Positioning method and device and intelligent driving equipment

Abstract

A positioning method and apparatus, and a vehicle. The method comprises: acquiring first position information of a first light source (S301); determining a first ambient light sensor corresponding to the first light source, the first ambient light sensor being located in an ambient light sensor group (S302); and determining second position information of the vehicle according to the orientation information of the first ambient light sensor and the first position information (S303). Through the method, the vehicle can be positioned in a low-cost and high-precision manner in a scene with insufficient natural light.

Description

Positioning method, device and intelligent driving equipment Technical Field

[0001] The present application relates to the field of intelligent driving, and more specifically, to a positioning method, apparatus, and intelligent driving device. Background Art

[0002] As vehicles are widely used in daily life, the accuracy of vehicle positioning has become increasingly important. Currently, most vehicles can be positioned using the Global Navigation Satellite System (GNSS).

[0003] However, GNSS positioning accuracy is unstable and cannot be performed in some scenarios (for example, scenarios with poor network signals). In these scenarios, although visual fusion positioning technology can assist or replace GNSS for positioning, since the perception object of visual fusion positioning technology is visible light, the precision and accuracy of vehicle positioning are reduced in scenarios where the vehicle lacks natural light. In addition, although laser fusion positioning technology can also perform positioning, the perception object of laser fusion positioning technology is laser, and the application cost of this technology is relatively high. Therefore, in scenarios where the vehicle lacks natural light, how to locate the vehicle at low cost and with high precision is an urgent problem that needs to be solved.

[0004] Summary of the Invention

[0005] The present application provides a positioning method, apparatus, and intelligent driving device, which enable the intelligent driving device to perform positioning in a low-cost, high-precision manner in scenes with insufficient natural light. The intelligent driving device includes a vehicle.

[0006] In a first aspect, a positioning method is provided, the method comprising: obtaining first position information of a first light source; determining a first ambient light sensor corresponding to the first light source, the first ambient light sensor being located in an ambient light sensor group, and the ambient light sensor group being installed on an intelligent driving device; and determining second position information of the intelligent driving device based on orientation information of the first ambient light sensor and the first position information.

[0007] The first light source may be a point light source on a road (e.g., a street lamp). The first location information may indicate the geographic location of the first light source. The first location information may be obtained from a high-precision map or a point cloud map, or from other devices via vehicle-to-everything (V2X) technology.

[0008] Optionally, the ambient light sensor group may include multiple ambient light sensors, whose overall shape (appearance) may be a smooth, continuous curved surface without any concave portion. The multiple ambient light sensors may sense light in a direction perpendicular to the curved surface of the ambient light sensors.

[0009] Optionally, the orientation information of the first ambient light sensor may be understood as the direction in which the first ambient light sensor faces the first light source. Furthermore, the orientation information may be the posture of the first ambient light sensor.

[0010] It should be understood that the positioning method provided in this application can be applied in scenes such as night, dusk, dawn, and evening.

[0011] In this application, the second position information of the intelligent driving device can be determined based on the orientation information of the first ambient light sensor and the first position information of the first light source. In this way, the intelligent driving device can be positioned in a low-cost and high-precision manner in scenes with insufficient natural light. The intelligent driving device includes a vehicle.

[0012] In combination with the first aspect, in certain implementations of the first aspect, determining the first ambient light sensor based on the light emitted by the first light source includes: obtaining the light intensity value corresponding to each ambient light sensor in the ambient light sensor group and the first light source; and determining that the ambient light sensor with the largest light intensity value in the ambient light sensor group is the first ambient light sensor.

[0013] The light intensity value corresponding to each ambient light sensor and the first light source can be obtained by obtaining the reading of each ambient light sensor, which includes: the sensor corresponding to the maximum reading is the first ambient light sensor.

[0014] Exemplarily, the reading may range from 0 to 90. A larger reading indicates a greater light intensity value corresponding to the ambient light sensor and the first light source, and the first light source directly or approximately directly illuminates the first ambient light sensor.

[0015] In this application, the light intensity values ​​corresponding to each ambient light sensor in the ambient light sensor group and the first light source can be counted to determine that the sensor with the largest light intensity value is the first ambient sensor. In this way, the first ambient light sensor corresponding to the first light source can be quickly and efficiently determined, thereby calculating the precise positioning information of the intelligent driving device.

[0016] In combination with the first aspect, in certain implementations of the first aspect, the orientation information is the position of the first ambient light sensor in a world coordinate system; before determining the second position information of the intelligent driving device based on the orientation information of the first ambient light sensor and the first position information, the method further includes: obtaining third position information of the intelligent driving device, where the third position information is determined based on a global navigation satellite system; determining the second position information of the intelligent driving device based on the orientation information of the first ambient light sensor and the first position information includes: determining fourth position information of the first light source based on the position of the first ambient light sensor in the world coordinate system, where the fourth position information is determined based on theoretical incident light of the first ambient light sensor and a first plane, where the first plane is a plane where the first light source is located, the first plane is determined based on a second plane, the second plane is a plane where the intelligent driving device is located, and the first plane is parallel to the second plane; determining a first offset vector based on the first position information and the fourth position information; and determining the second position information of the intelligent driving device based on the first offset vector and the third position information.

[0017] The world coordinate system may refer to an absolute coordinate system of a system. The world coordinate system may be a system that describes the positional relationship of objects on the earth, and may be used to represent the absolute position of objects on the earth.

[0018] Optionally, the third position information may be rough initial positioning information of the intelligent driving device, and the third position information may be used to determine which light source or light sources the intelligent driving device is located near.

[0019] After determining the position and posture of the first ambient light sensor in the world coordinate system, the theoretical incident light of the ambient light sensor can be obtained. The intersection of the theoretical incident light and the first plane is the fourth position information of the first light source. If the first position information of the intelligent driving device is accurate positioning information, the first position information and the fourth position information of the first light source are the same. There is no need to calibrate the third position information of the intelligent driving device. In most cases, the first position information and the fourth position information are not the same, and in this case, the offset vector needs to be calculated. The deviation vector can be understood as the distance between the first position information and the fourth position information. Using the offset vector to calibrate the third position information of the intelligent driving device can obtain the second position information (accurate positioning information of the intelligent driving device).

[0020] In the above calculation process, the first plane is determined based on the second plane. The first plane is the plane where the light source is located and is parallel to the second plane, which is the plane where the intelligent driving device is located. Optionally, the second plane is determined based on the driving direction and posture of the intelligent driving device. Alternatively, if the intelligent driving device is considered a point in the world coordinate system, the second plane can be a tangent plane to that point on the road surface.

[0021] It should be understood that the theoretical incident light, the first plane and the second plane can be respectively expressed in the world coordinate system as: the theoretical incident light equation, the first plane equation and the second plane equation.

[0022] It should also be understood that, in this application, the positioning information of the intelligent driving device and the position information of the intelligent driving device have the same meaning.

[0023] In this application, when the initial position information of the intelligent driving device is inaccurate, the theoretical incident light can be determined based on the position of the first ambient light sensor in the world coordinate system, and the theoretical positioning point of the first light source can be obtained, thereby obtaining an offset vector, and using this offset vector to calibrate the initial position of the intelligent driving device. In this way, accurate positioning information of the intelligent driving device can be obtained.

[0024] In combination with the first aspect, in some implementations of the first aspect, the method also includes: obtaining fifth position information of the second light source; determining a second ambient light sensor corresponding to the second light source, the second ambient light sensor being located in the ambient light sensor group; determining the sixth position information of the second light source based on the position of the second ambient light sensor in the world coordinate system, the sixth position information being determined by the theoretical incident light of the second ambient light sensor and the third plane; the third plane is the plane where the second light source is located, the third plane is determined based on the second plane, and the second plane is parallel to the third plane; determining a second offset vector based on the fifth position information and the sixth position information; determining the second position information of the intelligent driving device based on the first offset vector and the third position information includes: determining the second position information based on the first offset vector, the second offset vector and the third position information.

[0025] Optionally, in the present application, when the intelligent driving device is located between two light sources, the correct first ambient light sensor and second ambient light sensor can be determined by performing mathematical analysis on the readings of the ambient light sensor group.

[0026] Optionally, local maximum values ​​of the ambient light sensor group may be analyzed to obtain local maximum light intensity readings corresponding to the first light source and the second light source, thereby obtaining information of the first ambient light sensor and the second ambient light sensor.

[0027] In the present application, when the acquired initial position information of the intelligent driving device is inaccurate, if the intelligent driving device is located between two light sources, the second offset vector can be determined based on the fifth position information and the sixth position information of the second light source, so that the initial position of the intelligent driving device can be calibrated according to the first offset vector and the second offset vector, which is conducive to obtaining more accurate position information of the intelligent driving device.

[0028] In combination with the first aspect, in some implementations of the first aspect, the ambient light sensor group includes a plurality of ambient light sensors, and a surface of each of the plurality of ambient light sensors is a smooth curved surface without concavities.

[0029] Optionally, the ambient light sensor group may be a component that is smooth and continuous as a whole, without any concave curved surface.

[0030] In the present application, the surface of each ambient light sensor in the ambient light sensor group is a smooth surface without concave curves. In this way, it is helpful to obtain theoretical incident light more accurately, thereby obtaining more accurate position information of the intelligent driving device.

[0031] In combination with the first aspect, in some implementations of the first aspect, the ambient light sensor group includes solar panels, and the solar panels are distributed on the top of the intelligent driving device.

[0032] In the present application, the ambient light sensor group may include a solar panel. In this way, the intelligent driving device can be charged while driving and can also achieve low-cost, high-precision positioning.

[0033] In a second aspect, a positioning device is provided, which includes: an acquisition unit and a processing unit: the acquisition unit is used to obtain first position information of a first light source; the processing unit is used to: determine a first ambient light sensor corresponding to the first light source, the first ambient light sensor is located in an ambient light sensor group, and the ambient light sensor group is installed on an intelligent driving device; and determine second position information of the intelligent driving device based on the orientation information of the first ambient light sensor and the first position information.

[0034] In combination with the second aspect, in certain implementations of the second aspect, the acquisition unit is further used to obtain the light intensity value corresponding to each ambient light sensor in the ambient light sensor group and the first light source; the processing unit is used to determine that the ambient light sensor with the largest light intensity value in the ambient light sensor group is the first ambient light sensor.

[0035] In combination with the second aspect, in certain implementations of the second aspect, the orientation information is the position of the first ambient light sensor in the world coordinate system; the acquisition unit is also used to obtain third position information of the intelligent driving device, and the third position information is determined based on the global navigation satellite system; the processing unit is used to: determine the fourth position information of the first light source according to the position of the first ambient light sensor in the world coordinate system, and the fourth position information is determined based on the theoretical incident light of the first ambient light sensor and the first plane, the first plane is the plane where the first light source is located, the first plane is determined based on the second plane, the second plane is the plane where the intelligent driving device is located, and the first plane is parallel to the second plane; determine a first offset vector based on the first position information and the fourth position information; determine the second position information of the intelligent driving device based on the first offset vector and the third position information.

[0036] In combination with the second aspect, in some implementations of the second aspect, the acquisition unit is also used to obtain the fifth position information of the second light source; the processing unit is also used to: determine the second ambient light sensor corresponding to the second light source, the second ambient light sensor is located in the ambient light sensor group; and determine the sixth position information of the second light source based on the posture of the second ambient light sensor in the world coordinate system, the sixth position information is determined by the theoretical incident light of the second ambient light sensor and the third plane; the third plane is the plane where the second light source is located, the third plane is determined based on the second plane, and the second plane is parallel to the third plane; determine the second offset vector based on the fifth position information and the sixth position information; determine the second position information based on the first offset vector, the second offset vector and the third position information.

[0037] In combination with the second aspect, in some implementations of the second aspect, the ambient light sensor group includes a plurality of ambient light sensors, and a surface of each of the plurality of ambient light sensors is a smooth curved surface without concavities.

[0038] In combination with the second aspect, in certain implementations of the second aspect, the ambient light sensor group includes solar panels, and the solar panels are distributed on the top of the intelligent driving device.

[0039] In a third aspect, a positioning device is provided, comprising: at least one processor and a memory, wherein the at least one processor is coupled to the memory and is configured to read and execute instructions in the memory, so that the device implements the method in the first aspect and various implementations described above.

[0040] In a fourth aspect, a computer-readable medium is provided, wherein the computer-readable medium stores a program code, and when the computer program code is run on a computer, the computer executes the method in the above-mentioned first aspect and its various implementations.

[0041] In a fifth aspect, a chip is provided, which includes a circuit for executing the methods in the above aspects.

[0042] In a sixth aspect, an intelligent driving device is provided, which includes: the positioning device in the second to third aspects and an ambient light sensor group, wherein the ambient light sensor group includes multiple ambient light sensors, and the surface of each of the multiple ambient light sensors is a smooth and non-concave curved surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] FIG1 is a functional schematic diagram of an intelligent driving device provided in an embodiment of the present application;

[0044] FIG2 is a system architecture applicable to the positioning method provided in an embodiment of the present application;

[0045] FIG3 is a schematic flow chart of a positioning method provided in an embodiment of the present application;

[0046] FIG4 is a schematic flow chart of another positioning method provided in an embodiment of the present application;

[0047] FIG5 is a schematic diagram of the position of an ambient light sensor group on a vehicle provided in an embodiment of the present application;

[0048] FIG6 is a schematic diagram of the shape and orientation of an ambient light sensor group provided in an embodiment of the present application;

[0049] FIG7 is a line graph showing the incident angle of light and the luminous flux per unit area of ​​an ambient light sensor provided by an embodiment of the present application;

[0050] FIG8 is a schematic diagram of ambient light sensor readings that can be obtained by a sub-sensor provided in an embodiment of the present application;

[0051] FIG9 is a schematic diagram of a method for determining a positioning point M provided in an embodiment of the present application;

[0052] FIG10 is an application scenario applicable to the positioning method provided in an embodiment of the present application;

[0053] FIG11 is another application scenario applicable to the positioning method provided in an embodiment of the present application;

[0054] FIG12 is a positioning device provided in an embodiment of the present application;

[0055] FIG13 is another positioning device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In this application, "at least one" refers to one or more, and "more than one" refers to two or more. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0057] In the embodiments of this application, prefixes such as "first" and "second" are used only to distinguish different description objects and have no limiting effect on the position, order, priority, quantity, or content of the described objects. The use of prefixes such as ordinal numbers in the embodiments of this application to distinguish description objects does not constitute a limitation on the described objects. For a statement of the described objects, please refer to the description in the context of the claims or embodiments, and the use of such prefixes should not constitute an unnecessary limitation.

[0058] As vehicles are widely used in daily life, the accuracy of vehicle positioning has become increasingly important. Currently, most vehicles can be positioned using the GNSS system.

[0059] However, GNSS positioning accuracy is unstable and cannot be achieved in some scenarios (for example, scenarios with poor network signals). In these scenarios, although visual fusion positioning technology can assist or replace GNSS positioning, because visual fusion positioning technology perceives visible light, the precision and accuracy of vehicle positioning are reduced in scenarios with insufficient natural light. In particular, due to differences in the use of algorithms, the expected error in vehicle positioning accuracy and stability at night may increase by 2 to 4 times.

[0060] Furthermore, while laser fusion positioning technology can also provide positioning, it relies on lasers as sensors, resulting in relatively high energy, procurement, and computing costs. Therefore, finding a low-cost, high-precision vehicle location solution in specific scenarios with insufficient natural light is a pressing issue. Examples of these scenarios include nighttime, dusk, dawn, and evening.

[0061] This application provides a positioning method, apparatus, and intelligent driving device that enable intelligent driving devices, including vehicles, to be positioned in low-cost, high-precision manner in scenarios with insufficient natural light. The technical solutions in the embodiments of this application will be described below with reference to the accompanying drawings.

[0062] FIG1 is a functional schematic diagram of an intelligent driving device 100 provided in an embodiment of the present application. It should be understood that FIG1 and the related description are merely examples and do not limit the intelligent driving device in the embodiment of the present application.

[0063] During implementation, the intelligent driving device 100 can be configured in a fully or partially autonomous driving mode, or can be manually driven by a user. For example, the intelligent driving device 100 can obtain environmental information about its surroundings through the perception system 120 and, based on analysis of the environmental information, derive an autonomous driving strategy to achieve fully autonomous driving, or present the analysis results to the user to achieve partially autonomous driving.

[0064] The intelligent driving device 100 may include multiple subsystems, such as a perception system 120, a computing platform 130, and a display device 140. Alternatively, the intelligent driving device 100 may include more or fewer subsystems, and each subsystem may include one or more components. Furthermore, each subsystem and component of the intelligent driving device 100 may be interconnected via wired or wireless means.

[0065] The perception system 120 may include several sensors for sensing information about the environment surrounding the intelligent driving device 100. For example, the perception system 120 may include a positioning system, which may be a global positioning system (GPS), a Beidou system, or other positioning systems. The perception system 120 may include one or more of an inertial measurement unit (IMU), a laser radar, a millimeter-wave radar, an ultrasonic radar, and a camera.

[0066] Some or all functions of the intelligent driving device 100 can be controlled by the computing platform 130. The computing platform 130 may include processors 131 to 13n (n is a positive integer). A processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with the ability to read and execute instructions, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented by an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration file to implement the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, the processor may also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc. In addition, the computing platform 130 may also include a memory for storing instructions, and some or all of the processors 131 to 13n may call the instructions in the memory to implement corresponding functions.

[0067] The computing platform 130 can control the functions of the intelligent driving device 100 based on input received from various subsystems (e.g., the perception system 120). In some embodiments, the computing platform 130 can be used to provide control over many aspects of the intelligent driving device 100 and its subsystems.

[0068] Optionally, the above components are only an example. In actual applications, the components in the above modules may be added or deleted according to actual needs. Figure 1 should not be understood as a limitation to the embodiments of the present application.

[0069] While traveling on a road, the intelligent driving device 100 can identify objects in its surroundings to determine adjustments to its current speed. These objects can be other vehicles, traffic control devices, or other types of objects. In some examples, each identified object can be considered independently, and the speed adjustment to be made by the intelligent driving device 100 can be determined based on its respective characteristics, such as its current speed, acceleration, and distance from the vehicle.

[0070] Optionally, the intelligent driving device 100 or a perception and computing device associated with the intelligent driving device 100 (e.g., computing platform 130) can predict the behavior of the identified objects based on the characteristics of the identified objects and the state of the surrounding environment (e.g., traffic, rain, ice on the road, etc.). Optionally, each identified object depends on the behavior of each other, so all identified objects can be considered together to predict the behavior of a single identified object.

[0071] The intelligent driving device 100 in this application may include: road vehicles, water vehicles, air vehicles, industrial equipment, agricultural equipment, or entertainment equipment, etc. For example, the intelligent driving device can be a vehicle, which is a vehicle in a broad sense, and can be a vehicle (such as a commercial vehicle, a passenger car, a motorcycle, a flying car, a train, etc.), an industrial vehicle (such as a forklift, a trailer, a tractor, etc.), an engineering vehicle (such as an excavator, a bulldozer, a crane, etc.), agricultural equipment (such as a mower, a harvester, etc.), amusement equipment, a toy vehicle, etc. The embodiment of this application does not specifically limit the type of vehicle. For another example, the intelligent driving device can be a vehicle such as an airplane or a ship.

[0072] The following uses a vehicle as an example of an intelligent driving device to illustrate the technical problems that need to be solved in this application and the technical solutions adopted.

[0073] Before introducing the positioning method, the system architecture applicable to the positioning method provided in the embodiment of the present application is first introduced.

[0074] FIG2 is a system architecture 200 applicable to the positioning method provided in an embodiment of the present application. The system architecture shown in FIG2 can be applied to the intelligent driving device 100 in FIG1 .

[0075] As shown in Figure 2, architecture 200 may include: a sensor abstraction module 210, a perception module 220, a positioning module 230, and a planning and control module 240. Taking the vehicle's autonomous driving scenario as an example, the sensor abstraction module 210 can pre-process input data based on the sensor type and input the pre-processed data into the perception module 220 and the positioning module 230. The perception module 220 can obtain the vehicle's driving environment data based on the input data and send the driving environment data to the positioning module 230. The positioning module 230 can locate the vehicle based on the vehicle's driving environment data and the data pre-processed by the sensor abstraction module 210, and input the positioning result data into the planning and control module 240. The planning and control module 240 can implement the autonomous driving function based on the positioning result data.

[0076] The embodiment of the present application optimizes the data output by the sensor abstraction module 210 and the perception module 220 to the positioning module 230, thereby improving the accuracy of vehicle positioning.

[0077] It should be understood that the sensor abstraction module 210 and the perception module 220 may be located in the perception system 120 of FIG. 1 , and the positioning module 230 and the planning control module 240 may be located in the computing platform 130 of FIG. 1 .

[0078] FIG3 is a schematic flow chart of a positioning method 300 provided in an embodiment of the present application. Method 300 may be performed by the intelligent driving device 100 in FIG1 , or by the computing platform 130 in the intelligent driving device 100, or by a system on chip (SOC) in the computing platform 130, or by a processor in the computing platform 130. Method 300 may include steps S301-S303.

[0079] S301: Acquire first position information of a first light source.

[0080] The first light source may be a point light source on a road (e.g., a street lamp). The first location information may be used to indicate the geographic location of the first light source. The first location information may be obtained from a high-precision map or a point cloud map, or from other communication devices via the Internet of Vehicles.

[0081] S302: Determine a first ambient light sensor corresponding to the first light source.

[0082] Optionally, the ambient light sensor group includes multiple ambient light sensors, whose overall shape (appearance) can be a smooth and continuous curved surface without any concave parts, and the light perception direction of each of the multiple ambient light sensors can be a direction perpendicular to the curved surface of the ambient light sensor.

[0083] S303 : Determine second position information of the vehicle according to the orientation information of the first ambient light sensor and the first position information.

[0084] Optionally, the orientation information of the first ambient light sensor may be understood as the direction in which the first ambient light sensor faces the first light source. Furthermore, the orientation information may be the posture of the first ambient light sensor.

[0085] In an embodiment of the present application, the second position information of the vehicle can be determined based on the orientation information of the first ambient light sensor and the first position information of the first light source. In this way, the vehicle can be positioned in a low-cost and high-precision manner in a scene with insufficient natural light.

[0086] In one possible implementation, determining the first ambient light sensor based on the light emitted by the first light source includes: obtaining the light intensity value corresponding to each ambient light sensor in the ambient light sensor group and the first light source; and determining that the ambient light sensor with the largest light intensity value in the ambient light sensor group is the first ambient light sensor.

[0087] The light intensity value corresponding to each ambient light sensor and the first light source can be obtained by obtaining the reading of each ambient light sensor, which includes: the sensor corresponding to the maximum reading is the first ambient light sensor.

[0088] Illustratively, the reading may range from 0 to 90. A larger reading indicates a greater light intensity value corresponding to the ambient light sensor and the first light source, and the first light source directly or approximately directly illuminates the first ambient light sensor.

[0089] In an embodiment of the present application, the light intensity values ​​corresponding to the ambient light sensor and the first light source can be counted to determine that the sensor with the largest light intensity value is the first ambient sensor. In this way, the first ambient light sensor corresponding to the first light source can be quickly and efficiently determined, thereby calculating the precise positioning information of the vehicle.

[0090] In one possible implementation, the orientation information is the position of the first ambient light sensor in the world coordinate system; before determining the second position information of the vehicle based on the orientation information of the first ambient light sensor and the first position information, the method also includes: obtaining third position information of the vehicle, and the third position information is determined based on a global navigation satellite system; determining the second position information of the vehicle based on the orientation information of the first ambient light sensor and the first position information includes: determining the fourth position information of the first light source based on the position of the first ambient light sensor in the world coordinate system, and the fourth position information is determined based on the theoretical incident light of the first ambient light sensor and a first plane, the first plane is the plane where the first light source is located, the first plane is determined based on the second plane, the second plane is the plane where the vehicle is located, and the first plane is parallel to the second plane; determining a first offset vector based on the first position information and the fourth position information; and determining the second position information of the vehicle based on the first offset vector and the third position information.

[0091] The world coordinate system may refer to an absolute coordinate system of a system. The world coordinate system may be a system that describes the positional relationship of objects on the earth, and may be used to represent the absolute position of objects on the earth.

[0092] Optionally, the third position information may be rough initial positioning information of the vehicle, and based on the third position information, it can be determined which light source or light sources the vehicle is located near.

[0093] After determining the position of the first ambient light sensor in the world coordinate system, the theoretical incident light of the ambient light sensor can be obtained. The intersection of the theoretical incident light and the first plane is the fourth position information of the first light source. If the first position information of the vehicle is accurate positioning information, the first position information and the fourth position information of the first light source are the same. There is no need to calibrate the third position information of the vehicle. In most cases, the first position information and the fourth position information are not the same, and in this case, an offset vector needs to be calculated. The deviation vector can be understood as the distance between the first position information and the fourth position information. Using the offset vector to calibrate the third position information of the vehicle can obtain the second position information (accurate positioning information of the vehicle).

[0094] In the above calculation process, the first plane is determined based on the second plane. The first plane is the plane where the light source is located and is parallel to the second plane, which is the plane where the vehicle is located. Alternatively, the second plane can be determined based on the vehicle's direction and posture. Alternatively, if the vehicle is considered a point in the world coordinate system, the second plane can be a tangent plane to that point on the road surface.

[0095] It should be understood that the theoretical incident light, the first plane and the second plane can be respectively expressed in the world coordinate system as: the theoretical incident light equation, the first plane equation and the second plane equation.

[0096] It should also be understood that in the embodiments of the present application, the vehicle positioning information and the vehicle position information have the same meaning.

[0097] In the embodiment of the present application, when the acquired initial vehicle position information is inaccurate, the theoretical incident light can be determined based on the position of the first ambient light sensor in the world coordinate system, and the theoretical positioning point of the first light source can be obtained, thereby obtaining an offset vector, and the offset vector is used to calibrate the initial position of the vehicle. In this way, accurate vehicle positioning information can be obtained.

[0098] In one possible implementation, the method also includes: obtaining fifth position information of the second light source; determining a second ambient light sensor corresponding to the second light source, the second ambient light sensor being located in the ambient light sensor group; determining the sixth position information of the second light source based on the posture of the second ambient light sensor in the world coordinate system, the sixth position information being determined by the theoretical incident light of the second ambient light sensor and the third plane; the third plane is the plane where the second light source is located, the third plane is determined based on the second plane, and the second plane is parallel to the third plane; determining a second offset vector based on the fifth position information and the sixth position information; determining the second position information of the vehicle based on the first offset vector and the third position information includes: determining the second position information based on the first offset vector, the second offset vector and the third position information.

[0099] Alternatively, if the vehicle is located between two light sources, the correct first and second ambient light sensors may be determined by mathematically analyzing the ambient light sensor group readings.

[0100] Optionally, the local maximum values ​​of the ambient light sensor group may be analyzed to obtain the local maximum light intensity values ​​corresponding to the first light source and the second light source, thereby obtaining correct information of the first ambient light sensor and the second ambient light sensor.

[0101] In an embodiment of the present application, when the acquired initial position information of the vehicle is inaccurate, if the vehicle is located between two light sources, the second offset vector can be determined based on the fifth position information and the sixth position information of the second light source, so that the initial position of the vehicle can be calibrated according to the first offset vector and the second offset vector, which is conducive to obtaining more accurate vehicle position information.

[0102] In a possible implementation, the ambient light sensor group includes a plurality of ambient light sensors, and a surface of each of the plurality of ambient light sensors is a smooth curved surface without concavities.

[0103] Optionally, the ambient light sensor is a component that is smooth and continuous as a whole and has no concave curved surface.

[0104] In the embodiment of the present application, the surface of each ambient light sensor in the ambient light sensor group is a smooth surface without concave curves. In this way, it is helpful to obtain theoretical incident light more accurately, thereby obtaining more accurate vehicle position information.

[0105] In a possible implementation, the ambient light sensor group includes solar panels, and the solar panels are distributed on a top of the vehicle.

[0106] In an embodiment of the present application, the ambient light sensor group may include a solar panel. In this way, the vehicle can realize both charging function and low-cost, high-precision positioning while driving.

[0107] FIG4 is a schematic flow chart of another positioning method 400 provided in an embodiment of the present application. Method 400 may be executed by the intelligent driving device 100 in FIG1 , or by the computing platform 130 in the intelligent driving device 100, or by the SOC in the computing platform 130, or by the processor in the computing platform 130. Method 400 is a specific description of the implementation of method 300. As shown in FIG4 , method 400 may include the following steps.

[0108] S401, obtaining sensor parameters at the current moment.

[0109] Among them, the sensor parameters may include: light source geographic location information and vehicle positioning information. The light source geographic location information can be used to indicate the geographic location of a point light source (e.g., a street lamp) lighting on the road. The light source geographic location information can be 3D information, which can be obtained from a high-precision map or point cloud map, or from other devices through the Internet of Vehicles. The vehicle's positioning information may be positioning information with lower positioning accuracy, but it is sufficient to determine which light source or between which two light sources the vehicle is located. The positioning information can be obtained through GNSS, an inertial navigation system (INS) or an odometer. Alternatively, the positioning information can be obtained through data fusion of GNSS, INS and odometer.

[0110] The sensor may be an ambient light sensor group (ALSG), which may be composed of several ambient light sensors (sub-sensors). The ambient light sensor may sense electromagnetic waves within a specific wavelength range in the environment. The ambient light sensor includes but is not limited to a light pressure sensor, an infrared sensor, a solar panel, and the like.

[0111] It should be understood that the geographical location information of the light source in method 400 may be the first location information in method 300 , and the positioning information of the vehicle may be the third location information in method 300 .

[0112] The position of the ALSG sensor in the vehicle may be as shown in FIG5 , wherein the design of the ALSG sensor may meet the following conditions:

[0113] (1) The overall shape of ALSG is homeomorphic to the hemisphere topology and has a convex hull.

[0114] (2) The ALSG is equipped with multiple sub-sensors to ensure that incident light from any direction directly above or slightly above the vehicle is directed directly to and only directly hits one sub-sensor. Adjacent sub-sensors need to have a certain angular difference to ensure that all sub-sensors face different directions. That is, the shape and orientation of the sub-sensors can be as shown in (a) to (c) of Figure 6, where each small area in the hemisphere can represent the photosensitive surface of the sub-sensor.

[0115] (3) The direction in which the sub-sensor perceives light is perpendicular to the curved surface of the sub-sensor's photosensitive surface.

[0116] (4) The position of the sub-sensor is fixed, so that the physical position of each sub-sensor and the direction of the received direct light are constant in the vehicle coordinate system.

[0117] It should be understood that the shapes and orientations of the sub-sensors shown in (a) to (c) in Figure 6 are merely exemplary illustrations, and the actual shapes and orientations of the sub-sensors may vary based on the actual application of the sub-sensors. For example, the photosensitive surface shapes of the sub-sensors in (a) to (c) in Figure 6 may be quadrilaterals with equal areas. For another example, the angles between different sub-sensors may not be equal.

[0118] S402 , determining the sub-sensor V having the maximum light intensity value.

[0119] Taking a scene where a vehicle is traveling under a light source as an example, it is assumed that there is a main light source L near the vehicle. Since the main light source L is closer to the vehicle, its brightness exceeds that of other light sources.

[0120] Figure 7 shows a line graph of the incident angle of light and the luminous flux per unit area of ​​the ALSG. The horizontal axis represents the angle between the incident light and the normal to the sub-sensor's photosensitive surface, i.e., the incident angle of the light; the vertical axis represents the luminous flux per unit area of ​​the ALSG. As can be seen from the graph, the luminous flux per unit area decreases as the incident angle of the light increases. When the light is direct, i.e., when the angle of incidence is 0, the luminous flux per unit area is maximum. Therefore, only sub-sensors exposed to direct or nearly direct light will receive the maximum ambient light sensor reading.

[0121] It should be understood that when the incident angle of the ambient light sensor's photosensitive surface is 0, it can be called vertical incidence, or simply direct incidence. When the incident angle is less than a preset threshold, it can be called nearly direct incidence. The setting of this preset threshold can depend on the density of the ALSG. The smaller the difference between adjacent angles, the smaller the preset threshold can be set.

[0122] As shown in Figure 8, this figure is a schematic diagram of the ambient light sensor readings that can be obtained by different sub-sensors. The small circles in the figure represent sub-sensors. It can be seen from the figure that the point marked as 90 is the sub-sensor that is directly or nearly directly exposed to light. This sub-sensor is recorded as sensor V. This sub-sensor has the highest reading and is easily obtained by the system.

[0123] It should also be understood that the sensor V in method 400 may be the first ambient light sensor or the second ambient light sensor in method 300 .

[0124] S403: Acquire the position and posture of the sensor V in the vehicle coordinate system.

[0125] Specifically, as can be seen from step S401, the sensor V is a sub-sensor, and its position on the ALSG is fixed, that is, the position P of the sensor V in the vehicle coordinate system is v-car It can be a constant or a fixed value. In the same coordinate system, the position P of the sensor V v-car The only transformation matrix T v The position of the sensor V is converted to the pose of the vehicle's rear axle center, which is also the vehicle's pose. In this process, the position of the sensor V's pose can refer to the three-dimensional geometric coordinates of the sensor V in the vehicle coordinate system, and the pose can refer to the direction vector of the direct light directly hitting the sensor V.

[0126] S404: Obtain the position and posture of the sensor V in the world coordinate system.

[0127] Specifically, since the position accuracy in the vehicle's posture is low and the posture is relatively high, the posture of the sensor V in the world coordinate system can be obtained by the following formula.

[0128] Pv-world =P car-world T v -1

[0129] Among them, P v-world is the pose of the sensor V in the world coordinate system, P car-world is the vehicle’s position in the world coordinate system, T v is the transformation matrix.

[0130] After obtaining the position and posture of the sensor V in the world coordinate system, we can further obtain the theoretical incident light F of the sensor V. The theoretical incident light F can be expressed in the form of a system of straight line equations in the world coordinate system (mathematically, the coordinates of the points on the straight line and the direction of the straight line are known, and the equation of the straight line can be determined). That is, if the positioning result is accurate, the actual incident light from the light source L should shine on the sensor V along the theoretical incident light F.

[0131] In geographic coordinate systems such as the Universal Transverse Mercator Grid (UTM), a small area can be considered as Euclidean space. The distance D from the light source L to the theoretical incident light F can be obtained by the point-to-straight-line distance formula. L-F。 If D L-F If F is equal to or close to 0, it means that F passes through the light source L, and the light source L can be regarded as incident light. The vehicle positioning result is accurate. In this case, the positioning result can be directly input into the vehicle positioning planning module. Steps S405 to S407 are no longer performed.

[0132] Optionally, in the embodiment of the present application, the light source L may be a point light source, and further, the light source L may be a street lamp.

[0133] S405: Obtain the offset from the light source to the direct light.

[0134] In most cases, since the vehicle positioning information obtained in step S401 is of low accuracy, D L-F It is often not equal to or close to 0. Therefore, F cannot be regarded as the real incident light, but only the real incident parallel light. At this time, the tangent plane equation C1 of the vehicle relative to the road in the world coordinate system can be determined based on the vehicle's posture in the world coordinate system (mathematically, a certain vehicle posture can obtain a certain tangent plane), and the parallel plane C2 passing through the light source L can be obtained through C1.

[0135] As shown in Figure 9, the large hemisphere is the ambient light sensor group, the plane where the large hemisphere is located is C1, the plane where the light source is located is C2, and the intersection point M is the intersection point of F and plane C2. The offset vector can be determined based on the intersection point M, the intersection point of the real incident light and C2. Since the real incident light is parallel to F, and C1 is parallel to C2, the offset vector It is also the offset vector between the initial positioning and the actual positioning.

[0136] It should be understood that the plane C2 in method 400 may be the first plane or the third plane in method 300, the plane C1 may be the second plane in method 300, the intersection point M may be the fourth position information in method 300, and the offset vector It can be the first offset vector in method 300.

[0137] S406: Move the initial positioning position to obtain an optimized positioning point.

[0138] In most cases, the ground is relatively flat and the error between the initial positioning position of the vehicle and the actual position does not exceed 15 meters. Therefore, it can be assumed that the ground is equivalent to C1. At this time, according to the initial positioning position P car-world +Offset Vector The optimized vehicle positioning position P can be obtained opt After obtaining the optimized vehicle positioning position P opt The data can then be input into the vehicle's positioning planning module. Step S407 is no longer performed.

[0139] It should be understood that the above vehicle positioning position P opt It may be the second location information in method 300 .

[0140] S407: Determine whether iteration is required based on the optimization result of the positioning point.

[0141] In other cases, when the ground curvature is large, it is necessary to obtain the ground topography through the vehicle's map module and perform special processing. The processing method can be to use Newton's method, that is, to obtain the curvature of the ground from the map module, and calculate the curvature and offset vector according to the curvature and offset vector. Get P opt The tangent plane equation at the point, then P opt Considered as a new initial positioning position, steps S404 to S406 are iterated. When the modulus of is less than the preset threshold, or the number of iterations is greater than or equal to the preset number, the iteration is stopped and P opt Input into the vehicle's positioning planning module.

[0142] It should be understood that the curvature of the ground can be used to represent the degree of undulation of the ground. A larger curvature value indicates that the ground is more uneven and the degree of undulation of the ground is greater.

[0143] It should also be understood that the above method 400 is described using the scenario of a vehicle traveling under a single light source as an example. When the vehicle is located between two light sources (e.g., two streetlights), the processing method is similar to the above method 400. That is, there are two sub-sensors V, which are the sub-sensors with the maximum readings in the ambient light sensor group corresponding to each light source. In this case, the positioning optimization calculation of method 400 can be performed on the two sensors separately to obtain two optimized positioning points P. opt1 and P opt2 , you can take P opt1 and P opt2 The midpoint of the connecting line is used as the positioning point. In this way, higher positioning accuracy can usually be achieved. In addition, the above method can also be applied to scenes with multiple light sources.

[0144] In an embodiment of the present application, the position of the positioning point can be determined based on the posture of the ambient light sensor in the world coordinate system, and the offset vector between the position of the positioning point and the real light source position can be calculated, and the positioning of the vehicle can be calibrated using the offset vector. In this way, the vehicle can be positioned in a low-cost and high-precision manner in scenarios where natural light is insufficient.

[0145] FIG10 is an application scenario applicable to the positioning method provided in an embodiment of the present application, and method 300 and method 400 can be applied to this application scenario.

[0146] As shown in Figure 10, one or more solar panels can be deployed on the roof of a vehicle. Sensors can be placed beneath each panel to measure the panel's power generation efficiency or voltage. There's a corresponding relationship between the intensity of incident light and the panel's voltage: the stronger the incident light, the higher the panel's voltage. Because the panels are arranged in a streamlined pattern on the vehicle, there's omnidirectional light exposure above and slightly above the panels. As long as there's a sufficient density of voltage sensors, the design requirements for the ambient light sensor group in methods 300 and 400 can be met. Therefore, the entire vehicle's panels can be considered an ALSG. When the vehicle is driven at night under point light sources, the panels' photoelectric reactions generate electricity, allowing the voltage sensor readings to indirectly reflect the incident light intensity on each panel. This enables nighttime vehicle positioning using methods 300 and 400.

[0147] It should be understood that, in a specific scenario, if light parallel to α is incident directly or nearly directly on an object at any angle α within a certain range, then the object can be considered to be illuminated by omnidirectional light within that angle range in that scenario. In the embodiment of the present application, when a vehicle is traveling at night and illuminated by a light source, omnidirectional light is present within the angle range directly above and slightly above the ALSG.

[0148] In the embodiment of the present application, the ambient light sensor is set as a solar panel, which can not only meet the charging needs of the vehicle while driving, but also can locate the vehicle at night in a low-cost and high-precision manner.

[0149] FIG11 is another application scenario applicable to the positioning method provided in an embodiment of the present application, and method 300 and method 400 can be applied to this application scenario.

[0150] As shown in FIG11(a), during normal vehicle operation, the vehicle's central control screen displays an interface 1100 and a function bar 1110. Interface 1100 includes user account login information 1101, a Bluetooth icon 1102, a Wi-Fi icon 1103, a cellular network signal icon 1104, an in-vehicle map application search box 1105, a card 1106 displaying all installed vehicle applications, a card 1107 displaying in-vehicle music applications, a card 1108 displaying the vehicle's remaining battery life and remaining range, and a card 1109 displaying the vehicle's 360-degree surround view function. The in-vehicle map application search box 1105 may include a user-configured home control 11051 and a location control 11052. The function bar 1110 includes an icon 1111 for switching to the central control large screen desktop, a vehicle internal circulation icon 1112, a driver's seat heating function icon 1113, a driver's area air-conditioning temperature display icon 1114, a passenger area air-conditioning temperature display icon 1115, a passenger seat heating function icon 1116 and a volume setting icon 1117.

[0151] The user can view the vehicle's location on the map in real time through the location control 11052. When the vehicle detects that the user clicks the location control 11052, the interface 1100 may display a graphical user interface (GUI) as shown in FIG11(b).

[0152] In the GUI shown in FIG11(b), in certain circumstances (e.g., when the network signal is poor), GNSS positioning may be inaccurate. In this case, a prompt box 1118 may be displayed on the interface 1100 to inform the user that the current vehicle positioning accuracy is poor and whether to optimize the positioning based on nearby light sources. When the vehicle detects that the user has clicked the optimization control in the prompt box 1118, the vehicle may optimize the vehicle positioning based on the above-described method 300 or method 400.

[0153] For example, as shown in (c) in Figure 11, the vehicle can determine the light source closest to the vehicle based on the initial positioning information (inaccurate positioning information), and can determine the first ambient light sensor based on the nearest light source. According to the position of the first ambient light sensor in the world coordinate system, the theoretical incident light of the first ambient light sensor can be determined, and the first offset vector can be determined. Then, the first offset vector can be used to calibrate the initial positioning information of the vehicle to obtain the precise positioning information of the vehicle.

[0154] As shown in the GUI (d) in FIG11 , after optimizing the initial positioning information of the vehicle using method 300 or method 400, the precise position of the vehicle on the map can be displayed on the interface 1100, and a prompt box 1119 can be displayed to inform the user that the positioning optimization of the vehicle is successful.

[0155] It should be understood that the above-mentioned vehicle may be the intelligent driving device 100 in FIG. 1 , and the interface 1100 may be the interface displayed on the display device 140 in FIG. 1 .

[0156] The embodiments of the present application also provide an apparatus for implementing any of the above methods, which includes a unit for implementing each step performed by the intelligent driving device 100 in any of the above methods.

[0157] Figure 12 is a schematic diagram of a positioning device 1200 provided in an embodiment of the present application. The device 1200 may include an acquisition unit 1210, a storage unit 1220, and a processing unit 1230. The acquisition unit 1210 is used to acquire instructions and / or data. The acquisition unit 1210 may also be referred to as a communication interface or communication unit. The storage unit 1220 is used to implement corresponding storage functions and store corresponding instructions and / or data. The processing unit 1230 is used to perform data processing. The processing unit 1230 can read the instructions and / or data in the storage unit to enable the device 1200 to implement the aforementioned positioning method.

[0158] In one possible implementation, the device 1200 includes: an acquisition unit 1210 and a processing unit 1230, the acquisition unit 1210 is used to obtain first position information of a first light source; the processing unit 1230 is used to determine a first ambient light sensor corresponding to the first light source, the first ambient light sensor is located in an ambient light sensor group, and the ambient light sensor group is installed on an intelligent driving device; and determine the second position information of the intelligent driving device based on the orientation information and the first position information of the first ambient light sensor.

[0159] In one possible implementation, the acquisition unit 1210 is further used to obtain the light intensity value corresponding to each ambient light sensor in the ambient light sensor group and the first light source; the processing unit 1230 is used to determine that the ambient light sensor with the largest light intensity value in the ambient light sensor group is the first ambient light sensor.

[0160] In one possible implementation, the orientation information is the position of the first ambient light sensor in the world coordinate system; the acquisition unit 1210 is also used to obtain third position information of the intelligent driving device, and the third position information is determined based on the global navigation satellite system; the processing unit 1230 is used to: determine the fourth position information of the first light source according to the position of the first ambient light sensor in the world coordinate system, and the fourth position information is determined based on the theoretical incident light of the first ambient light sensor and the first plane, and the first plane is the plane where the first light source is located, and the first plane is determined based on the second plane, and the second plane is the plane where the intelligent driving device is located, and the first plane is parallel to the second plane; determine the first offset vector according to the first position information and the fourth position information; determine the second position information of the intelligent driving device according to the first offset vector and the third position information.

[0161] In one possible implementation, the acquisition unit 1210 is also used to obtain the fifth position information of the second light source; the processing unit 1230 is also used to: determine the second ambient light sensor corresponding to the second light source, and the second ambient light sensor is located in the ambient light sensor group; and determine the sixth position information of the second light source according to the posture of the second ambient light sensor in the world coordinate system, and the sixth position information is determined by the theoretical incident light of the second ambient light sensor and the third plane; the third plane is the plane where the second light source is located, and the third plane is determined based on the second plane, and the second plane is parallel to the third plane; determine the second offset vector according to the fifth position information and the sixth position information; determine the second position information according to the first offset vector, the second offset vector and the third position information.

[0162] In a possible implementation, the ambient light sensor group includes a plurality of ambient light sensors, and a surface of each of the plurality of ambient light sensors is a smooth curved surface without concavities.

[0163] In one possible implementation, the ambient light sensor group includes a solar panel, which is distributed on the top of the intelligent driving device.

[0164] It should be understood that the division of the units in the above device is only a division of logical functions, and in actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated.

[0165] Optionally, if the device 1200 is located in the intelligent driving device 100, the processing unit 1230 may be the processor 131 shown in FIG. 1 .

[0166] Optionally, if the device 1200 is located in the system architecture 200 , the acquisition unit 1210 may be the perception module 220 , and the processing unit 1230 may be the positioning module 230 .

[0167] FIG13 is a schematic diagram of another positioning device 1300 provided in an embodiment of the present application. The device 1300 can be applied to the intelligent driving device 100 in FIG1 .

[0168] The positioning device 1300 includes a memory 1310, a processor 1320, and a communication interface 1330. The memory 1310, processor 1320, and communication interface 1330 are connected via an internal connection path. The memory 1310 is used to store instructions, and the processor 1320 is used to execute the instructions stored in the memory 1310 to control the communication interface 1330 to obtain information or to cause the positioning device to execute the positioning methods described in the above embodiments. Optionally, the memory 1310 can be coupled to the processor 1320 via an interface or integrated with the processor 1320.

[0169] It should be noted that the communication interface 1330 may be a transceiver such as, but not limited to, a transceiver. The communication interface 1330 may also include an input / output interface.

[0170] The processor 1320 stores one or more computer programs, which include instructions. When the instructions are executed by the processor 1320, the positioning device 1300 executes the positioning method in each of the above embodiments.

[0171] During implementation, each step of the above method can be completed by an integrated logic circuit of the hardware in the processor 1320 or by instructions in the form of software. The method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 1310, and the processor 1320 reads the information in the memory 1310 and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

[0172] Optionally, the acquisition unit 1210 may be the communication interface 1330 in FIG. 13 , which may implement the acquisition unit 1210 in FIG. 12 ; the memory 1310 in FIG. 13 may implement the storage unit in FIG. 12 ; and the processor 1320 in FIG. 13 may implement the processing unit 1230 in FIG. 12 .

[0173] Optionally, the device 1200 or the device 1300 may be a computing platform, which may be an in-vehicle computing platform or a cloud computing platform.

[0174] Optionally, the device 1200 or the device 1300 may be located in the intelligent driving device 100 in FIG. 1 .

[0175] Optionally, the device 1200 or the device 1300 may be the computing platform 130 in the intelligent driving device in FIG. 1 .

[0176] An embodiment of the present application further provides a computer-readable medium storing a program code. When the computer program code is executed on a computer, the computer executes any one of the methods in FIG. 3 or FIG. 4 .

[0177] An embodiment of the present application further provides a chip, comprising: a circuit, wherein the circuit is used to execute any one of the methods in FIG. 3 or FIG. 4 above.

[0178] The present application also provides an intelligent driving device comprising the positioning device shown in either FIG12 or FIG13 and an ambient light sensor group, wherein the ambient light sensor group comprises a plurality of ambient light sensors, each of which has a smooth, non-concave curved surface. The intelligent driving device may be a vehicle.

[0179] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0180] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0181] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0182] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0183] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0184] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling 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 method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0185] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A positioning method, characterized in that: The method comprises: Acquiring first position information of a first light source; Determining a first ambient light sensor corresponding to the first light source, where the first ambient light sensor is located in an ambient light sensor group, and the ambient light sensor group is installed on an intelligent driving device; Second position information of the intelligent driving device is determined according to the orientation information of the first ambient light sensor and the first position information.

2. The method according to claim 1, wherein The determining of the first ambient light sensor according to the light emitted by the first light source includes: Obtaining a light intensity value corresponding to each ambient light sensor in the ambient light sensor group and the first light source; The ambient light sensor with the largest light intensity value in the ambient light sensor group is determined as the first ambient light sensor.

3. The method according to claim 1 or 2, wherein: The orientation information is the position of the first ambient light sensor in the world coordinate system; Before determining the second position information of the intelligent driving device according to the orientation information of the first ambient light sensor and the first position information, the method further includes: Obtaining third location information of the intelligent driving device, where the third location information is determined based on a global navigation satellite system; The determining the second position information of the intelligent driving device according to the orientation information of the first ambient light sensor and the first position information includes: Determining fourth position information of the first light source based on a position of the first ambient light sensor in the world coordinate system, where the fourth position information is determined based on theoretical incident light from the first ambient light sensor and a first plane, where the first plane is a plane where the first light source is located, the first plane is determined based on a second plane, the second plane is a plane where the intelligent driving device is located, and the first plane is parallel to the second plane; determining a first offset vector according to the first position information and the fourth position information; The second position information of the intelligent driving device is determined according to the first offset vector and the third position information.

4. The method according to claim 3, wherein The method further comprises: acquiring fifth position information of the second light source; determining a second ambient light sensor corresponding to the second light source, where the second ambient light sensor is located in the ambient light sensor group; determining, based on the position of the second ambient light sensor in the world coordinate system, sixth position information of the second light source, where the sixth position information is determined by theoretical incident light from the second ambient light sensor and a third plane; the third plane is a plane where the second light source is located, the third plane is determined based on the second plane, and the second plane is parallel to the third plane; determining a second offset vector according to the fifth position information and the sixth position information; The determining, according to the first offset vector and the third position information, the second position information of the intelligent driving device includes: The second position information is determined according to the first offset vector, the second offset vector and the third position information.

5. The method according to any one of claims 1 to 4, characterized in that The ambient light sensor group includes a plurality of ambient light sensors, and a surface of each of the plurality of ambient light sensors is a smooth curved surface without concavities.

6. The method according to any one of claims 1 to 5, characterized in that The ambient light sensor group includes a solar panel, and the solar panel is distributed on the top of the intelligent driving device.

7. A positioning device, characterized in that: The device comprises an acquisition unit and a processing unit: The acquiring unit is configured to acquire first position information of the first light source; The processing unit is used to: Determining a first ambient light sensor corresponding to the first light source, where the first ambient light sensor is located in an ambient light sensor group, and the ambient light sensor group is installed on an intelligent driving device; and Second position information of the intelligent driving device is determined according to the orientation information of the first ambient light sensor and the first position information.

8. The device according to claim 7, wherein The acquisition unit is further configured to acquire a light intensity value corresponding to each ambient light sensor in the ambient light sensor group and the first light source; The processing unit is configured to determine that the ambient light sensor with the largest light intensity value in the ambient light sensor group is the first ambient light sensor.

9. The device according to claim 7 or 8, characterized in that The orientation information is the position of the first ambient light sensor in the world coordinate system; The acquiring unit is further configured to acquire third position information of the intelligent driving device, where the third position information is determined based on a global navigation satellite system; The processing unit is configured to: Determining fourth position information of the first light source based on a position of the first ambient light sensor in the world coordinate system, where the fourth position information is determined based on theoretical incident light from the first ambient light sensor and a first plane, where the first plane is a plane where the first light source is located, the first plane is determined based on a second plane, the second plane is a plane where the intelligent driving device is located, and the first plane is parallel to the second plane; determining a first offset vector according to the first position information and the fourth position information; The second position information of the intelligent driving device is determined according to the first offset vector and the third position information.

10. The device according to claim 9, wherein The acquiring unit is further configured to acquire fifth position information of the second light source; The processing unit is further configured to: determining a second ambient light sensor corresponding to the second light source, where the second ambient light sensor is located in the ambient light sensor group; and determining, based on the position of the second ambient light sensor in the world coordinate system, sixth position information of the second light source, where the sixth position information is determined by theoretical incident light from the second ambient light sensor and a third plane; the third plane is a plane where the second light source is located, the third plane is determined based on the second plane, and the second plane is parallel to the third plane; determining a second offset vector according to the fifth position information and the sixth position information; The second position information is determined according to the first offset vector, the second offset vector and the third position information.

11. The device according to any one of claims 7 to 10, characterized in that The ambient light sensor group includes a plurality of ambient light sensors, and a surface of each of the plurality of ambient light sensors is a smooth curved surface without concavities.

12. The device according to any one of claims 7 to 11, characterized in that The ambient light sensor group includes a solar panel, and the solar panel is distributed on the top of the intelligent driving device.

13. A positioning device, characterized in that: include: A processor and a memory, wherein the processor is coupled to the memory and is configured to read and execute instructions in the memory to perform the method according to any one of claims 1 to 6.

14. A computer-readable medium, characterized in that The computer-readable medium stores a program code, and when the computer program code is run on a computer, the computer is caused to perform the method according to any one of claims 1 to 6.

15. A chip, characterized in that: include: A circuit for executing the method according to any one of claims 1 to 6.

16. An intelligent driving device, characterized in that: include: The positioning device and ambient light sensor group according to any one of claims 7 to 13, wherein the ambient light sensor group comprises a plurality of ambient light sensors, and the surface of each of the plurality of ambient light sensors is a smooth curved surface without concave portions.

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