KR102533246B1 - Navigation Apparutaus and Driver Assistance Apparatus Having The Same - Google Patents

Abstract

A navigation device according to an embodiment includes a GPS module for receiving GPS information of a vehicle including a GPS measurement location, a pseudo distance measurement value with a satellite, and a location of the satellite; an inertial sensor for measuring inertial information including acceleration and angular velocity of the vehicle; and a GPS location accuracy estimator for calculating an error level of the GPS measurement location based on the GPS information and estimating an accuracy of the GPS measurement location from the calculated error level, and an accuracy of the GPS information and the GPS measurement location. and a navigation processor including a state variable estimator that updates state variables based on the inertial information, wherein the navigation processor can obtain the position, speed, and moving direction of the vehicle through the updated state variables. .

Description

Navigation device and vehicle driving assistance device including the same {Navigation Apparutaus and Driver Assistance Apparatus Having The Same}

The present invention relates to a navigation device for recognizing the position, speed and direction of a vehicle by converging an inertial sensor and a GPS sensor, and a vehicle driving assistance device including the same.

A vehicle is a device that allows a user to move in a desired direction. A typical example is a car.

According to the classification according to the prime mover used, automobiles include an internal combustion engine automobile, an external combustion engine automobile, a gas turbine automobile, or an electric vehicle.

An electric vehicle refers to a vehicle that uses electricity as energy to turn an electric motor, and includes pure electric vehicles, hybrid electric vehicles (HEV), plug-in hybrid electric vehicles (PHEV), and hydrogen fuel cell electric vehicles (FCEV).

Recently, for the safety or convenience of drivers, pedestrians, etc., the development of smart vehicles has been actively pursued.

An intelligent car is a state-of-the-art car that integrates information technology (IT) technology, and is also called a smart car. Intelligent vehicles provide optimal traffic efficiency through the introduction of cutting-edge systems of the vehicle itself as well as interworking with the Intelligent Transportation System (ITS).

In addition, research on sensors mounted on such intelligent vehicles is being actively conducted. In detail, cameras, infrared sensors, radars, GPS, Lidar, gyroscopes, etc. are used in intelligent vehicles, and among them, cameras occupy an important position as sensors that act as substitutes for human eyes.

Therefore, due to the development of various types of sensors and electronic equipment, vehicles equipped with driving assistance functions (ADAS) that assist users in driving and improve driving safety and convenience are drawing attention.

Before providing driving assistance functions (ADAS) and autonomous driving functions, it is necessary to first obtain navigation information including the location, speed, and direction of movement of the vehicle.

And most technologies currently use a global positioning system (GPS) to acquire navigation information.

However, since it is difficult to precisely measure the position of the GPS, it is difficult to use it for driving assistance functions or autonomous driving requiring precise data.

In order to compensate for this problem, technologies for recognizing a location by converging an inertial navigation system (INS) and a GPS with an inertial sensor have been proposed. This sensor fusion technology can supplement the weaknesses of INS and GPS respectively.

As an example of the prior art, there is a technology related to a navigation system and method for recognizing the position, speed, and direction of a platform by sensor fusion of IONS and GPS. In detail, the navigation system includes a GPS module for measuring absolute coordinates of the vehicle from information received from satellites, an inertial sensor, and an optical sensor. And the navigation system integrates the IONS module for measuring the relative coordinates, speed and direction of the vehicle, the absolute coordinates of the vehicle measured by the GPS module, and the relative coordinates, speed and direction of the vehicle measured by the IONS module. It is characterized by further including a control unit for determining the location, speed and direction of travel of the vehicle by determining the location, speed and direction of travel of the vehicle even when the GPS module does not receive signals from satellites for a certain period of time.

However, the prior invention only considers the case where the GPS module cannot be used due to GPS signal disconnection, and when combining GPS information and inertial sensor information, only absolute coordinates obtained from GPS are used, and the accuracy of navigation information is limited. there is. In addition, since an optical sensor is used in addition to an inertial sensor, there is a problem in that cost is excessively consumed and excessive resources are consumed for operating the system.

As another example, by combining radio frequency identification (RFID) positioning technology with a positioning device that combines an incomplete global positioning system (GPS) and an inertial navigation system (INS), even when the GPS signal is disconnected There is a technology related to an integrated positioning device combining radio recognition/satellite positioning/inertial navigation, which enables stable and continuous positioning information to be obtained using RFID positioning information and INS positioning information. In addition, in order to solve problems that may appear in the GPS/INS combination method, the above technology uses radio frequency identification (RFID) positioning in GPS/INS incomplete positioning devices that may cause GPS signal disconnection and INS accumulation of errors over time. By combining technologies, we propose a method to solve problems that may appear in GPS/INS positioning devices. However, the above technology has a problem in that an additional sensor is required to use radio frequency identification (RFID) positioning technology, and infrastructure construction is required. In addition, the above technology considers only the disconnection of the GPS signal and does not consider multipath errors that may occur in urban conditions.

That is, the prior art uses a GPS module and an inertial sensor module for positioning, but considers only the GPS signal disconnection situation, and there is a limit to the need for additional sensors to overcome this.

In this paper, the vehicle position, speed, and heading angle were estimated using the GPS module, vehicle odometer, and gyro as sensors for vehicle navigation. An extended Kalman filter was used as the sensor information fusion method.

In particular, there is no special consideration in this prior paper for the case where a large error occurs in the GPS location, such as in an urban environment, whereas in this patent, the GPS error level is estimated to match the actual error, thereby providing a stable location of the vehicle even in an urban environment. made to do

In addition, to estimate the position of the vehicle, this prior paper used a vehicle odometer, but this patent uses an accelerometer and does not require additional communication to obtain vehicle travel information.

As another example, for vehicle navigation, a GPS module, an odometer, and a gyro are used as sensors to estimate vehicle position, speed, and heading angle, and there is a technology that uses a particle filter as a sensor information convergence method. However, the above technique also has a problem in that it does not consider multipath errors that may occur in urban conditions. In addition, in order to estimate the position of the vehicle, the vehicle odometer must be used, which requires an additional communication module for communication with the vehicle ECU.

That is, in the prior art described above, since the error level of GPS information is maintained at a constant value in an open field environment with high GPS information accuracy, the position result calculated by the INS/GPS Integrated System may have high accuracy. However, in the prior art, since the error level of the GPS position cannot be accurately known in an environment where a large error occurs in the GPS position, such as in a city center, when the inertial sensor information and GPS information are fused, the GPS position information is compared to the actual GPS position error level. can only be trusted As a result, this causes a large error in the position result calculated by the INS/GPS Integrated System.

As described above, the prior art has a problem of adding a separate unnecessary configuration such as an optical sensor or a communication module in order to fuse GPS and inertial sensor information, which consequently increases cost and causes unnecessary process consumption. .

In addition, the prior art cannot accurately estimate the error level of the GPS location in an environment where a large error occurs in the GPS location due to the threat of multi-path error, such as in a city center. Therefore, when the inertial sensor information and GPS information are fused, the GPS location information is trusted compared to the actual GPS location error level, resulting in a large error in the location result calculated by the INS/GPS Integrated System.

The present invention is to solve the above-mentioned problems, it is possible to combine the inertial sensor and GPS information without an additional sensor, and for the case where a large error occurs in the GPS position as in an urban situation through the position accuracy estimation unit of the GPS module It is intended to propose a navigation device that can stably provide the location of a vehicle even in an urban environment by estimating the GPS error level to match the actual error, and a vehicle driving assistance device including the same.

A navigation device according to an embodiment includes a GPS module for receiving GPS information of a vehicle including a GPS measurement location, a pseudo distance measurement value with a satellite, and a location of the satellite; an inertial sensor for measuring inertial information including acceleration and angular velocity of the vehicle; and a GPS location accuracy estimator for calculating an error level of the GPS measurement location based on the GPS information and estimating an accuracy of the GPS measurement location from the calculated error level, and an accuracy of the GPS information and the GPS measurement location. and a navigation processor including a state variable estimator that updates state variables based on the inertial information, wherein the navigation processor can obtain the position, speed, and moving direction of the vehicle through the updated state variables. .

In another aspect, a navigation device according to an embodiment includes a GPS module for obtaining GPS information; an inertial sensor for acquiring inertial information including acceleration and angular velocity of the vehicle; and a navigation processor for acquiring navigation information of the vehicle calculated based on the GPS information and inertial information, wherein the navigation processor calculates a multipath error from the GPS information, and calculates the multipath error as a GPS measurement location A GPS position accuracy estimator that converts to an accuracy of , updates a state variable based on the GPS information and the inertia information, and estimates an error of the state variable based on the GPS measurement position accuracy in a state variable update process, and estimates the error and a state variable estimator for updating the state variable by reflecting .

The navigation device according to the embodiment may provide robust location recognition information by fusing inertial information and GPS information.

In particular, in the navigation device according to the embodiment, the present invention has a large error in GPS position in a case where there is a lot of threat of multi-path error, such as in an urban environment, which has been considered as a limitation of positioning methods through a combination of a GPS module and an INS sensor. Even in the case of occurrence, the positioning performance of GPS/INS navigation can be improved by more accurately estimating the error level of the GPS position.

In addition, the navigation device according to the embodiment has the advantage of being able to fuse inertial information and GPS information without a separate additional unit.

1 shows an appearance of a vehicle including a vehicle driving assistance device equipped with a navigation device according to an embodiment of the present invention.
2 shows a block diagram of a navigation device according to an embodiment of the present invention.
3 illustrates a process of obtaining navigation information by a navigation device according to an embodiment of the present invention.
4 is a graph comparing navigation information obtained by a navigation device according to an embodiment of the present invention, navigation information simply received from a GPS, and navigation information of an actual vehicle.
5 is a block diagram of a vehicle driving assistance device including a navigation device according to an embodiment of the present invention.
6 is an example of an internal block diagram of the vehicle of FIG. 1 including the aforementioned vehicle driving assistance device.

Hereinafter, the embodiments disclosed in this specification will be described in detail with reference to the accompanying drawings, but the same or similar elements are given the same reference numerals regardless of reference numerals, and redundant description thereof will be omitted. The suffixes "module" and "unit" for components used in the following description are given or used together in consideration of ease of writing the specification, and do not have meanings or roles that are distinct from each other by themselves. In addition, in describing the embodiments disclosed in this specification, if it is determined that a detailed description of a related known technology may obscure the gist of the embodiment disclosed in this specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in this specification, the technical idea disclosed in this specification is not limited by the accompanying drawings, and all changes included in the spirit and technical scope of the present invention , it should be understood to include equivalents or substitutes.

Terms including ordinal numbers, such as first and second, may be used to describe various components, but the components are not limited by the terms. These terms are only used for the purpose of distinguishing one component from another.

It is understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, but other elements may exist in the middle. It should be. On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it should be understood that no other element exists in the middle.

Singular expressions include plural expressions unless the context clearly dictates otherwise.

In this application, terms such as "comprise" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

A vehicle described in this specification may be a concept including a car and a motorcycle. Hereinafter, vehicles will be mainly described with respect to vehicles.

The vehicle described in this specification may be a concept including all of an internal combustion engine vehicle having an engine as a power source, a hybrid vehicle having an engine and an electric motor as a power source, an electric vehicle having an electric motor as a power source, and the like.

In the following description, the left side of the vehicle means the left side of the driving direction of the vehicle, and the right side of the vehicle means the right side of the driving direction of the vehicle.

In the following description, unless otherwise noted, a left hand drive (LHD) vehicle will be mainly described.

In the following description, a vehicle driving assistance device is a separate device provided in a vehicle, and is described as exchanging necessary information with the vehicle through data communication to execute a vehicle driving assistance function. However, a set of some of vehicle units may be defined as a vehicle driving assistance device.

Also, when the vehicle driving assistance device is a separate device, at least some of the units (see FIG. 5 ) of the vehicle driving assistance device are not included in the vehicle driving assistance device and may be units of the vehicle or other devices mounted in the vehicle. there is. In addition, it can be understood that these external units are included in the vehicle driving assistance device by transmitting and receiving data through an interface unit of the vehicle driving assistance device.

For convenience of description, the vehicle driving assistance device according to the embodiment will be described as directly including each unit shown in FIG. 5 .

Hereinafter, with reference to FIGS. 1 to 4 , the navigation device 1 according to the embodiment will be described in detail.

Referring to FIG. 1 , a vehicle 700 according to an embodiment may include wheels 13FL and 13RL rotated by a power source and a navigation device 1 .

The navigation device 1 may be directly included in the vehicle driving assistance device 100 that provides driving assistance functions (ADAS), or may transmit navigation information to the vehicle driving assistance device 100 as a separate module. Also, the navigation device 1 may be provided in the vehicle itself.

In the following description, the navigation device 1 is a separate device and will be described based on acquiring navigation information while exchanging necessary information with the vehicle 700 and/or the vehicle driving assistance device 100 through data communication.

Here, the navigation information may include at least one or more of map information related to vehicle driving, lane information, vehicle location information, set destination information, and route information according to the destination. In particular, the navigation information obtained by the navigation device 1 includes the location, speed, and direction of movement of the vehicle.

The navigation device 1 according to the embodiment can combine the location information of the GPS module and the information of the inertial sensor without a separate additional sensor, and at this time, the error level of the GPS information is estimated through the location accuracy estimation unit of the GPS module. In addition, navigation information can be provided accurately and stably even in urban conditions where multi-path errors can occur significantly.

In particular, the navigation device 1 according to the embodiment more accurately estimates the error level of the GPS position even when a large error occurs in the GPS position in a case where there is a large threat of multi-path error, such as in an urban environment. Positioning System)/INS (Inertial Navigation System) positioning performance of navigation can be improved

In detail, referring to FIG. 2 , the navigation device 1 includes a GPS module 10 for obtaining GPS information of a vehicle, an inertial sensor 20 for obtaining inertial information of a vehicle, and a fusion of GPS information and inertial information. It may include a navigation processor 50 that calculates navigation information. The navigation processor 50 may further include a GPS location accuracy estimator 30 for estimating the accuracy of GPS information and a state variable estimator 40 using an extended Kalman filter.

First, the GPS module 10 may receive GPS information from satellites. In detail, the GPS module 10 may obtain GPS information using a signal transmitted from a satellite.

The GPS information obtained by the GPS module 10 may include a GPS measurement location, a distance between at least one satellite and a vehicle (hereinafter referred to as "pseudorange with a satellite"), and a location of the at least one satellite. .

That is, the GPS module 10 serves to measure the absolute coordinates of the vehicle based on the earth-centered earth-fixed coordinate system, and may further receive pseudoranges and satellite positions as other information in the process.

Next, the inertial sensor 20 serves to measure acceleration and angular velocity of the vehicle, including an acceleration sensor and a gyro sensor.

Since the GPS module 10 and the inertial sensor 20 are widely known in the art, detailed descriptions of the operation of the inertial sensor 20 module will be omitted.

Next, the GPS location accuracy estimator 30 may estimate an error level of the GPS measurement location provided by the GPS module 10 .

In general, the GPS module 10 may provide an error level for a GPS measurement position as a specific value.

However, in an environment with severe multi-path error, such as an urban environment in which a large number of reflectors are disposed, such as a building, the error level value provided by the GPS module 10 is completely different from the actual error.

In this way, when the state variables of the vehicle are estimated based on the error level provided by the GPS module 10, it becomes a major factor in degrading the performance of the state variable estimation unit 40 using the extended Kalman filter, and as a result, the navigation device. The vehicle position measured in (1) has a large error.

Therefore, the GPS position accuracy estimation unit 30 according to the embodiment calculates the error level of the GPS measurement position based on the GPS information and estimates the error level of the GPS measurement position to be close to the error level of the actual GPS measurement value, The state variable estimation accuracy of the state variable estimator 40 can be improved even in an environment with extreme multipath errors.

Meanwhile, the error level of the GPS measurement location calculated by the GPS location accuracy estimation unit 30 indicates the accuracy of the GPS measurement location in a different meaning.

The state variable estimator 40 may update the state variable of the extended Kalman filter based on the GPS information, the estimated GPS position accuracy, and the inertial information.

Here, the Extended Kalman Filter is an algorithm developed to apply a Kalman filter to a nonlinear system, and may include a nonlinear system equation, a linearized system equation for error estimation, and a linearized measurement equation. The extended Kalman filter can estimate the state variable with an optimal value probabilistically by estimating the amount of error of the state variable using GPS information and the estimated GPS location accuracy and compensating for it in the state variable.

Here, the state variable may include information on at least one of vehicle latitude, longitude, northward speed, eastward speed, vehicle heading angle, accelerometer x-direction bias error, accelerometer y-direction bias error, and gyro z-direction bias error. there is.

Finally, the navigation processor 50 may calculate navigation information including the current location, speed and direction of movement of the vehicle based on the state variables acquired by the state variable estimation unit 40 .

As such, the navigation information calculated by the navigation device 1 is based on the GPS position accuracy estimation unit 30 calculating the positional error level of the GPS trajectory and reflecting the error level to perform the extended Kalman filter algorithm. It is possible to have the position of the vehicle precisely calculated to be closer to the actual position of the vehicle.

In terms of hardware, the navigation processor 50 includes application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), It may be implemented using at least one of processors, controllers, micro-controllers, microprocessors, and electrical units for performing other functions.

Hereinafter, with reference to FIGS. 1 to 3 , a process in which the navigation device 1 acquires navigation information using GPS location accuracy will be described in detail.

The navigation device 1 may first initialize all parameters. (200) Here, the parameter means each parameter included in the state variable.

That is, the navigation device 1 may initialize all parameters when it is determined that navigation information should be precisely obtained by fusing the GPS module 10 and the inertial sensor 20 .

In particular, if the navigation device 1 determines that the vehicle has entered the downtown area, multi-path errors will increase. In preparation for this, parameters may be initialized and the location of the vehicle may be determined using the navigation method of the present embodiment. .

If navigation information is already being acquired by the navigation method of the embodiment, the state variable of the extended Kalman filter updated based on the information of the inertial sensor 20 before receiving the GPS information may be maintained without initializing the parameters. (218)

Next, the navigation device 1 determines whether GPS information has been received from the GPS module 10 . (202) Here, the GPS information may include a GPS measurement location, a pseudo-range with a satellite, and a satellite location.

If GPS information is not received from the GPS module 10, in order to correct the previous GPS information with the inertial sensor 20 information, a step of obtaining inertial information from the inertial sensor 20 may be performed.

Next, when information is received from the GPS module 10, GPS location accuracy is estimated through the GPS information. (204)

In detail, the GPS position accuracy estimator 30 may obtain a residual error by comparing the pseudorange measurement value and the pseudorange estimate obtained from the satellite position, and by projecting the residual error to the GPS measurement location, error can be calculated. Since this residual error is an error mainly caused by a multipath error, it can accurately reflect the actual error between the location of the actual vehicle and the GPS measurement location.

Also, the error of the GPS measurement position obtained in this way may be converted into GPS positioning accuracy.

Next, the state variable estimator 40 may update the state variable of the extended Kalman filter using the GPS information and the estimated GPS location accuracy. (206)

After parameter initialization, the updated state variable is information based on GPS information, and after the state variable is updated with the inertial sensor 20 information, the updated state variable based on the GPS information and position accuracy is a fusion of GPS information and inertial information. contains information. That is, when GPS information and inertial information are fused, the reliability of the fused information can be further improved by reflecting the GPS location accuracy and merging.

After updating the state variable, the navigation processor 50 can obtain accurate current navigation information of the current vehicle by correcting the position, speed, and heading angle of the current vehicle using the updated state variable. (208)

Meanwhile, parameters reflecting inertial information may be updated to obtain next navigation information of the vehicle.

That is, the navigation device 1 may determine whether information about the inertial sensor 20 is received from the inertial sensor 20 module 20 . (210).

If information is received from the inertial sensor 20 module, the navigation processor 50 may correct an error in the information of the inertial sensor 20 using a state variable. (212)

Then, the state variable estimation unit 40 may update the state variables of the extended Kalman filter based on the corrected inertial sensor 20 information. (214)

Finally, the state variable estimator 40 updates the nonlinear equation of the extended Kalman filter (216).

In addition, the updated state variable may be used as a parameter for obtaining navigation information of the next vehicle.

That is, when the GPS module 10 acquires next GPS information after acquiring current navigation information, next navigation information may be obtained using a previous parameter reflecting inertial information.

The navigation device 1 according to the embodiment estimates the location of the vehicle by integrating GPS information and information of the inertial sensor 20 by reflecting the error of the accurate GPS measurement position, and thus an urban environment in which excessive multipath errors may occur. Accurate navigation information can also be obtained from .

Hereinafter, a detailed operation algorithm of the navigation processor 50 including the GPS position accuracy estimation unit 30 and the state variable estimation unit 40 will be described in detail.

The detailed location accuracy estimation method of the GPS location accuracy estimation unit 30 is as follows.

Equations 1 to 6 are equations of an algorithm performed in the GPS positioning accuracy estimation 30.

...(2)

...(2)

...(3)

...(3)

All of the variables in Equation 1 except for the residual error are values provided by the general GPS module 10.

In Equation 1, the Hgps matrix is equal to Equation 2.

는 i번째 위성의 시선 벡터로 수학식 3과 같이 계산한다.in Equation 2

is the line of sight vector of the ith satellite and is calculated as in Equation 3.

는 지구중심 지구고정 좌표계 기준 i번째 위성의 위치이다. GPS 모듈(10)에서 제공되는 정보를 바탕으로 계산이 가능하다. 이는 종래에 널리 알려진 기술이므로 구체적인 내용은 생략하도록 한다.in Equation 3

is the position of the ith satellite based on the geocentric geostationary coordinate system. It can be calculated based on the information provided by the GPS module 10. Since this is a widely known technique in the prior art, specific details will be omitted.

In Equation 1, the residual error between the pseudorange measurement value and the estimated value has a larger value as the multipath error is greatly included in the pseudorange measurement value in an urban environment. Therefore, by projecting the pseudorange residual error into the position domain, the position error due to the pseudorange residual error can be calculated as shown in Equation 4.

Equation 4 represents the position error based on the earth-fixed earth-centered coordinate system, and it is necessary to convert it into latitude and longitude criteria in order to apply it to the state variable estimation unit 40. To do this, follow the two steps below. First, by using Equation 5, the position error based on the Earth-fixed Earth-centered coordinate system is converted into a North-East-Down (NED) coordinate system standard.

...(2)

...(2)

는 각각 사용자 위치의 위도 및 경도를 나타내고 이는 GPS 모듈(10)에서 제공된다. 그런 다음 수학식 6를 이용하여 NED(North-East-Down) 좌표계 기준 위치 오차를 위도, 경도 오차(

)로 변환시킨다. in Equation 5

denotes the latitude and longitude of the user's location, respectively, which is provided by the GPS module 10. Then, using Equation 6, the North-East-Down (NED) coordinate system reference position error is a latitude, longitude error (

) is converted to

Equation 6 is a value obtained by estimating the GPS position error due to the pseudorange residual error, and is applied as a standard deviation value of the GPS measurement position error in the state variable estimation unit 40.

Next, a specific embodiment of the state variable estimation unit 40 using the extended Kalman filter will be described.

The Extended Kalman Filter is an algorithm developed to apply a Kalman filter to a nonlinear system and consists of a nonlinear system equation, a linearized system equation for error estimation, and a linearized measured value equation. In the extended Kalman filter, an optimal value can be estimated probabilistically by estimating the amount of error in the state variable using the measurement value and compensating for it in the state variable.

General formulas and application methods of the Extended Kalman Filter will be omitted, and the nonlinear system equation, linearized system equation, and linearized measurement equation required when applying this algorithm to the Extended Kalman Filter will be mainly described.

Equations 7 to 8 are equations of nonlinear equations for the nonlinear equation update 216 of the extended Kalman filter.

The state variable of the nonlinear system of Figure 1 is as shown in Equation 7.

Latitude, longitude, northward speed, eastward speed, vehicle heading angle, accelerometer x-direction bias error, accelerometer y-direction bias error, and gyro z-direction bias error are shown in order from the far left. The antibody fixed coordinate system is defined as the front direction of the vehicle in the x direction, the right direction of the vehicle in the y direction, and the downward direction of the vehicle in the z direction. Have an axis gyro attached to measure the vehicle's z-axis angular velocity.

Equation 8 represents the nonlinear system equation for the defined state variables.

The values used in Equation 8 are as follows.

The altitude is calculated using the value output from the GPS module 10, and the acceleration and angular velocity are calculated using the measured values of the accelerometer and gyro. Here, the bias error of the accelerometer and the gyro is corrected using the value estimated by the Kalman filter.

Equations 9 to 14 are equations for performing the state variable update 214 of the extended Kalman filter through the inertial sensor 20 information.

Next, Equation 9 represents the linearized system equation.

는 수학식 7에서 정의한 상태변수의 오차 량을 나타내고 수학식 10와 같이 자세히 쓸 수 있다.of Equation 9

Represents the error amount of the state variable defined in Equation 7 and can be written in detail as in Equation 10.

Equation 11 represents the process noise of the linearized system equation and represents noise of the x-direction accelerometer, noise of the y-direction accelerometer, noise of the z-direction gyro, and noise of the bias of the x-direction accelerometer, respectively.

The stochastic nature of each value shown in Equation 11 is as shown in Equation 12. It has an average of 0 and has a standard deviation of a specific value. This standard deviation value is a value determined by the specifications of the accelerometer sensor and gyro sensor used, and is generally specified in the datasheet of each sensor.

The details of the F matrix of Equation 9 are as shown in Equation 13.

The values used in Equation 13 are as follows.

Details of the G matrix of Equation 9 are as shown in Equation 14.

Next, the linearized measurement equation is described.

Equations 15 to 19 are equations for performing state variable update 206 of the extended Kalman filter through GPS information.

Equation 15 represents the linearized measurement equation.

Equation 16 represents the measurement used in Equation 15.

...(2)

...(2)

The error of the state variable is estimated by applying the difference between the state variable calculated by integrating the nonlinear system equation of Equation 8 and the value provided from the GPS module 10 to Equation 16.

Equation 17 represents the H matrix used in Equation 15.

는 GPS 측정치 오차를 나타내는 값으로 각각은 수학식 18과 같이 나타내어 진다.in Equation 15

Is a value representing a GPS measurement error, and each is expressed as in Equation 18.

In Equation 18, the stochastic nature of each measurement error is defined as Equation 19. The speed and heading errors excluding the measurement position error are set using the speed accuracy value using the value provided by the GPS module 10 .

The standard deviation value of latitude and longitude errors in Equation 19 is calculated as in Equation 20 using the value calculated using Equation 6 in the GPS position accuracy estimation unit 30.

3 is a comparison between a trajectory result calculated by the navigation device 1 according to an embodiment of the present invention, a trajectory result received from the GPS module 10, and an actual trajectory. When driving starts after initializing each sensor and motion vehicle at the starting point, the GPS location accuracy is estimated (30) based on the information of the GPS module (10), which is extended Kalman together with the information of the inertial sensor (20) module (20). It is used in the filter algorithm to calculate the trajectory of the vehicle.

In FIG. 3 , the location trajectory of the vehicle according to the GPS measurement location shows a difference from the actual location trajectory of the vehicle because the location error due to the multi-path error is included.

However, in the case of the position trajectory of the vehicle calculated by the navigation device 1, since the GPS position accuracy estimation unit 30 calculates the position error level of the GPS trajectory and reflects it to perform the extended Kalman filter algorithm, the GPS trajectory It can be seen that the position is calculated to be close to the actual trajectory.

Referring to FIG. 5 , such a navigation device 1 may be directly included in a vehicle driving assistance device 100 that provides vehicle driving assistance functions (ADAS).

In order to provide the vehicle driving assistance function, accurate positioning of the vehicle position must be preceded. Therefore, if the vehicle driving assistance device 100 is provided with the navigation device 1 according to the embodiment, the performance of the vehicle driving assistance function can be improved. there is.

The vehicle driving assistance apparatus 100 includes an inertial sensor 20, a module 20, an input unit 110, a communication unit 120, an interface unit 130, a memory 140, a sensor unit 155, a processor 170 , a display unit 180, an audio output unit 185, and a power supply unit 190.

Also, the communication unit 120 includes the GPS module 10, and the processor includes the above-described GPS location accuracy estimation unit 30 and the state variable estimation unit 40.

However, the units of the vehicle driving assistance apparatus 100 shown in FIG. 5 are not essential to implement the vehicle driving assistance apparatus 100, so the vehicle driving assistance apparatus 100 described in this specification has the components listed above. It may have more or fewer components than elements.

Describing each configuration in detail, the vehicle driving assistance device 100 may include an input unit 110 that detects a user's input.

For example, the user inputs settings for the vehicle driving assistance function provided by the vehicle driving assistance device 100 through the input unit 110, or turns on/off the power of the vehicle driving assistance device 100. You can do execution input to turn off (off).

The input unit 110 includes a gesture input unit that detects a user gesture (eg, an optical sensor) and a touch input unit that detects a touch (eg, a touch sensor, a touch key, or a touch input unit). A user input may be sensed by including at least one of a mechanical key, etc.) and a microphone that detects a voice input.

Next, the vehicle driving assistance device 100 may include a communication unit 120 that communicates with other vehicles 510 , the terminal 600 , and the server 500 .

The vehicle driving assistance apparatus 100 may receive communication information including at least one of navigation information, other vehicle driving information, and traffic information through the communication unit 120 . Conversely, the vehicle driving assistance device 100 may transmit information about the present vehicle through the communication unit 120 .

In detail, the communication unit 120 receives at least one of location information, weather information, and road traffic condition information (eg, TPEG (Transport Protocol Expert Group)) from the mobile terminal 600 or/and the server 500. can receive

Also, the communication unit 120 may receive traffic information from the server 500 equipped with an intelligent traffic system (ITS). Here, the traffic information may include traffic signal information, lane information, vehicle surrounding information, or location information.

Also, the communication unit 120 may transmit navigation information from the server 500 or/and the mobile terminal 600 .

For example, the communication unit 120 may receive the real-time location of the vehicle as navigation information. In detail, the communication unit 120 may acquire the location of the vehicle by including the GPS module 10 or/and a WiFi (Wireless Fidelity) module.

Also, the communication unit 120 may receive driving information of the other vehicle 510 from the other vehicle 510 and transmit the vehicle information to share the driving information between vehicles. Here, the mutually shared driving information may include at least one of vehicle movement direction information, location information, vehicle speed information, acceleration information, movement path information, forward/reverse information, adjacent vehicle information, and turn signal information. .

Also, when a user gets into a vehicle, the user's mobile terminal 600 and the vehicle driving assistance device 100 may perform pairing with each other either automatically or by the user's execution of an application.

The communication unit 120 may exchange data with another vehicle 510, the mobile terminal 600, or the server 500 in a wireless manner.

In detail, the communication unit 120 may perform wireless communication using a wireless data communication method. As a wireless data communication method, technical standards or communication methods for mobile communication (eg, GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), CDMA2000 (Code Division Multi Access 2000), EV-DO (Enhanced Voice-Data Optimized or Enhanced Voice-Data Only), WCDMA (Wideband CDMA), HSDPA (High Speed Downlink Packet Access), HSUPA (High Speed Uplink Packet Access), LTE (Long Term Evolution), LTE-A (Long Term Evolution-Advanced), etc.) can be used.

In addition, the communication unit 120 may use wireless Internet technology, for example, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance), Wireless Broadband (WiBro), World Interoperability for Microwave Access (WiMAX), High Speed Downlink Packet Access (HSDPA), High Speed Uplink Packet Access (HSUPA), Long Term Evolution (LTE), Long Term Evolution (LTE-A) Term Evolution-Advanced) and the like can be used.

In addition, the communication unit 120 may use short range communication, for example, Bluetooth™, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), and Ultra Wideband (UWB). ), ZigBee, NFC (Near Field Communication), Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, and wireless USB (Wireless Universal Serial Bus) technology.

In addition, the vehicle driving assistance device 100 is paired with a mobile terminal inside the vehicle using a short-distance communication method, and uses a long-distance wireless communication module of the mobile terminal to communicate wirelessly with other vehicles 510 or the server 500, etc. data can be exchanged.

Next, the vehicle driving assistance device 100 may include an interface unit 130 that receives vehicle data or transmits a signal processed or generated by the processor 170 to the outside.

In detail, the vehicle driving assistance device 100 may receive at least one of other vehicle driving information, navigation information, and sensor information through the interface unit 130 .

In addition, the vehicle driving assistance device 100 may transmit a control signal for executing a vehicle driving assistance function or information generated by the vehicle driving assistance device 100 to the control unit 770 of the vehicle through the interface unit 130. can

To this end, the interface unit 130 may perform data communication with at least one of the controller 770 inside the vehicle, the AVN (Audio Video Navigation) device 400, and the sensing unit 760 by wired or wireless communication. can

In detail, the interface unit 130 may receive navigation information through data communication with the controller 770, the AVN device 400, or/and a separate navigation device.

Also, the interface unit 130 may receive sensor information from the control unit 770 or the sensing unit 760 .

Here, the sensor information includes at least one of vehicle direction information, location information, vehicle speed information, acceleration information, tilt information, forward/backward information, fuel information, distance information from the front and rear vehicles, distance information between the vehicle and lanes, and turn signal information. It may contain one or more pieces of information.

In addition, the sensor information includes a heading sensor, a yaw sensor, a gyro sensor, a position module, a vehicle forward/backward sensor, a wheel sensor, a vehicle speed sensor, It may be obtained from a vehicle body tilt detection sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor by steering wheel rotation, a vehicle internal temperature sensor, a vehicle internal humidity sensor, a door sensor, and the like. Meanwhile, the position module may include the GPS module 10 for receiving GPS information.

Also, the interface unit 130 may receive a user input received through the user input unit 110 of the vehicle. The interface unit 130 may receive user input from an input unit of the vehicle or through the control unit 770 . That is, when the input unit is disposed within the vehicle itself, a user input may be received through the interface unit 130 .

Also, the interface unit 130 may receive traffic information obtained from the server 500 . The server 500 may be a server located in a traffic control center that controls traffic. For example, when traffic information is received from the server 500 through the communication unit 120 of the vehicle, the interface unit 130 may receive the traffic information from the control unit 770.

Next, the memory 140 may store various data for the overall operation of the vehicle driving assistance device 100, such as a program for processing or control by the processor 170.

In addition, the memory 140 may store a plurality of application programs (applications) driven by the vehicle driving assistance device 100, data for operation of the vehicle driving assistance device 100, and commands. . At least some of these application programs may be downloaded from an external server through wireless communication. In addition, at least some of these application programs may exist on the vehicle driving assistance device 100 from the time of shipment for basic functions (eg, driving assistance information guide function) of the vehicle driving assistance device 100 .

Also, these application programs may be stored in the memory 140 and driven by the processor 170 to perform the operation (or function) of the vehicle driving assistance device 100 .

Meanwhile, the memory 140 may store data for identifying an object included in an image. For example, the memory 140 may store data for confirming what the object corresponds to by a predetermined algorithm when a predetermined object is detected in an image around the vehicle acquired through the camera 160. .

For example, if a predetermined object such as a lane, a traffic sign, a two-wheeled vehicle, or a pedestrian is included in an image acquired through the camera 160, the memory 140 determines what the object corresponds to by a predetermined algorithm. data to be stored.

The memory 140 is a hardware type, a flash memory type, a hard disk type, a solid state disk type (SSD type), a silicon disk drive type (SDD type), and a multimedia card micro type. (multimedia card micro type), card-type memory (eg SD or XD memory, etc.), RAM (random access memory; RAM), SRAM (static random access memory), ROM (read-only memory; ROM), EEPROM It may include at least one type of storage medium among electrically erasable programmable read-only memory (PROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, and optical disk.

In addition, the vehicle driving assistance device 100 may be operated in relation to a web storage performing a storage function of the memory 140 on the Internet.

Next, the monitoring unit may obtain information about the situation inside the vehicle.

The information detected by the monitoring unit includes face recognition information, fingerprint recognition information, iris-scan information, retina-scan information, hand geo-metry information, and voice recognition information. recognition) information. And the monitoring unit may include other sensors that sense the biometric information.

Next, the vehicle driving assistance device 100 may further include a sensor unit 155 that detects objects around the vehicle. The vehicle driving assistance apparatus 100 may include a separate sensor unit 155 to detect surrounding objects, and may receive sensor information obtained from the sensing unit 770 of the vehicle through the interface unit 130. . In addition, the sensor information obtained in this way may be included in vehicle surrounding information.

The sensor unit 155 may include at least one of a distance sensor 150 that detects the position of an object located around the vehicle and a camera 160 that acquires an image by photographing the surroundings of the vehicle.

First, the distance sensor 150 may precisely detect the position of an object in the vehicle, the direction in which the object is separated, the separation distance, or the moving direction of the object. The distance sensor 150 continuously measures the position of the detected object and can accurately detect a change in the positional relationship with the present vehicle.

The distance sensor 150 may detect an object located in at least one area among front, rear, left, and right areas of the vehicle. To this end, the distance sensor 150 may be disposed at various locations in the vehicle.

In detail, referring to FIG. 3 , the distance sensor 150 may be disposed at at least one of front and rear and left and right sides of the vehicle body and the ceiling.

The distance sensor 150 may include one or more of various distance measurement sensors such as a lidar sensor, a laser sensor, an ultrasonic waves sensor, and a stereo camera.

For example, the distance sensor 150 is a laser sensor, and uses a time-of-flight (TOF) method or/and a phase-shift method according to a laser signal modulation method to detect distance between a vehicle and a vehicle. Positional relationships between objects can be accurately measured.

Meanwhile, information about the object may be obtained by the processor 170 analyzing an image captured by the camera 160 .

In detail, the vehicle driving assistance device 100 photographs the surroundings of the vehicle with the camera 160, and the processor 170 analyzes the obtained image around the vehicle to detect objects around the vehicle, determines the properties of the object, and detects the sensor 170. information can be generated.

Here, the image information is at least one information among the type of object, traffic signal information displayed by the object, the distance between the object and the vehicle, and the location of the object, and may be included in the sensor information.

In detail, the processor 170 generates image information by performing object analysis such as detecting an object in an image captured through image processing, tracking the object, measuring a distance to the object, and confirming the object. can

Such a camera 160 may be provided in various locations.

In detail, the camera 160 may include an inside camera 160f that acquires a front image by photographing the front of the vehicle from inside the vehicle.

Also, referring to FIG. 3 , the plurality of cameras 160 may be respectively disposed at at least one or more positions among left, rear, right, front, and ceiling positions of the vehicle.

In detail, the left camera 160b may be disposed within a case surrounding a left side mirror. Alternatively, the left camera 160b may be disposed outside the case surrounding the left side mirror. Alternatively, the left camera 160b may be disposed in an area outside the left front door, the left rear door, or the left fender.

The right camera 160c may be disposed in a case surrounding a right side mirror. Alternatively, the right camera 160c may be disposed outside the case surrounding the right side mirror. Alternatively, the right camera 160c may be disposed in an area outside a right front door, a right rear door, or a right fendere.

Also, the rear camera 160d may be disposed near a rear license plate or a trunk switch. The front camera 160a may be disposed near the emblem or near the radiator grill.

Meanwhile, the processor 170 may synthesize images captured from all directions to provide an around view image of the vehicle viewed from a top view. When creating an around-view image, a boundary between each image area is generated. Such a boundary portion may be naturally displayed by image blending.

In addition, the ceiling camera 160e may be disposed on the ceiling of the vehicle to take pictures in all directions of the vehicle.

The camera 160 may directly include an image sensor and an image processing module. The camera 160 may process still images or moving images obtained by an image sensor (eg, CMOS or CCD). Also, the image processing module may process a still image or a moving image obtained through an image sensor, extract necessary image information, and transmit the extracted image information to the processor 170 .

Next, the vehicle driving assistance apparatus 100 may further include a display unit that displays graphic images related to vehicle driving assistance functions.

The display unit may include a plurality of displays.

In detail, the display unit may include a first display unit 180a that projects and displays graphic images on the windshield W of the vehicle. That is, the first display unit 180a is a Head Up Display (HUD) and may include a projection module that projects a graphic image onto the windshield W. Also, a projection graphic image projected by the projection module may have a certain degree of transparency. Accordingly, the user may simultaneously view the behind the graphic image and the graphic image.

In addition, such a graphic image may be overlapped with a projected image projected on the windshield W to achieve Augmented Reality (AR).

Meanwhile, the display unit may include a second display unit 180b that is separately installed inside the vehicle and displays an image of a vehicle driving assistance function.

In detail, the second display unit 180b may be a display of a vehicle navigation device or a cluster on the front side of the vehicle.

In addition, the second display unit 180b includes a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), At least one of a flexible display, a 3D display, and an e-ink display may be included.

The second display unit 180b may be combined with the gesture input unit to form a touch screen.

Next, the audio output unit 185 may output an audio message confirming a description of the function of the vehicle driving assistance device 100 and whether or not it is executed. That is, the vehicle driving assistance apparatus 100 complements descriptions of functions of the vehicle driving assistance apparatus 100 through audio output of the audio output unit 185 as well as visual display through the display unit 180. can

In addition, the power supply unit 190 may receive external power and internal power under the control of the processor 170 to supply power necessary for the operation of each component.

Finally, the vehicle driving assistance device 100 may include a processor 170 that controls overall operations of each unit in the vehicle driving assistance device 100 .

In addition, the processor 170 may control at least some of the components discussed in conjunction with FIG. 3 in order to drive an application program. Furthermore, the processor 170 may combine and operate at least two or more of the components included in the vehicle driving assistance apparatus 100 to drive the application program.

In terms of hardware, the processor 170 includes application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors ( 170), controllers, micro-controllers, microprocessors 170, and other electrical units for performing functions.

In addition, the processor 170 may be controlled by the controller or control various functions of the vehicle through the controller.

Also, the processor 170 controls general operations of the vehicle driving assistance device 100 in addition to operations related to the application programs stored in the memory 140 . The processor 170 may provide or process appropriate information or functions to a user by processing signals, data, information, etc. input or output through the components described above or by running an application program stored in the memory 170.

The processor 170 may obtain navigation information using the inertial sensor 20 module and the GPS module 10 .

In this case, the navigation information may be directly calculated by including the GPS location accuracy estimation unit 30 and the state variable estimation unit 40 .

Details are replaced with the description of the navigation device 1 described above.

In addition, the processor 170 is capable of lane-by-lane route assistance using the precisely positioned navigation information, AEB (Autonomous Emergency BrakingLDW (Lane Departure Warning) and LKA (Lane Keeping Assist), HBA (High Beam Assistance) , FCW (Forward Collision Warning), ACC (adapted cruise control), or AEB pedestrian (during both day and night), etc. may provide vehicle driving assistance functions.

In addition, the processor 170 may provide an autonomous driving function using accurately positioned navigation information.

Referring to FIG. 6 , the aforementioned vehicle driving assistance device 100 may be directly included in a vehicle.

The vehicle 700 includes a communication unit 710, an input unit 720, a sensing unit 760, an output unit 740, a vehicle driving unit 750, a memory 730, an interface unit 780, a control unit 770, and a power supply unit. 790, the vehicle driving assistance device 100, and the AVN device 400. Here, a unit included in the vehicle driving assistance apparatus 100 and a unit having the same name among units described in the vehicle will be described as being included in the vehicle.

The communication unit 710 may include one or more modules enabling wireless communication between the vehicle and the mobile terminal 600, between the vehicle and the external server 500, or between the vehicle and another vehicle 510. Also, the communication unit 710 may include one or more modules that connect the vehicle to one or more networks.

The communication unit 710 may include a broadcast receiving module 711, a wireless Internet module 712, a short-distance communication module 713, a location information module 714, and an optical communication module 715.

The broadcast reception module 711 receives a broadcast signal or broadcast-related information from an external broadcast management server through a broadcast channel. Here, broadcasting includes radio broadcasting or TV broadcasting.

The wireless Internet module 712 refers to a module for wireless Internet access, and may be built into or external to a vehicle. The wireless Internet module 712 is configured to transmit and receive radio signals in a communication network based on wireless Internet technologies.

Wireless Internet technologies include, for example, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Wi-Fi (Wireless Fidelity) Direct, DLNA (Digital Living Network Alliance), WiBro (Wireless Broadband), WiMAX ( World Interoperability for Microwave Access), HSDPA (High Speed Downlink Packet Access), HSUPA (High Speed Uplink Packet Access), LTE (Long Term Evolution), LTE-A (Long Term Evolution-Advanced), etc., and the wireless Internet module 712 transmits and receives data according to at least one wireless Internet technology within a range including Internet technologies not listed above. For example, the wireless Internet module 712 may exchange data with the external server 500 wirelessly. The wireless Internet module 712 may receive weather information and road traffic condition information (eg, Transport Protocol Expert Group (TPEG)) information from the external server 500 .

The short-range communication module 713 is for short-range communication, and includes Bluetooth™, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, Short-range communication may be supported using at least one of near field communication (NFC), wireless-fidelity (Wi-Fi), Wi-Fi Direct, and wireless universal serial bus (USB) technologies.

The short-range communication module 713 may perform short-range communication between the vehicle and at least one external device by forming wireless area networks. For example, the short-distance communication module 713 may exchange data with the mobile terminal 600 wirelessly. The short-range communication module 713 may receive weather information and road traffic condition information (eg, Transport Protocol Expert Group (TPEG)) from the mobile terminal 600 . For example, when a user gets into a vehicle, the user's mobile terminal 600 and the vehicle may perform pairing with each other automatically or by the user's execution of an application.

The location information module 714 is a module for obtaining the location of a vehicle, and a representative example thereof is a Global Positioning System (GPS) module. For example, if a vehicle utilizes a GPS module, the location of the vehicle may be obtained using a signal transmitted from a GPS satellite.

The optical communication module 715 may include a light emitting unit and a light receiving unit.

The light receiver may receive information by converting a light signal into an electrical signal. The light receiving unit may include a photo diode (PD) for receiving light. Photodiodes can convert light into electrical signals. For example, the light receiver may receive information of the preceding vehicle through light emitted from a light source included in the preceding vehicle.

The light transmitting unit may include at least one light emitting device for converting an electrical signal into an optical signal. Here, the light emitting element is preferably an LED (Light Emitting Diode). The optical transmission unit converts an electrical signal into an optical signal and transmits it to the outside. For example, the light emitting unit may emit an optical signal to the outside through flickering of a light emitting device corresponding to a predetermined frequency. Depending on the embodiment, the light emitting unit may include a plurality of light emitting element arrays. Depending on the embodiment, the light emitting unit may be integrated with a lamp provided in a vehicle. For example, the light emitting unit may be at least one of a headlamp, a taillight, a brake light, a direction indicator light, and a vehicle sidelight. For example, the optical communication module 715 may exchange data with another vehicle 510 through optical communication.

The input unit 720 may include a driving control unit 721, a camera 195, a microphone 723, and a user input unit 724.

The driving control unit 721 receives a user input for vehicle driving. (See FIG. 2 described below.) The driving control unit 721 may include a steering input unit 721A, a shift input unit 721D, an acceleration input unit 721C, and a brake input unit 721B.

The steering input unit 721A receives an input of a vehicle traveling direction from a user. The steering input unit 721A is preferably formed in a wheel shape to enable steering input by rotation. Depending on the embodiment, the steering input unit 721A may be formed as a touch screen, touch pad, or button.

The shift input unit 721D receives inputs of parking (P), forward (D), neutral (N), and reverse (R) of the vehicle from the user. The shift input unit 721D is preferably formed in a lever shape. Depending on the embodiment, the shift input unit 721D may be formed as a touch screen, touch pad, or button.

The acceleration input unit 721C receives an input for vehicle acceleration from the user. The brake input unit 721B receives an input for decelerating the vehicle from the user. The acceleration input means 721C and the brake input means 721B are preferably formed in the form of pedals. Depending on the embodiment, the acceleration input unit 721C or the brake input unit 721B may be formed as a touch screen, touch pad, or button.

The camera 722 may include an image sensor and an image processing module. The camera 722 may process still images or moving images obtained by an image sensor (eg, CMOS or CCD). The image processing module may process a still image or video acquired through an image sensor, extract necessary information, and transmit the extracted information to the controller 770 . Meanwhile, the vehicle may include a camera 722 that captures an image in front of the vehicle or an image around the vehicle and a monitoring unit 725 that captures an image inside the vehicle.

The monitoring unit 725 may obtain an image of the occupant. The monitoring unit 725 may obtain an image for biometric recognition of the occupant.

Meanwhile, in FIG. 24, the monitoring unit 725 and the camera 722 are shown as being included in the input unit 720, but the camera 722 is described as a configuration included in the vehicle driving assistance device 100 as described above. It could be.

The microphone 723 may process an external acoustic signal into electrical data. The processed data can be used in various ways depending on the function being performed in the vehicle. The microphone 723 may convert a user's voice command into electrical data. The converted electrical data may be transmitted to the controller 770 .

Meanwhile, according to embodiments, the camera 722 or the microphone 723 may be a component included in the sensing unit 760 rather than a component included in the input unit 720 .

The user input unit 724 is for receiving information from a user. When information is input through the user input unit 724, the controller 770 can control the operation of the vehicle to correspond to the input information. The user input unit 724 may include a touch input unit or a mechanical input unit. Depending on the embodiment, the user input unit 724 may be disposed in one area of the steering wheel. In this case, the driver may manipulate the user input unit 724 with his/her fingers while holding the steering wheel.

The sensing unit 760 senses a signal related to driving of the vehicle. To this end, the sensing unit 760 includes a collision sensor, a wheel sensor, a speed sensor, an inclination sensor, a weight sensor, a heading sensor, a yaw sensor, and a gyro sensor. , position module, vehicle forward / backward sensor, battery sensor, fuel sensor, tire sensor, steering sensor by steering wheel rotation, vehicle internal temperature sensor, vehicle internal humidity sensor, ultrasonic sensor, radar, lidar, etc. can

Accordingly, the sensing unit 760 provides vehicle collision information, vehicle direction information, vehicle location information (GPS information), vehicle angle information, vehicle speed information, vehicle acceleration information, vehicle tilt information, vehicle forward/backward information, and battery information. , Fuel information, tire information, vehicle lamp information, vehicle internal temperature information, vehicle internal humidity information, and sensing signals for a steering wheel rotation angle may be obtained.

Meanwhile, the sensing unit 760 includes, in addition, an accelerator pedal sensor, a pressure sensor, an engine speed sensor, an air flow sensor (AFS), an intake temperature sensor (ATS), a water temperature sensor (WTS), and a throttle. A position sensor (TPS), a TDC sensor, a crank angle sensor (CAS), and the like may be further included.

The sensing unit 760 may include a biometric information sensing unit. The biometric information detection unit detects and obtains the biometric information of the occupant. Biometric information includes fingerprint recognition information, iris-scan information, retina-scan information, hand geo-metry information, facial recognition information, voice recognition ( Voice recognition) information may be included. The biometric information detection unit may include a sensor that senses the biometric information of the occupant. Here, the monitoring unit 725 and the microphone 723 may operate as sensors. The biometric information sensor may obtain hand shape information and face recognition information through the monitoring unit 725 .

The output unit 740 is for outputting information processed by the controller 770, and may include a display unit 741, a sound output unit 742, and a haptic output unit 743.

The display unit 741 may display information processed by the controller 770. For example, the display unit 741 may display vehicle-related information. Here, the vehicle-related information may include vehicle control information for direct control of the vehicle or vehicle driving assistance information for driving guidance to the vehicle driver. In addition, the vehicle-related information may include vehicle state information indicating a current state of the vehicle or vehicle driving information related to driving of the vehicle.

The display unit 741 includes a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED), and a flexible display. display), a 3D display, and an e-ink display.

The display unit 741 may implement a touch screen by forming a mutual layer structure or integrally with the touch sensor. Such a touch screen may function as a user input unit 724 providing an input interface between the vehicle and the user and provide an output interface between the vehicle and the user. In this case, the display unit 741 may include a touch sensor that senses a touch on the display unit 741 so that a control command can be received by a touch method. Using this, when a touch is made to the display unit 741, the touch sensor can sense the touch, and the controller 770 can generate a control command corresponding to the touch based on this. Contents input by the touch method may be letters or numbers, or menu items that can be instructed or designated in various modes.

Meanwhile, the display unit 741 may include a cluster so that the driver can check vehicle condition information or vehicle driving information while driving. Clusters can be located above the dashboard. In this case, the driver can check the information displayed on the cluster while keeping his/her gaze in front of the vehicle.

Meanwhile, according to embodiments, the display unit 741 may be implemented as a Head Up Display (HUD). When the display unit 741 is implemented as a HUD, information may be output through a transparent display provided on the windshield. Alternatively, the display unit 741 may include a projection module to output information through an image projected on the windshield.

The audio output unit 742 converts the electrical signal from the control unit 770 into an audio signal and outputs it. To this end, the sound output unit 742 may include a speaker or the like. The sound output unit 742 may also output sound corresponding to the operation of the user input unit 724 .

The haptic output unit 743 generates a tactile output. For example, the haptic output unit 743 may vibrate a steering wheel, a seat belt, and a seat so that the user can recognize the output.

The vehicle driving unit 750 may control the operation of various vehicle devices. The vehicle driving unit 750 includes a power source driving unit 751, a steering driving unit 752, a brake driving unit 753, a lamp driving unit 754, an air conditioning driving unit 755, a window driving unit 756, an airbag driving unit 757, a sunroof A driving unit 758 and a suspension driving unit 759 may be included.

The power source driver 751 may perform electronic control of the power source in the vehicle.

For example, when a fossil fuel-based engine (not shown) is the power source, the power source driver 751 may perform electronic control of the engine. This makes it possible to control the output torque of the engine and the like. When the power source driving unit 751 is an engine, the speed of the vehicle may be limited by limiting engine output torque under the control of the control unit 770 .

As another example, when an electric motor (not shown) is a power source, the power source driver 751 may control the motor. This makes it possible to control the rotational speed and torque of the motor.

The steering driver 752 may perform electronic control of a steering apparatus in the vehicle. This makes it possible to change the traveling direction of the vehicle.

The brake driver 753 may perform electronic control of a brake apparatus (not shown) in the vehicle. For example, the speed of the vehicle may be reduced by controlling the operation of the brakes disposed on the wheels. As another example, the driving direction of the vehicle may be adjusted to the left or right by differentiating the operation of the brakes respectively disposed on the left and right wheels.

The lamp driving unit 754 may control turning on/off of lamps disposed inside or outside the vehicle. In addition, the intensity and direction of the light of the lamp can be controlled. For example, control of direction indicator lamps and brake lamps may be performed.

The air conditioning driving unit 755 may perform electronic control of an air cinditioner (not shown) in the vehicle. For example, when the temperature inside the vehicle is high, the air conditioner may be operated to supply cool air to the inside of the vehicle.

The window driver 756 may perform electronic control of a window apparatus in the vehicle. For example, it is possible to control the opening or closing of left and right windows on the side of the vehicle.

The airbag driving unit 757 may perform electronic control of an airbag apparatus in the vehicle. For example, in case of danger, the airbag can be controlled to explode.

The sunroof driver 758 may perform electronic control of a sunroof apparatus (not shown) in the vehicle. For example, the opening or closing of the sunroof can be controlled.

The suspension driving unit 759 may perform electronic control of a suspension apparatus (not shown) in the vehicle. For example, when there is a curve on the road surface, the vibration of the vehicle may be reduced by controlling the suspension device.

The memory 730 is electrically connected to the controller 770. The memory 770 may store basic data for the unit, control data for controlling the operation of the unit, and input/output data. In terms of hardware, the memory 790 may be various storage devices such as ROM, RAM, EPROM, flash drive, hard drive, and the like. The memory 730 may store various data for overall operation of the vehicle, such as a program for processing or control of the control unit 770 .

The interface unit 780 may serve as a passage for various types of external devices connected to the vehicle. For example, the interface unit 780 may have a port connectable to the mobile terminal 600 and connect to the mobile terminal 600 through the port. In this case, the interface unit 780 may exchange data with the mobile terminal 600 .

Meanwhile, the interface unit 780 may serve as a passage through which electrical energy is supplied to the connected mobile terminal 600 . When the mobile terminal 600 is electrically connected to the interface unit 780, the interface unit 780 provides electrical energy supplied from the power supply unit 790 to the mobile terminal 600 under the control of the controller 770. do.

The controller 770 may control the overall operation of each unit in the vehicle. The controller 770 may be referred to as an Electronic Control Unit (ECU).

The control unit 770 may execute a function corresponding to the transmitted signal according to transmission of an execution signal from the vehicle driving assistance device 100 .

The controller 770, in terms of hardware, includes application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors ( It may be implemented using at least one of processors, controllers, micro-controllers, microprocessors, and electrical units for performing other functions.

The control unit 770 may delegate the role of the processor 170 described above. That is, the processor 170 of the vehicle driving assistance apparatus 100 may be directly set in the control unit 770 of the vehicle. In this embodiment, the vehicle driving assistance apparatus 100 may be understood to refer to a combination of some components of a vehicle.

Alternatively, the controller 770 may control components to transmit information requested by the processor 170 .

The power supply unit 790 may supply power required for operation of each component under the control of the control unit 770 . In particular, the power supply unit 770 may receive power from a battery (not shown) inside the vehicle.

The AVN (Audio Video Navigation) device 400 may exchange data with the controller 770 . The controller 770 may receive navigation information from the AVN device 400 or a separate navigation device (not shown). Here, the navigation information may include set destination information, route information according to the destination, map information related to vehicle driving, or vehicle location information.

The features, structures, effects, etc. described in the foregoing embodiments are included in at least one embodiment of the present invention, and are not necessarily limited to only one embodiment. Furthermore, the features, structures, effects, etc. illustrated in each embodiment can be combined or modified with respect to other embodiments by those skilled in the art in the field to which the embodiments belong. Therefore, contents related to these combinations and variations should be construed as being included in the scope of the present invention.

In addition, although the embodiments have been described above, these are merely examples and do not limit the present invention, and those of ordinary skill in the field to which the present invention belongs can exemplify the above to the extent that does not deviate from the essential characteristics of the present embodiment. It will be seen that various variations and applications that have not been made are possible. For example, each component specifically shown in the embodiments can be modified and implemented. And differences related to these variations and applications should be construed as being included in the scope of the present invention as defined in the appended claims.

Claims (7)

a GPS module for receiving vehicle GPS information including a GPS measurement location, a pseudorange measurement value with a satellite, and a location of the satellite;
an inertial sensor for measuring inertial information including acceleration and angular velocity of the vehicle; and
a GPS positioning accuracy estimator for calculating an error level of the GPS measurement position based on the GPS information and estimating an accuracy of the GPS measurement position from the calculated error level;
A navigation processor including a state variable estimator updating state variables based on the GPS information, the accuracy of the GPS measurement position, and the inertia information;
The GPS location accuracy estimation unit,
Estimating a pseudorange with the satellite based on the position of the satellite;
Calculating an error level of the GPS measurement position by comparing the estimated pseudorange with the satellite and a measured pseudorange with the satellite;
The navigation processor,
controlling the calculated error level of the GPS measurement position to be applied as a standard deviation value of the GPS measurement position error in the state variable estimation unit;
Obtaining the position, speed and direction of movement of the vehicle through the updated state variable
navigation device. delete According to claim 1,
The state variable estimation unit,
Updating a state variable based on the GPS information, the accuracy of the GPS measurement position, and the inertia information using an extended Kalman filter
navigation device. According to claim 3,
The extended Kalman filter,
Estimating the state variable by estimating an error amount of the state variable using the GPS information and the estimated GPS location accuracy and compensating for the error amount with the state variable
navigation device. According to claim 1,
The state variable is
Including the vehicle's latitude, longitude, northward speed, eastward speed, vehicle heading angle, accelerometer x-direction bias error, accelerometer y-direction bias error, and gyro z-direction bias error
navigation device. a GPS module that acquires GPS information;
an inertial sensor for obtaining inertial information including vehicle acceleration and angular velocity; and
A navigation processor configured to obtain navigation information of the vehicle calculated based on the GPS information and inertial information;
The navigation processor,
a GPS positioning accuracy estimator that calculates a multipath error from the GPS information and converts the multipath error into an accuracy of a GPS measurement location;
State variable estimation that updates state variables based on the GPS information and the inertia information, estimates an error of the state variable based on the GPS measurement location accuracy in the state variable update process, and updates the state variable by reflecting the error. including wealth,
The GPS position accuracy estimator estimates a pseudorange with the satellite based on the position of the satellite in the GPS information, compares the estimated pseudorange with the satellite and a pseudorange measurement with the satellite in the GPS information, Calculate the multipath error of the GPS measurement position among GPS information,
The state variable estimator applies the calculated multipath error of the GPS measurement location as a standard deviation value of the multipath error of the GPS measurement location
navigation device. A vehicle driving assistance device comprising the navigation device according to claim 1 and providing a vehicle driving assistance function.

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