Method for detecting an object on the roof of a vehicle and method for predicting the range of a vehicle

Abstract

The invention relates to a method for detecting an object (200) on the roof (120) of a vehicle (100), in which at least one image (300) of an interior (101) of the vehicle (100) is taken by means of a driver observation camera (140), wherein the image (300) contains a glass roof (121) of the vehicle (100), which is analyzed at least one image (300) with regard to the existence of an object (200) visible through the glass roof (121), and, if an object (200) is detected, information about the object (200) is given to a control unit (150) which calculates a prediction about the range of the vehicle (100).The invention further relates to a method for predicting the range of a vehicle (100), in which an air resistance is determined taking into account an object (200) arranged on the vehicle roof (120) of the vehicle (100) and a range prediction is calculated, wherein the existence of an object (200) arranged on the vehicle roof (120) of the vehicle (100) is detected, and a control unit (150) calculates a prediction of the range of the vehicle (100), wherein information classifying the object (200) is taken into account in the calculation of the prediction.

Description

[0001] The invention relates to a method for detecting an object on the roof of a vehicle according to the preamble of claim 1 and a method for predicting the range of a vehicle according to the preamble of claim 6.

[0002] In principle, methods and devices for predicting the range of vehicles are known from the prior art. The range can be determined for electric vehicles as well as conventionally powered vehicles. In the near future, electric vehicles of all kinds will increasingly be used. An important aspect here is the accurate determination of the range on a single battery charge. This range depends not only on a driver's driving style and battery capacity, but also, and especially, on the actual total weight and aerodynamics of the vehicle.

[0003] For example, attaching roof racks, roof boxes, or bicycle carriers to a vehicle affects its overall weight and aerodynamics. The maximum possible range of an electric vehicle on a single battery charge can be significantly impacted by the additional load and / or altered aerodynamics.

[0004] DE 20 2013 000 855 U1 describes a device for monitoring vehicle roof loads of a motor vehicle using a bracket and a mirror, in which vehicle roof loads applied to the vehicle roof of motor vehicles can be seen by means of a mirror in the driver's field of vision, which is mounted inside or outside the passenger compartment.

[0005] DE 10 2020 112 549 A1 describes a method for measuring an attachment mounted on a vehicle. The method serves to detect a collision hazard and comprises receiving at least one image from a camera of a mobile device, wherein the at least one image depicts an exterior area of ​​the vehicle and the attachment mounted on the vehicle; recognizing the exterior area of ​​the vehicle in the at least one image; assigning a three-dimensional model of the vehicle to the recognized exterior area of ​​the vehicle, wherein the three-dimensional model describes spatial dimensions of the vehicle; recognizing the attachment in the at least one image; and determining the spatial dimensions of the recognized attachment based on the assignment of the three-dimensional model to the recognized exterior area of ​​the vehicle.

[0006] DE 10 2019 007 493 A1 describes a method for determining the range of a vehicle, in which the vehicle weight and air resistance are determined, taking into account roof-mounted equipment and trailer loads, and are included in the range calculation. The weight of the roof-mounted equipment and trailer loads is optically detected using a scanner, sensor, and / or code. Furthermore, a device for carrying out the method is described, in which at least one scanner and / or sensor is arranged on a roof rail of the vehicle, capable of optically detecting a code, such as a barcode or QR code.

[0007] The invention is based on the objective of providing an improved method for detecting an object on the roof of a vehicle and an improved method for predicting the range of a vehicle.

[0008] The object of detecting an object on the roof of a vehicle is achieved according to the invention by a method comprising the features of the characterizing part of claim 1. With regard to predicting the range of a vehicle, the object of detecting an object on the roof of a vehicle is achieved according to the invention by a method comprising the features of the characterizing part of claim 6.

[0009] Advantageous embodiments of the invention are the subject of the dependent claims.

[0010] In a method for detecting an object on the roof of a vehicle, it is proposed that at least one image of the interior of the vehicle is taken by means of a driver observation camera, wherein the image contains a glass roof of the vehicle, which is analyzed for the existence of an object visible through the glass roof, and, if an object is detected, information about the object is given to a control unit that calculates a prognosis, i.e. a prediction about the range of the vehicle.

[0011] Mounting an object such as a roof box on the vehicle roof increases the vehicle's rolling resistance. Detecting a mounted object can improve the accuracy of predicting the electric range. The driver observation camera should be used to detect the object.

[0012] The field of view of the driver observation camera mounted on or in the cockpit, in combination with a glass roof and object recognition intelligence implemented in a control unit, such as the head unit (i.e., a central control unit), can be used to detect an object on the vehicle's roof. In a further step, the object can be more precisely classified to estimate its impact on driving resistance as accurately as possible. This information can then be used to improve the accuracy of the range prediction.

[0013] According to the invention, a driver observation camera is used in a central position in the vehicle with a viewing angle towards the driver and / or passenger, which has sufficient resolution to detect at least different brightness levels in order to determine shadows and / or detailed information about an object arranged on the vehicle roof, for example a roof box.

[0014] Object recognition can advantageously be achieved by detecting an object based on a brightness difference between the object and a reference surface, whereby an edge of the object visible in the glass roof is detected based on the brightness difference between the object and the reference surface, for example its surroundings in the glass roof, and an object covering the entire glass roof is detected based on a brightness difference between the object and the reference surface, for example a side window of the vehicle.

[0015] If a roof box is small enough to create a shadow line above the glass roof, it must be assumed to be mounted. From this shadow line, a new drag coefficient (Cd) and the increased frontal area (A) of the vehicle can either be calculated using the base area of ​​the roof box, or a standard Cd value and A surcharge can be used from a database or reference table. If the camera resolution is high enough to recognize and calculate the dimensions of the roof box, or even to extract information from a marking, such as a printed label on the roof box (model number, part number, etc.), this information should be used to determine the new Cd value and the new frontal area of ​​the vehicle, possibly using the dimensions from a database or reference table.

[0016] If a roof box is larger than the area of ​​the glass roof, no shading edge is visible in this area. Differences in brightness can be detected by comparing the box to the external light source via the side window. If the brightness differs significantly, a roof box must be assumed to be mounted. A standard drag coefficient (Cd) and A-value surcharge can be applied from a reference database.

[0017] The information obtained about the presence of a roof box and the resulting worsened drag coefficient and increased frontal area can then be made available to the control unit that calculates the electric range prediction, thus significantly improving the prediction quality.

[0018] Alternatively or additionally, the method according to the invention can provide that an object is detected based on a marking visible to the driver's observation camera through the glass roof. It can further be provided that at least one piece of information classifying the object is extracted from the marking and this information is transmitted to the control unit, which calculates the vehicle's range prediction. A marking can, for example, be attached to the underside of a roof box and contain object-classifying information, such as a QR code, from which the type of roof box, any increase in the vehicle's frontal area caused by it, or other information related to driving resistance can be derived.

[0019] Alternatively or additionally, it may be provided that a user is prompted via a vehicle user interface to enter at least one piece of information classifying the object, and that this information is then sent to the control unit, which calculates the vehicle's range prediction. For example, the driver may be prompted to select or enter the dimensions or model number of the roof box via a user interface such as a touchscreen.

[0020] The problem is further solved by a method for predicting a vehicle's range, in which air resistance is determined taking into account an object located on the vehicle's roof, and a range prediction is calculated. The existence of such an object on the vehicle's roof is determined by a method of the type described above, and a control unit calculates a range prediction, incorporating information that classifies the object into the calculation. This information can then be included in the vehicle's range prediction, thus significantly improving the prediction accuracy.

[0021] In one embodiment of the method according to the invention, it may be provided that information classifying the object is estimated, or taken from a value memory of the control unit, or extracted from a marking of the object, or entered by a user via a user interface of the vehicle.

[0022] An advantageous further development of the method consists in continuously determining the remaining capacity of a traction battery and / or the remaining fuel level during a journey, and continuously updating the forecast of the vehicle's range during the journey, taking into account the remaining capacity and / or the remaining fuel level.

[0023] An advantageous further development of the process involves the use of artificial intelligence, which is pre-trained based on images and independently recognizes the dimensions of the installed roof box and then selects the new drag coefficient and the new frontal area of ​​the vehicle from a database.

[0024] With each new installation situation, the system's intelligence is further trained. To improve or support this training, the driver can also be prompted, for example, by entering the dimensions or model number of the roof box via an existing user interface in the vehicle, such as an instrument cluster, dashboard, touchscreen, or similar device.

[0025] Exemplary embodiments of the invention are explained in more detail below with reference to drawings.

[0026] This shows: Fig. 1 schematically a driver observation camera, Fig. 2 schematically depicts an installation situation of a driver observation camera, Fig. 3 schematically a vehicle with a roof box, Fig. 4 schematically shows a view into the interior of a vehicle, Fig. 5 schematically an object recognition according to a first embodiment, and Fig. 6 schematically an object recognition according to a second embodiment.

[0027] Corresponding parts are marked with the same reference symbols in the figures.

[0028] Fig. Figure 1 shows an example of a driver observation camera 140, which includes an IR imager 141, an IR light source 142, a dot projector 143, and an RGB imager 144, and which can be used, among other things, for interior monitoring and driver monitoring. As shown in particular in Fig. As can be seen in Figure 2, the driver observation camera 140 is located in the front area of ​​the interior 101 of a vehicle 100 and is oriented opposite to the direction of travel, i.e., towards the rear. In the specific embodiment, the driver observation camera 140 is located centrally on the top of the cockpit 130. Below the driver observation camera 140, the cockpit 130 has a user interface 160, which is designed as a touchscreen 161 and allows user input. The user interface 160 is in a data-conducting connection with a control unit 150, which is configured to calculate a prediction of the range of a vehicle 100, as is the case, for example, in Fig. 3 is shown.

[0029] Fig. Figure 3 shows a vehicle 100, which has a traction battery 102, vehicle doors 110 with side windows 111, and a vehicle roof 120 with a glass roof 121. Two roof racks 210 are mounted on the vehicle roof 120, and an object 200, which in this specific case is a roof box 201, is located on the roof racks 210.

[0030] Fig. Figure 4 shows the interior 101 of vehicle 100. Fig. 3 from the perspective of the driver observation camera 140, where the area depictable in image 300 is indicated by a frame. In image 300, two users 400 of the vehicle 100 are visible. In addition, the side windows 111 of the vehicle doors 110 and the glass roof 121 arranged in the vehicle roof 120 are visible.

[0031] The Fig. 5 and Fig. Figure 6 shows three examples of ways to detect an object 200 arranged on the vehicle roof 120.

[0032] In Fig. In Figure 5, the entire glass roof 121 is shaded by an object 200, namely a large roof box 201, which means that the glass roof 121 in Figure 300 has a significantly lower brightness value than the side windows 111 of the vehicle doors 110. Based solely on this difference in brightness and the fact that the entire glass roof 121 is darkened, the control unit 150 can conclude that it is a large roof box 201 and, when calculating the predicted range of the vehicle 100, can use a correspondingly increased drag coefficient (Cd value), which may be stored, for example, in a memory location of the driver observation camera 140 or the control unit 150.

[0033] In Fig. Figure 2 illustrates two different methods of object recognition.

[0034] The first method of object recognition is based on edge detection. Since the roof box 201 is narrower than the glass roof 121 in this case, light passes through the glass roof 121 on both sides of the roof box 201. In this case, the driver observation camera 140 or the control unit 150 can identify the edges 202 of the object 200, i.e., in this specific case, the roof box 201, from the difference in brightness between the roof box 201 and the unshaded areas of the glass roof 121. The width of the roof box 201 can also be calculated from the distance between the edges 202, and the object 200 can be classified based on this value, for example, as a narrow or medium-width roof box 201. Alternatively or additionally, a user 400 of the vehicle 100 can use a user interface 160, as described in Fig. 2 is shown, prompting the user to enter information classifying object 200.

[0035] The second method of object recognition is based on the extraction of information classifying the object 200 from a marker 203, which is attached to the underside of the roof box 201 and which may, for example, contain a QR code from which the type of roof box 201, an increase in the frontal area of ​​the vehicle 100 caused by it, or other information related to driving resistance can be derived.

[0036] The driver observation camera 140 is used to detect an object 200, such as a roof box 201, through the glass roof 121. When an object 200 is detected, the information is sent to a control unit 150 in the vehicle 100, which adjusts the predicted range based on the increased air and rolling resistance. The weight can either be entered manually or an average value can be used. The aerodynamic data of the roof box 201 can either be retrieved from the cloud via the COM module or stored in the memory of the control unit 150. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] DE 20 2013 000 855 U1

[0004] DE 10 2020 112 549 A1

[0005] DE 10 2019 007 493 A1

[0006]

Claims

[1] Method for detecting an object (200) on the vehicle roof (120) of a vehicle (100), characterized by , that by means of a driver observation camera (140) at least one image (300) of an interior (101) of the vehicle (100) is taken, wherein the image (300) includes a glass roof (121) of the vehicle (100), that at least one image (300) is analyzed with regard to the existence of an object (200) visible through the glass roof (121), and, When an object (200) is detected, information about the object (200) is given to a control unit (150) which calculates a prediction about the range of the vehicle (100). [2] Method according to claim 1, characterized by , that an object (200) is detected due to a brightness difference between the object (200) and a reference surface, whereby an edge (202) of the object (200) visible in the glass roof (121) is detected due to the difference in brightness between the object (200) and its surroundings in the glass roof (121) and an object (200) covering the entire glass roof (121) is detected due to a difference in brightness between the object (200) and a side window (111) of the vehicle (100). [3] Method according to claim 1 or 2, characterized by , that an object (200) is detected by means of a marking (203) of the object (200) visible to the driver observation camera (140) through the glass roof (121). [4] Method according to claim 3, characterized by , that at least one piece of information classifying the object (200) is extracted from the marking (203) and the information is given to the control unit (150) which calculates the prediction of the vehicle's range (100). [5] Method according to any one of claims 1 to 3, characterized by, that a user (400) is prompted via a user interface (160) of the vehicle (100) to input at least one piece of information classifying the object (200) and the information is given to the control unit (150) which calculates the prediction of the vehicle's (100) range. [6] Method for predicting the range of a vehicle (100) in which an air resistance is determined taking into account an object (200) arranged on the roof (120) of the vehicle (100) and a range prediction is calculated, characterized by , that the existence of an object (200) arranged on the vehicle roof (120) of the vehicle (100) is detected by a method according to one of claims 1 to 3, and a control unit (150) calculates a forecast of the vehicle's (100) range, taking into account information classifying the object (200) when calculating the forecast. [7] Method according to claim 6, characterized by , that information classifying the object (200) is estimated, or taken from a value memory of the control unit (150), or extracted from a mark (203) of the object (200), or entered by a user (400) via a user interface (160) of the vehicle (100). [8] Method according to claim 6 or 7, characterized by , that during a journey, the remaining capacity of a traction battery (102) and / or the remaining fuel level of a fuel tank is continuously determined, and The forecast of the vehicle's range (100) during the journey is continuously updated, taking into account the remaining capacity and / or the remaining fill level.

Images