CN111062320B - Overpass identification method and related products - Google Patents

Abstract

The embodiment of the present application discloses a viaduct identification method and related products, which are characterized in that they are applied to electronic equipment, and the electronic equipment includes: a sensor module. The method includes: obtaining a lane video of the current driving lane; according to the The lane video determines the first recognition result of the current driving lane; receives the sensing data collected by the sensor module, and determines the second recognition result of the current driving lane based on the sensed data; if the first recognition result The comparison with the second identification result is successful, and it is determined that the current driving lane is a viaduct lane. Implementing the embodiments of the present application has the advantage of improving the accuracy of viaduct scene recognition.

Description

Viaduct identification methods and related products

Technical field

This application relates to the field of electronic technology, specifically to a viaduct identification method and related products.

Background technique

With the improvement of residents' living standards, cars have become an important means of transportation in daily life, and the demand for car navigation is also increasing.

In the process of driving a car, mobile terminals are usually used for map navigation. When identifying common viaduct scenes on urban roads, satellite data is usually used to judge. However, satellite data is susceptible to environmental interference and the data reliability is not high. , resulting in low accuracy of viaduct scene recognition and low user experience.

Contents of the invention

Embodiments of the present application provide a method for identifying viaducts and related products, which are used to identify viaduct scenes based on lane videos and sensor data, which is beneficial to improving the accuracy of viaduct scene recognition and improving user experience.

In a first aspect, embodiments of the present application provide a method for identifying viaducts, which is applied to electronic equipment. The electronic equipment includes: a sensor module. The method includes:

Get the lane video of the current driving lane;

Determine the first identification result of the current driving lane based on the lane video;

Receive the sensing data collected by the sensor module, and determine the second recognition result of the current driving lane based on the sensed data;

If the comparison between the first recognition result and the second recognition result is successful, it is determined that the current driving lane is a viaduct lane.

In a second aspect, embodiments of the present application provide a viaduct identification device, which is applied to electronic equipment. The electronic equipment includes: a sensor module, and the device includes:

The acquisition unit is used to acquire the lane video of the current driving lane;

A determination unit configured to determine the first recognition result of the current driving lane based on the lane video;

A receiving unit, configured to receive the sensing data collected by the sensor module, and determine the second recognition result of the current driving lane based on the sensed data;

A comparison unit configured to determine that the current driving lane is a viaduct lane if the comparison between the first recognition result and the second recognition result is successful.

In a third aspect, embodiments of the present application provide an electronic device. The electronic device includes a processor, a memory, a communication interface, and one or more programs. The one or more programs are stored in the memory and are The configuration is executed by the processor, and the program includes instructions for executing some or all of the steps described in the method described in the first aspect of the embodiment of the present application.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, wherein the above-mentioned computer-readable storage medium is used to store a computer program, wherein the above-mentioned computer program is executed by a processor to implement the first embodiment of the present application. Some or all of the steps described in the method in one aspect.

In the fifth aspect, embodiments of the present application provide a computer program product, wherein the above-mentioned computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the above-mentioned computer program is operable to cause the computer to execute the implementation of the present application. Examples include some or all of the steps described in the method described in the first aspect. The computer program product may be a software installation package.

It can be seen that in the embodiment of the present application, the electronic device obtains the lane video of the current driving lane; determines the first recognition result of the current driving lane based on the lane video; receives the sensing data collected by the sensor module, The second recognition result of the current driving lane is determined based on the sensed data; if the first recognition result and the second recognition result are successfully compared, the current driving lane is determined to be a viaduct lane. In this way, the viaduct scene can be identified based on lane video and sensor data, which will help improve the accuracy of viaduct scene recognition and improve user experience.

Description of the drawings

In order to explain the embodiments of the present application or the technical solutions in the prior art more clearly, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without exerting creative efforts.

Figure 1 is a schematic structural diagram of an electronic device provided by an embodiment of the present application;

Figure 2 is a schematic flow chart of an viaduct identification method provided by an embodiment of the present application;

Figure 3 is a schematic flow chart of another viaduct identification method provided by an embodiment of the present application;

Figure 4 is a human-computer interaction diagram of another viaduct identification method provided by an embodiment of the present application;

Figure 5 is a schematic structural diagram of an electronic device provided by an embodiment of the present application;

Figure 6 is a schematic structural diagram of an overpass identification device provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present invention.

The terms "first", "second", "third" and "fourth" in the description, claims and drawings of the present invention are used to distinguish different objects, rather than describing a specific sequence. . Furthermore, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes Other steps or units inherent to such processes, methods, products or devices.

Reference herein to "an embodiment" means that a particular feature, result or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art understand, both explicitly and implicitly, that the embodiments described herein may be combined with other embodiments.

In the following, some terms used in this application are explained to facilitate understanding by those skilled in the art.

Electronic devices may include various handheld devices with wireless communication capabilities, vehicle-mounted devices, wearable devices (such as smart watches, smart bracelets, pedometers, etc.), computing devices or other processing devices that are connected to wireless modems, and various Various forms of user equipment (User Equipment, UE), mobile station (Mobile Station, MS), terminal equipment (terminal device), etc. For convenience of description, the devices mentioned above are collectively referred to as electronic devices.

Please refer to Figure 1. Figure 1 is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application. The electronic device 100 includes a storage and processing circuit 110, and a sensor 170 connected to the storage and processing circuit 110, wherein:

Electronic device 100 may include control circuitry, which may include storage and processing circuitry 110 . The storage and processing circuitry 110 may be memory such as hard drive memory, non-volatile memory (such as flash memory or other electronically programmable read-only memories used to form solid state drives, etc.), volatile memory (such as static or dynamic random access memory). memory, etc.), etc., are not limited by the embodiments of this application. Processing circuitry in storage and processing circuitry 110 may be used to control the operation of electronic device 100 . The processing circuit can be implemented based on one or more microprocessors, microcontrollers, digital signal processors, baseband processors, power management units, audio codec chips, application specific integrated circuits, display driver integrated circuits, etc.

The storage and processing circuitry 110 may be used to run software in the electronic device 100, such as Internet browsing applications, Voice over Internet Protocol (VOIP) phone calling applications, email applications, media playback applications, operating system functions wait. These software can be used to perform some control operations, for example, camera-based image acquisition, ambient light measurement based on ambient light sensor, proximity sensor measurement based on proximity sensor, information based on status indicators such as status indicators such as light-emitting diodes. Display functions, touch sensor-based touch event detection, functions associated with displaying information on multiple (e.g., layered) displays, operations associated with performing wireless communication functions, operations associated with collecting and generating audio signals Operations, control operations associated with collecting and processing button press event data, and other functions in the electronic device 100 are not limited by the embodiments of the present application.

Electronic device 100 may include input-output circuitry 150 . The input-output circuit 150 may be used to enable the electronic device 100 to input and output data, that is, allow the electronic device 100 to receive data from an external device and also allow the electronic device 100 to output data from the electronic device 100 to an external device. The input-output circuit 150 may further include a sensor 170 . Sensors 170 may include ambient light sensors, light and capacitive based proximity sensors, fingerprint recognition modules, touch sensors (e.g., light based touch sensors and/or capacitive touch sensors, where the touch sensors may be part of a touch display screen , can also be used independently as a touch sensor structure), such as acceleration sensors and other sensors.

The electronic device 100 may also include a camera 140. The camera 140 may include an infrared camera, a color image camera, etc. The camera may be a front camera or a rear camera. The fingerprint recognition module may be integrated under the display screen for collecting fingerprint images. The fingerprint recognition module may be at least one of the following: an optical fingerprint recognition module, an ultrasonic fingerprint recognition module, etc., which is not limited here. The above-mentioned front camera can be arranged below the front display screen, and the above-mentioned rear camera can be arranged below the rear display screen. Of course, the above-mentioned front camera or rear camera may not be integrated with the display screen. Of course, in practical applications, the above-mentioned front camera or rear camera may also be a lifting structure. The specific implementation of the present application does not limit the above-mentioned front camera. Or the specific structure of the rear camera.

The input-output circuit 150 may also include one or more display screens. When there are multiple display screens, such as two display screens, one display screen may be disposed in front of the electronic device, and the other display screen may be disposed in front of the electronic device. behind, such as display screen 130. The display screen 130 may include one or a combination of a liquid crystal display screen, an organic light-emitting diode display screen, an electronic ink display screen, a plasma display screen, a display screen using other display technologies. The display screen 130 may include an air pressure sensor, a global navigation satellite positioning GNSS sensor, and may also include a touch sensor array (ie, the display screen 130 may be a touch display screen). The touch sensor may be a capacitive touch sensor formed from an array of transparent touch sensor electrodes, such as indium tin oxide (ITO) electrodes, or may be a touch sensor formed using other touch technologies, such as sonic touch, pressure sensitive touch, resistive Touch, optical touch, etc. are not limited in the embodiments of this application.

Communication circuitry 120 may be used to provide electronic device 100 with the ability to communicate with external devices. Communication circuitry 120 may include analog and digital input-output interface circuitry, and wireless communication circuitry based on radio frequency signals and/or optical signals. Wireless communication circuits in communication circuit 120 may include radio frequency transceiver circuits, power amplifier circuits, low noise amplifiers, switches, filters, and antennas. The communication circuit 120 may include a first Wi-Fi channel and a second Wi-Fi channel, and the first Wi-Fi channel and the second Wi-Fi channel run simultaneously to implement dual Wi-Fi functions. For example, the wireless communication circuit in the communication circuit 120 may include circuitry for supporting near field communication (NFC) by transmitting and receiving near field coupled electromagnetic signals. For example, communication circuitry 120 may include a near field communication antenna and a near field communication transceiver. Communication circuitry 120 may also include cellular phone transceivers and antennas, wireless local area network transceiver circuits and antennas, and the like.

The electronic device 100 may further include batteries, power management circuitry, and other input-output units 160 . The input-output unit 160 may include buttons, joysticks, click wheels, scroll wheels, touch pads, keypads, keyboards, cameras, light emitting diodes and other status indicators, etc.

A user may input commands through the input-output circuit 150 to control the operation of the electronic device 100 and may use the output data of the input-output circuit 150 to receive status information and other output from the electronic device 100 .

Based on the electronic device described in Figure 1 above, it can be used to implement the following functions:

Get the lane video of the current driving lane;

Determine the first identification result of the current driving lane based on the lane video;

Receive the sensing data collected by the sensor module, and determine the second recognition result of the current driving lane based on the sensed data;

If the comparison between the first recognition result and the second recognition result is successful, it is determined that the current driving lane is a viaduct lane.

Please refer to Figure 2. Figure 2 is a schematic flow chart of an viaduct identification method provided by an embodiment of the present application. It is applied to the electronic device described in Figure 1. The electronic device includes: a sensor module. The viaduct identification method includes:

Step 201: Obtain the lane video of the current driving lane;

Optionally, when it is detected that the target vehicle is started, the camera module corresponding to the electronic device is started, and the camera module is used to collect the lane video corresponding to the current driving lane of the target vehicle.

Among them, the lane video is the video data in the driving direction of the target vehicle.

Step 202: Determine the first recognition result of the current driving lane according to the lane video;

Optionally, obtain a preset image recognition algorithm, execute the image recognition algorithm on the lane video, and obtain a first recognition result corresponding to the current driving lane, where the first recognition result may include: a first preset result or Second preset result.

Optionally, obtain a pre-trained image recognition model, use the car video as input to the image recognition model, and obtain the first recognition result corresponding to the current driving lane.

Step 203: Receive the sensing data collected by the sensor module, and determine the second recognition result of the current driving lane based on the sensed data;

Optionally, obtaining the first recognition result and receiving the sensing data collected by the sensor module according to the first recognition result includes: determining whether the first recognition result includes the first preset result, and if the first recognition result includes the third A preset result, generates an air pressure change value acquisition instruction and a global navigation satellite positioning GNSS data acquisition instruction, generates a first sensing data acquisition instruction based on the air pressure change value acquisition instruction and the GNSS data acquisition instruction, and sends the first sensor data acquisition instruction to the sensor module A first sensing data acquisition instruction; if the first recognition result does not contain the first preset result, determine whether the first recognition result contains the second preset result; if the first recognition result contains the second preset result, Generate air pressure change value acquisition instructions. A second sensing data acquisition instruction is generated according to the air pressure change value acquisition instruction, and the second sensing data acquisition instruction is sent to the sensor module.

Further, receive a sensing data acquisition response returned by the sensor module, and extract the sensing data from the sensing data acquisition response, where the sensing data may include: first sensing data or second sensing data, Obtain a preset judgment model, use the sensor data as input to the judgment model, and obtain a second recognition result corresponding to the current driving lane.

Step 204: If the comparison between the first recognition result and the second recognition result is successful, determine that the current driving lane is a viaduct lane.

Optionally, if the first identification result includes the first preset result, the second identification result may include: air pressure identification result and GNSS identification result, and the GNSS identification result may include: satellite number identification result and satellite signal-to-noise ratio identification result. ; If the first recognition result includes a second preset result, the second recognition result may include: air pressure recognition result. Optionally, if the first recognition result includes the first preset result, extract the air pressure recognition result and the GNSS recognition result from the second recognition result, and determine whether the air pressure recognition result includes the first preset result. If the air pressure If the recognition result does not contain the first preset result, the comparison between the first recognition result and the second recognition result is unsuccessful; if the air pressure recognition result contains the first preset result, obtain the satellite number identification result from the GNSS recognition result. , determine whether the satellite number identification result includes the first preset result. If the satellite number identification result does not include the first preset result, the comparison between the first identification result and the second identification result is unsuccessful; if The satellite identification result includes the first preset result, the satellite signal-to-noise ratio identification result is obtained from the GNSS identification result, and it is determined whether the satellite signal-to-noise ratio identification result includes the first preset result. If the satellite signal-to-noise ratio identification result If the first preset result is not included, it is determined that the comparison between the first identification result and the second identification result is unsuccessful. If the satellite signal-to-noise ratio identification result includes the first preset result, it is determined that the first identification result and the second identification result are not successful. The two recognition results are compared successfully and the current driving lane is determined to be the viaduct lane.

Optionally, after determining that the current driving lane is the viaduct lane, obtain the air pressure change value and determine whether the air pressure change value is greater than 0. If the air pressure change value is greater than 0, it is determined that the target vehicle is exiting the viaduct; if the air pressure change value If it is less than 0, it is determined that the target vehicle is entering the viaduct state.

Optionally, after determining that the current driving lane is the viaduct lane, obtain the change value of the number of satellites and determine whether the change value of the number of satellites is greater than 0. If the change value of the number of satellites is greater than 0, it is determined that the target vehicle is driving into the viaduct; if the If the change value of the number of satellites is less than 0, it is determined that the target vehicle is exiting the viaduct.

In a possible example, determining the first recognition result of the current driving lane based on the lane video includes: acquiring m frames of images contained in the lane video, where m is an integer greater than 0; The m-frame images execute an image recognition algorithm to obtain n-frame viaduct images containing viaduct lanes in the m-frame images, where n is an integer greater than or equal to 0 and less than or equal to m; based on the preset scene proportion calculation formula Calculate the m frames of images and the n frames of viaduct images to obtain the viaduct scene ratio; determine whether the viaduct scene ratio is greater than the preset scene ratio threshold, if the viaduct scene ratio is greater than the scene ratio threshold, according to The preset occlusion rate algorithm calculates the n frames of viaduct images to determine the n viaduct occlusion rates corresponding to the n frames of viaduct images; determines the average viaduct occlusion rate based on the n viaduct occlusion rates, and determines the average viaduct Whether the occlusion rate is greater than the preset occlusion rate threshold; if the average viaduct occlusion rate is not greater than the occlusion rate threshold, determine the first recognition result to be the first preset result; otherwise, determine the first recognition result to be Second preset result.

The scene proportion threshold may include: 50%, 60%, 70%, etc., which is not limited here.

The occlusion rate threshold may include: 60%, 65%, 70%, etc., which is not limited here.

Optionally, obtain m frames of images contained in the lane video, where any one of the m frames of images includes: the current lane, the current lane line, and the adjacent lane environment; perform an image recognition algorithm on the m frames of images, where , this image recognition algorithm is used to identify the viaduct lanes in the image, obtain n frames of viaduct images, obtain the preset viaduct scene proportion calculation formula, calculate the n frames of viaduct images and m frame images, and determine the viaduct scene proportion, where, The viaduct scene ratio calculation formula may include: a=/m*100%, where a is the viaduct scene ratio. Determine whether the viaduct scene ratio a is greater than the preset scene ratio threshold. If it is greater, obtain n frames of the viaduct image. n viaduct occlusion rates, where the viaduct occlusion rate represents the proportion of viaduct blocked pixels to viaduct pixels, calculate the average viaduct occlusion rate of n viaduct occlusion rates, and determine whether the average viaduct occlusion rate is greater than the preset occlusion rate threshold , if greater than, determine the first recognition result as the first preset result, if not greater, determine the first recognition result as the second preset result, determine whether the average viaduct occlusion rate is greater than the first condition threshold, if the average viaduct occlusion rate rate is not greater than the first condition threshold, it is determined that the second preset result satisfies the first condition. If the average viaduct occlusion rate is greater than the first condition threshold, it is determined that the second preset result satisfies the second condition; if the viaduct scene proportion is less than The scene proportion threshold is used to determine whether the viaduct scene proportion is less than the second condition threshold. If not, it is determined that the first recognition result is the second preset result and meets the first condition. If it is less than the first recognition result, it is determined that the first recognition result is The second preset result satisfies the second condition.

In a possible example, receiving the sensing data collected by the sensor module includes: if the first recognition result includes the first preset result, receiving the first sensor data collected by the sensor module. Sensing data, wherein the first sensing data includes: air pressure change value and global navigation satellite positioning GNSS data; if the first identification result includes the second preset result, receive the collection by the sensor module The second sensing data, wherein the second sensing data includes: the air pressure change value.

The first preset result indicates that the current lane is an unobstructed viaduct lane, and the second preset result indicates that the current lane is a non-viaduct lane or the current lane is an occluded viaduct lane.

Wherein, the air pressure change value is the difference between the first air pressure collected at the first time corresponding to the lane video and the second air pressure collected at the second time corresponding to the lane video;

Among them, the GNSS data includes: satellite number change value and satellite signal-to-noise ratio change value. The satellite number change value is the first number of satellites collected at the first time corresponding to the lane video and the second time corresponding to the lane video. The difference in the number of second satellites collected; the change value of the satellite signal-to-noise ratio is the signal-to-noise ratio of the first satellite collected at the first time corresponding to the lane video and the second satellite signal collected at the second time corresponding to the lane video. The difference in noise ratio.

In a possible example, determining the second recognition result of the current driving lane based on the sensed data includes: if the sensing data includes the first sensing data, determining the second recognition result of the current driving lane based on the air pressure change value. Determine the air pressure recognition result, determine the GNSS recognition result based on the GNSS data, determine the second recognition result based on the air pressure recognition result and the GNSS recognition result; if the sensing data includes the second sensing data, Then the air pressure identification result is determined based on the air pressure change value, and the second identification result is determined based on the air pressure identification result.

Wherein, the air pressure identification result may include: a first preset result and a second preset result; the GNSS identification result may include: a satellite number identification result and a satellite signal-to-noise ratio identification result, and the satellite number identification result may include: a first A preset result and a second preset result. The satellite signal-to-noise ratio identification result may include: a first preset result and a second preset result. In a possible example, determining the air pressure recognition result based on the air pressure change value includes: obtaining the air pressure change value and a preset altitude change value calculation formula; using the air pressure change value as the altitude change value Input the calculation formula to determine the altitude change value corresponding to the air pressure change value; determine whether the altitude change value is greater than the preset altitude change threshold; if the altitude change value is greater than the altitude change threshold, determine the air pressure recognition The result is the first preset result; otherwise, the air pressure identification result is determined to be the second preset result.

Optionally, obtain the air pressure change value x, calculate the absolute value |x| of the air pressure change value x, obtain the preset air pressure change value threshold, and determine whether the absolute value |x| is greater than the air pressure change value threshold. If the absolute value If the value |x| is greater than the air pressure change threshold, the air pressure recognition result is determined to be the first preset result. If the absolute value |

Optionally, obtain the air pressure change value x, calculate the absolute value |x| of the air pressure change value x, obtain the height change value calculation formula, and substitute the absolute value |x| into the height change value calculation formula to obtain the height change value h , where the altitude change value calculation formula may include: h=44300*(1-|x|/p ₀ ) ^1/5.256 , where p ₀ is the standard atmospheric pressure value.

The height change threshold may include: 5 meters, 10 meters, 15 meters, etc., which are not limited here.

In a possible example, determining the GNSS identification result based on the GNSS data includes: the GNSS data includes: a satellite number change value and a satellite signal-to-noise ratio change value, then the GNSS identification result includes: satellite Quantity identification results and satellite signal-to-noise ratio identification results; determine whether the satellite quantity change value is greater than the preset quantity change threshold, and if the satellite quantity change value is greater than the quantity change threshold, determine that the satellite quantity identification result is the The first preset result, otherwise, determine the satellite number identification result as the second preset result; determine whether the satellite signal-to-noise ratio change value is greater than the preset signal-to-noise ratio change threshold, and if the satellite signal-to-noise ratio change value If the noise ratio change value is greater than the signal-to-noise ratio change threshold, the satellite signal-to-noise ratio identification result is determined to be the first preset result. Otherwise, the satellite signal-to-noise ratio identification result is determined to be the second preset result. result.

The quantity change threshold may include: 10, 15, 20, etc., which are not limited here.

The signal-to-noise ratio change threshold may include: 5, 10, 15, etc., which are not limited here.

The first preset result is used to indicate that the current lane is a viaduct lane, and the second preset result is used to indicate that the current lane is a non-viaduct lane.

In a possible example, if the comparison between the first recognition result and the second recognition result is successful, the method includes: determining whether the first recognition result and the second recognition result are consistent, and if the first recognition result is consistent with the second recognition result, If a recognition result is consistent with the second recognition result, it is determined that the comparison between the first recognition result and the second recognition result is successful; if the first recognition result is inconsistent with the second recognition result, it is determined that the first recognition result is inconsistent with the second recognition result. The comparison between a recognition result and the second recognition result is unsuccessful.

Optionally, if the first recognition result includes a first preset result, a preset first comparison rule is obtained, and the first recognition result and the second recognition result are compared according to the first comparison rule, wherein the first recognition result is compared with the second recognition result. A comparison rule may include: obtaining the air pressure identification result, the satellite number identification result, and the satellite signal-to-noise ratio identification result from the second identification result, and judging the first identification result, the air pressure identification result, the satellite number identification result, and the satellite signal-to-noise ratio. Whether the recognition results all contain the first preset result, and if the first recognition result, air pressure recognition result, satellite number recognition result and satellite signal-to-noise ratio recognition result all contain the first preset result, determine whether the first recognition result is the same as the second preset result. The recognition results are consistent, and it is determined that the first recognition result and the second recognition result are successfully compared. If at least one of the air pressure recognition results, satellite number recognition results, and satellite signal-to-noise ratio recognition results has at least one recognition result that does not contain the first preset result, it is determined The first recognition result is inconsistent with the second recognition result, and it is determined that the comparison between the first recognition result and the second recognition result is unsuccessful.

Optionally, if the first recognition result includes a second preset result, analyze the second preset result, and if the second preset result meets the first condition, extract the air pressure recognition result from the second recognition result. , determine whether the air pressure recognition result contains the first preset result. If the air pressure recognition result contains the first preset result, it is determined that the first recognition result and the second recognition result are successfully compared, and the current driving lane is determined to be a viaduct lane. ; If the air pressure recognition result does not include the first preset result, it is determined that the comparison between the first recognition result and the second recognition result is unsuccessful.

Further, if the second preset result satisfies the second condition, it is determined that the comparison between the first recognition result and the second recognition result is unsuccessful.

In conjunction with the above example, an example will be used to illustrate below. Assume that the first recognition result includes a first preset result. The first preset result may include: an unobstructed viaduct scene. The second preset result may include: an occluded viaduct scene. Non-viaduct scene, wherein if the second preset result is the occluded viaduct scene, it is determined that the second preset result satisfies the first condition; if the second preset result is a non-viaduct scene, it is determined that the second preset result is a non-viaduct scene. The preset result satisfies the second condition; when the first recognition result is the first preset result, the second recognition result is obtained, and it is judged whether the air pressure recognition result, satellite number recognition result and satellite signal-to-noise ratio recognition result are all the first preset result. Suppose the result is, if yes, the comparison between the first recognition result and the second recognition result is successful. If there is at least one second preset result among the air pressure recognition result, satellite number recognition result and satellite signal-to-noise ratio recognition result, then the first recognition result The comparison with the second recognition result is unsuccessful; when the first recognition result is the second preset result and meets the first condition, that is, when the first recognition result is a blocked viaduct scene, determine whether the air pressure recognition result includes the first preset result. , if yes, the comparison between the first recognition result and the second recognition result is successful; if not, the comparison between the first recognition result and the second recognition result is unsuccessful; when the first recognition result is the second preset result and satisfies the th condition, the comparison between the first recognition result and the second recognition result is unsuccessful.

It can be seen that in the embodiment of the present application, the electronic device obtains the lane video of the current driving lane; determines the first recognition result of the current driving lane based on the lane video; receives the sensing data collected by the sensor module, The second recognition result of the current driving lane is determined based on the sensed data; if the first recognition result and the second recognition result are successfully compared, the current driving lane is determined to be a viaduct lane. In this way, the viaduct scene can be identified based on lane video and sensor data, which will help improve the accuracy of viaduct scene recognition and improve user experience.

Please refer to Figure 3. Figure 3 is a schematic flow chart of another viaduct identification method provided by an embodiment of the present application. It is applied to the electronic device described in Figure 1. The electronic device includes: a sensor module. The viaduct identification method includes:

Step 301: Obtain the lane video of the current driving lane;

Step 302: Determine the first recognition result of the current driving lane according to the lane video;

Step 303: If the first recognition result includes the first preset result, receive the first sensing data collected by the sensor module, where the first sensing data includes: air pressure change value and global Navigation satellite positioning GNSS data;

Step 304: If the first recognition result includes the second preset result, receive the second sensing data collected by the sensor module, where the second sensing data includes: the air pressure change value ;

Step 305: Determine the second identification result of the current driving lane based on the sensed data;

Step 306: If the comparison between the first recognition result and the second recognition result is successful, determine that the current driving lane is a viaduct lane.

The specific description of the above-mentioned steps 301 to 306 may refer to the corresponding steps of the viaduct identification method described in FIG. 2 .

It can be seen that in the embodiment of the present application, the electronic device obtains the lane video of the current driving lane; determines the first recognition result of the current driving lane based on the lane video; if the first recognition result includes the first preset result, Then receive the first sensing data collected by the sensor module, where the first sensing data includes: air pressure change value and global navigation satellite positioning GNSS data; if the first recognition result includes the second preset result, then Receive the second sensing data collected by the sensor module, wherein the second sensing data includes: the air pressure change value; determine the second recognition result of the current driving lane based on the sensed data; if the first recognition result The comparison with the second identification result is successful, and it is determined that the current driving lane is a viaduct lane. In this way, the viaduct lane can be identified through lane video, air pressure change values and GNSS data, which will help improve the accuracy of viaduct scene recognition and improve user experience.

Please refer to Figure 4. Figure 4 is a schematic flow chart of another viaduct identification method provided by an embodiment of the present application. It is applied to the electronic device described in Figure 1. The electronic device includes: a sensor module. The viaduct identification method includes:

Step 401: Obtain the lane video of the current driving lane;

Step 402: Determine the first recognition result of the current driving lane according to the lane video;

Step 403: Receive the sensing data collected by the sensor module;

Step 404: If the sensing data includes the first sensing data, determine the air pressure identification result based on the air pressure change value, determine the GNSS identification result based on the GNSS data, and determine the air pressure identification result and the GNSS based on the air pressure identification result. The recognition result determines the second recognition result;

Step 405: If the sensing data includes the second sensing data, determine the air pressure identification result based on the air pressure change value, and determine the second identification result based on the air pressure identification result;

Step 406: If the comparison between the first recognition result and the second recognition result is successful, determine that the current driving lane is a viaduct lane.

The specific description of the above-mentioned steps 401 to 406 may refer to the corresponding steps of the viaduct identification method described in FIG. 2 .

It can be seen that in the embodiment of the present application, the electronic device obtains the lane video of the current driving lane; determines the first recognition result of the current driving lane based on the lane video; receives the sensing data collected by the sensor module; if the sensor module If the sensing data includes the first sensing data, the air pressure recognition result is determined based on the air pressure change value, the GNSS recognition result is determined based on the GNSS data, and the second recognition result is determined based on the air pressure recognition result and the GNSS recognition result; if the sensor If the sensed data includes the second sensed data, the air pressure recognition result is determined based on the air pressure change value, and the second recognition result is determined based on the air pressure recognition result; if the first recognition result is successfully compared with the second recognition result, the air pressure recognition result is determined. The current driving lane is the viaduct lane. In this way, the first recognition result can be determined based on the lane video, the second recognition result can be determined through the air pressure change value and GNSS data, and the viaduct lane and viaduct scene can be identified by comparing the first recognition result and the second recognition result, which is beneficial to improving the viaduct scene recognition accuracy and improve user experience.

Consistent with the embodiments shown in Figures 2, 3, and 4, please refer to Figure 5. Figure 5 is a schematic structural diagram of an electronic device 500 provided by an embodiment of the present application. As shown in the figure, the electronic device The device 500 includes an application processor 510, a memory 520, a communication interface 530, a sensor module 540, and one or more programs 521, wherein the one or more programs 521 are stored in the above-mentioned memory 520 and configured by the above-mentioned Executed by application processor 510, the one or more programs 521 include instructions for performing the following steps:

Get the lane video of the current driving lane;

Determine the first identification result of the current driving lane based on the lane video;

Receive the sensing data collected by the sensor module, and determine the second recognition result of the current driving lane based on the sensed data;

If the comparison between the first recognition result and the second recognition result is successful, it is determined that the current driving lane is a viaduct lane.

It can be seen that in the embodiment of the present application, the electronic device obtains the lane video of the current driving lane; determines the first recognition result of the current driving lane based on the lane video; receives the sensing data collected by the sensor module, The second recognition result of the current driving lane is determined based on the sensed data; if the first recognition result and the second recognition result are successfully compared, the current driving lane is determined to be a viaduct lane. In this way, the viaduct scene can be identified based on lane video and sensor data, which will help improve the accuracy of viaduct scene recognition and improve user experience.

In a possible example, in determining the first recognition result of the current driving lane based on the lane video, the instructions in the program are specifically used to perform the following operations: obtain m contained in the lane video Frame images, where m is an integer greater than 0; perform an image recognition algorithm on the m frame images to obtain n frames of viaduct images containing viaduct lanes in the m frame images, where n is greater than or equal to 0, less than or An integer equal to m; calculate the m-frame image and the n-frame viaduct image according to the preset scene ratio calculation formula to obtain the viaduct scene ratio; determine whether the viaduct scene ratio is greater than the preset scene ratio threshold, and if The viaduct scene proportion is greater than the scene proportion threshold, the n frames of viaduct images are calculated according to the preset occlusion rate algorithm, and the n viaduct occlusion rates corresponding to the n frames of viaduct images are determined; according to the n viaducts The occlusion rate determines the average viaduct occlusion rate, and determines whether the average viaduct occlusion rate is greater than a preset occlusion rate threshold; if the average viaduct occlusion rate is not greater than the occlusion rate threshold, determines the first recognition result to be the first preset Assume the result; otherwise, determine the first recognition result to be the second preset result.

In a possible example, in terms of receiving the sensing data collected by the sensor module, the instructions in the program are specifically used to perform the following operations: if the first recognition result includes the first preset As a result, the first sensing data collected by the sensor module is received, wherein the first sensing data includes: air pressure change value and global navigation satellite positioning GNSS data; if the first identification result includes the third If the second preset result is obtained, the second sensing data collected by the sensor module is received, wherein the second sensing data includes: the air pressure change value.

In a possible example, in determining the second recognition result of the current driving lane based on the sensed data, the instructions in the program are specifically used to perform the following operations: if the sensed data includes the The first sensing data determines the air pressure recognition result based on the air pressure change value, determines the GNSS recognition result based on the GNSS data, and determines the second recognition result based on the air pressure recognition result and the GNSS recognition result; if If the sensing data includes the second sensing data, the air pressure identification result is determined based on the air pressure change value, and the second identification result is determined based on the air pressure identification result.

In a possible example, in determining the air pressure recognition result based on the air pressure change value, the instructions in the program are specifically used to perform the following operations: obtain the air pressure change value and the preset altitude change value calculation formula ; Use the air pressure change value as the input of the height change value calculation formula to determine the height change value corresponding to the air pressure change value; determine whether the height change value is greater than the preset height change threshold, if the height change value If the value is greater than the altitude change threshold, the air pressure recognition result is determined to be the first preset result; otherwise, the air pressure recognition result is determined to be the second preset result.

In a possible example, in determining the GNSS identification result based on the GNSS data, the instructions in the program are specifically used to perform the following operations: the GNSS data includes: satellite number change values and satellite signal noise ratio change value, then the GNSS identification results include: satellite number identification results and satellite signal-to-noise ratio identification results; determine whether the satellite number change value is greater than the preset number change threshold, if the satellite number change value is greater than the Quantity change threshold, determine the satellite quantity identification result as the first preset result, otherwise, determine the satellite quantity identification result as the second preset result; determine whether the satellite signal-to-noise ratio change value is greater than the preset result Assuming a signal-to-noise ratio change threshold, if the satellite signal-to-noise ratio change value is greater than the signal-to-noise ratio change threshold, determine the satellite signal-to-noise ratio identification result as the first preset result, otherwise, determine the The satellite signal-to-noise ratio identification result is the second preset result.

In a possible example, if the comparison between the first recognition result and the second recognition result is successful, the instructions in the program are specifically used to perform the following operations: determine whether the first recognition result and the second recognition result are compared. Whether the second recognition result is consistent, if the first recognition result is consistent with the second recognition result, it is determined that the comparison between the first recognition result and the second recognition result is successful; if the first recognition result It is inconsistent with the second identification result, and it is determined that the comparison between the first identification result and the second identification result is unsuccessful.

The above mainly introduces the solution of the embodiment of the present application from the perspective of the execution process on the method side. It can be understood that, in order to implement the above functions, the electronic device includes corresponding hardware structures and/or software modules that perform each function. Persons skilled in the art should easily realize that, with the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is performed by hardware or computer software driving the hardware depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each specific application, but such implementations should not be considered beyond the scope of this application.

Embodiments of the present application can divide the electronic device into functional units according to the above method examples. For example, each functional unit can be divided corresponding to each function, or two or more functions can be integrated into one control unit. The above integrated units can be implemented in the form of hardware or software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical function division. In actual implementation, there may be other division methods.

Figure 6 is a functional unit block diagram of the viaduct identification device 600 involved in the embodiment of the present application. The viaduct identification device 600 is applied to electronic equipment. The viaduct identification device 600 includes an acquisition unit 601, a determination unit 602, a receiving unit 603 and a comparison unit. Unit 604, where:

The acquisition unit 601 is used to acquire the lane video of the current driving lane;

Determining unit 602, configured to determine the first recognition result of the current driving lane according to the lane video;

The receiving unit 603 is configured to receive the sensing data collected by the sensor module, and determine the second recognition result of the current driving lane based on the sensed data;

The comparison unit 604 is configured to determine that the current driving lane is a viaduct lane if the comparison between the first recognition result and the second recognition result is successful.

It can be seen that in the embodiment of the present application, the electronic device obtains the lane video of the current driving lane; determines the first recognition result of the current driving lane based on the lane video; receives the sensing data collected by the sensor module, The second recognition result of the current driving lane is determined based on the sensed data; if the first recognition result and the second recognition result are successfully compared, the current driving lane is determined to be a viaduct lane. In this way, the viaduct scene can be identified based on lane video and sensor data, which will help improve the accuracy of viaduct scene recognition and improve user experience.

In a possible example, in determining the first recognition result of the current driving lane based on the lane video, the determination unit 602 is specifically configured to: obtain m frames of images contained in the lane video, Where, m is an integer greater than 0; perform an image recognition algorithm on the m frame images to obtain n frames of viaduct images containing viaduct lanes in the m frame images, where n is greater than or equal to 0 and less than or equal to m. Integer; calculate the m-frame image and the n-frame viaduct image according to the preset scene ratio calculation formula to obtain the viaduct scene ratio; determine whether the viaduct scene ratio is greater than the preset scene ratio threshold, if the viaduct If the scene proportion is greater than the scene proportion threshold, the n frames of viaduct images are calculated according to the preset occlusion rate algorithm to determine the n viaduct occlusion rates corresponding to the n frames of viaduct images; determined based on the n viaduct occlusion rates Average viaduct occlusion rate, determine whether the average viaduct occlusion rate is greater than the preset occlusion rate threshold; if the average viaduct occlusion rate is not greater than the occlusion rate threshold, determine the first recognition result as the first preset result; Otherwise, the first recognition result is determined to be the second preset result.

In a possible example, in terms of receiving the sensing data collected by the sensor module, the receiving unit 603 is specifically configured to: if the first recognition result includes the first preset result, then Receive the first sensing data collected by the sensor module, where the first sensing data includes: air pressure change values and global navigation satellite positioning GNSS data; if the first recognition result includes the second preset As a result, the second sensing data collected by the sensor module is received, wherein the second sensing data includes: the air pressure change value.

In a possible example, in determining the second recognition result of the current driving lane based on the sensed data, the receiving unit 603 is specifically configured to: if the sensed data includes the first sensed data, sense data, determine the air pressure recognition result based on the air pressure change value, determine the GNSS recognition result based on the GNSS data, determine the second recognition result based on the air pressure recognition result and the GNSS recognition result; if the sensing If the data includes the second sensing data, the air pressure identification result is determined based on the air pressure change value, and the second identification result is determined based on the air pressure identification result.

In a possible example, in determining the air pressure identification result based on the air pressure change value, the receiving unit 603 is specifically configured to: obtain the air pressure change value and a preset height change value calculation formula; The air pressure change value is used as the input of the height change value calculation formula to determine the height change value corresponding to the air pressure change value; it is judged whether the height change value is greater than the preset height change threshold. If the height change value is greater than the preset height change threshold, If the height change threshold is determined, the air pressure recognition result is determined to be the first preset result; otherwise, the air pressure recognition result is determined to be the second preset result.

In a possible example, in determining the GNSS identification result based on the GNSS data, the receiving unit 603 is specifically configured to: the GNSS data includes: a satellite number change value and a satellite signal-to-noise ratio change value , then the GNSS identification results include: satellite number identification results and satellite signal-to-noise ratio identification results; determine whether the satellite number change value is greater than the preset number change threshold, if the satellite number change value is greater than the number change threshold , determine that the satellite number identification result is the first preset result, otherwise, determine that the satellite number identification result is the second preset result; determine whether the satellite signal-to-noise ratio change value is greater than the preset signal Noise ratio change threshold. If the satellite signal-to-noise ratio change value is greater than the signal-to-noise ratio change threshold, the satellite signal-to-noise ratio identification result is determined to be the first preset result. Otherwise, the satellite signal-to-noise ratio identification result is determined to be the first preset result. The ratio recognition result is the second preset result.

In a possible example, if the comparison between the first recognition result and the second recognition result is successful, the comparison unit 604 is specifically configured to: determine whether the first recognition result and the second recognition result are compared successfully. Whether the second recognition result is consistent, if the first recognition result is consistent with the second recognition result, it is determined that the comparison between the first recognition result and the second recognition result is successful; if the first recognition result is consistent with the second recognition result, If the second recognition result is inconsistent, it is determined that the comparison between the first recognition result and the second recognition result is unsuccessful.

Embodiments of the present application also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program causes the computer to execute part or all of the steps of any method described in the above method embodiments. , the above-mentioned computer includes electronic equipment.

Embodiments of the present application also provide a computer program product. The computer program product includes a non-transitory computer-readable storage medium storing a computer program. The computer program is operable to cause the computer to execute any of the methods described in the above method embodiments. Some or all steps of a method. The computer program product may be a software installation package, and the computer includes electronic equipment.

It should be noted that for the sake of simple description, the foregoing method embodiments are expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence. Because in accordance with this application, certain steps may be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily necessary for this application.

In the above embodiments, each embodiment is described with its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

In the several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the above units is only a logical function division. In actual implementation, there may be other divisions. For example, multiple units or components may be combined or integrated. to another system, or some features can be ignored, or not implemented. On the other hand, the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical or other forms.

The units described above as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or software functional units.

If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, It includes several instructions to cause a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the above methods in various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable memory. The memory can include: a flash disk. , read-only memory (English: Read-Only Memory, abbreviation: ROM), random access device (English: Random Access Memory, abbreviation: RAM), magnetic disk or optical disk, etc.

The embodiments of the present application have been introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and the core idea of the present application; at the same time, for Those of ordinary skill in the art will have changes in the specific implementation and application scope based on the ideas of the present application. In summary, the content of this description should not be understood as a limitation of the present application.

Claims (9)

1. An elevated bridge identification method, characterized by being applied to an electronic device, the electronic device comprising: a sensor module, the method comprising:

acquiring a lane video of a current driving lane;

determining a first recognition result of the current driving lane according to the lane video, wherein the first recognition result comprises: acquiring m frames of images contained in the lane video, wherein m is an integer greater than 0; performing an image recognition algorithm on the m-frame images to obtain n-frame viaduct images containing viaduct lanes in the m-frame images, wherein n is an integer greater than or equal to 0 and less than or equal to m; calculating the m frames of images and the n frames of viaduct images according to a preset scene proportion calculation formula to obtain viaduct scene proportions; judging whether the viaduct scene proportion is larger than a preset scene proportion threshold value, if so, calculating the n frames of viaduct images according to a preset shielding rate algorithm, and determining n viaduct shielding rates corresponding to the n frames of viaduct images; determining an average viaduct shielding rate according to the n viaduct shielding rates, and judging whether the average viaduct shielding rate is greater than a preset shielding rate threshold value; if the average overhead bridge shielding rate is not greater than the shielding rate threshold, determining that the first recognition result is a first preset result; otherwise, determining the first identification result as a second preset result;

Receiving sensing data acquired by the sensor module, and determining a second recognition result of the current driving lane according to the sensing data;

and if the first recognition result is successfully compared with the second recognition result, determining that the current driving lane is a viaduct lane.

2. The method of claim 1, wherein the receiving the sensor data collected by the sensor module comprises:

if the first identification result includes the first preset result, receiving first sensing data acquired by the sensor module, wherein the first sensing data includes: barometric pressure change values and global navigation satellite positioning, GNSS, data;

if the first identification result includes the second preset result, receiving second sensing data acquired by the sensor module, wherein the second sensing data includes: the air pressure variation value.

3. The method of claim 2, wherein said determining a second recognition result of the current driving lane based on the sensed data comprises:

if the sensing data comprises the first sensing data, determining an air pressure identification result according to the air pressure change value, determining a GNSS identification result according to the GNSS data, and determining a second identification result according to the air pressure identification result and the GNSS identification result;

If the sensing data comprises the second sensing data, determining an air pressure identification result according to the air pressure change value, and determining the second identification result according to the air pressure identification result.

4. A method according to claim 3, wherein said determining an air pressure identification result from said air pressure variation value comprises:

acquiring the air pressure change value and a preset height change value calculation formula;

taking the air pressure change value as the input of the height change value calculation formula, and determining a height change value corresponding to the air pressure change value;

judging whether the height change value is larger than a preset height change threshold value, and if the height change value is larger than the height change threshold value, determining the air pressure identification result as the first preset result;

otherwise, determining the air pressure identification result as the second preset result.

5. The method of claim 4, wherein said determining said GNSS identification results from said GNSS data comprises:

the GNSS data includes: the satellite quantity change value and the satellite signal-to-noise ratio change value, and the GNSS identification result comprises: satellite number recognition results and satellite signal-to-noise ratio recognition results;

Judging whether the satellite quantity change value is larger than a preset quantity change threshold value, if the satellite quantity change value is larger than the quantity change threshold value, determining that the satellite quantity recognition result is the first preset result, otherwise, determining that the satellite quantity recognition result is the second preset result;

judging whether the satellite signal-to-noise ratio change value is larger than a preset signal-to-noise ratio change threshold, if so, determining that the satellite signal-to-noise ratio identification result is the first preset result, otherwise, determining that the satellite signal-to-noise ratio identification result is the second preset result.

6. The method of claim 1, wherein if the comparison of the first recognition result and the second recognition result is successful, comprising:

judging whether the first recognition result is consistent with the second recognition result or not, and if the first recognition result is consistent with the second recognition result, determining that the first recognition result is successfully compared with the second recognition result; if the first recognition result is inconsistent with the second recognition result, determining that the comparison of the first recognition result and the second recognition result is unsuccessful.

7. A overpass identification device, characterized by being applied to an electronic device, the electronic device comprising: a sensor module, the apparatus comprising:

the acquisition unit is used for acquiring a lane video of the current driving lane;

the determining unit is used for determining a first recognition result of the current driving lane according to the lane video, and comprises the following steps: acquiring m frames of images contained in the lane video, wherein m is an integer greater than 0; performing an image recognition algorithm on the m-frame images to obtain n-frame viaduct images containing viaduct lanes in the m-frame images, wherein n is an integer greater than or equal to 0 and less than or equal to m; calculating the m frames of images and the n frames of viaduct images according to a preset scene proportion calculation formula to obtain viaduct scene proportions; judging whether the viaduct scene proportion is larger than a preset scene proportion threshold value, if so, calculating the n frames of viaduct images according to a preset shielding rate algorithm, and determining n viaduct shielding rates corresponding to the n frames of viaduct images; determining an average viaduct shielding rate according to the n viaduct shielding rates, and judging whether the average viaduct shielding rate is greater than a preset shielding rate threshold value; if the average overhead bridge shielding rate is not greater than the shielding rate threshold, determining that the first recognition result is a first preset result; otherwise, determining the first identification result as a second preset result;

The receiving unit is used for receiving the sensing data acquired by the sensor module and determining a second recognition result of the current driving lane according to the sensing data;

and the comparison unit is used for determining that the current driving lane is a viaduct lane if the first recognition result and the second recognition result are successfully compared.

8. An electronic device comprising a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-6.

9. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program, which is executed by a processor to implement the method of any one of claims 1 to 6.