WO2020253857A1 - 传感器的控制方法、装置和传感器 - Google Patents
传感器的控制方法、装置和传感器 Download PDFInfo
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- WO2020253857A1 WO2020253857A1 PCT/CN2020/097296 CN2020097296W WO2020253857A1 WO 2020253857 A1 WO2020253857 A1 WO 2020253857A1 CN 2020097296 W CN2020097296 W CN 2020097296W WO 2020253857 A1 WO2020253857 A1 WO 2020253857A1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0423—Input/output
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/421—Determining position by combining or switching between position solutions or signals derived from different satellite radio beacon positioning systems; by combining or switching between position solutions or signals derived from different modes of operation in a single system
- G01S19/426—Determining position by combining or switching between position solutions or signals derived from different satellite radio beacon positioning systems; by combining or switching between position solutions or signals derived from different modes of operation in a single system by combining or switching between position solutions or signals derived from different modes of operation in a single system
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
- B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
- B60R16/023—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/01—Determining conditions which influence positioning, e.g. radio environment, state of motion or energy consumption
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/003—Transmission of data between radar, sonar or lidar systems and remote stations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/23—Pc programming
- G05B2219/23399—Adapt set parameter as function of measured conditions
Definitions
- This application relates to vehicle driving technology, in particular to a sensor control method, device and sensor.
- LRR Long Range Radar
- ACC Adaptive Cruise Control
- FCW Forward collision warning
- FCW Automatic emergency braking
- AEB Automatic Emergency Brake
- MRR Middle Range Radar
- SRR Short Range Radar
- BSD Blind Spot Detection
- LCA Lane Change Assistance
- FCTA Backward target crossing warning
- Functions such as Rear Cross Traffic Alert (RCTA), Exit Assistant Function (EAF), Forward Cross Traffic Alert (FCTA) and other functions can accurately detect targets within a certain range around the vehicle.
- RCTA Rear Cross Traffic Alert
- EAF Exit Assistant Function
- FCTA Forward Cross Traffic Alert
- the LRR is installed at the exact center of the front bumper of the vehicle, the azimuth angle is 0°, when the height is less than 50cm, the elevation angle is set to 1.5°, and when the height exceeds 50cm, the elevation angle is set to 0°, which can realize the truck 150 meters, 100 meters for cars and 60 meters for pedestrians.
- LRR's ACC, FCW, AEB and other functions have a significant safety reminder effect when the driver is distracted, tired or sleepy or fails to notice the situation ahead when using a mobile phone.
- SRR in BSD, LCA and other fields can effectively reduce the risk factor caused by the inconvenience of the driver in the night, fog, heavy rain and other climatic conditions, and avoid the driver during the merge operation. , The danger of collision between adjacent lanes and blind spots of the "view”.
- the present application provides a sensor control method, device and sensor, so as to improve the flexible control of the sensor and save the external space of the vehicle.
- this application provides a sensor control method, including:
- Acquire first indication information where the first indication information is used to indicate a first scenario; determine a configuration parameter of at least one sensor according to the first indication information, and the configuration parameter corresponds to the first scenario; The configuration parameters are sent to the at least one sensor.
- the application realizes that the same sensor supports the measurement requirements under various conditions in the driving of the vehicle, improves the flexible control of the sensor, and can save the external space of the vehicle.
- the determining a configuration parameter of at least one sensor according to the first indication information includes: generating a configuration parameter corresponding to the first scenario; or, according to at least one preset
- the parameter correspondence relationship determines the configuration parameter, and the parameter correspondence relationship includes a correspondence relationship between a scenario and a configuration parameter.
- configuration parameters can be determined in multiple ways to improve flexibility.
- the configuration parameters include any one or more of the following parameters: working mode, measurement period, and measurement time.
- the method further includes: receiving a capability message sent by the at least one sensor; and determining a configuration parameter set according to the capability message, and the configuration parameter belongs to the configuration parameter set.
- the configuration parameters of the sensor are determined according to the first scenario, and the configuration parameters are configured according to the capabilities of the sensor, so as to avoid system abnormality caused by parameter configuration when the sensor does not support configuration.
- it further includes: receiving a configuration completion response message.
- this application provides a sensor control method, including:
- the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; the determining the first scene according to the measurement information includes: according to the speed information, pedestrians At least one of detection information and positioning information determines the first scene.
- this application provides a sensor control method, including:
- Report measurement information where the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; receive configuration parameters; and perform configuration according to the configuration parameters.
- the method further includes: sending a capability message, where the capability message is used to indicate the functional configuration supported by the sensor.
- the sending the capability message before the sending the capability message, it further includes: downloading a first version of software from a server; and the sending the capability message includes: sending the capability message according to the first version of the software.
- the method further includes: sending a configuration complete response message, where the configuration complete response message is used to instruct the sensor to complete parameter configuration.
- the present application provides a sensor control device, including:
- the obtaining module is configured to obtain first indication information, where the first indication information is used to indicate a first scenario; and the determining module is configured to determine a configuration parameter of at least one sensor according to the first indication information, and the configuration parameter is consistent with the Corresponding to the first scenario; a sending module, configured to send the configuration parameters to the at least one sensor.
- the determining module is specifically configured to generate a configuration parameter corresponding to the first scenario; or, to determine the configuration parameter according to at least one preset correspondence relationship between the parameters, the The parameter correspondence relationship includes the correspondence relationship between scenarios and configuration parameters.
- the configuration parameters include any one or more of the following parameters: working mode, measurement period, and measurement time.
- the acquiring module is further configured to receive a capability message sent by the at least one sensor; the determining module is further configured to determine a configuration parameter set according to the capability message, the configuration parameter It belongs to the configuration parameter set.
- the acquiring module is further configured to receive a configuration completion response message.
- the present application provides a sensor control device, including:
- the receiving module is used to receive measurement information from at least one sensor; the determining module is used to determine the first scene according to the measurement information; the transmitting module is used to send first indication information, and the first indication information is used to indicate Describe the first scene.
- the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; the determining module is specifically configured to select among speed information, pedestrian detection information, and positioning information. At least one of determines the first scene.
- this application provides a sensor, including:
- Sending module used to report measurement information, the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; receiving module, used to receive configuration parameters; configuration module, used to configure according to the configuration parameters .
- the sending module is further configured to send a capability message, where the capability message is used to indicate the functional configuration supported by the sensor.
- the receiving module is further configured to download the first version of software from a server; the sending module is specifically configured to send the capability message according to the first version of the software.
- the sending module is further configured to send a configuration completion response message, where the configuration completion response message is used to instruct the sensor to complete parameter configuration.
- the present application provides a sensor control device, including:
- a receiving module configured to receive measurement information from a sensor; a processing module, configured to determine a first scene according to the measurement information, and determine a configuration parameter of at least one sensor, the configuration parameter corresponding to the first scene; a sending module , Used to send the configuration parameter to the at least one sensor.
- the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; the processing module is specifically configured to select among speed information, pedestrian detection information, and positioning information. At least one of determines the first scene.
- the processing module is specifically configured to generate a configuration parameter corresponding to the first scenario; or, determine the configuration parameter according to at least one preset corresponding relationship between the parameters, and
- the parameter correspondence relationship includes the correspondence relationship between scenarios and configuration parameters.
- the configuration parameters include any one or more of the following parameters: working mode, measurement period, and measurement time of the sensor.
- the receiving module is further configured to receive a capability message sent by the sensor; the processing module is further configured to determine a configuration parameter set according to the capability message, and the configuration parameter belongs to all The configuration parameter collection.
- the present application provides a sensor control system, including: a control device and a sensor, wherein the control device adopts the device described in any one of the fourth, fifth, and seventh aspects, and the sensor adopts the aforementioned The sensor of any one of the sixth aspect.
- the present application provides a computer-readable storage medium including a computer program, which when executed on a computer, causes the computer to execute the method described in any one of the first to third aspects.
- the present application provides a computer program, when the computer program is executed by a computer, it is used to execute the method described in any one of the first to third aspects.
- this application provides a chip including a processor and a memory, the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the first to The method of any one of the three aspects.
- FIG. 1 is an exemplary functional block diagram of a vehicle 100 according to an embodiment of the present application
- Fig. 2 is an exemplary functional block diagram of a sensor control system according to an embodiment of the application
- FIG. 3 is a flowchart of a sensor control method according to an embodiment of the application.
- FIG. 4 is another flowchart of the sensor control method according to the embodiment of the application.
- FIG. 5 is a schematic structural diagram of a sensor control device according to an embodiment of the application.
- FIG. 6 is another schematic diagram of the structure of the sensor control device according to the embodiment of the application.
- FIG. 7 is a schematic structural diagram of a sensor according to an embodiment of the application.
- FIG. 8 is another schematic structural diagram of the sensor control device according to the embodiment of the application.
- FIG. 9 is a schematic structural diagram of a control entity of a sensor according to an embodiment of the application.
- At least one (item) refers to one or more, and “multiple” refers to two or more.
- “And/or” is used to describe the association relationship of associated objects, indicating that there can be three types of relationships, for example, “A and/or B” can mean: only A, only B, and both A and B , Where A and B can be singular or plural.
- the character “/” generally indicates that the associated objects are in an “or” relationship.
- the following at least one item (a)” or similar expressions refers to any combination of these items, including any combination of a single item (a) or plural items (a).
- At least one (a) of a, b or c can mean: a, b, c, "a and b", “a and c", “b and c", or "a and b and c" ", where a, b, and c can be single or multiple.
- Fig. 1 is an exemplary functional block diagram of a vehicle 100 according to an embodiment of the present application.
- the components coupled to or included in the vehicle 100 may include a propulsion system 110, a sensor system 120, a control system 130, peripheral equipment 140, a power source 150, a computing device 160, and a user interface 170.
- the components of the vehicle 100 may be configured to work in a manner interconnected with each other and/or with other components coupled to various systems.
- the power source 150 may provide power to all components of the vehicle 100.
- the computing device 160 may be configured to receive data from the propulsion system 110, the sensor system 120, the control system 130, and the peripheral device 140 and control them.
- the computing device 160 may also be configured to generate a display of images on the user interface 170 and receive input from the user interface 170.
- vehicle 100 may include more, fewer, or different systems, and each system may include more, fewer, or different components.
- systems and components shown can be combined or divided in any manner, which is not specifically limited in this application.
- the computing device 160 may include a processor 161, a transceiver 162, and a memory 163.
- the computing device 160 may be a controller or part of a controller of the vehicle 100.
- the memory 163 may store instructions 1631 running on the processor 161 and may also store map data 1632.
- the processor 161 included in the computing device 160 may include one or more general-purpose processors and/or one or more special-purpose processors (eg, image processors, digital signal processors, etc.). As far as the processor 161 includes more than one processor, such processors may work alone or in combination.
- the computing device 160 may implement a function of controlling the vehicle 100 based on input received through the user interface 170.
- the transceiver 162 is used for communication between the computing device 160 and various systems.
- the memory 163 may further include one or more volatile storage components and/or one or more non-volatile storage components, such as optical, magnetic and/or organic storage devices, and the memory 163 may be fully or partially connected to the processor 161 integrated.
- the memory 163 may contain instructions 1631 (eg, program logic) executable by the processor 161 to execute various vehicle functions, including any of the functions or methods described herein.
- the propulsion system 110 may provide power movement for the vehicle 100.
- the propulsion system 110 may include an engine/engine 114, an energy source 113, a transmission 112, and wheels/tires 111.
- the propulsion system 110 may additionally or alternatively include other components in addition to the components shown in FIG. 1. This application does not specifically limit this.
- the sensor system 120 may include several sensors for sensing information about the environment in which the vehicle 100 is located. As shown in FIG. 1, the sensors of the sensor system 120 include a global positioning system (Global Positioning System, GPS) 126, an Inertial Measurement Unit (IMU) 125, a lidar sensor 124, a camera sensor 123, and a millimeter wave radar sensor 122 And a stopper 121 for modifying the position and/or orientation of the sensor.
- the GPS 126 may be any sensor used to estimate the geographic position of the vehicle 100. To this end, the GPS 126 may include a transceiver to estimate the position of the vehicle 100 relative to the earth based on satellite positioning data.
- the computing device 160 may be used in conjunction with the map data 1632 to use the GPS 126 to estimate the road on which the vehicle 100 is traveling.
- the IMU 125 may be used to sense the position and orientation change of the vehicle 100 based on the inertial acceleration and any combination thereof.
- the combination of sensors in IMU 125 may include, for example, an accelerometer and a gyroscope.
- other combinations of sensors in IMU 125 are also possible.
- the lidar sensor 124 can be regarded as an object detection system that uses light sensing to detect objects in the environment where the vehicle 100 is located.
- the lidar sensor 124 may be an optical remote sensing technology that measures the distance to the target or other attributes of the target by illuminating the target with light.
- the lidar sensor 124 may include a laser source and/or laser scanner configured to emit laser pulses, and a detector for receiving reflections of the laser pulses.
- the lidar sensor 124 may include a laser rangefinder reflected by a rotating mirror, and scan laser light around the digital scene in one or two dimensions, so as to collect distance measurement values at specified angular intervals.
- the lidar sensor 124 may include components such as light (eg, laser) sources, scanners and optical systems, light detectors and receiver electronics, and location and navigation systems. The lidar sensor 124 determines the distance of the object by scanning the laser light reflected from an object, and can form a 3D environment map with a centimeter-level accuracy.
- the camera sensor 123 may include any camera (for example, a still camera, a video camera, etc.) for acquiring an image of the environment in which the vehicle 100 is located. To this end, the camera sensor 123 may be configured to detect visible light, or may be configured to detect light from other parts of the spectrum, such as infrared light or ultraviolet light. Other types of camera sensors 123 are also possible. The camera sensor 123 may be a two-dimensional detector, or may have a three-dimensional space range detection function. In some examples, the camera sensor 123 may be a distance detector, for example, which is configured to generate a two-dimensional image indicating the distance from the camera sensor 123 to several points in the environment. To this end, the camera sensor 123 may use one or more distance detection technologies.
- the camera sensor 123 may be configured to use structured light technology, in which the vehicle 100 uses a predetermined light pattern, such as a grid or a checkerboard pattern, to illuminate an object in the environment, and the camera sensor 123 is used to detect the predetermined light pattern from the object. Reflection. Based on the distortion in the reflected light pattern, the vehicle 100 may be configured to detect the distance of the point on the object.
- the predetermined light pattern may include infrared light or light of other wavelengths.
- the millimeter-wave radar sensor 122 generally refers to an object detection sensor with a wavelength of 1 to 10 mm, and the approximate frequency range is 10 GHz to 200 GHz.
- the measurement value of the millimeter-wave radar sensor 122 has depth information and can provide the distance of the target; secondly, because the millimeter-wave radar sensor 122 has an obvious Doppler effect and is very sensitive to speed, it can directly obtain the speed of the target. Puller frequency shift can extract the speed of the target.
- the two mainstream automotive millimeter wave radar application frequency bands are 24GHz and 77GHz respectively.
- the wavelength of the former is about 1.25cm, which is mainly used for short-distance sensing, such as the surrounding environment of the car body, blind spots, parking assistance, lane change assistance, etc.; the latter wavelength About 4mm, used for medium and long distance measurement, such as auto following, adaptive cruise (ACC), emergency braking (AEB), etc.
- the sensor system 120 may also include additional sensors, including, for example, sensors that monitor the internal systems of the vehicle 100 (eg, O 2 monitor, fuel gauge, oil temperature, etc.).
- the sensor system 120 may also include other sensors. This application does not specifically limit this.
- the control system 130 may be configured to control the operation of the vehicle 100 and its components.
- the control system 130 may include a steering unit 136, a throttle 135, a braking unit 134, a sensor fusion algorithm 133, a computer vision system 132, and a navigation/route control system 131.
- the control system 130 may additionally or alternatively include other components in addition to the components shown in FIG. 1. This application does not specifically limit this.
- the peripheral device 140 may be configured to allow the vehicle 100 to interact with external sensors, other vehicles, and/or users.
- the peripheral device 140 may include, for example, a wireless communication system 144, a touch screen 143, a microphone 142, and/or a speaker 141.
- the peripheral device 140 may additionally or alternatively include other components in addition to the components shown in FIG. 1. This application does not specifically limit this.
- the power supply 150 may be configured to provide power to some or all of the components of the vehicle 100.
- the power source 150 may include, for example, a rechargeable lithium ion or lead-acid battery.
- one or more battery packs may be configured to provide power.
- Other power supply materials and configurations are also possible.
- the power source 150 and the energy source 113 may be implemented together, as in some all-electric vehicles.
- the components of the vehicle 100 may be configured to work in a manner of interconnecting with other components inside and/or outside of their respective systems. To this end, the components and systems of the vehicle 100 may be communicatively linked together through a system bus, a network, and/or other connection mechanisms.
- FIG. 2 is an exemplary functional block diagram of the sensor control system according to an embodiment of the application, as shown in FIG. 2.
- the system can be used in vehicles, and can also be used in other carriers. The following description takes the vehicle as the carrier.
- the system includes at least one sensor installed and a control entity of the sensor.
- the control entity of the sensor may include a sensor management entity and a scene decision entity.
- the sensor may use any one or more of the sensor system 120 shown in FIG.
- the sensor, the sensor management entity and the scene decision entity may be integrated into one physical device.
- the one physical device may be, for example, the computing device 160 shown in FIG. 1.
- the sensor management entity and the scene decision entity may also be two independent entities. Physical equipment, the two independent physical equipment may be, for example, the computing device 160 shown in FIG.
- the two independent physical equipment may be, for example, the processor 161 and the transceiver in the computing device 160 shown in FIG. 162, and then the two share the memory 163.
- the sensor management entity and the scene decision entity of this application can be implemented in any achievable combination, and this application does not make specific limitations.
- Fig. 3 is a flow chart of a sensor control method according to an embodiment of this application. As shown in Fig. 3, the method in this embodiment may include:
- Step 301 At least one sensor reports measurement information.
- the at least one sensor may include at least one of GPS 126, IMU 125, lidar sensor 124, camera sensor 123, millimeter wave radar sensor 122, and brake 121.
- the senor may also include at least one of, for example, an oxygen (O2) monitor, a fuel gauge, and an oil temperature gauge.
- O2 oxygen
- the GPS 126 may be any sensor used to estimate the geographic position of the vehicle 100.
- the IMU 125 may be used to sense the position and orientation change of the vehicle 100 based on the inertial acceleration and any combination thereof.
- the combination of sensors in the IMU 125 may include, for example, an accelerometer and a gyroscope.
- the lidar sensor 124 can be regarded as an object detection system, which uses light to illuminate the target to measure the distance to the target.
- the camera sensor 123 may include any camera (for example, a still camera, a video camera, etc.) for acquiring an image of the environment in which the vehicle 100 is located.
- the camera sensor 123 may be a distance detector, for example, which is configured to generate a two-dimensional image indicating the distance from the camera sensor 123 to several points in the environment. To this end, the camera sensor 123 may use one or more distance detection technologies.
- the measurement value of the millimeter-wave radar sensor 122 has depth information and can provide the distance of the target; secondly, because the millimeter-wave radar sensor 122 has an obvious Doppler effect and is very sensitive to speed, it can directly obtain the speed of the target. Puller frequency shift can extract the speed of the target.
- the two mainstream automotive millimeter wave radar application frequency bands are 24GHz and 77GHz respectively.
- the wavelength of the former is about 1.25cm, which is mainly used for short-distance sensing, such as the surrounding environment of the car body, blind spots, parking assistance, lane change assistance, etc.; the latter wavelength About 4mm, used for medium and long distance measurement, such as auto following, adaptive cruise (ACC), emergency braking (AEB), etc.
- ACC adaptive cruise
- AEB emergency braking
- the measurement information of the vehicle's latitude and longitude, speed, orientation, and distance to surrounding objects can be acquired in real time or periodically, and then the vehicle can be assisted or unmanned based on these measurement information.
- drive For example, use the latitude and longitude to determine the location of the vehicle, or use the speed and orientation to determine the direction and purpose of the vehicle for a period of time in the future, or use the distance of surrounding objects to determine the number and density of obstacles around the vehicle.
- the measurement information in this application may include at least one of speed information, pedestrian detection information, and positioning information, where the pedestrian detection information may include the number and location of pedestrians in the surrounding environment, pedestrian density, etc., and the positioning information may include the current location The latitude and longitude or the latitude and longitude marked on the map.
- the sensor can perform measurement periodically, and then report the measurement information to the sensor management entity, and the sensor management entity forwards the measurement information to the scene decision entity, or the sensor directly reports to the scene decision entity.
- Step 302 The scenario decision entity determines the first scenario according to the measurement information.
- the first scene is used to indicate the scene where the carrier of the sensor is located.
- the measurement information reported by the sensor can reflect the position, speed, orientation and distance of the surrounding objects of the sensor.
- the scene decision entity can pre-classify according to different values of the measurement information, and set each category A name, so that the correspondence between the category name and the actual value of the measurement information can be established.
- different scene names are used to represent different measurement information categories. It is assumed that the scene names include downtown scenes, suburban scenes, and highway scenes. Among them, the measurement information corresponding to the downtown scene may include the number of surrounding pedestrians (the number is greater than the first threshold).
- the measurement information corresponding to the suburban scene may include, for example, the number of surrounding pedestrians (the number is less than or equal to the first threshold and greater than the fourth threshold), the distance to the surrounding pedestrians (the distance is greater than the second threshold and less than or equal to the sixth threshold), Speed (the speed is greater than the third threshold and less than or equal to the seventh threshold), location (the location can be combined with map data to determine that the corresponding road belongs to the suburbs), etc.; the measurement information corresponding to the highway scene may include the number of surrounding pedestrians, for example (The number is less than or equal to the fourth threshold), the distance to the surrounding pedestrians (the distance is greater than the sixth threshold), the speed (the speed is greater than the seventh threshold), and the location (the location combined with map data can determine that the corresponding road belongs to Highway)
- the scene decision entity can determine the category to which it belongs according to the specific value of the obtained measurement information, that is, the name of the category.
- the first scenario in this application is the name of the category to which the determined specific value of the measurement information belongs.
- Step 303 The scenario decision entity sends first indication information to the sensor management entity, where the first indication information is used to indicate the first scenario.
- the scene decision entity in this application determines the first scene, when the category of the first scene is the same as the category of the first scene determined last time, it indicates that the scene category where the sensor carrier is located has not changed, so the scene decision entity You can choose not to send the first instruction information, or you can choose to send the first instruction information to the sensor management entity, and the sensor management entity determines whether to reconfigure the configuration parameters of the sensor.
- the scene decision entity must send the first indication information to the sensor management entity to Trigger the sensor management entity to reconfigure the configuration parameters of the sensor.
- Step 304 The sensor management entity determines configuration parameters of the sensor according to the first indication information, and the configuration parameters correspond to the first scenario.
- the scene decision entity classifies according to the different values of the measurement information, sets a name for each category, and establishes the correspondence between the category name and the actual value of the measurement information.
- the sensor management entity the corresponding relationship between the category name and the configuration parameters of the sensor is established in advance.
- the configuration parameters may include, for example, any one or more of the working mode, measurement period, and measurement time of the sensor.
- the at least one sensor may include at least one of GPS 126, IMU 125, lidar sensor 124, camera sensor 123, millimeter wave radar sensor 122, and brake 121.
- the senor may also include at least one of, for example, an O2 monitor, a fuel gauge, and an oil temperature gauge.
- Each sensor can be configured with working mode, measurement period, measurement time, etc.
- GPS 126 may include high-precision positioning mode (for example, accurate to the house number) and low-precision positioning mode (for example, accurate to the road level);
- IMU 125 and camera sensor 123 may include periodic measurement (for example, according to the configured measurement period Measurement) and event-triggered measurement (for example, measurement is triggered based on a certain set event, the event may be, for example, that the vehicle speed change exceeds a set threshold);
- the lidar sensor 124 and the millimeter wave radar sensor 122 may include LRR mode and MRR mode And SRR mode, etc. Based on the performance of the aforementioned sensors, the working status can be controlled by configuration parameters.
- the configuration parameters corresponding to the downtown scene can include GPS 126 working in high-precision positioning mode, IMU 125 and The camera sensor 123 reports measurement information every fixed time at a set period.
- the lidar sensor 124 and the millimeter wave radar sensor 122 work in SRR mode;
- the configuration parameters corresponding to the suburban scene can include GPS 126 working in low-precision positioning mode, and IMU 125 working in low-precision positioning mode.
- the set period reports measurement information at regular intervals.
- the camera sensor 123 reports measurement information when it detects pedestrians within the set range.
- the lidar sensor 124 and millimeter wave radar sensor 122 work in MRR mode; configuration parameters corresponding to highway scenes It may include GPS 126 working in a low-precision positioning mode, IMU 125 and camera sensor 123 reporting measurement information when a pedestrian or vehicle is detected within a set range, and lidar sensor 124 and millimeter wave radar sensor 122 working in LRR mode.
- the sensor management entity can generate the configuration parameters corresponding to the first scene directly after obtaining the first scene based on the correspondence between the category name and the configuration parameters of the sensor, or in the locally stored configuration parameters according to the correspondence Query the configuration parameters matching the first scenario, so that the sensor works in a corresponding manner under the control of the configuration parameters.
- the sensor management entity may first determine whether the first scene indicated by the first indication information is the same as the first scene acquired when the configuration parameters of the sensor were previously configured. If they are the same, there is no need to reconfigure the configuration parameters of the sensor. If they are different, the configuration parameters of the sensor need to be reconfigured according to the first scenario indicated by the first indication information. For example, the first scene acquired when the configuration parameters of the sensor was configured last time was a downtown scene, and the first scene indicated by the first indication information received this time was a suburban scene, the sensor management entity needs to reconfigure the sensor's configuration according to the suburban scene. Configuration parameters.
- the sensor management entity needs to reconfigure the sensor according to the busy market scene Configuration parameters.
- Step 305 The sensor management entity sends the configuration parameters to the sensor.
- Step 306 The sensor is configured according to the configuration parameters.
- the sensor After the sensor receives the configuration parameters reconfigured by the sensor management entity, it completes its configuration according to the specific values in the configuration parameters. For example, GPS 126 is configured to work in high-precision positioning mode, and IMU 125 and camera sensor 123 are set at intervals of The measurement information is reported at a fixed time.
- the lidar sensor 124 and the millimeter-wave radar sensor 122 work in SRR mode; or, the GPS 126 works in low-precision positioning mode, and the IMU 125 reports measurement information every fixed time at a set period, and the camera sensor 123 works in When pedestrians within the set range are detected, the measurement information is reported, and the lidar sensor 124 and millimeter wave radar sensor 122 work in MRR mode; or the GPS 126 works in low-precision positioning mode, and the IMU 125 and camera sensor 123 detect the set range When pedestrians or vehicles appear inside, the measurement information is reported, and the lidar sensor 124 and the millimeter wave radar sensor 122 work in the LRR mode.
- the senor can work under different configuration parameter values to adapt to different first scenarios.
- Such a control method is flexible and diverse, and is also very efficient.
- Step 307 The sensor sends a configuration completion response message to the sensor management entity.
- the sensor informs the sensor management entity through the configuration completion response message, and the parameter configuration is completed.
- the same sensor can support the measurement requirements under various conditions in the driving of the vehicle, improve the flexible control of the sensor, and save the external space of the vehicle.
- FIG. 4 is another flowchart of the sensor control method according to an embodiment of the application. As shown in FIG. 4, the method in this embodiment may include:
- Step 401 At least one sensor sends a capability message to the sensor management entity.
- At least one sensor informs the sensor management entity of its own current capability, that is, the supported function configuration, for example, whether it supports parameter configuration, whether it supports multiple working modes, and which tasks are supported Mode and parameter configuration, etc.
- at least one sensor can download the first version of the software through the server, and the first version of the software is higher than the existing version of the sensor.
- the first version of the software is in terms of measurement accuracy, algorithms and/or functions of the sensor.
- the sensor can realize its own version upgrade after installing the first version of the software. After the upgrade, the sensor sends a capability message to inform the sensor management entity of the functional configuration supported after the upgrade.
- Step 402 The sensor management entity determines a configuration parameter set according to the capability message.
- the sensor management entity can determine whether the sensor supports parameter configuration, whether it supports multiple working modes, and which working modes and parameter configurations are supported, so as to determine the configuration parameter set.
- the at least one sensor may include at least one of GPS 126, IMU 125, lidar sensor 124, camera sensor 123, millimeter wave radar sensor 122, and brake 121.
- the senor may also include at least one of, for example, an O2 monitor, a fuel gauge, and an oil temperature gauge.
- GPS 126 may include high-precision positioning mode (for example, accurate to the house number) and low-precision positioning mode (for example, accurate to the road level), or may not support mode change, that is, GPS 126 can only work in one mode ;
- IMU125 and camera sensor 123 can support periodic measurement (for example, measurement according to the configured measurement period), and can also support event-triggered measurement (for example, measurement based on a set event trigger, the event may be, for example, the speed change exceeds the set Fixed threshold), or only one of the foregoing two measurement methods is supported;
- the lidar sensor 124 and the millimeter wave radar sensor 122 can support three modes: LRR mode, MRR mode and SRR mode.
- Step 403 At least one sensor reports measurement information.
- step 403 in this embodiment is similar to step 301 in the first embodiment of the above method, and will not be repeated here.
- Step 404 The scenario decision entity determines the first scenario according to the measurement information.
- step 404 in this embodiment is similar to step 302 in the first embodiment of the above method, and will not be repeated here.
- Step 405 The scenario decision entity sends first indication information to the sensor management entity, where the first indication information is used to indicate the first scenario.
- step 405 in this embodiment is similar to step 303 in the first embodiment of the above method, and will not be repeated here.
- Step 406 The sensor management entity determines the configuration parameter of the sensor according to the first indication information, and the configuration parameter belongs to the configuration parameter set and corresponds to the first scenario.
- the sensor management entity determines the configuration parameter corresponding to the first scenario from the configuration parameter set determined in step 402, that is, the configuration parameter set limits the range of configuration parameters for the sensor management entity, and the sensor management entity can only be within the range of the configuration parameter. Determine the configuration parameters inside to avoid system abnormalities caused by parameter configuration when the sensor does not support configuration.
- Step 407 The sensor management entity sends the configuration parameters to the sensor.
- step 407 in this embodiment is similar to step 305 in the first embodiment of the above method, and will not be repeated here.
- Step 408 The sensor is configured according to the configuration parameters.
- step 408 in this embodiment is similar to step 306 in the first embodiment of the above method, and will not be repeated here.
- Step 409 The sensor sends a configuration completion response message to the sensor management entity.
- step 409 in this embodiment is similar to step 307 in the first embodiment of the method, and will not be repeated here.
- the configuration parameters of the sensor are determined according to the first scenario, and the configuration parameters are configured according to the capabilities of the sensor, so as to avoid system abnormality caused by parameter configuration when the sensor does not support configuration.
- FIG. 5 is a schematic structural diagram of a sensor control device according to an embodiment of the application.
- the device in this embodiment can be applied to the above-mentioned sensor management entity, which includes: an acquisition module 501, a determination module 502, and a sending module 503.
- the obtaining module 501 is configured to obtain first indication information, and the first indication information is used to indicate a first scenario
- the determining module 502 is configured to determine configuration parameters of at least one sensor according to the first indication information, The configuration parameter corresponds to the first scenario
- the sending module 503 is configured to send the configuration parameter to the at least one sensor.
- the determining module 502 is specifically configured to generate configuration parameters corresponding to the first scenario; or, determine the configuration parameters according to at least one preset corresponding relationship of parameters, so
- the parameter correspondence relationship includes the correspondence relationship between scenarios and configuration parameters.
- the configuration parameters include any one or more of the following parameters: working mode, measurement period, and measurement time of the sensor.
- the acquiring module 501 is further configured to receive a capability message sent by the sensor; the determining module 502 is further configured to determine a configuration parameter set according to the capability message, and the configuration parameter It belongs to the configuration parameter set.
- the obtaining module 501 is further configured to receive a configuration completion response message.
- FIG. 6 is another structural schematic diagram of the sensor control device according to the embodiment of the application.
- the device in this embodiment can be applied to the above-mentioned scenario decision entity, which includes: a receiving module 601, a determining module 602, and a sending module 603 , Where the receiving module 601 is used to receive measurement information from the sensor; the determining module 602 is used to determine the first scene according to the measurement information; the sending module 603 is used to send the first indication information, the first indication information Used to indicate the first scene.
- the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; the determining module 602 is specifically configured to be based on the speed information, pedestrian detection information, and positioning information At least one of determines the first scene.
- Fig. 7 is a schematic structural diagram of a sensor according to an embodiment of the application. As shown in Fig. 7, the device of this embodiment may include: a sending module 701, a receiving module 702, and a configuration module 703. The sending module 701 is used to report measurement information.
- the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; the receiving module 702 is configured to receive configuration parameters; and the configuration module 703 is configured to perform configuration according to the configuration parameters.
- the sending module 701 is further configured to send a capability message, where the capability message is used to indicate the functional configuration supported by the sensor.
- the receiving module 702 is further configured to download the first version of software from a server; the sending module 701 is specifically configured to send the capability message according to the first version of the software.
- the sending module 701 is further configured to send a configuration complete response message, where the configuration complete response message is used to instruct the sensor to complete parameter configuration.
- FIG. 8 is another structural schematic diagram of the sensor control device according to the embodiment of the application.
- the device of this embodiment may include: a receiving module 801, a processing module 802, and a sending module 803.
- the receiving module 801 To receive measurement information from a sensor; a processing module 802, configured to determine a first scene according to the measurement information, and determine a configuration parameter of at least one sensor, the configuration parameter corresponding to the first scene; a sending module 803, Sending the configuration parameters to the at least one sensor.
- the measurement information includes at least one of speed information, pedestrian detection information, and positioning information; the processing module 802 is specifically configured to be based on the speed information, pedestrian detection information, and positioning information At least one of determines the first scene.
- the processing module 802 is specifically configured to generate configuration parameters corresponding to the first scenario; or, determine the configuration parameters according to at least one preset corresponding relationship of parameters, so
- the parameter correspondence relationship includes the correspondence relationship between scenarios and configuration parameters.
- the configuration parameters include any one or more of the following parameters: working mode, measurement period, and measurement time of the sensor.
- the receiving module 801 is further configured to receive a capability message sent by the sensor; the processing module 802 is further configured to determine a configuration parameter set according to the capability message, and the configuration parameter It belongs to the configuration parameter set.
- the foregoing device embodiment may be used to implement the technical solution of the method embodiment shown in FIG. 2 or 3, and its implementation principles and technical effects are similar, and will not be repeated here.
- FIG. 9 is a schematic structural diagram of a control entity of a sensor according to an embodiment of the application.
- the sensor control entity 900 may be the sensor management entity or the scene decision entity involved in the foregoing embodiment.
- the control entity 900 of the sensor includes a processor 901 and a transceiver 902.
- the sensor control entity 900 further includes a memory 903.
- the processor 901, the transceiver 902, and the memory 903 can communicate with each other through an internal connection path to transfer control signals and/or data signals.
- the memory 903 is used to store computer programs.
- the processor 901 is configured to execute a computer program stored in the memory 903, so as to implement each function in the foregoing device embodiment.
- the memory 903 may also be integrated in the processor 901 or independent of the processor 901.
- the sensor control entity 900 may also include an antenna 904 for transmitting the signal output by the transceiver 902.
- the transceiver 902 receives signals through an antenna.
- the sensor control entity 900 may further include a power supply 905 for providing power to various devices or circuits in the vehicle-mounted equipment.
- the sensor control entity 900 may also include an input unit 906, a display unit 907 (also can be considered as an output unit), an audio circuit 908, a camera 909, and a sensor 910. one or more.
- the audio circuit may also include a speaker 9091, a microphone 9082, etc., which will not be repeated.
- This application also provides a computer-readable storage medium with a computer program stored on the computer-readable storage medium.
- the computer program When the computer program is executed by a computer, the computer executes the steps and/or processing in any of the above-mentioned method embodiments. .
- the computer program product includes computer program code.
- the computer program code runs on a computer, the computer program code enables the computer to execute the steps and/or processing in any of the above method embodiments.
- the application also provides a chip including a processor.
- the memory for storing the computer program is provided independently of the chip, and the processor is used to execute the computer program stored in the memory to execute the steps and/or processing in any method embodiment.
- the chip may also include a memory and a communication interface.
- the communication interface may be an input/output interface, a pin, an input/output circuit, or the like.
- the processor mentioned in the above embodiments may be an integrated circuit chip with signal processing capability.
- the steps of the foregoing method embodiments may be completed by hardware integrated logic circuits in the processor or instructions in the form of software.
- the processor can be a general-purpose processor, digital signal processor (digital signal processor, DSP), application-specific integrated circuit (ASIC), field programmable gate array (field programmable gate array, FPGA) or other Programming logic devices, discrete gates or transistor logic devices, discrete hardware components.
- the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
- the steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed and completed by a hardware encoding processor, or executed and completed by a combination of hardware and software modules in the encoding processor.
- the software module can be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers.
- the storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.
- the memory mentioned in the above embodiments may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
- the non-volatile memory can be read-only memory (ROM), programmable read-only memory (programmable ROM, PROM), erasable programmable read-only memory (erasable PROM, EPROM), and electronic Erase programmable read-only memory (electrically EPROM, EEPROM) or flash memory.
- the volatile memory may be random access memory (RAM), which is used as an external cache.
- RAM random access memory
- static random access memory static random access memory
- dynamic RAM dynamic random access memory
- DRAM dynamic random access memory
- SDRAM synchronous dynamic random access memory
- double data rate synchronous dynamic random access memory double data rate SDRAM, DDR SDRAM
- enhanced synchronous dynamic random access memory enhanced SDRAM, ESDRAM
- serial link DRAM SLDRAM
- direct rambus RAM direct rambus RAM
- the disclosed system, device, and method may be implemented in other ways.
- the device embodiments described above are only illustrative.
- the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components can be combined or It can be integrated into another system, or some features can be ignored or not implemented.
- the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
- the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
- each unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
- the function 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 storage medium.
- the technical solution of this application essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (personal computer, server, or network device, etc.) execute all or part of the steps of the method described in each embodiment of the present application.
- the aforementioned storage media include: U disk, mobile hard disk, read-only memory (read-only memory, ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program code .
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Abstract
一种传感器的控制方法、装置和传感器。该控制方法包括:获取第一指示信息,第一指示信息用于指示第一场景;根据第一指示信息确定至少一个传感器的配置参数,配置参数与第一场景相对应;将配置参数发送给至少一个传感器。该控制方法可以应用于自动驾驶或智能驾驶中,具体可以用于辅助驾驶或无人驾驶,通过雷达或摄像头等传感器参数的配置可以实现传感器的灵活控制,并且可以节省车辆外部空间。
Description
本申请要求于2019年6月21日提交中国专利局、申请号为201910542746.8、申请名称为“传感器的控制方法、装置和传感器”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
本申请涉及车辆驾驶技术,尤其涉及一种传感器的控制方法、装置和传感器。
长距雷达(Long Range Radar,LRR)具有测距与防碰撞功能,广泛应用于自适应巡航控制(Adaptive Cruise Control,ACC)、前向碰撞警告(Forward Collision Warning,FCW)、自动紧急刹车(Automatic Emergency Brake,AEB)等领域。中距雷达(Middle Range Radar,MRR)和短距雷达(Short Range Radar,SRR)具有盲点检测(Blind Spot Detection,BSD)、车道变换辅助(Lane Change Assistance,LCA)、后向目标横穿警告(Rear Cross Traffic Alert,RCTA)、开门辅助(Exit Assistant Function,EAF)、前向目标横穿警告(Forward Cross Traffic Alert,FCTA)等功能,能精确探测车辆前后左右一定范围内的目标。可见不同的应用场景对雷达的检测距离有不同的需求,LRR、MRR和SRR均在高级驾驶辅助系统(Advanced Driving Assistant System,ADAS)中承担重要的功能。
相关技术中,将LRR安装在车辆前方保险杠的正中心位置,方位角为0°,当高度低于50cm时仰角设置为1.5°,当高度超过50cm时仰角设置为0°,这样可以实现卡车150米,汽车100米,行人60米的运动目标检测能力。LRR的ACC、FCW、AEB等功能在驾驶者分神、疲劳犯困或者使用手机等未能注意到前方状况时具有显著的安全提示效果。而作为ADAS系统中的典型应用,SRR在BSD、LCA等领域可以有效降低驾驶员在夜晚、雾天、大雨等气候恶劣条件下观察不便导致的危险系数,以及避免驾驶员在并道操作过程中,相邻车道和“视野”盲区可能碰撞的险境。
但是,车辆应用复杂,并不断出现新的应用,未来复杂的自动驾驶场景下需要大量不同类型的雷达,一方面车辆外部空间有限,难以为多种应用同时加装多种不同类型的雷达,另一方面随着不同类型的雷达数量的增加会增加车载雷达管理和控制的复杂度。
发明内容
本申请提供一种传感器的控制方法、装置和传感器,以提高传感器的灵活控制,并且可以节省车辆外部空间。
第一方面,本申请提供一种传感器的控制方法,包括:
获取第一指示信息,所述第一指示信息用于指示第一场景;根据所述第一指示信息确定至少一个传感器的配置参数,所述配置参数与所述第一场景相对应;将所述配置参数发送给所述至少一个传感器。
本申请通过根据第一场景确定传感器的配置参数,实现同一传感器支持车辆行驶中的各种情况下的测量需求,提高传感器的灵活控制,并且可以节省车辆外部空间。
在一种可能的实现方式中,所述根据所述第一指示信息确定至少一个传感器的配置参数,包括:生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
本申请可以通过多种方式确定配置参数,提高灵活性。
在一种可能的实现方式中,所述配置参数包括以下任一种或多种参数:工作模式、测量周期和测量时间。
在一种可能的实现方式中,还包括:接收所述至少一个传感器发送的能力消息;根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
本申请,通过根据第一场景确定传感器的配置参数,且配置参数是根据传感器的能力配置的,避免在传感器不支持配置的情况下,进行参数配置而导致系统异常。
在一种可能的实现方式中,还包括:接收配置完成响应消息。
第二方面,本申请提供一种传感器的控制方法,包括:
接收来自至少一个传感器的测量信息;根据所述测量信息确定第一场景;发送第一指示信息,所述第一指示信息用于指示所述第一场景。
在一种可能的实现方式中,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述根据所述测量信息确定第一场景,包括:根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。
第三方面,本申请提供一种传感器的控制方法,包括:
上报测量信息,所述测量信息包括速度信息、行人检测信息和定位信息中的至少一种;接收配置参数;根据所述配置参数进行配置。
在一种可能的实现方式中,还包括:发送能力消息,所述能力消息用于指示所述传感器支持的功能配置。
在一种可能的实现方式中,所述发送能力消息之前,还包括:从服务器下载第一版本软件;所述发送能力消息,包括:根据所述第一版本软件发送所述能力消息。
在一种可能的实现方式中,还包括:发送配置完成响应消息,所述配置完成响应消息用于指示所述传感器完成参数配置。
第四方面,本申请提供一种传感器的控制装置,包括:
获取模块,用于获取第一指示信息,所述第一指示信息用于指示第一场景;确定模块,用于根据所述第一指示信息确定至少一个传感器的配置参数,所述配置参数与所述第一场景相对应;发送模块,用于将所述配置参数发送给所述至少一个传感器。
在一种可能的实现方式中,所述确定模块,具体用于生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
在一种可能的实现方式中,所述配置参数包括以下任一种或多种参数:工作模式、测量周期和测量时间。
在一种可能的实现方式中,所述获取模块,还用于接收所述至少一个传感器发送的能力消息;所述确定模块,还用于根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
在一种可能的实现方式中,所述获取模块,还用于接收配置完成响应消息。
第五方面,本申请提供一种传感器的控制装置,包括:
接收模块,用于接收来自至少一个传感器的测量信息;确定模块,用于根据所述测量信息确定第一场景;发送模块,用于发送第一指示信息,所述第一指示信息用于指示所述第一场景。
在一种可能的实现方式中,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述确定模块,具体用于根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。
第六方面,本申请提供一种传感器,包括:
发送模块,用于上报测量信息,所述测量信息包括速度信息、行人检测信息和定位信息中的至少一种;接收模块,用于接收配置参数;配置模块,用于根据所述配置参数进行配置。
在一种可能的实现方式中,所述发送模块,还用于发送能力消息,所述能力消息用于指示所述传感器支持的功能配置。
在一种可能的实现方式中,所述接收模块,还用于从服务器下载第一版本软件;所述发送模块,具体用于根据所述第一版本软件发送所述能力消息。
在一种可能的实现方式中,所述发送模块,还用于发送配置完成响应消息,所述配置完成响应消息用于指示所述传感器完成参数配置。
第七方面,本申请提供一种传感器的控制装置,包括:
接收模块,用于接收来自传感器的测量信息;处理模块,用于根据所述测量信息确定第一场景,确定至少一个传感器的配置参数,所述配置参数与所述第一场景相对应;发送模块,用于将所述配置参数发送给所述至少一个传感器。
在一种可能的实现方式中,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述处理模块,具体用于根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。
在一种可能的实现方式中,所述处理模块,具体用于生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
在一种可能的实现方式中,所述配置参数包括以下任一种或多种参数:所述传感器的工作模式、测量周期和测量时间。
在一种可能的实现方式中,所述接收模块,还用于接收所述传感器发送的能力消息;所述处理模块,还用于根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
第八方面,本申请提供一种传感器的控制系统,包括:控制装置和传感器,其中,所述控制装置采用上述第四、五、七方面中任一项所述的装置,所述传感器采用上述第六方面中任一项所述的传感器。
第九方面,本申请提供一种计算机可读存储介质,包括计算机程序,所述计算机程序在计算机上被执行时,使得所述计算机执行上述第一至三方面中任一项所述的方法。
第十方面,本申请提供一种计算机程序,当所述计算机程序被计算机执行时,用于执行上述第一至三方面中任一项所述的方法。
第十一方面,本申请提供一种芯片,包括处理器和存储器,所述存储器用于存储计算机程序,所述处理器用于调用并运行所述存储器中存储的计算机程序,以执行上述第一至三方面中任一项所述的方法。
图1是本申请实施例车辆100的一种示例性功能框图;
图2为本申请实施例传感器的控制系统的一种示例性功能框图;
图3为本申请实施例传感器的控制方法的一个流程图;
图4为本申请实施例传感器的控制方法的另一个流程图;
图5为本申请实施例传感器的控制装置的一个结构示意图;
图6为本申请实施例传感器的控制装置的另一个结构示意图;
图7为本申请实施例传感器的结构示意图;
图8为本申请实施例传感器的控制装置的又一个结构示意图;
图9为本申请实施例传感器的控制实体的结构示意图。
为使本申请的目的、技术方案和优点更加清楚,下面将结合本申请中的附图,对本申请中的技术方案进行清楚、完整地描述,显然,所描述的实施例是本申请一部分实施例,而不是全部的实施例。基于本申请中的实施例,本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例,都属于本申请保护的范围。
本申请的说明书实施例和权利要求书及附图中的术语“第一”、“第二”等仅用于区分描述的目的,而不能理解为指示或暗示相对重要性,也不能理解为指示或暗示顺序。此外,术语“包括”和“具有”以及他们的任何变形,意图在于覆盖不排他的包含,例如,包含了一系列步骤或单元。方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元,而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
应当理解,在本申请中,“至少一个(项)”是指一个或者多个,“多个”是指两个或两个以上。“和/或”,用于描述关联对象的关联关系,表示可以存在三种关系,例如,“A和/或B”可以表示:只存在A,只存在B以及同时存在A和B三种情况,其中A,B可以是单数或者复数。字符“/”一般表示前后关联对象是一种“或”的关系。“以下至少一项(个)”或其类似表达,是指这些项中的任意组合,包括单项(个)或复数项(个)的任意组合。例如,a,b或c中的至少一项(个),可以表示:a,b,c,“a和b”,“a和c”,“b和c”,或“a和b和c”,其中a,b,c可以是单个,也可以是多个。
图1是本申请实施例车辆100的一种示例性功能框图。如图1所示,耦合到车辆100或包括在车辆100中的组件可以包括推进系统110、传感器系统120、控制系统130、外围设备140、电源150、计算装置160以及用户接口170。车辆100的组件可以被配置为以与彼此互连和/或与耦合到各系统的其它组件互连的方式工作。例如,电源150可以向车辆100的所有组件提供电力。计算装置160可以被配置为从推进系统110、传感器系统120、控制系统130和外围设备140接收数据并对它们进行控制。计算装置160还可以被 配置为在用户接口170上生成图像的显示并从用户接口170接收输入。
需要说明的是,在其它示例中,车辆100可以包括更多、更少或不同的系统,并且每个系统可以包括更多、更少或不同的组件。此外,示出的系统和组件可以按任意种的方式进行组合或划分,本申请对此不做具体限定。
计算装置160可以包括处理器161、收发器162和存储器163。计算装置160可以是车辆100的控制器或控制器的一部分。存储器163可以存储在处理器161上运行的指令1631,还可以存储地图数据1632。包括在计算装置160中的处理器161可包括一个或多个通用处理器和/或一个或多个专用处理器(例如,图像处理器、数字信号处理器等)。就处理器161包括多于一个处理器而言,这种处理器可单独工作或组合工作。计算装置160可实现基于通过用户接口170接收的输入控制车辆100的功能。收发器162用于该计算装置160与各个系统间的通信。存储器163进而可以包括一个或多个易失性存储组件和/或一个或多个非易失性存储组件,诸如光、磁和/或有机存储装置,并且存储器163可以全部或部分与处理器161集成。存储器163可以包含可由处理器161运行的指令1631(例如,程序逻辑),以运行各种车辆功能,包括本文中描述的功能或方法中的任何一个。
推进系统110可以为车辆100提供动力运动。如图1所示,推进系统110可以包括引擎/发动机114、能量源113、传动装置(transmission)112和车轮/轮胎111。另外,推进系统110可以额外地或可替换地包括除了图1所示出的组件以外的其他组件。本申请对此不做具体限定。
传感器系统120可以包括用于感测关于车辆100所位于的环境的信息的若干个传感器。如图1所示,传感器系统120的传感器包括全球定位系统(Global Positioning System,GPS)126、惯性测量单元(Inertial Measurement Unit,IMU)125、激光雷达传感器124、相机传感器123、毫米波雷达传感器122以及用于修改传感器的位置和/或朝向的制动器121。GPS 126可以为用于估计车辆100的地理位置的任何传感器。为此,GPS 126可以包括收发器,基于卫星定位数据估计车辆100相对于地球的位置。在示例中,计算装置160可以用于结合地图数据1632使用GPS 126来估计车辆100行驶的道路。IMU 125可以用于基于惯性加速度及其任意组合来感测车辆100的位置和朝向变化。在一些示例中,IMU125中传感器的组合可包括例如加速度计和陀螺仪。另外,IMU 125中传感器的其它组合也是可能的。激光雷达传感器124可以被看作物体检测系统,该传感器使用光感测检测车辆100所位于的环境中的物体。通常激光雷达传感器124可以通过利用光照射目标来测量到目标的距离或目标的其它属性的光学遥感技术。作为示例,激光雷达传感器124可以包括被配置为发射激光脉冲的激光源和/或激光扫描仪,和用于为接收激光脉冲的反射的检测器。例如,激光雷达传感器124可以包括由转镜反射的激光测距仪,并且以一维或二维围绕数字化场景扫描激光,从而以指定角度间隔采集距离测量值。在示例中,激光雷达传感器124可包括诸如光(例如,激光)源、扫描仪和光学系统、光检测器和接收器电子器件之类的组件,以及位置和导航系统。激光雷达传感器124通过扫描一个物体上反射回来的激光确定物体的距离,可以形成精度高达厘米级的3D环境图。相机传感器123可以包括用于获取车辆100所位于的环境的图像的任何相机(例如,静态相机、视频相机等)。为此,相机传感器123可以被配置为检测可见光,或可以被配置为检测来自光谱的其它部分(诸如红外光或紫外光)的光。其它类型的相机传感器123也是可能的。相机传感器 123可以是二维检测器,或可以具有三维空间范围检测功能。在一些示例中,相机传感器123例如可以是距离检测器,其被配置为生成指示从相机传感器123到环境中的若干点的距离的二维图像。为此,相机传感器123可以使用一种或多种距离检测技术。例如,相机传感器123可以被配置为使用结构光技术,其中车辆100利用预定光图案,诸如栅格或棋盘格图案,对环境中的物体进行照射,并且使用相机传感器123检测从物体的预定光图案的反射。基于反射的光图案中的畸变,车辆100可以被配置为检测到物体上的点的距离。预定光图案可以包括红外光或其它波长的光。毫米波雷达传感器(Millimeter-Wave Radar)122通常指波长为1~10mm的物体检测传感器,频率大致范围是10GHz~200GHz。毫米波雷达传感器122的测量值具备深度信息,可以提供目标的距离;其次,由于毫米波雷达传感器122有明显的多普勒效应,对速度非常敏感,可以直接获得目标的速度,通过检测其多普勒频移可将目标的速度提取出来。目前主流的两种车载毫米波雷达应用频段分别为24GHz和77GHz,前者波长约为1.25cm,主要用于短距离感知,如车身周围环境、盲点、泊车辅助、变道辅助等;后者波长约为4mm,用于中长距离测量,如自动跟车、自适应巡航(ACC)、紧急制动(AEB)等。
传感器系统120也可以包括额外的传感器,包括例如监视车辆100的内部系统的传感器(例如,O2监视器、燃油量表、机油温度,等等)。传感器系统120还可以包括其它传感器。本申请对此不做具体限定。
控制系统130可以被配置为控制车辆100及其组件的操作。为此,控制系统130可以包括转向单元136、油门135、制动单元134、传感器融合算法133、计算机视觉系统132、导航/路线控制系统131。控制系统130可以额外地或可替换地包括除了图1所示出的组件以外的其他组件。本申请对此不做具体限定。
外围设备140可以被配置为允许车辆100与外部传感器、其它车辆和/或用户交互。为此,外围设备140可以包括例如无线通信系统144、触摸屏143、麦克风142和/或扬声器141。外围设备140可以额外地或可替换地包括除了图1所示出的组件以外的其他组件。本申请对此不做具体限定。
电源150可以被配置为向车辆100的一些或全部组件提供电力。为此,电源150可以包括例如可再充电锂离子或铅酸电池。在一些示例中,一个或多个电池组可被配置为提供电力。其它电源材料和配置也是可能的。在一些示例中,电源150和能量源113可以一起实现,如一些全电动车中那样。
车辆100的组件可以被配置为以与在其各自的系统内部和/或外部的其它组件互连的方式工作。为此,车辆100的组件和系统可以通过系统总线、网络和/或其它连接机制通信地链接在一起。
图2为本申请实施例传感器的控制系统的一种示例性功能框图,如图2所示。该系统可以应用在车辆中,也可以应用在其他的使用载体中。下面以车辆为载体来进行说明。该系统包括安装的至少一个传感器和传感器的控制实体,传感器的控制实体又可以包括传感器管理实体和场景决策实体,其中,传感器可以采用图1所示的传感器系统120中的任一种或多种传感器,传感器管理实体和场景决策实体可以是一个整体集成在一个实体设备中,该一个实体设备可以是例如图1所示的计算装置160,传感器管理实体和场景决策实体也可以是两个独立的实体设备,该两个独立的实体设备可以分别是例如图1所示的计算 装置160,或者该两个独立的实体设备可以分别是例如图1所示的计算装置160中的处理器161和收发器162组成的实体,然后二者共享存储器163。需要说明的是,本申请传感器管理实体和场景决策实体可以采用任意可实现的组合方式实现,本申请不做具体限定。
为了更好地理解本申请实施例,以下以与图2所示的系统相同或相似的系统为例对本申请实施例进行说明。
图3为本申请实施例传感器的控制方法的一个流程图,如图3所示,本实施例的方法可以包括:
步骤301、至少一个传感器上报测量信息。
如上所述,在一些示例中,至少一个传感器可以包括GPS 126、IMU 125、激光雷达传感器124、相机传感器123、毫米波雷达传感器122以及制动器121中的至少一个。
在另一些示例中,传感器还可以包括例如氧气(O2)监视器、燃油量表、机油温度表等中的至少一个。
示例性的,GPS 126可以为用于估计车辆100的地理位置的任何传感器。IMU 125可以用于基于惯性加速度及其任意组合来感测车辆100的位置和朝向变化。IMU 125中传感器的组合可包括例如加速度计和陀螺仪。激光雷达传感器124可以被看作物体检测系统,该传感器利用光照射目标来测量到目标的距离。相机传感器123可以包括用于获取车辆100所位于的环境的图像的任何相机(例如,静态相机、视频相机等)。在一些示例中,相机传感器123例如可以是距离检测器,其被配置为生成指示从相机传感器123到环境中的若干点的距离的二维图像。为此,相机传感器123可以使用一种或多种距离检测技术。毫米波雷达传感器122的测量值具备深度信息,可以提供目标的距离;其次,由于毫米波雷达传感器122有明显的多普勒效应,对速度非常敏感,可以直接获得目标的速度,通过检测其多普勒频移可将目标的速度提取出来。目前主流的两种车载毫米波雷达应用频段分别为24GHz和77GHz,前者波长约为1.25cm,主要用于短距离感知,如车身周围环境、盲点、泊车辅助、变道辅助等;后者波长约为4mm,用于中长距离测量,如自动跟车、自适应巡航(ACC)、紧急制动(AEB)等。
可见,将上述传感器安装在车身上,可以实时或周期性地获取传感器感测到车辆的经纬度、速度、朝向、周围物体的距离等测量信息,再根据这些测量信息实现车辆的辅助驾驶或无人驾驶。例如,利用经纬度确定车辆的位置,或利用速度和朝向确定车辆在未来一段时间的行驶方向和目的,或利用周围物体的距离确定车辆周围的障碍物数量、密度等。本申请中测量信息可以包括速度信息,行人检测信息和定位信息中的至少一种,其中,行人检测信息可以包括周围环境中的行人数量和位置,行人密度等,定位信息可以包括当前所处位置的经纬度或该经纬度在地图上的标注等。
传感器可以周期性的进行测量,然后将测量信息上报给传感器管理实体,由传感器管理实体将测量信息转发给场景决策实体,或者传感器直接上报给场景决策实体。
步骤302、场景决策实体根据测量信息确定第一场景。
第一场景用于表示传感器的载体所在场景。在一些示例中,传感器上报的测量信息能体现出传感器的载体的位置、速度、朝向和周围物体的距离等,场景决策实体可以预先根据测量信息的不同取值进行分类,给每一个类别设定一个名称,这样可以建立起类别名称和测量信息的实际取值之间的对应关系。例如,以不同的场景名称表示不同的测量信息类 别,假设场景名称包括闹市场景、郊区场景和高速路场景,其中,闹市场景对应的测量信息例如可以包括周围行人的数量(该数量大于第一阈值)、和周围行人的距离(该距离小于或等于第二阈值)、速度(该速度小于或等于第三阈值)、位置(该位置结合地图数据可以确定出其对应的道路属于闹市区)等;郊区场景对应的测量信息例如可以包括周围行人的数量(该数量小于或等于第一阈值且大于第四阈值)、和周围行人的距离(该距离大于第二阈值且小于或等于第六阈值)、速度(该速度大于第三阈值且小于或等于第七阈值)、位置(该位置结合地图数据可以确定出其对应的道路属于郊区)等;高速路场景对应的测量信息例如可以包括周围行人的数量(该数量小于或等于第四阈值)、和周围行人的距离(该距离大于第六阈值)、速度(该速度大于第七阈值)、位置(该位置结合地图数据可以确定出其对应的道路属于高速路)等。
可见场景决策实体可以根据得到的测量信息的具体取值确定其所属的类别,即该类别的名称。本申请中第一场景即为确定出的测量信息的具体取值所属的类别的名称。
步骤303、场景决策实体向传感器管理实体发送第一指示信息,第一指示信息用于指示第一场景。
本申请中场景决策实体确定出第一场景后,当该第一场景的类别和前一次确定出的第一场景的类别相同时,其表明传感器的载体所在场景类别没有发生改变,因此场景决策实体可以选择不发送第一指示信息,也可以选择向传感器管理实体发送第一指示信息,由传感器管理实体决定是否重新配置传感器的配置参数。当该第一场景的类别和前一次确定出的第一场景的类别不同时,其表明传感器的载体所在场景类别发生了改变,因此场景决策实体就必须向传感器管理实体发送第一指示信息,以触发传感器管理实体重新配置传感器的配置参数。
步骤304、传感器管理实体根据第一指示信息确定传感器的配置参数,配置参数与第一场景相对应。
如上所述,场景决策实体根据测量信息的不同取值进行分类,给每一个类别设定一个名称,建立了类别名称和测量信息的实际取值之间的对应关系。而在传感器管理实体,则预先建立了类别名称和传感器的配置参数之间的对应关系。配置参数例如可以包括传感器的工作模式、测量周期和测量时间中的任一种或多种。
同样如上所述,在一些示例中,至少一个传感器可以包括GPS 126、IMU 125、激光雷达传感器124、相机传感器123、毫米波雷达传感器122以及制动器121中的至少一个。
在另一些示例中,传感器还可以包括例如O2监视器、燃油量表、机油温度表等中的至少一个。
各传感器可以为其配置工作模式、测量周期、测量时间等。例如,GPS 126可以包括高精度定位模式(例如可精确到门牌号)和低精度定位模式(例如可精确到道路级别);IMU 125和相机传感器123可以包括周期性测量(例如根据配置的测量周期进行测量)和事件触发测量(例如基于某个设定的事件触发进行测量,该事件例如可以是车速变化超过设定阈值);激光雷达传感器124和毫米波雷达传感器122可以包括LRR模式、MRR模式和SRR模式等。基于前述各传感器的性能,可以通过配置参数控制其工作状态。
例如,以不同的场景名称表示不同的测量信息类别,假设场景名称包括闹市场景、郊区场景和高速路场景,其中,闹市场景对应的配置参数可以包括GPS 126以高精度定位模 式工作,IMU 125和相机传感器123以设定周期每隔固定时间上报测量信息,激光雷达传感器124和毫米波雷达传感器122以SRR模式工作;郊区场景对应的配置参数可以包括GPS 126以低精度定位模式工作,IMU 125以设定周期每隔固定时间上报测量信息,相机传感器123在检测到设定范围内出现行人时上报测量信息,激光雷达传感器124和毫米波雷达传感器122以MRR模式工作;高速路场景对应的配置参数可以包括GPS 126以低精度定位模式工作,IMU 125和相机传感器123在检测到设定范围内出现行人或车辆时上报测量信息,激光雷达传感器124和毫米波雷达传感器122以LRR模式工作。
可见传感器管理实体可以基于类别名称和传感器的配置参数之间的对应关系,在获取到第一场景后,或者直接生成与第一场景对应的配置参数,或者根据对应关系在本地存储的配置参数中查询与第一场景匹配的配置参数,以使传感器在配置参数的控制下以对应的方式工作。
在一种可能的实现方式中,传感器管理实体接收到第一指示信息后,可以先判断第一指示信息所指示的第一场景和前一次配置传感器的配置参数时获取的第一场景是否相同,若相同,则不需要重新配置传感器的配置参数,若不同,则需要根据第一指示信息所指示的第一场景重新配置传感器的配置参数。例如,前一次配置传感器的配置参数时获取的第一场景为闹市场景,而此次接收的第一指示信息所指示的第一场景为郊区场景,传感器管理实体就需要根据郊区场景重新配置传感器的配置参数。或者,前一次配置传感器的配置参数时获取的第一场景为高速路场景,而此次接收的第一指示信息所指示的第一场景为闹市场景,传感器管理实体就需要根据闹市场景重新配置传感器的配置参数。
步骤305、传感器管理实体将配置参数发送给传感器。
步骤306、传感器根据配置参数进行配置。
传感器收到传感器管理实体重新配置的配置参数后,根据配置参数中的具体取值完成自身的配置,例如,GPS 126配置以高精度定位模式工作,IMU 125和相机传感器123以设定周期每隔固定时间上报测量信息,激光雷达传感器124和毫米波雷达传感器122以SRR模式工作;或者,GPS 126以低精度定位模式工作,IMU 125以设定周期每隔固定时间上报测量信息,相机传感器123在检测到设定范围内出现行人时上报测量信息,激光雷达传感器124和毫米波雷达传感器122以MRR模式工作;或者GPS 126以低精度定位模式工作,IMU 125和相机传感器123在检测到设定范围内出现行人或车辆时上报测量信息,激光雷达传感器124和毫米波雷达传感器122以LRR模式工作。
可见传感器可以在不同的配置参数取值下工作以适应不同的第一场景,这样的控制方法灵活多样,同时也很高效。
步骤307、传感器向传感器管理实体发送配置完成响应消息。
传感器通过配置完成响应消息告知传感器管理实体,参数配置完成。本申请,通过根据第一场景确定传感器的配置参数,实现同一传感器支持车辆行驶中的各种情况下的测量需求,提高传感器的灵活控制,并且可以节省车辆外部空间。
图4为本申请实施例传感器的控制方法的另一个流程图,如图4所示,本实施例的方法可以包括:
步骤401、至少一个传感器向传感器管理实体发送能力消息。
在系统工作之前或任一传感器的能力发生变化时,至少一个传感器通知传感器管理实 体其自身当前的能力,即支持的功能配置,例如,是否支持参数配置、是否支持多种工作模式以及支持哪些工作模式和参数配置等。在一些示例中,至少一个传感器可以通过服务器下载第一版本软件,该第一版本软件高于传感器现有的版本软件,例如,第一版本软件在传感器的测量精度、算法和/或功能等方面相较于现有的版本软件有升级,传感器安装了第一版本软件后可以实现自身版本升级,升级后传感器发送能力消息,以告知传感器管理实体升级后支持的功能配置。
步骤402、传感器管理实体根据能力消息确定配置参数集合。
基于至少一个传感器的能力消息,传感器管理实体可以确定传感器是否支持参数配置、是否支持多种工作模式以及支持哪些工作模式和参数配置等,从而确定配置参数集合。
如上所述,在一些示例中,至少一个传感器可以包括GPS 126、IMU 125、激光雷达传感器124、相机传感器123、毫米波雷达传感器122以及制动器121中的至少一个。
在另一些示例中,传感器还可以包括例如O2监视器、燃油量表、机油温度表等中的至少一个。
受能力限制,各传感器的可以支持的工作模式、测量周期、测量时间等各有不同。例如,GPS 126可以包括高精度定位模式(例如可精确到门牌号)和低精度定位模式(例如可精确到道路级别),也可能不支持模式改变,即GPS 126只能工作在一种模式下;IMU125和相机传感器123可以支持周期性测量(例如根据配置的测量周期进行测量),也可以支持事件触发测量(例如基于某个设定的事件触发进行测量,该事件例如可以是车速变化超过设定阈值),或者前述两种测量方式只支持其中之一;激光雷达传感器124和毫米波雷达传感器122可以支持LRR模式、MRR模式和SRR模式三种模式。
因此在收到能力消息后,根据传感器的能力确定传感器的配置参数集合,即确定哪些配置参数的取值是可以配给该传感器。
步骤403、至少一个传感器上报测量信息。
本实施例步骤403和上述方法实施例一的步骤301的技术原理类似,此处不再赘述。
步骤404、场景决策实体根据测量信息确定第一场景。
本实施例步骤404和上述方法实施例一的步骤302的技术原理类似,此处不再赘述。
步骤405、场景决策实体向传感器管理实体发送第一指示信息,第一指示信息用于指示第一场景。
本实施例步骤405和上述方法实施例一的步骤303的技术原理类似,此处不再赘述。
步骤406、传感器管理实体根据第一指示信息确定传感器的配置参数,配置参数属于配置参数集合且与第一场景相对应。
传感器管理实体从步骤402确定出的配置参数集合中确定与第一场景相对应的配置参数,即配置参数集合给传感器管理实体限定了配置参数的范围,传感器管理实体只可以在该配置参数的范围内确定配置参数,避免在传感器不支持配置的情况下,进行参数配置而导致系统异常。
步骤407、传感器管理实体将配置参数发送给传感器。
本实施例步骤407和上述方法实施例一的步骤305的技术原理类似,此处不再赘述。
步骤408、传感器根据配置参数进行配置。
本实施例步骤408和上述方法实施例一的步骤306的技术原理类似,此处不再赘述。
步骤409、传感器向传感器管理实体发送配置完成响应消息。
本实施例步骤409和上述方法实施例一的步骤307的技术原理类似,此处不再赘述。
本申请,通过根据第一场景确定传感器的配置参数,且配置参数是根据传感器的能力配置的,避免在传感器不支持配置的情况下,进行参数配置而导致系统异常。
图5为本申请实施例传感器的控制装置的一个结构示意图,如图5所示,本实施例的装置可以应用于上述传感器管理实体,其包括:获取模块501、确定模块502和发送模块503,其中,获取模块501,用于获取第一指示信息,所述第一指示信息用于指示第一场景;确定模块502,用于根据所述第一指示信息确定至少一个传感器的配置参数,所述配置参数与所述第一场景相对应;发送模块503,用于将所述配置参数发送给所述至少一个传感器。
在一种可能的实现方式中,所述确定模块502,具体用于生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
在一种可能的实现方式中,所述配置参数包括以下任一种或多种参数:所述传感器的工作模式、测量周期和测量时间。
在一种可能的实现方式中,所述获取模块501,还用于接收所述传感器发送的能力消息;所述确定模块502,还用于根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
在一种可能的实现方式中,所述获取模块501,还用于接收配置完成响应消息。
图6为本申请实施例传感器的控制装置的另一个结构示意图,如图6所示,本实施例的装置可以应用于上述场景决策实体,其包括:接收模块601、确定模块602和发送模块603,其中,接收模块601,用于接收来自传感器的测量信息;确定模块602,用于根据所述测量信息确定第一场景;发送模块603,用于发送第一指示信息,所述第一指示信息用于指示所述第一场景。
在一种可能的实现方式中,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述确定模块602,具体用于根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。图7为本申请实施例传感器的结构示意图,如图7所示,本实施例的装置可以包括:发送模块701,接收模块702和配置模块703,其中,发送模块701,用于上报测量信息,所述测量信息包括速度信息、行人检测信息和定位信息中的至少一种;接收模块702,用于接收配置参数;配置模块703,用于根据所述配置参数进行配置。
在一种可能的实现方式中,所述发送模块701,还用于发送能力消息,所述能力消息用于指示所述传感器支持的功能配置。
在一种可能的实现方式中,所述接收模块702,还用于从服务器下载第一版本软件;所述发送模块701,具体用于根据所述第一版本软件发送所述能力消息。
在一种可能的实现方式中,所述发送模块701,还用于发送配置完成响应消息,所述配置完成响应消息用于指示所述传感器完成参数配置。
图8为本申请实施例传感器的控制装置的又一个结构示意图,如图8所示,本实施例的装置可以包括:接收模块801、处理模块802和发送模块803,其中,接收模块801, 用于接收来自传感器的测量信息;处理模块802,用于根据所述测量信息确定第一场景,确定至少一个传感器的配置参数,所述配置参数与所述第一场景相对应;发送模块803,用于将所述配置参数发送给所述至少一个传感器。
在一种可能的实现方式中,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述处理模块802,具体用于根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。
在一种可能的实现方式中,所述处理模块802,具体用于生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
在一种可能的实现方式中,所述配置参数包括以下任一种或多种参数:所述传感器的工作模式、测量周期和测量时间。
在一种可能的实现方式中,所述接收模块801,还用于接收所述传感器发送的能力消息;所述处理模块802,还用于根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
上述装置实施例可以用于执行图2或3所示方法实施例的技术方案,其实现原理和技术效果类似,此处不再赘述。
图9为本申请实施例传感器的控制实体的结构示意图。如图9所示,传感器的控制实体900可以是上述实施例中涉及到的传感器管理实体或场景决策实体。传感器的控制实体900包括处理器901和收发器902。
可选地,传感器的控制实体900还包括存储器903。其中,处理器901、收发器902和存储器903之间可以通过内部连接通路互相通信,传递控制信号和/或数据信号。
其中,存储器903用于存储计算机程序。处理器901用于执行存储器903中存储的计算机程序,从而实现上述装置实施例中的各功能。
可选地,存储器903也可以集成在处理器901中,或者独立于处理器901。
可选地,传感器的控制实体900还可以包括天线904,用于将收发器902输出的信号发射出去。或者,收发器902通过天线接收信号。
可选地,传感器的控制实体900还可以包括电源905,用于给车载设备中的各种器件或电路提供电源。
除此之外,为了使得车载设备的功能更加完善,传感器的控制实体900还可以包括输入单元906、显示单元907(也可以认为是输出单元)、音频电路908、摄像头909和传感器910等中的一个或多个。音频电路还可以包括扬声器9091、麦克风9082等,不再赘述。
本申请还提供一种计算机可读存储介质,所述计算机可读存储介质上存储有计算机程序,所述计算机程序被计算机执行时,使得计算机执行上述任一方法实施例中的步骤和/或处理。
本申请还提供一种计算机程序产品,所述计算机程序产品包括计算机程序代码,当所述计算机程序代码在计算机上运行时,使得计算机执行上述任一方法实施例中的步骤和/或处理。
本申请还提供一种芯片,所述芯片包括处理器。用于存储计算机程序的存储器独立于 芯片而设置,处理器用于执行存储器中存储的计算机程序,以执行任一方法实施例中的步骤和/或处理。
进一步地,所述芯片还可以包括存储器和通信接口。所述通信接口可以是输入/输出接口、管脚或输入/输出电路等。
以上各实施例中提及的处理器可以是一种集成电路芯片,具有信号的处理能力。在实现过程中,上述方法实施例的各步骤可以通过处理器中的硬件的集成逻辑电路或者软件形式的指令完成。处理器可以是通用处理器、数字信号处理器(digital signal processor,DSP)、特定应用集成电路(application-specific integrated circuit,ASIC)、现场可编程门阵列(field programmable gate array,FPGA)或其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。本申请实施例公开的方法的步骤可以直接体现为硬件编码处理器执行完成,或者用编码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器,闪存、只读存储器,可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器,处理器读取存储器中的信息,结合其硬件完成上述方法的步骤。
上述各实施例中提及的存储器可以是易失性存储器或非易失性存储器,或可包括易失性和非易失性存储器两者。其中,非易失性存储器可以是只读存储器(read-only memory,ROM)、可编程只读存储器(programmable ROM,PROM)、可擦除可编程只读存储器(erasable PROM,EPROM)、电可擦除可编程只读存储器(electrically EPROM,EEPROM)或闪存。易失性存储器可以是随机存取存储器(random access memory,RAM),其用作外部高速缓存。通过示例性但不是限制性说明,许多形式的RAM可用,例如静态随机存取存储器(static RAM,SRAM)、动态随机存取存储器(dynamic RAM,DRAM)、同步动态随机存取存储器(synchronous DRAM,SDRAM)、双倍数据速率同步动态随机存取存储器(double data rate SDRAM,DDR SDRAM)、增强型同步动态随机存取存储器(enhanced SDRAM,ESDRAM)、同步连接动态随机存取存储器(synchlink DRAM,SLDRAM)和直接内存总线随机存取存储器(direct rambus RAM,DR RAM)。应注意,本文描述的系统和方法的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
本领域普通技术人员可以意识到,结合本文中所公开的实施例描述的各示例的单元及算法步骤,能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行,取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能,但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到,为描述的方便和简洁,上述描述的系统、装置和单元的具体工作过程,可以参考前述方法实施例中的对应过程,在此不再赘述。
在本申请所提供的几个实施例中,应该理解到,所揭露的系统、装置和方法,可以通过其它的方式实现。例如,以上所描述的装置实施例仅仅是示意性的,例如,所述单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,例如多个单元或组件可以结合或者可以集成到另一个系统,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口,装置或单元的间接耦合或通信连接,可以是电性,机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的,作为单元显示的部件可以是或者也可以不是物理单元,即可以位于一个地方,或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外,在本申请各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个计算机可读取存储介质中。基于这样的理解,本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质中,包括若干指令用以使得一台计算机设备(个人计算机,服务器,或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括:U盘、移动硬盘、只读存储器(read-only memory,ROM)、随机存取存储器(random access memory,RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述,仅为本申请的具体实施方式,但本申请的保护范围并不局限于此,任何熟悉本技术领域的技术人员在本申请揭露的技术范围内,可轻易想到变化或替换,都应涵盖在本申请的保护范围之内。因此,本申请的保护范围应以所述权利要求的保护范围为准。
Claims (31)
- 一种传感器的控制方法,其特征在于,包括:获取第一指示信息,所述第一指示信息用于指示第一场景;根据所述第一指示信息确定传感器的配置参数,所述配置参数与所述第一场景相对应,所述传感器支持至少一种工作模式,所述配置参数用于指示所述传感器处于第一工作模式,所述第一工作模式与第一场景相对应;将所述配置参数发送给所述传感器。
- 根据权利要求1所述的方法,其特征在于,所述根据所述第一指示信息确定传感器的配置参数,包括:生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
- 根据权利要求1或2所述的方法,其特征在于,所述配置参数包括以下任一种或多种参数:工作模式、测量周期和测量时间。
- 根据权利要求1-3中任一项所述的方法,其特征在于,还包括:接收所述传感器发送的能力消息,所述能力消息用于指示所述传感器支持的功能配置;根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
- 根据权利要求1-4中任一项所述的方法,其特征在于,还包括:接收配置完成响应消息,所述配置完成响应消息用于指示所述传感器完成参数配置。
- 一种传感器的控制方法,其特征在于,包括:接收来自传感器的测量信息,所述传感器支持至少一种工作模式;根据所述测量信息确定第一场景;发送第一指示信息,所述第一指示信息用于指示所述第一场景。
- 根据权利要求6所述的方法,其特征在于,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述根据所述测量信息确定第一场景,包括:根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。
- 一种传感器的控制方法,应用于传感器,其特征在于,包括:上报测量信息,所述测量信息包括速度信息、行人检测信息和定位信息中的至少一种;接收配置参数;所述传感器根据所述配置参数进行自身配置。
- 根据权利要求8所述的方法,其特征在于,还包括:发送能力消息,所述能力消息用于指示所述传感器支持的功能配置。
- 根据权利要求9所述的方法,其特征在于,所述发送能力消息之前,还包括:从服务器下载第一版本软件;所述发送能力消息,包括:根据所述第一版本软件发送所述能力消息。
- 根据权利要求8-10中任一项所述的方法,其特征在于,还包括:发送配置完成响应消息,所述配置完成响应消息用于指示所述传感器完成参数配置。
- 一种传感器的控制装置,其特征在于,包括:获取模块,用于获取第一指示信息,所述第一指示信息用于指示第一场景;确定模块,用于根据所述第一指示信息确定传感器的配置参数,所述配置参数与所述第一场景相对应,所述传感器支持至少一种工作模式,所述配置参数用于指示所述传感器处于第一工作模式,所述第一工作模式与第一场景相对应;发送模块,用于将所述配置参数发送给所述传感器。
- 根据权利要求12所述的装置,其特征在于,所述确定模块,具体用于生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
- 根据权利要求12或13所述的装置,其特征在于,所述配置参数包括以下任一种或多种参数:工作模式、测量周期和测量时间。
- 根据权利要求12-14中任一项所述的装置,其特征在于,所述获取模块,还用于接收所述传感器发送的能力消息,所述能力消息用于指示所述传感器支持的功能配置;所述确定模块,还用于根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
- 根据权利要求11-15中任一项所述的装置,其特征在于,所述获取模块,还用于接收配置完成响应消息,所述配置完成响应消息用于指示所述传感器完成参数配置。
- 一种传感器的控制装置,其特征在于,包括:接收模块,用于接收来自传感器的测量信息,所述传感器支持至少一种工作模式;确定模块,用于根据所述测量信息确定第一场景;发送模块,用于发送第一指示信息,所述第一指示信息用于指示所述第一场景。
- 根据权利要求17所述的装置,其特征在于,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述确定模块,具体用于根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。
- 一种传感器,其特征在于,包括:发送模块,用于上报测量信息,所述测量信息包括速度信息、行人检测信息和定位信息中的至少一种;接收模块,用于接收配置参数;配置模块,用于根据所述配置参数进行自身配置。
- 根据权利要求19所述的装置,其特征在于,所述发送模块,还用于发送能力消息,所述能力消息用于指示所述传感器支持的功能配置。
- 根据权利要求20所述的装置,其特征在于,所述接收模块,还用于从服务器下载第一版本软件;所述发送模块,具体用于根据所述第一版本软件发送所述能力消息。
- 根据权利要求19-21中任一项所述的方法,其特征在于,所述发送模块,还用于发送配置完成响应消息,所述配置完成响应消息用于指示所述传感器完成参数配置。
- 一种传感器的控制装置,其特征在于,包括:接收模块,用于接收来自传感器的测量信息;处理模块,用于根据所述测量信息确定第一场景,确定传感器的配置参数,所述配置参数与所述第一场景相对应,所述传感器支持至少一种工作模式,所述配置参数用于指示所述传感器处于第一工作模式,所述第一工作模式与第一场景相对应;发送模块,用于将所述配置参数发送给所述传感器。
- 根据权利要求23所述的装置,其特征在于,所述测量信息包括速度信息,行人检测信息和定位信息中的至少一种;所述处理模块,具体用于根据所述速度信息,行人检测信息和定位信息中的至少一种确定所述第一场景。
- 根据权利要求23或24所述的装置,其特征在于,所述处理模块,具体用于生成与所述第一场景相对应的配置参数;或者,根据预先设定的至少一个参数对应关系确定所述配置参数,所述参数对应关系包括场景和配置参数之间的对应关系。
- 根据权利要求23-25中任一项所述的装置,其特征在于,所述配置参数包括以下任一种或多种参数:所述传感器的工作模式、测量周期和测量时间。
- 根据权利要求23-26中任一项所述的装置,其特征在于,所述接收模块,还用于接收所述传感器发送的能力消息;所述处理模块,还用于根据所述能力消息确定配置参数集合,所述配置参数属于所述配置参数集合。
- 一种传感器的控制系统,其特征在于,包括:控制装置和传感器,其中,所述控制装置采用权利要求11-18或23-27中任一项所述的装置,所述传感器采用权利要求19-22中任一项所述的传感器。
- 一种计算机可读存储介质,其特征在于,包括计算机程序,所述计算机程序在计算机上被执行时,使得所述计算机执行权利要求1-11中任一项所述的方法。
- 一种计算机程序,其特征在于,当所述计算机程序被计算机执行时,用于执行权利要求1-11中任一项所述的方法。
- 一种芯片,其特征在于,包括处理器和存储器,所述存储器用于存储计算机程序,所述处理器用于调用并运行所述存储器中存储的计算机程序,以执行如权利要求1-11中任一项所述的方法。
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102022201219B3 (de) | 2022-02-07 | 2023-03-02 | Zf Friedrichshafen Ag | Fahrzeugsystem, insbesondere für eine E/E-(Elektrisch/Elektronische)-Architektur und Fahrzeug |
Families Citing this family (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10479356B1 (en) | 2018-08-17 | 2019-11-19 | Lyft, Inc. | Road segment similarity determination |
US11928557B2 (en) | 2019-06-13 | 2024-03-12 | Lyft, Inc. | Systems and methods for routing vehicles to capture and evaluate targeted scenarios |
US11788846B2 (en) * | 2019-09-30 | 2023-10-17 | Lyft, Inc. | Mapping and determining scenarios for geographic regions |
US11816900B2 (en) | 2019-10-23 | 2023-11-14 | Lyft, Inc. | Approaches for encoding environmental information |
US12039785B2 (en) | 2019-10-23 | 2024-07-16 | Lyft, Inc. | Approaches for encoding environmental information |
CN113110149B (zh) * | 2021-03-31 | 2022-04-08 | 德氪微电子(深圳)有限公司 | 一种车载安全监视控制方法及其系统 |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103707826A (zh) * | 2013-12-17 | 2014-04-09 | 华南理工大学 | 一种自适应调整驾驶模式的汽车感应系统 |
CN104477168A (zh) * | 2014-11-28 | 2015-04-01 | 长城汽车股份有限公司 | 汽车中的自适应巡航系统及方法 |
CN104691447A (zh) * | 2013-12-04 | 2015-06-10 | 通用汽车环球科技运作有限责任公司 | 用于动态地聚焦车辆传感器的系统和方法 |
JP2018005830A (ja) * | 2016-07-08 | 2018-01-11 | トヨタ自動車株式会社 | 車両の制御装置 |
CN109017803A (zh) * | 2018-07-14 | 2018-12-18 | 安徽中科美络信息技术有限公司 | 一种车载终端工作模式控制方法及车载终端 |
CN109017802A (zh) * | 2018-06-05 | 2018-12-18 | 长沙智能驾驶研究院有限公司 | 智能驾驶环境感知方法、装置、计算机设备和存储介质 |
CN109532824A (zh) * | 2018-12-19 | 2019-03-29 | 杭州湘滨电子科技有限公司 | 一种水平泊车的路沿识别方法 |
KR101947473B1 (ko) * | 2017-05-29 | 2019-04-29 | 국민대학교산학협력단 | 후방 차량을 고려한 안전 운전 지원 장치 및 방법 |
Family Cites Families (25)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP4977806B2 (ja) * | 2010-08-09 | 2012-07-18 | パナソニック株式会社 | レーダイメージング装置、イメージング方法及びそのプログラム |
DE102014014307A1 (de) * | 2014-09-25 | 2016-03-31 | Audi Ag | Verfahren zum Betrieb einer Mehrzahl von Radarsensoren in einem Kraftfahrzeug und Kraftfahrzeug |
KR101628503B1 (ko) * | 2014-10-27 | 2016-06-08 | 현대자동차주식회사 | 운전자 보조장치 및 그 작동 방법 |
US10384643B2 (en) * | 2015-01-14 | 2019-08-20 | GM Global Technology Operations LLC | Virtual keyfob for vehicle sharing |
US10167015B2 (en) * | 2015-05-11 | 2019-01-01 | GM Global Technology Operations LLC | System for retrofitting vehicle automation |
KR101892026B1 (ko) * | 2015-11-10 | 2018-08-27 | 현대자동차주식회사 | 차량의 원격 주차 제어 방법 및 장치 |
US10919574B2 (en) * | 2015-11-10 | 2021-02-16 | Hyundai Motor Company | Automatic parking system and automatic parking method |
US10606257B2 (en) * | 2015-11-10 | 2020-03-31 | Hyundai Motor Company | Automatic parking system and automatic parking method |
JP6344402B2 (ja) * | 2016-01-20 | 2018-06-20 | トヨタ自動車株式会社 | 車両の運転支援装置 |
US9990783B2 (en) * | 2016-02-16 | 2018-06-05 | GM Global Technology Operations LLC | Regulating vehicle access using cryptographic methods |
US9796390B2 (en) * | 2016-02-29 | 2017-10-24 | Faraday&Future Inc. | Vehicle sensing grid having dynamic sensing cell size |
KR102513745B1 (ko) * | 2016-04-15 | 2023-03-24 | 주식회사 에이치엘클레무브 | 운전 지원 장치 |
US9760827B1 (en) * | 2016-07-22 | 2017-09-12 | Alpine Electronics of Silicon Valley, Inc. | Neural network applications in resource constrained environments |
US11305766B2 (en) * | 2016-09-26 | 2022-04-19 | Iprd Group, Llc | Combining driver alertness with advanced driver assistance systems (ADAS) |
JP6598305B2 (ja) * | 2016-09-26 | 2019-10-30 | オムロンオートモーティブエレクトロニクス株式会社 | 車両通信システム、車載機、携帯機 |
JP6447610B2 (ja) * | 2016-10-28 | 2019-01-09 | トヨタ自動車株式会社 | 車両制御システム、車両制御装置 |
CN107071147B (zh) * | 2017-03-08 | 2020-01-14 | Oppo广东移动通信有限公司 | 一种参数调整方法及设备 |
US10514462B2 (en) * | 2017-12-13 | 2019-12-24 | Luminar Technologies, Inc. | Training a machine learning based model of a vehicle perception component based on sensor settings |
CN108375775B (zh) * | 2018-01-17 | 2020-09-29 | 上海禾赛光电科技有限公司 | 车载探测设备及其参数的调整方法、介质、探测系统 |
CN108681436B (zh) * | 2018-03-13 | 2020-09-22 | Oppo广东移动通信有限公司 | 画质参数调节方法、装置、终端及存储介质 |
US10683004B2 (en) * | 2018-04-09 | 2020-06-16 | Ford Global Technologies, Llc | Input signal management for vehicle park-assist |
CN109552289B (zh) * | 2018-11-29 | 2020-06-02 | 辽宁工业大学 | 一种汽车自适应辅助制动系统及其控制方法 |
CN109774584B (zh) * | 2019-01-21 | 2021-07-13 | 安徽天健环保车辆部件有限公司 | 一种客车用智能雨量灯光控制系统及控制方法 |
KR20200139443A (ko) * | 2019-06-04 | 2020-12-14 | 주식회사 만도 | 운전자 보조 시스템 및 그 제어 방법 |
US20230029093A1 (en) * | 2021-07-20 | 2023-01-26 | Nissan North America, Inc. | Computing Framework for Vehicle Decision Making and Traffic Management |
-
2019
- 2019-06-21 CN CN202211143926.7A patent/CN115616952A/zh active Pending
- 2019-06-21 CN CN201910542746.8A patent/CN112114541B/zh active Active
- 2019-06-21 CN CN202211144289.5A patent/CN115657515A/zh active Pending
-
2020
- 2020-06-20 WO PCT/CN2020/097296 patent/WO2020253857A1/zh unknown
- 2020-06-20 EP EP20826259.2A patent/EP3974262A4/en active Pending
-
2021
- 2021-12-21 US US17/557,645 patent/US20220113371A1/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104691447A (zh) * | 2013-12-04 | 2015-06-10 | 通用汽车环球科技运作有限责任公司 | 用于动态地聚焦车辆传感器的系统和方法 |
CN103707826A (zh) * | 2013-12-17 | 2014-04-09 | 华南理工大学 | 一种自适应调整驾驶模式的汽车感应系统 |
CN104477168A (zh) * | 2014-11-28 | 2015-04-01 | 长城汽车股份有限公司 | 汽车中的自适应巡航系统及方法 |
JP2018005830A (ja) * | 2016-07-08 | 2018-01-11 | トヨタ自動車株式会社 | 車両の制御装置 |
KR101947473B1 (ko) * | 2017-05-29 | 2019-04-29 | 국민대학교산학협력단 | 후방 차량을 고려한 안전 운전 지원 장치 및 방법 |
CN109017802A (zh) * | 2018-06-05 | 2018-12-18 | 长沙智能驾驶研究院有限公司 | 智能驾驶环境感知方法、装置、计算机设备和存储介质 |
CN109017803A (zh) * | 2018-07-14 | 2018-12-18 | 安徽中科美络信息技术有限公司 | 一种车载终端工作模式控制方法及车载终端 |
CN109532824A (zh) * | 2018-12-19 | 2019-03-29 | 杭州湘滨电子科技有限公司 | 一种水平泊车的路沿识别方法 |
Non-Patent Citations (1)
Title |
---|
See also references of EP3974262A4 |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102022201219B3 (de) | 2022-02-07 | 2023-03-02 | Zf Friedrichshafen Ag | Fahrzeugsystem, insbesondere für eine E/E-(Elektrisch/Elektronische)-Architektur und Fahrzeug |
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CN112114541A (zh) | 2020-12-22 |
CN115616952A (zh) | 2023-01-17 |
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US20220113371A1 (en) | 2022-04-14 |
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EP3974262A4 (en) | 2022-11-02 |
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