Device and method for monitoring the surrounding environment of a vehicle

Abstract

An apparatus for monitoring the surrounding environment of a vehicle may include: a sensor unit including a plurality of detection sensors configured to detect an object outside the vehicle according to a frame having a predetermined period; and a control unit configured to: extract a stationary object from the external objects detected by the sensor unit by using the behavior information of the vehicle, map the extracted stationary object to a preset grid map, add occupancy information to each grid constituting the grid map according to whether the stationary object is mapped to the grid map, calculate an occupancy probability parameter indicating the probability that the stationary object will be located at each grid based on the occupancy information of the grids within the grid map added to a plurality of frames, and monitor the surrounding environment of the vehicle based on the calculated occupancy probability parameter.

Description

Technical Field

[0001] Exemplary embodiments of the present disclosure relate to an apparatus and a method for monitoring a surrounding environment of a vehicle, and more particularly, to an apparatus and a method for monitoring a surrounding environment of a vehicle by using an OGM (Occupancy Grid Map). Background Art

[0002] A vehicle radar refers to a device that detects an external object within a detection area while a vehicle is moving and alerts a driver to assist the driver in safely driving the vehicle. Figure 1A And Figure 1B illustrates an area where a general vehicle radar transmits a radar signal to detect an external object. The vehicle radar operates to transmit a radar signal according to a frame having a predetermined period and detect an external object. As Figure 1B shown, signal characteristics (e.g., waveform, frequency, range resolution, angular resolution, maximum sensing range, and FoV (Field of View)) of the transmitted radar signal vary according to a system of a vehicle to which the radar is applied. Examples of the system include DAS (Driver Assistance System) such as BSD (Blind Spot Detection), LCA (Lane Change Assistance), or RCTA (Rear Cross Traffic Alert).

[0003] The related art of the present disclosure is disclosed in Korean Patent Application Publication No. 10-2013-0130843, published on December 2, 2013. Summary of the Invention

[0004] Various embodiments relate to an apparatus and a method for monitoring a surrounding environment of a vehicle, which can improve detection accuracy of an external object when monitoring the surrounding environment of the vehicle by radar.

[0005] In an embodiment, there is provided an apparatus for monitoring a surrounding environment of a vehicle, the apparatus may include: a sensor unit including a plurality of detection sensors for detecting an object outside the vehicle according to a frame at a predetermined period; and a control unit configured to: extract a stationary object from the external objects detected by the sensor unit, map the extracted stationary object to a preset grid map, calculate an occupancy probability parameter indicating a probability that the stationary object will be located on a grid of the grid map based on the mapping result, and monitor the surrounding environment of the vehicle based on the calculated occupancy probability parameter. The control unit maps the extracted stationary object to the grid map while updating the grid map by changing an index of each grid constituting the grid map according to behavior information of the vehicle.

[0006] When a predefined grid map update condition is satisfied according to a longitudinal or lateral movement distance of the vehicle, the control unit may update the grid map from the (K-1)th frame to the Kth frame.

[0007] The grid map update condition can be the following: the longitudinal movement distance of the vehicle is greater than the longitudinal dimension of the grid, or the lateral movement distance of the vehicle is greater than the lateral dimension of the grid.

[0008] The control unit can update the grid map by changing the index of each grid in the (K - 1)-th frame for the K-th frame based on the longitudinal movement distance, lateral movement distance, and longitudinal angle change of the vehicle.

[0009] The control unit can use a rotation matrix to update the grid map, and the rotation matrix rotates the grid map according to the longitudinal and lateral movement distances of the vehicle from the (K - 1)-th frame to the K-th frame, the index of each grid in the (K - 1)-th frame, and the yaw rate of the vehicle.

[0010] The control unit can convert the position information of the extracted stationary object into an index corresponding to the grid map, and can map the extracted stationary object to the grid map by specifying the target grid corresponding to the converted index in the grid map.

[0011] The control unit can add occupancy information with a first value to the target grid to which the stationary object is mapped, and can add occupancy information with a second value to the remaining grids, where the second value is less than the first value.

[0012] The control unit can determine an extended mapping area that extends the set range relative to the target grid to which the stationary object is mapped, and can monitor the surrounding environment of the vehicle by adding occupancy information with a first value to each grid constituting the extended mapping area to calculate the occupancy probability parameter.

[0013] The set range can be predefined according to the distance and speed resolution of the signal waveform sent from the detection sensor.

[0014] The control unit can update the grid map according to whether the predefined grid map update condition is satisfied when switching from the (K - 1)-th frame to the K-th frame, while correcting the grid map update error caused by the inherent error in the factor used to determine whether the grid map update condition is satisfied.

[0015] When correcting the grid map update error when updating the grid map by switching from the (K - 1)-th frame to the K-th frame, the control unit can compare the first extended mapping area with the second extended mapping area to correct the occupancy probability parameter of each grid constituting the second extended mapping area, where the first extended mapping area is an area that extends the set range relative to the target grid to which the stationary object is mapped in the (K - 1)-th frame, and the second extended mapping area is an area that extends the set range relative to the target grid to which the stationary object is mapped in the K-th frame.

[0016] For the K-th frame, compared with the (K-1)-th frame, the control unit may specify, in the grid of the second extended mapping area, a first area composed of grids with an increased occupancy probability parameter, and specify, in the grid of the first extended mapping area, a second area composed of grids with a decreased occupancy probability parameter, and then replace the occupancy probability parameter of the second area with that of the first area to correct the occupancy probability parameter of each grid constituting the second extended mapping area.

[0017] The control unit may determine a peak grid with the maximum occupancy probability parameter among the grids in the grid map, and when the occupancy probability parameter of the peak grid is equal to or greater than the threshold defined for the peak grid, determine that a stationary object is located on the peak grid.

[0018] In another embodiment, a method for monitoring the surrounding environment of a vehicle is provided. The method includes: extracting, by a control unit, a stationary object from objects outside the vehicle detected by a sensor unit, the sensor unit including a plurality of detection sensors for detecting objects outside the vehicle according to frames at a predetermined period; mapping, by the control unit, the extracted stationary object to a preset grid map, and calculating, by the control unit, an occupancy probability parameter indicating the probability that the stationary object will be located on the grid of the grid map based on the mapping result; and monitoring, by the control unit, the surrounding environment of the vehicle based on the calculated occupancy probability parameter. The grid map has a longitudinal axis, a transverse axis, and an index set relative to the vehicle, and during the process of calculating the occupancy probability parameter by the control unit, the extracted stationary object is mapped to the grid map while the grid map is updated by changing the index of each grid constituting the grid map according to the behavior information of the vehicle.

[0019] In other embodiments, a device for monitoring the surrounding environment of a vehicle is provided. The device includes: a sensor unit including a plurality of detection sensors for detecting objects outside the vehicle according to frames at a predetermined period; and a control unit configured to: extract a stationary object from the external objects detected by the sensor unit, map the extracted stationary object to a preset grid map, calculate an occupancy probability parameter indicating the probability that the stationary object will be located on the grid of the grid map based on the mapping result, and monitor the surrounding environment of the vehicle by comparing the calculated occupancy probability parameter with a threshold defined in the grid of the grid map. The threshold is defined for each of a plurality of regions in the grid map, and the plurality of regions are divided according to whether the detection regions of the same detection sensor overlap with each other in each frame and whether the detection regions of two adjacent detection sensors overlap with each other in the same frame.

[0020] The threshold may be determined by a radar equation in response to the intensity of the received signal input to the sensor unit.

[0021] The plurality of regions may include independent regions, which have a first threshold and are defined as the regions in the grid map sensed by the first detection sensor in the Kth frame, where K is a natural number.

[0022] The plurality of regions may include single-overlap regions, which have a second threshold and are defined as the regions in the grid map that are the overlapping regions of the regions sensed by the first detection sensor in the (K + 1)th frame after the Kth frame and the independent regions.

[0023] The plurality of regions may include multi-overlap regions, which have a third threshold and are defined as the regions in the grid map that are the overlapping regions of the regions sensed by the second detection sensor adjacent to the first detection sensor in the Kth frame or the (K + 1)th frame and the single-overlap regions.

[0024] Each of the first threshold to the third threshold may have a linear part, which is a part that linearly increases in response to the intensity of the received signal input to the sensor unit, and the relationship of "first threshold < second threshold < third threshold" may be established in the overlapping part of the respective linear parts of the first threshold to the third threshold.

[0025] According to an embodiment of the present disclosure, the device and method for monitoring the surrounding environment of a vehicle according to this embodiment may map the stationary objects detected by radar to a preset grid map, add occupancy information to each grid constituting the grid map according to whether the stationary objects are mapped to the grid map, and then calculate an occupancy probability parameter according to the occupancy information added to each grid in the grid map of multiple frames to be monitored to monitor the surrounding environment of the vehicle, where the occupancy probability parameter indicates the probability that a stationary object will be located at the corresponding grid. Therefore, when monitoring the surrounding environment of a vehicle by radar, the device and method can improve the detection accuracy of external objects. Description of the Drawings

[0026] Figure 1A and Figure 1B is a diagram showing the area where a general vehicle radar transmits radar signals to detect external objects.

[0027] Figure 2 is a block diagram for describing the configuration of a device for monitoring the surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0028] Figure 3 is a diagram showing the grid map in a device for monitoring the surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0029] Figures 4 to 8 is a diagram showing the process of setting the threshold of the grid map in a device for monitoring the surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0030] Figures 9A to 9C and Figure 10 is a diagram showing a process of updating a grid map in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0031] Figure 11 is a diagram showing a process of mapping a stationary object to a grid map in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0032] Figures 12 to 14 is a diagram showing a process of determining an extended mapping area in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0033] Figure 15 and Figure 16A 、 Figure 16B is a diagram showing a process of correcting an occupancy probability parameter in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0034] Figures 17 to 20 is a diagram showing a process of correcting a shadow grid in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0035] Figure 21 is a flowchart for describing a method for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure. Specific Embodiment

[0036] Hereinafter, a device and a method for monitoring a surrounding environment of a vehicle will be described with reference to the accompanying drawings through various exemplary embodiments. It should be noted that the drawings are not drawn to an exact scale, and for the convenience and clarity of description, the thickness of lines or the dimensions of components may be exaggerated. In addition, the terms used herein are defined by considering the functions of the present disclosure and may be changed according to the customization or intention of a user or an operator. Therefore, the terms should be defined based on the overall disclosure set forth herein.

[0037] Figure 2 is a configuration block diagram for describing a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure, Figure 3 is a diagram showing a grid map in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure, Figures 4 to 8 is a diagram showing a process of setting a threshold of a grid map in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure, Figures 9A to 9C and Figure 10 is a diagram showing a process of updating a grid map in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure. Figure 11FIG. 0 is a diagram showing a process of mapping a stationary object to a grid map in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure. Figures 12 to 14 FIG. 2 is a diagram showing a process of determining an extended mapping region in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure. Figure 15 and Figure 16A 、 Figure 16B FIG. 8 is a diagram showing a process of correcting an occupancy probability parameter in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure. Figures 17 to 20 FIG. 10 is a diagram showing a process of correcting a shadow grid in a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure.

[0038] Referring Figure 2 to FIG. 15, a device for monitoring a surrounding environment of a vehicle according to an embodiment of the present disclosure may include a sensor unit 100 and a control unit 200.

[0039] The sensor unit 100 may include first to fourth detection sensors 110, 120, 130, and 140 corresponding to radar sensors of the vehicle. As Figure 2 shown, the first detection sensor 110 may correspond to a right rear (RR) radar sensor, the second detection sensor 120 may correspond to a left rear (RL) radar sensor, the third detection sensor 130 may correspond to a right front (FR) radar sensor, and the fourth detection sensor 140 may correspond to a left front (FL) radar sensor. Accordingly, the detection sensors 110, 120, 130, and 140 may be operated to detect an external object by a method of transmitting a radar signal according to a frame having a predefined period and receiving a signal reflected from the external object. In addition, as Figure 1A and Figure 1B shown, depending on a DAS (driver assistance system) (e.g., BSD, LCA, or RCTA) to which the radar sensor is applied, waveforms, frequencies, distance resolutions, angle resolutions, maximum sensing distances, and FoVs of radar signals transmitted from the radar sensor may have different characteristics for each frame.

[0040] The control unit 200 is configured to monitor a surrounding environment of the vehicle by controlling an operation of the DAS of the vehicle, and may be implemented as an ECU (electronic control unit), a processor, a CPU (central processing unit), or an SoC (system on a chip). The control unit 200 may drive an operating system or an application program to control a plurality of hardware components or software components connected to the control unit 200 and perform various data processing operations.

[0041] In this embodiment, the control unit 200 may be operable to extract stationary objects from external objects detected by the sensor unit 100 by using the behavior information of the vehicle, map the extracted stationary objects to a preset grid map, and add occupancy information to each grid constituting the grid map according to whether the stationary objects are mapped to the grid map. In addition, the control unit 200 may be operable to calculate an occupancy probability parameter indicating the probability that a stationary object will be located at each grid based on the occupancy information of the grids within the grid map added to a plurality of frames to be monitored, and monitor the surrounding environment of the vehicle based on the calculated occupancy probability parameter.

[0042] Hereinafter, the process of monitoring the surrounding environment of the vehicle will be described in detail for each of the detailed operations of the control unit 200.

[0043] 1. Stationary object extraction

[0044] First, the control unit 200 may extract stationary objects from external objects detected by the sensor unit 100 by using the behavior information of the vehicle and object information obtained based on the result of detecting external objects by the sensor unit 100. That is, the description of this embodiment focuses on the configuration for monitoring stationary objects rather than moving objects among various external objects around the vehicle.

[0045] The behavior information of the vehicle may include vehicle speed, yaw rate, speed change information, and steering angle, and the object information may include the number of external objects detected by the sensor unit 100, the longitudinal distance and lateral distance to each object, the longitudinal speed and lateral speed of each object, and the intensity of the received signal. The control unit 200 may extract only stationary objects from external objects by using the behavior information and object information of the vehicle. For example, the control unit 200 may distinguish moving objects from stationary objects by analyzing the relationship between the vehicle speed and the longitudinal / lateral speed of the object, so as to extract only stationary objects.

[0046] 2. Stationary object mapping

[0047] When extracting stationary objects, the control unit 200 may map the extracted stationary objects to a preset grid map. Before the mapping process of stationary objects, the grid map and the update process of the grid map will be described preferentially.

[0048] 2-1. Grid map

[0049] As Figure 3 shown, a grid map may be preset in the control unit 200, and the grid map has a size corresponding to the surrounding environment area to be monitored by the vehicle. In Figure 3 , X map_max represents the maximum distance in the longitudinal direction (the longitudinal size of the grid map), Ymap_max Represents the maximum distance in the horizontal direction (the horizontal dimension of the grid map), X map_min Represents the vertical reference position of the grid map, Y map_min Represents the horizontal reference position of the grid map, X map_step Represents the vertical dimension of each grid, and Y map_step Represents the horizontal dimension of each grid.

[0050] The vertical and horizontal axes of the grid map can be set based on the vehicle. If the vertical and horizontal axes of the grid map are set based on a specific point rather than the vehicle, more memory resources may be required depending on the driving mileage of the vehicle. In addition, for the surrounding area of the vehicle, it is effective to set a surrounding environment monitoring area required to output a warning to the driver or perform a driving control operation of the vehicle. Therefore, the vertical and horizontal axes of the grid map can be set based on the vehicle. Accordingly, the indices (coordinates (i, j)) of the grids constituting the grid map can also be set based on the vehicle, where i and j represent the vertical index and the horizontal index, respectively.

[0051] As Figure 4 shown, a threshold value can be defined for each grid in the grid map to determine whether a stationary object occupies each grid within the grid map. As will be described below, the threshold value is used as a value to be compared with an occupancy probability parameter and serves as a reference value for determining whether a stationary object is located at the corresponding grid. The threshold value can be defined for each grid based on a mathematical model according to the intensity of the received signal input to the sensor unit 100, and the mathematical model can correspond to the following well-known radar equation, where Pr represents the intensity of the received signal, Gt represents the antenna gain, and Rt represents the distance to the object:

[0052]

[0053] Specifically, according to the radar equation, the intensity of the received signal can vary according to the antenna gain and the relative distance to the object. Therefore, the probability of detecting the same object by radar may vary according to the position of the object. For example, when the object is located at a short distance, the intensity of the received signal is high, increasing the probability of object detection; while when the object is located at a long distance, the intensity of the received signal is low, decreasing the probability of object detection.

[0054] In addition, when the object is located at a position with high antenna gain, the intensity of the received signal is high, increasing the probability of object detection; while when the object is located at a position with low antenna gain, the intensity of the received signal is low, decreasing the probability of object detection. As described above, depending on the DAS (such as BSD, LCA, or RCTA) of the vehicle to which the radar sensor is applied, the waveform, frequency, range resolution, angle resolution, maximum sensing range, and FoV of the radar signal transmitted from the radar may have different characteristics for each frame. Therefore, each frame may include regions where an object can be repeatedly detected, while only specific frames may include regions where an object can be detected. Thus, the regions that are repeated in each frame may have a high probability of object detection, while the regions that are not repeated in each frame may have a low probability of object detection. This is because: during two frames, an object can be detected twice in the repeated regions, but only once in the non-repeated regions.

[0055] In addition, for two adjacent radar sensors, such as the RR radar sensor and the RL radar sensor, there may be regions where an object can be redundantly detected by the two radar sensors, and regions where an object can be detected by only one radar sensor. Therefore, the regions where an object can be redundantly detected by the two radar sensors may have a high probability of object detection, while the regions where an object can be detected by only one radar sensor may have a low probability of object detection. This is because: even if one radar sensor fails to detect an object in the regions where an object can be redundantly detected by the two radar sensors, the object can be detected by the other adjacent radar sensor. Conversely, when one radar sensor fails to detect an object in the regions where an object can be detected by only one radar sensor, the object cannot be detected by the other adjacent radar sensor.

[0056] Based on the above, the following two cases can be considered.

[0057] i) The case with the highest object detection probability: "the region with a short distance to the object and high antenna gain", "the detection regions repeated in each frame", and "the detection regions redundant between adjacent radar sensors"

[0058] ii) The case with the lowest object detection probability: "the region with a long distance to the object and low antenna gain", "the detection regions not repeated in each frame", and "the detection regions not redundant between adjacent radar sensors"

[0059] In the above two cases, it may be unreasonable to set the same threshold for all grids in order to determine whether each grid in the grid map is occupied. This is because: in case (i), even if there is actually no object, it may be erroneously determined that there is an object (false detection), while in case (ii), even if there is actually an object, it may be erroneously determined that there is no object (missed detection). Therefore, in the present embodiment, the thresholds of the respective grids can be set differently according to the object detection probability, thereby preventing erroneous determination (false detection and missed detection).

[0060] Specifically, the threshold can be set to different values for the independent regions, single-overlap regions, and multi-overlap regions within the grid map.

[0061] The independent region can be defined as the region sensed by the first detection sensor 110 within the grid map in the K-th frame, where K is a natural number, and the single-overlap region can be defined as the following region within the grid map, in which the independent region overlaps with the region sensed by the first detection sensor 110 in the (K + 1)-th frame different from the K-th frame (i.e., after the K-th frame). That is, the independent region and the single-overlap region are distinguished according to whether the detection regions of the same detection sensor in each frame overlap with each other. In the case where the first detection sensor is an RR radar Figure 5 the grids of the independent region are denoted by "0", and the grids of the single-overlap region are denoted by "1". The threshold of the grids of the independent region can be set lower than the threshold of the grids of the single-overlap region, which can compensate for possible false detection and missed detection of objects located in the independent region.

[0062] The multi-overlap region can be defined as the following region within the grid map, in which the region sensed by the second detection sensor 120 adjacent to the first detection sensor 110 overlaps with the single-overlap region in the same frame (the K-th or (K + 1)-th frame). That is, the multi-overlap region is determined according to whether the regions detected by the two adjacent detection sensors overlap with each other in the same frame. In the case where the first detection sensor is an RR radar and the second detection sensor is an RL radar Figure 6 the grids of the region sensed by the first detection sensor 110 are denoted by "0", and the grids of the region where the region sensed by the first detection sensor 110 and the region sensed by the second detection sensor 120 overlap with each other are denoted by "1". Therefore, as in the case where the first detection sensor is an RR radar and the second detection sensor is an RL radar Figure 7As shown, the grid map can be divided into: the independent region "0" sensed by the first detection sensor 110 in the Kth frame; the single-overlap region "1", which is the overlap region between the region sensed by the first detection sensor 110 in the Kth frame and the region sensed in the (K + 1)th frame; and the multi-overlap region "2", which is the overlap region sensed by the first detection sensor 110 and the second detection sensor 120 in the same frame and overlaps with the single-overlap region. When the thresholds for the independent region, the single-overlap region, and the multi-overlap region are defined as the first threshold, the second threshold, and the third threshold respectively, the relationship of "the first threshold < the second threshold < the third threshold" can be established in the part where the thresholds increase linearly, as Figure 8 shown.

[0063] 2-2. Grid Map Update

[0064] As described above, since the vertical axis, the horizontal index, and the index of the grid map are set based on the vehicle, the index of the grid map changes according to the behavior of the vehicle. Therefore, in order to map a stationary object to the grid map, a process of updating the grid map by changing the index of the grid map is required. In addition, even after the stationary object is mapped to the grid map, the index of the grid to which the stationary object is mapped needs to change according to the behavior of the vehicle. When the grid map is updated after the stationary object is mapped to the grid map, the index of the grid to which the stationary object is mapped also changes.

[0065] For this operation, during the period from the (K - 1)th frame to the Kth frame, when the longitudinal movement distance of the vehicle is greater than the longitudinal dimension of the grid or the lateral movement distance of the vehicle is greater than the lateral dimension of the grid, the control unit 200 can update the grid map. In this case, the control unit 200 can change the index of each grid in the (K - 1)th frame according to the index of each grid in the Kth frame based on the longitudinal movement distance, the lateral movement distance, and the longitudinal angle change of the vehicle.

[0066] Taking the index of the grid where the stationary object is located as the changed index as an example, Figure 9A shows the grid map in the (K - 1)th frame with the index of the grid where the stationary object is located. As Figure 9B shown, when the distance traveled by the vehicle in the longitudinal direction is greater than the longitudinal dimension of the grid, it is necessary to change the index of the stationary object on the grid map in the (K - 1)th frame based on the Kth frame, because the index of the stationary object on the grid map in the Kth frame is different from the index of the stationary object on the grid map in the (K - 1)th frame. When the vehicle according to Figure 9CWhen turning at a predetermined yaw rate as shown, the longitudinal or lateral movement distance of the vehicle becomes smaller than the longitudinal or lateral dimension of the grid. In this case, it is necessary to change the index of the stationary object on the grid map in the (K - 1)th frame based on the Kth frame because the index of the stationary object on the grid map in the Kth frame is different from the index of the stationary object on the grid map in the (K - 1)th frame. In this situation, the angular change based on the yaw rate can be reflected in the update of the grid map.

[0067] will refer to Figure 10 the modeling to describe the update process of the grid map based on Figures 9A to 9C the grid map.

[0068] First, the control unit 200 calculates the cumulative values of the yaw axis angle change and the movement displacement change of the vehicle during the time period from the (K - 1)th frame to the Kth frame according to Equation 1 below.

[0069] [Equation 1]

[0070] -Δθ_acc = Δθ_acc + Δθ

[0071]

[0072] -Δγ_acc = Δγ_acc + Δγ

[0073] In Equation 1, Δθ represents the instantaneous angular change of the yaw axis reference of the vehicle, Δθ_acc represents the cumulative angular change of the yaw axis reference during the time period from the (K - 1)th frame to the Kth frame, Δγ represents the instantaneous movement displacement of the vehicle, Vs represents the speed of the vehicle, dt represents the time period from the (K - 1)th frame to the Kth frame, represents the longitudinal unit vector, represents the lateral unit vector, and Δγ_acc represents the cumulative movement displacement of the vehicle during the time period from the (K - 1)th frame to the Kth frame.

[0074] The control unit 200 determines whether the grid map update condition is satisfied according to Equation 2 below.

[0075] [Equation 2]

[0076] Δx k = -Δγ·cos(Δθ)

[0077] Δy k = Δγ·sin(Δθ)

[0078] Δx k _acc = Δx k _acc + Δx k

[0079] Δy k_acc = Δy k _acc + Δy k

[0080]

[0081] In Equation 2, Δx k represents the longitudinal instantaneous movement distance of the vehicle, and Δy k represents the lateral instantaneous movement distance of the vehicle, and Δx k _acc represents the longitudinal cumulative movement distance of the vehicle, and Δy k acc represents the lateral cumulative movement distance of the vehicle.

[0082] When the grid map update condition is satisfied according to Equation 2, the control unit 200 updates the grid map according to the following Equation 3.

[0083] [Equation 3]

[0084]

[0085]

[0086]

[0087] In Equation 3, (i, i) represents the index of the grid, (i_update, j_update) represents the index of the updated grid, and floor represents the truncation operator. In Equation 3, the matrix acts as a rotation matrix for rotating the grid map according to the vehicle yaw rate:

[0088] 2-3. Static Object Mapping

[0089] According to the following Equation 4, the control unit 200 can convert the position information of the static object (i.e., the longitudinal distance and the lateral distance to the static object) into the index corresponding to the (updated) grid map.

[0090] [Equation 4]

[0091]

[0092]

[0093] In Equation 4, I tgt_n represents the longitudinal index of the target grid, J tgt_n represents the lateral index of the target grid, X tgt_n represents the longitudinal distance to the static object, and Y tgt_n represents the lateral distance to the static object.

[0094] As Figure 11As shown, by specifying the target grid corresponding to the changed index of the grid map, the control unit 200 can map the extracted stationary object to the grid map. In this case, the control unit 200 can add occupancy information with a first value to the target grid to which the stationary object is mapped, and add occupancy information with a second value to other grids. In this embodiment, the first value can be set to "1", and the second value can be set to "0". Therefore, the value "1" can be added as occupancy information to the target grid to which the stationary object is mapped, and the value "0" can be added as occupancy information to other grids not mapped by the stationary object. Hereinafter, the occupancy information added to the index (i, j) in the Kth frame will be represented by Pmap(i, j, k).

[0095] 3. Extended Mapping Region Determination

[0096] As described above, depending on the DAS (such as BSD, LCA, or RCTA) of the vehicle to which the radar sensor is applied, the waveform, frequency, range resolution, angle resolution, maximum sensing range, and FoV of the radar signal transmitted from the radar sensor may have different characteristics for each frame. Therefore, although the same stationary object is detected, the index of the detected stationary object may change in each frame because the signal characteristics are different in each frame. In this case, the occupancy probability parameter described below can be reduced by the number of signal waveforms used. Figure 12 The results obtained when the radar sensor detects the same stationary object by transmitting radar signals with a single waveform and multiple waveforms are shown. Compared with a single waveform, in the case of multiple waveforms, the occupied grids are scattered in each frame, reducing the probability of detecting a stationary object. When the threshold of the grid map is set to a lower value to compensate for the reduction of the occupancy probability parameter, the stationary object is likely to be misdetected due to clutter or noise.

[0097] To prevent misdetection, the control unit 200 according to this embodiment can add occupancy information to the target grid corresponding to the detected stationary object and the surrounding grids. Specifically, as Figure 13 shown, the control unit 200 can determine an extended mapping region that extends a preset range based on the target grid to which the stationary object is mapped, and calculate the occupancy probability parameter by adding occupancy information with a first value to each grid constituting the extended mapping region to monitor the surrounding environment of the vehicle. Considering the similarity (range resolution and velocity resolution) between signal waveforms, the preset range extended from the target grid can be predefined by the designer.

[0098] Figure 14Shows the results obtained when the radar sensor detects the same stationary object by transmitting radar signals with a single waveform and multiple waveforms. After setting the extended mapping area that extends a preset range from the target grid, even in the case of multiple waveforms, the probability of detecting a stationary object can be avoided from decreasing by the method of calculating the occupancy probability parameter of each grid that constitutes the extended mapping area as described below.

[0099] 4. Occupancy Probability Parameter Calculation

[0100] In this embodiment, the process of calculating the occupancy probability parameter of the grid map follows the occupancy probability calculation method of the general OGM (Occupancy Grid Map) based on Equation 5 below.

[0101] [Equation 5]

[0102]

[0103]

[0104]

[0105] In Equation 5, R 1:k represents the sensing data (the above object information) of the sensor unit 100 (radar sensor) from the first frame to the Kth frame, and V 1:k represents the behavior data (the above behavior information) of the vehicle from the first frame to the Kth frame, and l0 represents the prior probability (0 in this embodiment).

[0106] When the occupancy information Pmap(i,j,k) added to each grid in this embodiment is applied to the occupancy probability calculation method based on Equation 5 above, the occupancy probability parameter p is calculated according to Equation 6 below.

[0107] [Equation 6]

[0108]

[0109] In Equation 6, M represents the number of frames to be monitored.

[0110] 5. Grid Map Update Error Correction

[0111] The speed, moving displacement, and yaw axis angle change of the vehicle are obtained by sensors applied to the vehicle, and they are used as factors for determining whether the update condition of the grid map is satisfied. Since such sensed values inevitably contain errors, even if the update condition of the grid map is actually not satisfied due to the errors contained in the sensed values, it is determined that the update condition of the grid map has been satisfied. In this case, the grid map may be updated erroneously. As described above, during the update process of the grid map, the control unit 200 operates to change the index of the target grid to which the stationary object is mapped. Therefore, when the grid map is updated erroneously, an error may occur between the index corresponding to the actual position of the stationary object and the index of the stationary object mapped to the erroneously updated grid map. As a result, this error may lead to false detection and missed detection of the stationary object.

[0112] Reference will be made to Figure 15 (a) to (d) of to describe the occurrence of the error. Figure 15 (a) of shows that: the stationary object is mapped to grid ① in the (K - 1)th frame, and then grid ① expands a preset range to determine the first expanded mapping area; and Figure 15 (b) of shows that the above update condition of the grid map is satisfied in the Kth frame, thus updating the grid map. Since the grid map has been updated, the index of the grid to which the stationary object is mapped also changes, so that the grid to which the stationary object is mapped is updated to grid ②. In addition, the position of the stationary object actually detected by the sensor unit 100 still remains in grid ①. As a result, an error occurs between the index of the grid corresponding to the actual position of the stationary object and the index of the grid of the stationary object mapped to the updated grid map.

[0113] When the grid map is updated as the (K - 1)th frame switches to the Kth frame, by comparing the first expanded mapping area in the (K - 1)th frame with the second expanded mapping area in the Kth frame, the control unit 200 can correct each occupancy probability parameter of the grids constituting the second expanded mapping area, thereby correcting the above update error.

[0114] Reference Figure 15In (c) above, based on the K-th frame with respect to the (K-1)-th frame, the control unit 200 may specify, in the grid of the second extended mapping region, a first region composed of grids with an increased occupancy probability parameter. That is, this first region corresponds to the grids that were unoccupied in the (K-1)-th frame but are occupied in the K-th frame. In addition, based on the K-th frame with respect to the (K-1)-th frame, the control unit 200 may specify, in the grid of the first extended mapping region, a second region composed of grids with a decreased occupancy probability parameter. That is, the second region corresponds to the grids that were occupied in the (K-1)-th frame but are unoccupied in the K-th frame. In addition, by replacing the occupancy probability parameter of the second region with that of the first region, the control unit 200 may correct each occupancy probability parameter of the grids constituting the second extended mapping region in the K-th frame. Thus, as Figure 15 shown in (d), the extended mapping region may be constructed while matching the extended mapping region with the position of the stationary object actually detected by the sensor unit 100. When the state where the grids constituting the second region are unoccupied continues for a preset time, the occupancy probability parameter of the grids may be reset to "0".

[0115] Figure 16A shows an example of the occupancy probability parameter on the grid map before the update error of the grid map is updated. As Figure 16A shown, grid ① corresponds to a position with a lateral / longitudinal error from the actual position of the stationary object, but maintains a predetermined occupancy probability value, while grid ② corresponds to the actual position of the stationary object, but has an occupancy probability value lower than that of the surrounding grids because grid ② is a newly occupied grid.

[0116] Figure 16B shows an example of the occupancy probability parameter on the grid map after the update error of the grid map is corrected. As Figure 16B shown, grid ① is a previously occupied grid and has a low occupancy probability value after reset, while grid ② corresponds to the actual position of the stationary object and has an occupancy probability value higher than that of the surrounding grids because grid ② is a newly occupied grid but inherits a predetermined occupancy probability value.

[0117] 6. Correction of Shadow Region

[0118] As described above, the detection sensor according to the present embodiment may be implemented as a radar sensor. As Figure 17 shown, due to the FoV and installation characteristics (installation angle and position) of the radar sensor, there are shadow regions where the radar sensor cannot detect external objects.

[0119] To correct the shadow grids corresponding to the shadow regions, the control unit 200 may operate to correct the shadow grids by using a first method of receiving the occupancy probability parameter in the (K-1)-th frame or a second method of receiving the occupancy probability parameter of the grids around the shadow grids.

[0120] When the speed of the vehicle is equal to or higher than a preset reference value, the first method can be executed. As Figure 18 shown, the grid ① in the (K-1)th frame does not correspond to the shaded grid, so the occupancy probability parameter is retained. When the vehicle speed is equal to or higher than the reference value, the update process of the grid map is executed, and the grid ① in the Kth frame belongs to the shaded grid. In this case, the control unit 200 can set the occupancy probability parameter of the grid ① in the (K-1)th frame to the occupancy probability parameter of the shaded grid ① in the Kth frame, so as to minimize the loss caused by the missed detection of the radar sensor.

[0121] When the speed of the vehicle is lower than the reference value, the second method can be executed. That is, when the vehicle is traveling at a very low speed or stopped, even if the (K-1)th frame is switched to the Kth frame, the grid map is not updated. Therefore, the first method cannot be applied. In this case, the control unit 200 can operate to set the occupancy probability parameter of the grid around the shaded grid to the occupancy probability parameter of the shaded grid. In this case, as Figure 19 shown, the control unit 200 can execute the second method from the shaded grid located at the outermost position to obtain the occupancy probability parameter of the grid that is not the shaded grid. The control unit 200 can set the highest occupancy probability parameter among the occupancy probability parameters of the grids within a preset range (for example, one grid) of the shaded grid to the occupancy probability parameter of the corresponding shaded grid. Figure 20 Shows the result obtained by correcting the shaded area to set the occupancy probability parameter with a predetermined value to the shaded grid.

[0122] 7. Stationary Object Position Determination (Peak Detection)

[0123] When the grid map update, extended mapping area determination, update error correction, and shaded area correction are performed through the above process, the control unit 200 can operate to specify the grid where a stationary object is likely to be located based on the occupancy probability parameter of the grid within the extended mapping area.

[0124] That is, the control unit 200 can determine the peak grid with the highest occupancy probability parameter among the grids within the extended mapping area determined for multiple frames to be monitored. When the occupancy probability parameter of the peak grid is equal to or greater than the threshold defined for the peak grid, the control unit 200 can determine that the stationary object is located at the peak grid. When the vehicle is traveling, the control unit 200 can monitor the surrounding environment of the vehicle by repeatedly executing the stationary object position determination method based on "peak detection".

[0125] Figure 21 is a flowchart for describing a method for monitoring the surrounding environment of a vehicle according to an embodiment of the present disclosure. Reference will be made to Figure 21Describe a method for monitoring the surrounding environment of a vehicle according to this embodiment. Hereinafter, descriptions of content that duplicates the above will be omitted, and the following description will focus on the chronological configuration.

[0126] First, in step S100, the control unit 200 extracts stationary objects from the external objects of the vehicle detected by the sensor unit 100 by using the behavior information of the vehicle.

[0127] Then, in step S200, the control unit 200 maps the stationary objects extracted in step S100 to a preset grid map, adds occupancy information to each grid constituting the grid map according to whether the stationary objects are mapped to the grid map, and calculates an occupancy probability parameter based on the occupancy information of the grids within the grid map to be monitored in a plurality of frames, where the occupancy probability parameter indicates the probability that the stationary object will be located at the corresponding grid.

[0128] In step S200, the control unit 200 maps the stationary objects to the grid map while updating the grid map by changing the respective indices of the grids constituting the grid map according to the behavior information of the vehicle.

[0129] In addition, in step S200, the control unit 200 converts the position information of the stationary objects into indices corresponding to the grid map, maps the stationary objects to the grid map by specifying the target grid corresponding to the indices of the grid map, adds occupancy information with a first value to the target grid to which the stationary objects are mapped, and adds occupancy information with a second value to other grids, where the second value is less than the first value.

[0130] In addition, in step S200, the control unit 200 calculates the occupancy probability parameter by determining an extended mapping area that extends a preset range based on the target grid to which the stationary objects are mapped, and adding occupancy information with a first value to each grid constituting the extended mapping area.

[0131] In addition, in step S200, when the grid map is updated as the (K - 1)th frame switches to the Kth frame, the control unit 200 corrects the occupancy probability parameters of the grids constituting the second extended mapping area by comparing the first extended mapping area in the (K - 1)th frame with the second extended mapping area in the Kth frame. Specifically, based on the Kth frame on the (K - 1)th frame, the control unit 200 designates a first area composed of grids with an increased occupancy probability parameter in the grids of the second extended mapping area, and designates a second area composed of grids with a decreased occupancy probability parameter in the grids of the first extended mapping area. Then, by replacing the occupancy probability parameter of the second area with the occupancy probability parameter of the first area, the control unit 200 corrects the respective occupancy probability parameters of the grids constituting the second extended mapping area in the Kth frame.

[0132] In addition, in step S200, the control unit 200 corrects the shadow grid corresponding to the shadow area where the sensor unit 100 cannot detect an external object in the K-th frame by using a first method of receiving the occupancy probability parameter in the (K-1)-th frame or a second method of receiving the occupancy probability parameter of the grids around the shadow grid. In this case, when the speed of the vehicle is equal to or higher than a preset reference value, the control unit 200 corrects the shadow grid according to the first method, and when the speed of the vehicle is lower than the reference value, the control unit 200 corrects the shadow grid according to the second method.

[0133] After step S200, in step S300, the control unit 200 monitors the surrounding environment of the vehicle based on the occupancy probability parameter calculated in step S200. Specifically, the control unit 200 determines a peak grid having the highest occupancy probability parameter among the grids within the extended mapping area determined for a plurality of frames to be monitored. When the occupancy probability parameter of the peak grid is equal to or greater than a threshold defined for the peak grid, the control unit 200 determines that a stationary object is located at the peak grid.

[0134] Thus, the apparatus and method for monitoring the surrounding environment of a vehicle according to the present embodiment can map a stationary object detected by radar to a preset grid map, add occupancy information to each grid constituting the grid map according to whether the stationary object is mapped to the grid map, and then calculate an occupancy probability parameter based on the occupancy information added to each grid within the grid map for a plurality of frames to be monitored to monitor the surrounding environment of the vehicle, where the occupancy probability parameter indicates the probability that a stationary object will be located at the corresponding grid. Therefore, when monitoring the surrounding environment of a vehicle by radar, the apparatus and method can improve the detection accuracy of external objects.

[0135] For example, the embodiments described in this specification can be implemented by a method or process, a device, a software program, a data stream, or a signal. Although a feature is discussed only in a single context (e.g., only in a method), the discussed feature can be implemented in another type (e.g., a device or a program). The device can be implemented in suitable hardware, software, or firmware. The method can be implemented in a device such as a processor, which generally refers to a processing device including a computer, a microprocessor, an integrated circuit, or a programmable logic device. The processor also includes a communication device facilitating information communication between end users, such as a computer, a cellular phone, a PDA (Personal Digital Assistant), and other devices.

[0136] Although exemplary embodiments of the present disclosure are disclosed for illustrative purposes, those skilled in the art should recognize that various modifications, additions, and substitutions are possible without departing from the scope and spirit of the present disclosure defined in the appended claims. Therefore, the true technical scope of the present disclosure should be defined by the appended claims.

Claims

1. A device for monitoring the surrounding environment of a vehicle, comprising: A sensor unit including a plurality of detection sensors for detecting an object outside the vehicle according to a frame at a predetermined period; And A control unit configured to: extract a stationary object from the external objects detected by the sensor unit, map the extracted stationary object to a preset grid map, calculate an occupancy probability parameter indicating the probability that the stationary object will be located on a grid of the grid map based on the mapping result, and monitor the surrounding environment of the vehicle based on the calculated occupancy probability parameter, Wherein, the control unit maps the extracted stationary object to the grid map while updating the grid map by changing the index of each grid constituting the grid map according to the behavior information of the vehicle, Wherein, when a predefined grid map update condition is satisfied according to the longitudinal or lateral movement distance of the vehicle, the control unit updates the grid map from the (K - 1)th frame to the Kth frame, Wherein, the control unit further performs the following operations: When the speed of the vehicle is equal to or higher than a preset reference value, the control unit performs a first operation, in which when a grid of the grid map in the (K - 1)th frame does not correspond to a shaded grid, but after the vehicle moves, the position represented by the grid of the grid map in the (K - 1)th frame corresponds to the position represented by the shaded grid of the grid map in the Kth frame, the control unit sets the occupancy probability parameter of the shaded grid of the grid map in the Kth frame to the occupancy probability parameter of the grid of the grid map in the (K - 1)th frame, and When the speed of the vehicle is lower than the preset reference value, the control unit performs a second operation, in which when the grid map is not updated even when switching from the (K - 1)th frame to the Kth frame, the control unit sets the occupancy probability parameter of the shaded grid of the grid map in the Kth frame to the highest occupancy probability parameter among the occupancy probability parameters of the grids within a preset range from the shaded grid of the grid map in the Kth frame, Wherein, the shaded grid is a grid corresponding to the shadow area where the sensor unit cannot detect an external object due to the field of view and installation of the sensor unit.

2. The device according to claim 1, wherein The grid map update condition is as follows: the longitudinal movement distance of the vehicle is greater than the longitudinal dimension of the grid, or the lateral movement distance of the vehicle is greater than the lateral dimension of the grid.

3. The device according to claim 1, wherein The control unit updates the grid map by changing the index of each grid in the (K - 1)th frame for the Kth frame based on the longitudinal movement distance, lateral movement distance, and longitudinal angle change of the vehicle.

4. The apparatus according to claim 3, wherein The control unit updates the grid map using a rotation matrix that rotates the grid map according to the longitudinal and lateral movement distances of the vehicle from the (K - 1)th frame to the Kth frame, the index of each grid in the (K - 1)th frame, and the yaw rate of the vehicle.

5. The apparatus according to claim 1, wherein The control unit converts the position information of the extracted stationary object into an index corresponding to the grid map, and maps the extracted stationary object to the grid map by specifying a target grid in the grid map corresponding to the converted index.

6. The device according to claim 5, wherein, The control unit adds occupancy information having a first value to the target grid to which the stationary object is mapped, and adds occupancy information having a second value, which is smaller than the first value, to the remaining grids.

7. The device according to claim 6, wherein The control unit determines an extended mapping area that extends a set range with respect to the target grid to which the stationary object is mapped, and monitors the surrounding environment of the vehicle by adding occupancy information having the first value to each grid constituting the extended mapping area to calculate the occupancy probability parameter.

8. The apparatus according to claim 7, wherein, The set range is predefined according to the distance and speed resolution of the signal waveform transmitted from the detection sensor.

9. The device according to claim 1, wherein When switching from the (K-1)th frame to the Kth frame, the control unit updates the grid map according to whether a predefined grid map update condition is satisfied, and corrects the grid map update error caused by an inherent error in a factor used to determine whether the grid map update condition is satisfied.

10. The device according to claim 9, wherein, When correcting the grid map update error when updating the grid map by switching from the (K-1)th frame to the Kth frame, the control unit compares a first extended mapping area with a second extended mapping area to correct the occupancy probability parameter of each grid constituting the second extended mapping area, where the first extended mapping area is an area that extends a set range with respect to the target grid to which the stationary object is mapped in the (K-1)th frame, and the second extended mapping area is an area that extends a set range with respect to the target grid to which the stationary object is mapped in the Kth frame.

11. The apparatus according to claim 10, wherein, For the Kth frame compared with the (K-1)th frame, the control unit designates a first area composed of grids with increased occupancy probability parameters in the grids of the second extended mapping area, designates a second area composed of grids with decreased occupancy probability parameters in the grids of the first extended mapping area, and then replaces the occupancy probability parameter of the second area with that of the first area to correct the occupancy probability parameter of each grid constituting the second extended mapping area.

12. The device according to claim 1, wherein, The control unit determines a peak grid having the maximum occupancy probability parameter among the grids in the grid map, and when the occupancy probability parameter of the peak grid is equal to or greater than a threshold defined for the peak grid, determines that the stationary object is located on the peak grid.

13. A method for monitoring the surrounding environment of a vehicle, comprising: extracting, by a control unit, a stationary object from objects outside the vehicle detected by a sensor unit, the sensor unit including a plurality of detection sensors for detecting the external objects of the vehicle according to frames at a predetermined period; The control unit maps the extracted stationary object to a preset grid map, and calculates an occupancy probability parameter indicating the probability that the stationary object will be located on the grid of the grid map based on the mapping result; and the control unit monitors the surrounding environment of the vehicle based on the calculated occupancy probability parameter, where: the grid map has a longitudinal axis, a transverse axis, and an index set relative to the vehicle; and in the process of calculating the occupancy probability parameter by the control unit, the control unit maps the extracted stationary object to the grid map, and updates the grid map by changing the index of each grid constituting the grid map according to the behavior information of the vehicle; wherein the method further includes: when a predefined grid map update condition is satisfied according to the longitudinal or transverse movement distance of the vehicle, the control unit updates the grid map from the (K - 1)th frame to the Kth frame; when the speed of the vehicle is equal to or higher than a preset reference value, the control unit performs a first operation, in which when the grid of the grid map in the (K - 1)th frame does not correspond to a shaded grid, but after the vehicle moves, the position represented by the grid of the grid map in the (K - 1)th frame corresponds to the position represented by the shaded grid of the grid map in the Kth frame, the control unit sets the occupancy probability parameter of the shaded grid of the grid map in the Kth frame to the occupancy probability parameter of the grid of the grid map in the (K - 1)th frame; and when the speed of the vehicle is lower than the preset reference value, the control unit performs a second operation, in which when the grid map is not updated even when switching from the (K - 1)th frame to the Kth frame, the control unit sets the occupancy probability parameter of the shaded grid of the grid map in the Kth frame to the highest occupancy probability parameter among the occupancy probability parameters of the grids within a preset range from the shaded grid in the grid map in the Kth frame; wherein the shaded grid corresponds to the shadow area where the sensor unit cannot detect external objects due to the field of view and installation of the sensor unit.

14. An apparatus for monitoring the surrounding environment of a vehicle, comprising: a sensor unit including a plurality of detection sensors for detecting objects outside the vehicle according to frames at a predetermined period; and a control unit configured to: extract a stationary object from the external objects detected by the sensor unit, map the extracted stationary object to a preset grid map, calculate an occupancy probability parameter indicating the probability that the stationary object will be located on the grid of the grid map based on the mapping result, and monitor the surrounding environment of the vehicle by comparing the calculated occupancy probability parameter with a threshold defined in the grid of the grid map; wherein the threshold is defined for each of a plurality of regions in the grid map, and the plurality of regions are divided according to whether the detection regions of the same detection sensor overlap with each other in each frame and whether the detection regions of two adjacent detection sensors overlap with each other in the same frame. Wherein, when a predefined grid map update condition is satisfied according to the longitudinal or lateral movement distance of the vehicle, the control unit updates the grid map from the (K-1)th frame to the Kth frame. Wherein, the control unit further performs the following operations: When the speed of the vehicle is equal to or higher than a preset reference value, the control unit performs a first operation. In this first operation, when the grid of the grid map in the (K-1)th frame does not correspond to the shaded grid, but after the vehicle moves, the position represented by the grid of the grid map in the (K-1)th frame corresponds to the position represented by the shaded grid of the grid map in the Kth frame, the control unit sets the occupancy probability parameter of the shaded grid of the grid map in the Kth frame to the occupancy probability parameter of the grid of the grid map in the (K-1)th frame, and When the speed of the vehicle is lower than the preset reference value, the control unit performs a second operation. In this second operation, when the grid map is not updated even when switching from the (K-1)th frame to the Kth frame, the control unit sets the occupancy probability parameter of the shaded grid of the grid map in the Kth frame to the highest occupancy probability parameter among the occupancy probability parameters of the grids within a preset range from the shaded grid of the grid map in the Kth frame. Wherein, the shaded grid is a grid corresponding to the shadow area where the sensor unit cannot detect external objects due to the field of view and installation of the sensor unit.

15. The apparatus according to claim 14, wherein, The threshold is determined by the radar equation in response to the intensity of the received signal input to the sensor unit.

16. The apparatus according to claim 14, wherein, The multiple regions include an independent region, which has a first threshold and is defined as the region sensed by the first detection sensor in the grid map in the Kth frame, where K is a natural number.

17. The apparatus according to claim 16, wherein, The multiple regions include a single-overlap region, which has a second threshold and is defined as the region in the grid map that is the overlapping region of the region sensed by the first detection sensor in the (K+1)th frame after the Kth frame and the independent region.

18. The device according to claim 17, wherein, The multiple regions include a multi-overlap region, which has a third threshold and is defined as the region in the grid map that is the overlapping region of the region sensed by the second detection sensor adjacent to the first detection sensor in the Kth frame or the (K+1)th frame and the single-overlap region.

19. The apparatus according to claim 18, wherein, Each of the first threshold to the third threshold has a linear part, which is a part that linearly increases in response to the intensity of the received signal input to the sensor unit, and the relationship of "the first threshold < the second threshold < the third threshold" is established in the overlapping part of the linear parts of the first threshold to the third threshold.

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