KR102853271B1 - Signal processing module and system integration module using the same - Google Patents

Abstract

The present invention relates to a signal processing module, and may include a function weight table that stores weights for each first sensor according to an autonomous driving mode and an ADAS driving mode, and selects and outputs only the weights for each first sensor corresponding to a driving mode selected from among the autonomous driving mode and the ADAS driving mode, a first weight application unit that applies the weights for each sensor corresponding to the selected driving mode to sensing information of sensors for detecting an object to generate a function weight application signal, a road environment determination unit that determines a road environment based on the sensing information of the sensors, a road environment weight table that stores weights for each second sensor according to the road environment, and selects and outputs only the weights for each second sensor corresponding to a determination result of the road environment determination unit, and a second weight application unit that applies the weights for each second sensor corresponding to the determination result to the function weight application signal and outputs it as a data set.

Description

Signal processing module and system integration module including the same {SIGNAL PROCESSING MODULE AND SYSTEM INTEGRATION MODULE USING THE SAME}

The present invention relates to a signal processing module capable of supporting both autonomous driving and ADAS (Advanced Driver Assistance System) deployed in a vehicle, and a system integration module including the same.

As technology advances, vehicles are increasingly equipped with various sensors and electronic devices for user convenience. In particular, research is actively underway into Advanced Driver Assistance Systems (ADAS) to enhance user convenience. Furthermore, development of autonomous vehicles is also actively underway.

Since both advanced driver assistance systems and autonomous driving can be selected by the driver, the development of a system integration module that can apply both advanced driver assistance systems and autonomous driving is urgent.

An embodiment of the present invention seeks to provide a signal processing module and a system integration module including the same, to which both an advanced driver assistance system and autonomous driving can be applied.

An embodiment of the present invention provides a signal processing module capable of applying weights to sensing results of sensors used in an advanced driver assistance system or autonomous driving, and a system integration module including the same.

The technical problems of the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below.

A signal processing module according to an embodiment of the present invention may include a function weight table that stores weights for each first sensor according to an autonomous driving mode and an ADAS driving mode, and selects and outputs only the weights for each first sensor corresponding to a driving mode selected from among the autonomous driving mode and the ADAS driving mode, a first weight application unit that applies the weights for each sensor corresponding to the selected driving mode to sensing information of sensors for detecting an object to generate a function weight application signal, a road environment determination unit that determines a road environment based on the sensing information of the sensors, a road environment weight table that stores weights for each second sensor according to the road environment, and selects and outputs only the weights for each second sensor corresponding to a determination result of the road environment determination unit, and a second weight application unit that applies the weights for each second sensor corresponding to the determination result to the function weight application signal and outputs the result as a data set.

A system integration module according to another embodiment of the present invention may include a plurality of sensors for determining objects outside a vehicle, an internal communication module for communicating with control devices inside a vehicle, an external communication module for communicating with devices outside the vehicle, and a signal processing module for applying a first weight according to a driving mode and a second weight according to a road environment to information obtained by communicating with at least one of the plurality of sensors, the internal communication module, and the external communication module.

This technology can be applied to both advanced driver assistance systems (ADAS) and autonomous driving, and can further advance the development of ADAS and autonomous driving.

In addition, the present technology can improve the accuracy of object judgment by applying weights to the sensing results of sensors for judging objects.

In addition, various effects may be provided, either directly or indirectly, through this document.

FIG. 1 is a simplified configuration diagram of a vehicle to which a system integration module according to one embodiment of the present invention is applied.
FIG. 2 is a configuration diagram of a signal processing module included in a system integration module according to one embodiment of the present invention.
FIG. 3 and FIG. 4 are flowcharts for explaining the operation of a signal processing module included in a system integration module according to one embodiment of the present invention.
FIG. 5 is a flowchart for explaining the operation of a system integration module according to one embodiment of the present invention.

Hereinafter, some embodiments of the present invention will be described in detail with reference to exemplary drawings. When designating components in each drawing, it should be noted that, where possible, identical components will be given the same reference numerals, even if they appear in different drawings. Furthermore, when describing embodiments of the present invention, detailed descriptions of related known structures or functions will be omitted if they are deemed to hinder understanding of the embodiments of the present invention.

In describing components of embodiments of the present invention, terms such as first, second, A, B, (a), (b), etc. may be used. These terms are only intended to distinguish the components from other components, and the nature, order, or sequence of the components are not limited by these terms. Furthermore, unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning they have in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined in this application.

Hereinafter, embodiments of the present invention will be described in detail with reference to FIGS. 1 to 5.

FIG. 1 is a simplified configuration diagram of a vehicle to which a system integration module according to one embodiment of the present invention is applied.

Referring to FIG. 1, a system integration module according to one embodiment of the present invention may be formed integrally with the internal control units of a vehicle, or may be implemented as a separate device and connected to the control units of the vehicle by a separate connection means.

Referring to FIG. 1, a system integration module according to an embodiment of the present invention may include a plurality of modules. At least one of the plurality of modules may include a device and a sensor for detecting an object located outside the periphery of a vehicle. At least one of the plurality of modules may include a communication module that enables wired/wireless communication between components or devices inside the vehicle. At least one of the plurality of modules may include a communication module that enables wireless communication with a device outside the vehicle. At least one of the plurality of modules may include a motor for moving a plurality of modules mounted on the system integration module and a module for motor control.

For example, the system integration module may include at least one Lidar, an ultrasonic sensor, and a camera for detecting objects located around the vehicle.

The system integration module may include a module for storing high-precision maps. High-precision maps can be defined as maps with a significantly reduced margin of error, for example, an accuracy of within 10 cm. They can include information on lane-level information such as road centerlines and boundaries, as well as information on various structures such as traffic lights, signs, curbs, and road markings.

The system integration module may include a display for notifications. The display included in the system integration module may be configured to provide visual information to the outside of the vehicle.

The system integration module may include internal communication modules such as CAN (Controller Area Network), LIN (Local Internet Network), Flex-Ray, and Ethernet that enable wired/wireless communication between internal vehicle components or devices.

The system integration module may include an external communication module used for V2X (Vehicle to everything communication) that can connect to an external network to enable wireless communication with devices outside the vehicle.

The system integration module may include a sensor module movement motor and a sensor module controller for controlling the motor to move the position of a device, component or module mounted on the system integration module, such as a communication module, a display and an object detection device.

The system integration module may include a signal processing module that processes sensing signals from sensors such as lidar, cameras, and ultrasonic sensors for object detection. The signal processing module may perform signal processing that assigns weights to the sensing signals from the sensors for object detection.

To be more specific, the signal processing module can assign weights to each sensor according to functions such as autonomous driving selection and ADAS driving selection, and can assign weights to each sensor according to weather conditions, road information, and road conditions.

The system integration module configured in this manner can perform wired/wireless communication with sensors and devices mounted inside the vehicle, sensors and devices controlling the vehicle chassis, a driver output interface, and a vehicle control output interface.

For example, the system integration module can communicate with sensors and devices installed inside the vehicle, such as an in-vehicle camera, driving mode switch, navigation (NAV), in-vehicle ultrasonic sensors, and radar, either wired or wireless.

The system integration module can perform wired or wireless communication with sensors and devices for controlling the vehicle chassis, such as a steering wheel, an accelerator pedal, a brake pedal, a wheel speed sensor, a yaw rate sensor, a steering angle sensor, and a G sensor.

The system integration module can communicate with a driver output interface (wired or wireless) to provide visual and audio information to the driver. For example, the driver output interface may include speakers and displays installed inside the vehicle.

The system integration module can communicate with the vehicle control output interface via wired or wireless communication. For example, the system integration module can provide object and operation information detected inside and outside the vehicle to the vehicle control output interface.

The vehicle control output interface can control the movement of the vehicle based on information provided from the system integration module. The vehicle control output interface can control the engine control system, the braking control system, and the steering control system based on information provided from the system integration module.

FIG. 2 is a configuration diagram of a signal processing module included in a system integration module according to one embodiment of the present invention.

Referring to FIG. 2, a system integration module (100) according to an embodiment of the present invention may include a function weight table (110), a first weight application unit (120), a road environment judgment unit (130), a road environment weight table (140), and a second weight application unit (150).

The function weight table (110) can store function weights for each sensor. The function weight table (110) can select function weights for each sensor corresponding to a vehicle function selected by the driver and output them as function selection weights (T_s1).

For example, the function weight table (110) can store the sensor-specific function weights applied during autonomous driving and the sensor-specific function weights applied during ADAS driving. In addition, the function weight table (110) can select one sensor-specific weight among the sensor-specific function weights applied during autonomous driving and the sensor-specific function weights applied during ADAS driving based on a function selection signal (F_s) input according to the vehicle function selected by the driver, and output the selected sensor-specific function weight as a function selection weight (T_s1).

To explain in more detail, the function weight table (110) can output the function weights for each sensor used in autonomous driving as function selection weights (T_s1) when the function selection signal (F_s) is enabled, and can output the function weights for each sensor used in ADAS driving as function selection weights (T_s1) when the function selection signal (F_s) is disabled.

The first weight application unit (120) may receive a function selection weight (T_s1) from the function weight table (110) and may receive sensing signals (S_i) of sensors for detecting objects inside and outside the vehicle. The first weight application unit (120) may apply the function selection weight (T_s1) to the sensing signal (S_1) and output it as a function weight application signal (W_a). At this time, the sensing signal (S_i) may include sensing results of sensors for detecting objects inside and outside the vehicle, such as a sensing result of a lidar, a sensing result of an ultrasonic sensor, an acquired image of a camera, location information of a high-precision map according to a GPS (Global Positioning System), and a sensing result of a radar.

The road environment judgment unit (130) can judge the road environment on which the vehicle is currently driving based on the sensing signal (S_i).

For example, the road environment judgment unit (130) can judge the weather environment, road information, and road conditions of the road on which the vehicle is currently driving based on the sensing signal (S_i). At this time, the judgment of the weather environment may include judgment of the weather of the driving road, such as snow, rain, fog, etc., and judgment of the time, such as day and night. Judgment of the road information may include judgment of the road type, such as tunnels and bridges. Judgment of the road condition may include distinguishing between city driving and intercity driving, between highway driving and national road driving, and judging the traffic volume of the driving road.

The road environment weight table (140) can store road environment judgment weights for each sensor. The road environment weight table (140) can select at least one sensor-specific road environment judgment weight among the sensor-specific road environment judgment weights according to the judgment result of the road environment judgment unit (130), and output the selected sensor-specific road environment judgment weight as an environment judgment weight (T_s2).

For example, the road environment weight table (140) can select road environment judgment weights for each sensor corresponding to the judgment results of weather conditions, road information, and road conditions included in the road environment judgment results of the road environment judgment unit (130), and output the selected road environment judgment weights for each sensor as environment judgment weights (T_s2).

The second weight application unit (150) can receive a function weight application signal (W_a) from the first weight application unit (120) and an environment judgment weight (T_s2) from the road environment weight table (140). The second weight application unit (150) can apply the environment judgment weight (T_s2) to the function weight application signal (W_a) and output it as a weight application data set (SD). At this time, the weight application data set (SD) can be used for ADAS driving and autonomous driving.

FIG. 3 and FIG. 4 are flowcharts for explaining the operation of a signal processing module included in a system integration module according to one embodiment of the present invention.

FIG. 3 is a flowchart for explaining an operation method of a signal processing module included in a system integration module according to one embodiment of the present invention.

Referring to FIG. 3, the operation method of the signal processing module (100) may include a function selection step (S1), a weight selection step for each function selection sensor (S2), a first weight application step (S3), a road environment judgment step (S4), a weight selection step for each road environment judgment sensor (S5), and a second weight application step (S6).

The function selection step (S1) may include a step in which the driver selects autonomous driving and ADAS driving.

The weight selection step (S2) for each sensor in the function selection sensor may select weights for each sensor according to autonomous driving or weights for each sensor according to ADAS.

For example, weights may be selected for each piece of information that may be provided to the system integration module according to the present invention, such as image information (camera information) acquired from a camera, lidar information acquired from a lidar, ultrasonic information acquired from an ultrasonic sensor, external communication information acquired from an external communication module, high-precision map information acquired from GPS and a high-precision map, and radar information acquired from a radar. In addition, different weights may be selected for each piece of information depending on whether autonomous driving or ADAS driving is selected.

To give a more detailed example, if the weight for camera information during autonomous driving is A, the weight for camera information during ADAS driving may be B. A and B may be the same value or different values.

In summary, the weight selection step (S2) for each function selection sensor may include a step in which one of autonomous driving and ADAS driving is selected in the function selection step (S1) and weights for each sensor for the selected driving are selected.

The first weight application step (S3) may include a step of applying the weights for each sensor selected in the weight selection step (S2) for each function selection sensor to the sensing signal (S_1) provided to the signal processing module (100), i.e., information acquired from each sensor.

For example, the first weight application step (S3) may apply the camera weight selected in the weight selection step (S2) for each function selection sensor to the camera information. At this time, the camera weight selected in the weight selection step (S2) for each function selection sensor refers to the function camera weight, and the value of the function camera weight may be different or the same when autonomous driving or ADAS driving is selected.

The first weight application step (S3) may apply the lidar weight selected in the weight selection step (S2) for each function selection sensor to the lidar information. At this time, the lidar weight selected in the weight selection step (S2) for each function selection sensor refers to the functional lidar weight, and the value of the functional lidar weight may be different or the same when autonomous driving or ADAS driving is selected.

The first weight application step (S3) may apply the ultrasonic weight selected in the weight selection step (S2) for each function selection sensor to the ultrasonic information. At this time, the ultrasonic weight selected in the weight selection step (S2) for each function selection sensor refers to the functional ultrasonic weight, and the value of the functional ultrasonic weight may be different or the same when autonomous driving or ADAS driving is selected.

The first weight application step (S3) can apply the communication weight selected in the weight selection step (S2) for each function selection sensor to external communication information. At this time, the communication weight selected in the weight selection step (S2) for each function selection sensor refers to the functional communication weight, and the value of the functional communication weight may be different or the same when autonomous driving or ADAS driving is selected.

The first weight application step (S3) can apply the position weight selected in the weight selection step (S2) for each function selection sensor to the high-precision map information. At this time, the position weight selected in the weight selection step (S2) for each function selection sensor determines the function position weight, and the value of the function position weight may be different or the same when autonomous driving or ADAS driving is selected.

The first weight application step (S3) may apply the radar weight selected in the weight selection step (S2) for each function selection sensor to the radar information. At this time, the radar weight selected in the weight selection step (S2) for each function selection sensor refers to the functional radar weight, and the value of the functional radar weight may be different or the same when autonomous driving or ADAS driving is selected.

The road environment judgment step (S4) is a step for judging the environment of the road on which the vehicle is currently driving, and may include judgment of weather information including weather and time, judgment of road information including road types such as tunnels and bridges, and judgment of road conditions that distinguish between city and intercity driving, expressway and national road driving, and judgment of traffic volume on the driving road.

The weight selection step (S5) for each road environment judgment sensor may include a step of selecting a weight for each sensor corresponding to the result judged in the road environment judgment step (S4).

The second weight application step (S6) may include a step of applying weights for each sensor selected in the road environment judgment sensor weight selection step (S5) to the information to which weights were applied in the first weight application step (S3).

For example, the second weight application step (S6) may apply the camera weight selected in the weight selection step (S5) for each road environment judgment sensor to the camera information to which the functional weight was applied in the first weight application step (S3). At this time, the camera weight selected in the weight selection step (S5) for each road environment judgment sensor may refer to the road environment judgment camera weight.

The second weight application step (S6) may apply the lidar weight selected in the weight selection step (S5) for each road environment judgment sensor to the lidar information to which the functional weight was applied in the first weight application step (S3). At this time, the lidar weight selected in the weight selection step (S5) for each road environment judgment sensor may refer to a lidar weight for determining the road environment.

The second weight application step (S6) may apply the ultrasonic weight selected in the weight selection step (S5) for each road environment judgment sensor to the ultrasonic information to which the functional weight was applied in the first weight application step (S3). At this time, the ultrasonic weight selected in the weight selection step (S5) for each road environment judgment sensor may refer to the ultrasonic weight for determining the road environment.

The second weight application step (S6) may apply the communication weight selected in the weight selection step (S5) for each road environment judgment sensor to the communication information to which the functional weight was applied in the first weight application step (S3). At this time, the communication weight selected in the weight selection step (S5) for each road environment judgment sensor may refer to a road environment judgment communication weight.

The second weight application step (S6) may apply the position weight selected in the weight selection step (S5) for each road environment judgment sensor to the position information to which the functional weight was applied in the first weight application step (S3). At this time, the position weight selected in the weight selection step (S5) for each road environment judgment sensor may refer to a road environment judgment position weight.

The second weight application step (S6) may apply the radar weight selected in the weight selection step (S5) for each road environment judgment sensor to the radar information to which the functional weight was applied in the first weight application step (S3). At this time, the radar weight selected in the weight selection step (S5) for each road environment judgment sensor may refer to a road environment judgment radar weight.

FIG. 4 is a drawing for explaining in more detail the road environment judgment step (S4), the weight selection step (S5) for each road environment judgment sensor, and the second weight application step (S6) of FIG. 3.

As illustrated in Fig. 4, the road environment judgment step (S4) may include a weather environment judgment step (S11), a road information judgment step (S21), and a road situation judgment step (S31).

The weather environment judgment step (S11) is a step that judges the weather environment of the driving road based on external communication information and camera information, and can judge whether it is raining, snowing, or at night.

If, in the weather environment judgment step (S11), it is determined that it is raining, snowing, or at night, in the road environment judgment sensor weight selection step (S5), the highest weight can be selected for radar information and location information, and the lowest weight can be selected for camera information.

The weather environment weight application step (S12) can apply the highest weight selected in the road environment judgment sensor weight selection step (S5) to radar information and location information, and apply the lowest weight to camera information.

A step (S13) can be performed in which weighted sensing results (e.g., radar information, location information, and camera information) are output as a weather environment sensor signal data set through a weather environment judgment step (S11) and a weather environment weight application step (S12).

The road information judgment step (S21) is a step that judges the shape of the road on which the vehicle is currently driving, and can determine whether the road on which the vehicle is driving is a tunnel or a bridge.

If the road being driven is determined to be a tunnel or a bridge in the road information judgment step (S21), the highest weight can be selected for the lidar information and location information in the weight selection step (S5) for each road environment judgment sensor, and lower weights can be selected for the radar information and camera information than for the lidar and location information.

The road information weight application step (S22) can apply the highest weight to lidar information and location information, and apply a low weight to radar and camera information.

A step (S23) in which weighted sensing results (e.g., lidar information, location information, radar information, and camera information) are output as a road information sensor signal data set through a road information judgment step (S21) and a road information weight application step (S22) can be performed.

The road condition judgment step (S31) can distinguish between city and intercity driving, highway driving and national road driving, and determine the traffic volume on the driving road.

If it is determined that the driving is in a city with heavy traffic volume in the road condition judgment step (S31), the highest weight can be selected for the lidar information, camera information, and location information, and a lower weight can be selected for the radar information than the lidar information, camera information, and location information.

The road condition weighting application step (S32) can apply the highest weight to lidar information, camera information, and location information, and apply a low weight to radar information.

A step (S33) in which weighted sensing results (e.g., lidar information, camera information, location information, and radar information) are output as a road condition sensor signal data set through a road condition judgment step (S31) and a road condition weight application step (S32) can be performed.

The integrated judgment step (S40) may include a step of outputting sensing results with weights applied according to judgment of the road environment based on a weather environment sensor signal data set, a road information sensor signal data set, and a road condition sensor signal data set.

For example, the integrated judgment step (S40) may include a step of processing overlapping sensing results among the sensing results included in the weather environment sensor signal data set, the stone information sensor signal data set, and the road condition sensor signal data set.

If it is assumed that there is overlapping camera information in the weather environment sensor signal data set, the road information sensor signal data set, and the road condition sensor signal data set, an integrated judgment step (S40) may be performed to combine and output the values of the camera information of the weather environment sensor signal data set, the camera information of the road information sensor signal data set, and the camera information of the road condition sensor signal data set.

In addition, assuming that there is overlapping camera information in the weather environment sensor signal data set, the road information sensor signal data set, and the road condition sensor signal data set, an integrated judgment step (S40) may be performed that outputs only camera information having the same value among the values of the camera information of the weather environment sensor signal data set, the camera information of the road information sensor signal data set, and the camera information of the road condition sensor signal data set.

In addition, assuming that there is overlapping camera information in the weather environment sensor signal data set, the road information sensor signal data set, and the road condition sensor signal data set, an integrated judgment step (S40) may be performed that outputs only camera information having multiple identical values among the values of the camera information of the weather environment sensor signal data set, the camera information of the road information sensor signal data set, and the camera information of the road condition sensor signal data set.

FIG. 5 is a flowchart for explaining the operation of a system integration module according to one embodiment of the present invention.

The system integration module can receive sensing results from cameras, ultrasonic sensors, and radar installed inside the vehicle, in addition to the lidar, ultrasonic sensors, cameras, and high-precision maps mounted on the system integration module.

In this way, the system integration module can receive sensing results from sensors for determining objects existing inside or outside the vehicle.

Additionally, the system integration module can receive information used for vehicle driving from an external network of the vehicle through the communication module.

The system integration module according to the present invention applies weights according to the driving mode (autonomous driving or ADAS driving) selected by the driver and weights according to the environment of the road on which the vehicle is currently driving to all information provided to the system integration module, thereby utilizing the information for autonomous driving or ADAS driving, thereby being effective in safe driving through accurate object judgment.

The operation of the system integration module of the present invention is summarized as follows with reference to FIG. 5.

A function selection step (S50) for selecting autonomous driving or ADAS driving can be performed by a driver riding in a vehicle in which a system integration module according to the present invention is installed.

If the driver selects autonomous driving, an autonomous function weight selection step (S61) may be performed in which weights for each sensor according to autonomous driving are selected.

After the autonomous function weight selection step (S61) is performed, the autonomous function sensor signal processing step (S62) can be performed in which the selected sensor-specific weights are applied to the sensing information of each sensor.

When the autonomous function sensor signal processing step (S62) is performed, the autonomous function data set output step (S63) can be performed in which weighted sensing information for autonomous driving selection is output as an autonomous function data set.

After weights are selected based on the environment of the road being driven, a road environment sensor signal data processing step (S64) can be performed in which the selected weights are applied to the autonomous function data set output in the autonomous function data set output step (S63).

When the road environment sensor signal data processing step (S64) is performed, a road environment sensor signal data set output step (S65) can be performed in which an autonomous function data set with weights applied to the road environment is output as a road environment sensor signal data set.

A vehicle driving function application step (S66) may be performed to apply the road environment sensor signal data set to the vehicle's autonomous driving function.

Meanwhile, if the driver selects ADAS driving, an ADAS function weight selection step (S71) may be performed in which weights for each sensor according to ADAS driving are selected.

After the ADAS function weight selection step (S71) is performed, the ADAS function sensor signal processing step (S72) can be performed in which the selected sensor-specific weights are applied to the sensing information of each sensor.

When the ADAS function sensor signal processing step (S72) is performed, the ADAS function data set output step (S73) can be performed in which weighted sensing information for ADAS driving selection is output as an ADAS function data set.

After weights are selected based on the environment of the road being driven, a road environment sensor signal data processing step (S73) can be performed in which the selected weights are applied to the ADAS function data set output in the ADAS function data set output step (S73).

When the road environment sensor signal data processing step (S74) is performed, a road environment sensor signal data set output step (S75) can be performed in which an ADAS function data set with weights applied to the road environment is output as a road environment sensor signal data set.

A vehicle ADAS driving function application step (S76) of applying a road environment sensor signal data set to the vehicle ADAS driving function can be performed.

The above description is merely an example of the technical idea of the present invention, and those skilled in the art will appreciate that various modifications and variations can be made without departing from the essential characteristics of the present invention.

Accordingly, the embodiments disclosed in the present invention are intended to illustrate, rather than limit, the technical concept of the present invention, and the scope of the technical concept of the present invention is not limited by these embodiments. The scope of protection of the present invention should be interpreted by the following claims, and all technical concepts within the scope equivalent thereto should be construed as being included within the scope of the present invention.

Claims (7)

In a signal processing module that outputs a data set for judging objects during autonomous driving and ADAS driving,
A function weight table that stores weights for each first sensor according to an autonomous driving mode and an ADAS driving mode, and selects and outputs only the weights for each first sensor corresponding to a driving mode selected among the autonomous driving mode and the ADAS driving mode;
A first weight application unit that applies a weight for each first sensor corresponding to the selected driving mode to sensing information of sensors for detecting an object to generate a function weight application signal;
A road environment judgment unit that judges the road environment based on sensing information from the above sensors;
A road environment weight table that stores weights for each second sensor according to the road environment and selects and outputs only the weights for each second sensor corresponding to the judgment result of the road environment judgment unit; and
A second weight application unit that applies the second sensor-specific weight corresponding to the judgment result to the function weight application signal and outputs the result as a data set;
A signal processing module including .
In claim 1,
The above sensors are,
A signal processing module characterized by including at least one of a lidar, a radar, a camera, and an ultrasonic sensor.
In claim 2,
The above road environment judgment unit is,
A signal processing module characterized in that it determines the weather environment, road information, and road conditions of a road on which a vehicle is driving based on information acquired from at least one of the lidar, the radar, the camera, and the ultrasonic sensor.
In claim 3,
The above road environment judgment unit is,
Distinguish between rain or snow and no rain or snow, and between night and day.
Determines whether the road you are driving on is a tunnel or a bridge.
A signal processing module characterized by judging the traffic volume on a road while driving.
Multiple sensors for determining objects outside the vehicle;
An internal communication module for communicating with control devices inside the vehicle;
An external communication module for communicating with devices outside the vehicle; and
A signal processing module that applies a first weight according to the driving mode and a second weight according to the road environment to information obtained by communicating with at least one of the plurality of sensors, the internal communication module, and the external communication module;
Including,
The above signal processing module,
For each piece of sensing information, apply the first weight for each sensor for autonomous driving mode and ADAS driving mode,
A system integration module characterized in that a second weight for each sensor for the road environment is applied to each of the sensing information to which the first weight for each sensor for the autonomous driving mode and the ADAS driving mode is applied. delete In claim 5,
The above signal processing module,
A functional weight table that stores weights for each sensor for the autonomous driving mode and the ADAS driving mode, and outputs only the stored weights for each sensor corresponding to the driving mode selected among the autonomous driving mode and the ADAS driving mode as the first weight.
A first weight application unit that applies the first weight to each of the sensing information and outputs it as a function weight application signal;
A road environment judgment unit that judges the road environment from the above sensing information,
A road environment weight table that stores weights for each sensor for the above road environment and outputs only the stored weights for each sensor corresponding to the judgment result of the road environment as the second weights, and
A system integration module characterized by including a second weight application unit that applies the second weight to the above function weight application signal.