,其中H为道路高程信息,x为道路方向的位置信息,a,b,c,d为多项式系数,代表曲线的形状(参见图6),则可将积水边缘的位置直接带入该多项式得到积水边缘所在位置对应的高程信息。
在步骤S1504中,获取积水区域的最大水深处对应的道路的高程信息。
在一个示例中,车辆通过定位系统定位车辆当前的位置,再根据该位置对应的一段道路,在高精地图中查找该段道路的高程信息,找出该高程信息中的最小高程(也就是说道路最低处的高程),将该最小高程确定为积水区域的最大水深处对应的道路的高程。
在步骤S1505中,基于积水边缘的高程信息和积水区域的最大水深处对应的道路的高程信息,确定积水区域的最大积水深度。
计算水边缘的高程和积水区域的最大水深处对应的道路的高程的差值,即可确定积水区域的最大积水深度。
本申请实施例通过获取的积水边缘的高程和积水区域的最大水深处对应的道路的高程,基于两个高程的高程差即可确定积水区域的最大积水深度。大大简化了算法,降低了对终端的算力要求,提高了积水水深确定的效率。
容易理解的是,图9所提供的积水深度确定方法适用于地道桥场景,仅当车辆行驶 至地道桥场景时才启用该方案,图12所提供的积水深度确定方法适用于限高道路场景,当车辆行驶至限高道路时才启用该方案,图15所提供的积水深度确定方法适用于高精地图中具有道路高程信息时的场景,即当车辆可获取道路的高程信息时才启用该方案。因此,可在之前图3或图9或图12或图15的方法之前,增加判断道路场景的步骤,当车辆行驶前方为地道桥场景时,则执行图9的方案,当车辆行驶前方为限高道路场景时,则执行图12的方案,当车辆行驶前方路段对应的高精地图具有道路高程信息时,则执行图15的方案。
例如,可通过车辆的传感器系统感知前方道路场景,判断前方道路为何种场景,根据对应场景自动启用该场景对应的积水深度确定方法。或者,也可通过接收用户指令,根据用户下达的指令启用对应的方法。例如,驾驶员或车上乘客观察到前方道路为地道桥,则可通过向车辆下达启用图9所示的方案,检测前方道路的积水区域的最大积水水深。
应理解的,上述各步骤的序号的大小并不意味着执行顺序的先后,各步骤的执行顺序应以其功能和内在逻辑确定,而不应对本申请实施例的实施过程构成任何限定,例如步骤S303可以在步骤S301之前执行,即先获取道路坡角信息,再获取积水道路的图像信息。
本申请实施例还提供一种终端的控制方法,以该终端为车辆举例说明。
图16为本申请实施例提供的一种车辆的控制方法的流程图。如图16所示,该方法包括步骤S1601-S1602。
在步骤S1601中,检测确定距离车辆预设距离的积水区域的最大积水深度。
其中,预设距离可以为为用户设置,也可以为技术人员设置,还可以与本车传感器感应距离有关,本申请不做限定。
在一个示例中,检测确定积水区域的最大积水深度可采用上述图3-15中描述的任一方法确定,或者也可采用其他方法确定,本申请不做限定。
在步骤S1602中,根据所述积水区域的最大积水深度控制所述车辆。
例如,当最大积水深度大于车辆的预设阈值时(该预设阈值可以为车辆最大涉水深度),则发出警示信息,以警示驾驶人员前方水深超过车辆最大水深,或者直接控制车辆停止,或者退出自动驾驶模式,通知驾驶员接管驾驶,或者重新规划行驶路线,以绕过该积水区域。再例如,当最大积水深度大于车辆的预设阈值时,则发出警示信息和控制车辆停止,或者,发出警示信息和退出自动驾驶模式,或者发出警示信息和重新规划行驶路线,或者,控制车辆停止和退出自动驾驶模式,或者,控制车辆停止和重新规划行驶路线,或者,退出自动驾驶模式和重新规划行驶路线。再例如,当最大积水深度大于车辆的预设阈值时,则发出警示信息和控制车辆停止和退出自动驾驶模式,或者,发出警示信息和控制车辆停止和重新规划行驶路线,或者,退出自动驾驶模式和控制车辆停止和重新规划行驶路线。再例如,当最大积水深度大于车辆的预设阈值时,则发出警示信息和控制车辆停止和退出自动驾驶模式和重新规划行驶路线。
当最大积水深度小于车辆的预设阈值时,可发出车辆可安全通过的提示信息。示例性的,警示信息和提示信息均可通过视频、音频或视频和音频组合的方式进行警示或提示。
本申请实施例还提供了一种信息传输方法,该方法可应用于具有摄像功能的终端,以该终端为车辆举例说明。
图17为本申请实施例提供的一种信息传输方法的流程图。如图17所示,该方法包括 步骤S1701-S1702。
在步骤S1701中,检测确定距离车辆预设距离的积水区域的位置信息和/或积水区域的最大积水深度。
其中,预设距离可以为为用户设置,也可以为技术人员设置,还可以与本车传感器感应距离有关,本申请不做限定。
在一个示例中,检测确定积水区域的最大积水深度可采用上述图3-15中描述的任一方法确定,或者也可采用其他方法确定,本申请不做限定。积水区域的位置信息获取方法与第一边缘的空间位置确定方法类似,可参见上文描述,为了简洁,这里不再赘述。
在步骤S1702中,将车辆检测到的积水区域的位置信息和/或积水区域的最大积水深度,发送给其他车辆和/或上传至云端服务器。
例如,将车辆检测到的积水区域的位置信息和/或积水区域的最大积水深度,通过车联网发送给其他车辆,以使其他车辆了解该路段的状况,提前进行路线的规划。或者,将车辆检测到的积水区域的位置信息和/或积水区域的最大积水深度,上传到云端服务器,例如,存储高精地图的动态消息的云端服务器。
本申请实施例还提供了一种积水深度确定装置。
图18为本申请实施例提供的一种积水深度确定装置的结构示意图。该装置1800具有摄像头,如图18所示,该装置1800至少包括:
获取模块1801,用于获取所述摄像头采集的积水道路的图像信息和道路坡角信息,所述道路坡角信息包括所述第一边缘所在位置的道路坡角;
确定模块1802,用于基于所述积水道路的图像信息,确定积水边缘中第一边缘的空间位置信息;其中,所述第一边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘;
用于确定所述积水区域的最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息;
用于基于所述第一边缘的空间位置信息、道路坡角信息、所述最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述确定模块1802具体用于:
基于所述第一边缘的空间位置信息和所述最大水深处对应的道路位置信息,确定第一距离,所述第一距离表征所述第一边缘的空间位置至所述最大水深处对应的道路位置的距离;基于所述第一距离和所述道路坡角的正弦值的乘积,确定所述积水区域的最大积水深度。
在另一个可能的实现中,获取模块1801还用于,获取所述积水道路的坡向信息,所述坡向信息包括积水道路的坡向变化处的位置;
所述确定模块1802具体用于:基于所述积水道路的坡向变化处的位置,确定所述积水区域的最大水深处对应的道路位置信息。
在另一个可能的实现中,所述积水道路上方具有与其延伸方向不同的第一道路;
所述确定模块1802具体用于:基于所述第一道路的中心线在所述积水道路上的正 投影,确定所述积水区域的最大水深处对应的道路位置信息。
在另一个可能的实现中,所述确定模块1802具体用于:
基于所述第一边缘的空间位置信息和所述最大水深处对应的水面位置信息,确定第二距离,所述第二距离表征所述第一边缘的空间位置至所述最大水深处对应的水面位置的距离;
基于所述第二距离和所述道路坡角的正切值的乘积,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述积水道路为地道桥,所述积水道路的图像信息包括桥洞区域图像和道路区域图像;
所述确定模块1802具体用于:基于所述积水道路的图像信息确定桥洞区域图像和道路区域图像;
基于所述桥洞区域图像和道路区域图像的交界位置,确定所述积水区域的最大水深处对应的水面位置信息。
在另一个可能的实现中,所述确定模块1802具体用于:确定所述积水区域的最大水深处对应的道路位置坐标,所述道路位置坐标为二维坐标;
基于所述道路位置坐标,确定所述积水区域的最大水深处对应的水面位置信息。
在另一个可能的实现中,当所述积水区域道路设置限高装置时;
获取模块1801还用于,用于获取所述限高装置的限高值;
确定模块1802,用于基于所述限高值与所述终端当前所处位置信息,确定第一高差,所述第一高差表征所述终端当前所处位置和所述限高装置高度的差值;
基于所述终端当前所处位置信息、所述第一边缘的空间位置信息、道路坡角信息、限高值和第一高差,确定所述积水区域的最大积水深度。
在另一个可能的实现中,所述确定模块1802具体用于:
基于所述终端当前所处位置信息和所述第一边缘的空间位置信息,确定第三距离,所述第三距离表征所述终端当前所处位置至所述第一边缘的空间位置的距离;
基于所述第三距离和所述道路坡角的正弦值的乘积与所述第一高差,确定第二高差,所述第二高差表征所述限高装置与所述积水区域的水面的高差;
基于所述限高值与所述第二高差的差值,确定所述积水区域的最大积水深度。
根据本申请实施例的积水深度确定装置1800可对应于执行本申请实施例中描述的方法,并且积水深度确定装置1800中的各个模块的上述和其它操作和/或功能分别为了实现图3-15中的各个方法的相应流程,为了简洁,在此不再赘述。
本申请还提供了一种终端控制装置。
图19为本申请实施例提供的一种终端控制装置的结构示意图。该装置1900具有摄像头,如图19所示,该装置1900至少包括:
检测模块1901,用于检测确定距离车辆预设距离的积水区域的最大积水深度。
控制模块1902,用于根据所述积水区域的最大积水深度控制所述车辆。
根据本申请实施例的积水深度确定装置1900可对应于执行本申请实施例中描述的方法,并且积水深度确定装置1900中的各个模块的上述和其它操作和/或功能分别为了实现图16中的各个方法的相应流程,为了简洁,在此不再赘述。
本申请还提供了一种通信装置。
图20为本申请实施例提供的一种通信装置的结构示意图。如图20所示,该装置2000至少包括:
积水检测模块2001,用于检测确定距离车辆预设距离的积水区域的位置信息和/或积水区域的最大积水深度。
通信模块2002,将车辆检测到的积水区域的位置信息和/或积水区域的最大积水深度,发送给其他车辆和/或上传至云端服务器。
根据本申请实施例的通信装置2000可对应于执行本申请实施例中描述的方法,并且通信装置2000中的各个模块的上述和其它操作和/或功能分别为了实现图17中的各个方法的相应流程,为了简洁,在此不再赘述。
另外需说明的是,以上所描述的实施例仅仅是示意性的,其中所述作为分离部件说明的模块可以是或者也可以不是物理上分开的,作为模块显示的部件可以是或者也可以不是物理模块,即可以位于一个地方,或者也可以分布到多个网络模块上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。另外,本申请提供的设备实施例附图中,模块之间的连接关系表示它们之间具有通信连接,具体可以实现为一条或多条通信总线或信号线。
本申请还提供一种计算机可读存储介质,其上存储有计算机程序,当所述计算机程序在计算机中执行时,令计算机执行上述任一项方法。
本申请还提供一种计算机程序或计算机程序产品,该计算机程序或计算机程序产品包括指令,当该指令执行时,令计算机执行上述任一项方法。
本申请还提供一种芯片系统,包括处理器和存储器,所述存储器存储有程序指令,当所述存储器存储的程序指令被所述处理器调用执行时实现上述任一项方法。
图21为本申请实施例提供的一种积水深度确定设备的结构示意图。
如图21所示,所述积水深度确定设备2100包括处理器2101、存储器2102和通信接口2103。其中,处理器2101、存储器2102通信接口2103通信连接,也可以通过无线传输等其他手段实现通信。该通信接口2103用于与其他通信设备进行通信连接,例如获取道路信息,包括道路坡角、道路坡向,道路高程等,再例如向其他车辆发送信息或向云端服务器发送信息等;该存储器2102存储可执行程序代码,且处理器2101可以调用存储器2102中存储的程序代码执行前述方法实施例中的积水深度确定方法和/或终端控制方法和/或信息传输方法。
应理解,在本申请实施例中,该处理器2101可以是中央处理单元CPU,该处理器2101还可以是其他通用处理器、数字信号处理器(digital signal processor,DSP)、专用集成电路(application specific integrated circuit,ASIC)、现场可编程门阵列(field programmable gate array,FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者是任何常规的处理器等。
该存储器2102可以包括只读存储器和随机存取存储器,并向处理器2101提供指令和数据。存储器2102还可以包括非易失性随机存取存储器。例如,存储器2102还可以存储训练数据集。
该存储器2102可以是易失性存储器或非易失性存储器,或可包括易失性和非易失 性存储器两者。其中,非易失性存储器可以是只读存储器(read-only memory,ROM)、可编程只读存储器(programmable ROM,PROM)、可擦除可编程只读存储器(erasable PROM,EPROM)、电可擦除可编程只读存储器(electrically EPROM,EEPROM)或闪存。易失性存储器可以是随机存取存储器(random access memory,RAM),其用作外部高速缓存。通过示例性但不是限制性说明,许多形式的RAM可用,例如静态随机存取存储器(static RAM,SRAM)、动态随机存取存储器(DRAM)、同步动态随机存取存储器(synchronous DRAM,SDRAM)、双倍数据速率同步动态随机存取存储器(double data date SDRAM,DDR SDRAM)、增强型同步动态随机存取存储器(enhanced SDRAM,ESDRAM)、同步连接动态随机存取存储器(synchlink DRAM,SLDRAM)和直接内存总线随机存取存储器(direct rambus RAM,DR RAM)。
应理解,根据本申请实施例的积水深度确定设备2100可对应于本申请实施例中的积水深度确定装置,并可以对应于执行根据本申请实施例中图3-15所示方法中的相应主体,并且积水深度确定设备2100中的各个器件的上述和其它操作和/或功能分别为了实现图3-15的各个方法的相应流程,为了简洁,在此不再赘述。
本领域普通技术人员应该还可以进一步意识到,结合本文中所公开的实施例描述的各示例的单元及算法步骤,能够以电子硬件、计算机软件或者二者的结合来实现,为了清楚地说明硬件和软件的可互换性,在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行,取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能,但是这种实现不应认为超出本申请的范围。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分步骤是可以通过程序来指令处理器完成,所述的程序可以存储于计算机可读存储介质中,所述存储介质是非短暂性(英文:non-transitory)介质,例如随机存取存储器,只读存储器,快闪存储器,硬盘,固态硬盘,磁带(英文:magnetic tape),软盘(英文:floppy disk),光盘(英文:optical disc)及其任意组合。
以上所述,仅为本申请较佳的具体实施方式,但本申请的保护范围并不局限于此,任何熟悉本技术领域的技术人员在本申请揭露的技术范围内,可轻易想到的变化或替换,都应涵盖在本申请的保护范围之内。因此,本申请的保护范围应该以权利要求的保护范围为准。

Claims (24)

  1. 一种积水深度确定方法,其特征在于,包括:
    获取积水道路的图像信息;
    基于所述积水道路的图像信息,确定积水边缘中第一边缘的空间位置信息;其中,所述第一边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘;
    获取道路坡角信息,所述道路坡角信息包括所述第一边缘所在位置的道路坡角;
    确定所述积水区域的最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息;
    基于所述第一边缘的空间位置信息、道路坡角信息、所述最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息,确定所述积水区域的最大积水深度。
  2. 根据权利要求1所述的方法,其特征在于,所述基于所述第一边缘的空间位置信息、所述道路坡角信息和所述最大水深处对应的道路位置信息,确定所述积水区域的最大积水深度,包括:
    基于所述第一边缘的空间位置信息和所述最大水深处对应的道路位置信息,确定第一距离,所述第一距离表征所述第一边缘的空间位置至所述最大水深处对应的道路位置的距离;
    基于所述第一距离和所述道路坡角的正弦值的乘积,确定所述积水区域的最大积水深度。
  3. 根据权利要求1或2所述的方法,其特征在于,所述确定所述积水区域的最大水深处对应的道路位置信息,之前还包括:
    获取所述积水道路的坡向信息,所述坡向信息包括积水道路的坡向变化处的位置;
    所述确定所述积水区域的最大水深处对应的道路位置信息,包括:
    基于所述积水道路的坡向变化处的位置,确定所述积水区域的最大水深处对应的道路位置信息。
  4. 根据权利要求1或2所述的方法,其特征在于,所述积水道路上方具有与其延伸方向不同的第一道路;
    所述确定所述积水区域的最大水深处对应的道路位置信息,包括:
    基于所述第一道路的中心线在所述积水道路上的正投影,确定所述积水区域的最大水深处对应的道路位置信息。
  5. 根据权利要求1所述的方法,其特征在于,所述基于所述第一边缘的空间位置信息、道路坡角信息、所述积水区域的最大水深处对应的水面位置信息,确定所述积水区域的最大积水深度,包括:
    基于所述第一边缘的空间位置信息和所述最大水深处对应的水面位置信息,确定第二距离,所述第二距离表征所述第一边缘的空间位置至所述最大水深处对应的水面位置的距离;
    基于所述第二距离和所述道路坡角的正切值的乘积,确定所述积水区域的最大积水深度。
  6. 根据权利要求1或5所述的方法,其特征在于,所述积水道路为地道桥,所述积 水道路的图像信息包括桥洞区域图像和道路区域图像;
    所述确定所述积水区域的最大水深处对应的水面位置信息,包括:
    基于所述积水道路的图像信息确定桥洞区域图像和道路区域图像;
    基于所述桥洞区域图像和道路区域图像的交界位置,确定所述积水区域的最大水深处对应的水面位置信息。
  7. 根据权利要求1所述的方法,其特征在于,所述确定所述积水区域的最大水深处对应的水面位置信息,包括:
    确定所述积水区域的最大水深处对应的道路位置坐标,所述道路位置坐标为二维坐标;
    基于所述道路位置坐标,确定所述积水区域的最大水深处对应的水面位置信息。
  8. 根据权利要求1所述的方法,其特征在于,所述方法还包括:
    当所述积水区域道路设置限高装置时;
    获取所述限高装置的限高值;
    基于所述限高值与所述终端当前所处位置信息,确定第一高差,所述第一高差表征所述终端当前所处位置和所述限高装置高度的差值;
    基于所述终端当前所处位置信息、所述第一边缘的空间位置信息、道路坡角信息、限高值和第一高差,确定所述积水区域的最大积水深度。
  9. 根据权利要求8所述的方法,其特征在于,基于所述终端当前所处位置信息、所述第一边缘的空间位置信息、道路坡角信息、限高值和第一高差,确定所述积水区域的最大积水深度,包括:
    基于所述终端当前所处位置信息和所述第一边缘的空间位置信息,确定第三距离,所述第三距离表征所述终端当前所处位置至所述第一边缘的空间位置的距离;
    基于所述第三距离和所述道路坡角的正弦值的乘积与所述第一高差,确定第二高差,所述第二高差表征所述限高装置与所述积水区域的水面的高差;
    基于所述限高值与所述第二高差的差值,确定所述积水区域的最大积水深度。
  10. 一种终端的控制方法,其特征在于,包括:
    若所述积水区域的最大积水深度大于或等于预设阈值,则发出警示信息和/或控制所述终端停止和/或退出自动驾驶模式和/或重新规划行驶路线,所述最大积水深度是基于权利要求1-9任一项所述的方法确定。
  11. 根据权利要求10所述的方法,其特征在于,所述终端为车辆。
  12. 一种信息传输方法,其特征在于,包括:
    将积水区域的位置信息和/或所述积水区域的最大积水深度,发送给其他车辆和/或上传至高精地图的动态信息,其中,所述最大积水深度是基于权利要求1-9任一项所述的方法确定。
  13. 一种积水深度确定装置,其特征在于,包括:
    获取模块,用于获取积水道路的图像信息和道路坡角信息;其中,所述道路坡角信息包括所述第一边缘所在位置的道路坡角;
    确定模块,用于基于所述积水道路的图像信息,确定积水边缘中第一边缘的空间位置信息;其中,所述第一边缘为所述积水区域在所述积水道路延伸方向上的两个边缘中的任一边缘;
    用于确定所述积水区域的最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息
    用于基于所述第一边缘的空间位置信息、道路坡角信息、所述最大水深处对应的道路位置信息/所述积水区域的最大水深处对应的水面位置信息,确定所述积水区域的最大积水深度。
  14. 根据权利要求13所述的装置,其特征在于,所述确定模块具体用于:
    基于所述第一边缘的空间位置信息和所述最大水深处对应的道路位置信息,确定第一距离,所述第一距离表征所述第一边缘的空间位置至所述最大水深处对应的道路位置的距离;
    基于所述第一距离和所述道路坡角的正弦值的乘积,确定所述积水区域的最大积水深度。
  15. 根据权利要求13或14所述的装置,其特征在于,
    获取模块还用于,获取所述积水道路的坡向信息,所述坡向信息包括积水道路的坡向变化处的位置;
    所述确定模块具体用于:
    基于所述积水道路的坡向变化处的位置,确定所述积水区域的最大水深处对应的道路位置信息。
  16. 根据权利要求13或14所述的装置,其特征在于,所述积水道路上方具有与其延伸方向不同的第一道路;
    所述确定模块具体用于:
    基于所述第一道路的中心线在所述积水道路上的正投影,确定所述积水区域的最大水深处对应的道路位置信息。
  17. 根据权利要求13所述的装置,其特征在于,所述确定模块具体用于:
    基于所述第一边缘的空间位置信息和所述最大水深处对应的水面位置信息,确定第二距离,所述第二距离表征所述第一边缘的空间位置至所述最大水深处对应的水面位置的距离;
    基于所述第二距离和所述道路坡角的正切值的乘积,确定所述积水区域的最大积水深度。
  18. 根据权利要求13或17所述的装置,其特征在于,所述积水道路为地道桥,所述积水道路的图像信息包括桥洞区域图像和道路区域图像;
    所述确定模块具体用于:
    基于所述积水道路的图像信息确定桥洞区域图像和道路区域图像;
    基于所述桥洞区域图像和道路区域图像的交界位置,确定所述积水区域的最大水深处对应的水面位置信息。
  19. 根据权利要求13所述的装置,其特征在于,所述确定模块具体用于:
    确定所述积水区域的最大水深处对应的道路位置坐标,所述道路位置坐标为二维坐标;
    基于所述道路位置坐标,确定所述积水区域的最大水深处对应的水面位置信息。
  20. 根据权利要求13所述的装置,其特征在于,当所述积水区域道路设置限高装置时;
    所述获取模块还用于,获取所述限高装置的限高值;
    所述确定模块还用于,基于所述限高值与所述终端当前所处位置信息,确定第一高差,所述第一高差表征所述终端当前所处位置和所述限高装置高度的差值;
    基于所述终端当前所处位置信息、所述第一边缘的空间位置信息、道路坡角信息、限高值和第一高差,确定所述积水区域的最大积水深度。
  21. 根据权利要求20所述的装置,其特征在于,所述确定模块具体用于:
    基于所述终端当前所处位置信息和所述第一边缘的空间位置信息,确定第三距离,所述第三距离表征所述终端当前所处位置至所述第一边缘的空间位置的距离;
    基于所述第三距离和所述道路坡角的正弦值的乘积与所述第一高差,确定第二高差,所述第二高差表征所述限高装置与所述积水区域的水面的高差;
    基于所述限高值与所述第二高差的差值,确定所述积水区域的最大积水深度。
  22. 一种车辆,其特征在于,包括权利要求13-21任一项所述的积水深度确定装置。
  23. 一种芯片系统,其特征在于,包括处理器和存储器,所述存储器存储有程序指令,当所述存储器存储的程序指令被所述处理器调用执行时实现如权利要求1-12中任一项所述的方法。
  24. 一种计算机可读存储介质,其上存储有计算机程序,其特征在于,当所述计算机程序在计算机中执行时,令所述计算机执行权利要求1-12任一项所述的方法。
PCT/CN2021/078931 2021-03-03 2021-03-03 一种积水深度确定方法及装置 WO2022183415A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202180000406.8A CN113168535A (zh) 2021-03-03 2021-03-03 一种积水深度确定方法及装置
PCT/CN2021/078931 WO2022183415A1 (zh) 2021-03-03 2021-03-03 一种积水深度确定方法及装置

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2021/078931 WO2022183415A1 (zh) 2021-03-03 2021-03-03 一种积水深度确定方法及装置

Publications (1)

Publication Number Publication Date
WO2022183415A1 true WO2022183415A1 (zh) 2022-09-09

Family

ID=76875986

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/078931 WO2022183415A1 (zh) 2021-03-03 2021-03-03 一种积水深度确定方法及装置

Country Status (2)

Country Link
CN (1) CN113168535A (zh)
WO (1) WO2022183415A1 (zh)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106800003A (zh) * 2016-12-28 2017-06-06 智车优行科技(北京)有限公司 道路积水检测方法和系统、车辆
CN108510773A (zh) * 2017-02-28 2018-09-07 长城汽车股份有限公司 车辆的控制方法、系统及车辆
CN110053624A (zh) * 2018-01-18 2019-07-26 奥迪股份公司 驾驶辅助系统以及方法
US20200317206A1 (en) * 2019-04-02 2020-10-08 International Business Machines Corporation Fording depth estimation

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104050825B (zh) * 2013-03-13 2017-09-15 厦门歌乐电子企业有限公司 搭载于车辆上的终端装置、车辆及水坑路面的提醒方法
CN104318793B (zh) * 2014-10-21 2016-08-24 中山大学 一种道路水浸事件紧急疏导配流生成方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106800003A (zh) * 2016-12-28 2017-06-06 智车优行科技(北京)有限公司 道路积水检测方法和系统、车辆
CN108510773A (zh) * 2017-02-28 2018-09-07 长城汽车股份有限公司 车辆的控制方法、系统及车辆
CN110053624A (zh) * 2018-01-18 2019-07-26 奥迪股份公司 驾驶辅助系统以及方法
US20200317206A1 (en) * 2019-04-02 2020-10-08 International Business Machines Corporation Fording depth estimation

Also Published As

Publication number Publication date
CN113168535A (zh) 2021-07-23

Similar Documents

Publication Publication Date Title
CN108362295B (zh) 车辆路径引导设备和方法
KR102595897B1 (ko) 차선 결정 방법 및 장치
JP4370869B2 (ja) 地図データ更新方法および地図データ更新装置
KR101704405B1 (ko) 차선 인식 시스템 및 방법
KR20220033477A (ko) 자동 발렛 파킹 시스템의 위치 추정 장치 및 방법
CN110390240B (zh) 自动驾驶车辆中的车道后处理
WO2021056841A1 (zh) 定位方法、路径确定方法、装置、机器人及存储介质
US10942519B2 (en) System and method for navigating an autonomous driving vehicle
US11200432B2 (en) Method and apparatus for determining driving information
JP2019099138A (ja) 車線維持補助方法及び装置
US20170061203A1 (en) Detection device, detection method, computer program product, and information processing system
CN110779538A (zh) 相对于自主导航而跨本地和基于云的系统来分配处理资源
CN114174137A (zh) Adas或ad特征的源横向偏移
JP2018048949A (ja) 物体識別装置
CN116734828A (zh) 道路拓扑信息的确定、电子地图数据处理方法、电子设备
CN114694111A (zh) 车辆定位
JP6790951B2 (ja) 地図情報学習方法及び地図情報学習装置
US20210173095A1 (en) Method and apparatus for determining location by correcting global navigation satellite system based location and electronic device thereof
US20210048819A1 (en) Apparatus and method for determining junction
WO2022183415A1 (zh) 一种积水深度确定方法及装置
EP3835724B1 (en) Self-location estimation method and self-location estimation device
CN109144052B (zh) 用于自动驾驶车辆的导航系统及其方法
CN112654998A (zh) 一种车道线检测方法和装置
US11867526B2 (en) Map generation apparatus
CN115050205B (zh) 地图生成装置以及位置识别装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21928504

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21928504

Country of ref document: EP

Kind code of ref document: A1