Method for operating a traffic monitoring apparatus for a road user, and traffic monitoring apparatus

Abstract

The invention relates to a method for operating a traffic monitoring apparatus (110) for a road user (100), the traffic monitoring apparatus (110) comprising a sensor device (130) and at least one electromagnetic detector (120), the method comprising a step in which a sensor signal is read in via an interface from the sensor device (130), the sensor signal representing an image of a road user (100) detected in an area surrounding the traffic monitoring apparatus (110), and data from the electromagnetic detector being read in. The method also comprises a step in which the image of the road user is overlaid with the data from the electromagnetic detector. The method also comprises a step in which electromagnetic wave components are evaluated at different positions in the image in order to obtain an evaluation signal using the sensor signal. Furthermore, the method comprises a step in which a road user signal is determined using the evaluation signal, the road user signal representing road user data of the detected road user (100).

Description

[0001] Method for operating a traffic monitoring device for a road user and traffic monitoring device

[0002] State of the art

[0003] The invention is based on a method for operating a traffic monitoring device for a road user and a traffic monitoring device according to the preamble of the independent claims. The present invention also relates to a computer program.

[0004] US9658314 discloses a surveillance system for monitoring a detection area of ​​a traffic area and detecting various electromagnetic sources. EP3561536 discloses a radio viewing device, for example, for detecting and visualizing various radio sources.

[0005] DE102022202174A1, DE102014203754A1, DE102021134170A1 and DE102013006942B3 disclose traffic monitoring systems or traffic observation systems, which describe both imaging sensors and sensors for detecting electromagnetic waves.

[0006] Against this background, the approach presented here presents a method for operating a traffic monitoring device for a road user, a traffic monitoring device, a device using this method, and finally a corresponding computer program according to the main claims. The measures listed in the dependent claims enable advantageous refinements and improvements of the device specified in the independent claim.

[0007] The advantages that can be achieved with the approach presented here consist in particular in the creation of a method that can reliably and quickly determine road user data of a recorded road user.

[0008] A method for operating a traffic monitoring device for a road user, wherein the traffic monitoring device has a sensor device and an electromagnetic detector, comprises a step of reading in a sensor signal via an interface from the sensor device, wherein the sensor signal represents an image of a road user detected in an area surrounding the traffic monitoring device. Furthermore, data from the electromagnetic detector can be read in during the reading step and superimposed on the image of the road user in a superimposing step. Furthermore, the method comprises a step of evaluating electromagnetic wave components at different positions of the image to obtain an evaluation signal using the sensor signal.The method also comprises a step of determining a road user signal using the evaluation signal, wherein the road user signal represents road user data of the detected road user.

[0009] The traffic monitoring device can, for example, be a device for monitoring traffic, identifying individual road users, monitoring the speed of road users, or monitoring a toll obligation. For this purpose, the traffic monitoring device can be located adjacent to a traffic route, a road, or a carriageway, for example. The road user can have unique characteristics, such as the arrangement and number of electromagnetic emitters (radiators) relative to one another, which can be detected using a combination of electromagnetic wave detection and video image analysis. Using the approach presented here, wave emissions from electric motors, electric drives, or combustion engines (for example, based on the ignition pulses of the spark plugs) of the detected road user can be measured.On this basis, for example, the model, make, color and characteristics regarding the electromagnetic radiation of a detected vehicle as a road user can be determined as the road user data, even in the dark. The approach presented here can therefore also be understood as Make - Model - Color - Electromagnetic Spectrum. In addition, for example, the license plate of the road user can be recorded and evaluated. Electromagnetic detection directed at a vehicle as a road user is particularly preferred, which can be carried out as a spot measurement so that precisely one vehicle or generally one road user after the other can be measured. Furthermore, electromagnetic detection of the entire surroundings of the traffic monitoring device at an angle of up to 360 degrees is also advantageous for assessing the overall situation, e.g.the emissions of electromagnetic waves on the appropriate traffic area.

[0010] During the reading step, an image or a video, in particular a live video of the surrounding area of ​​the detected road user in an optically visible range and additionally or alternatively in an infrared or UV range, can be read in as an image. In addition, electromagnetically sensitive detectors detect electromagnetic fields emitted or reflected by the road user. A spectral analysis of a road user's emissions is carried out in the EM (electromagnetic) wavelength range (kHz-MHz range), e.g., to distinguish between electric vehicles and combustion engine vehicles as road users or their driving modes. This allows, for example, the positions of electromagnetic radiation sources (engine, drive, Wi-Fi transmitters, V2X transmitters, etc.) on the road user to be reliably recorded.In other words, the approach presented here can be carried out both in visible light and in non-visible light in the dark.

[0011] In the determination step, a distance and additionally or alternatively a relative arrangement between at least two positions in the image at which electromagnetic wave components were detected can be determined. Distances and / or arrangements of the positions with electromagnetic wave components to one another can represent unique characteristics of a road user. In particular, with knowledge of the distance of the road user (object to be measured) through a distance-measuring sensor, absolute measurements can be determined with a good degree of certainty. In the determination step, a specific model of a vehicle can thus be identified as a road user and / or a make of the vehicle as a road user. The detected regions with electromagnetic wave components can be specially marked and highlighted in the image, e.g., using exaggerated color schemes or with the characteristic features of IR thermal images.

[0012] In the determination step, the evaluation signal at different positions can be compared with expected wave components read from a database at corresponding positions in the image to obtain the road user data. This allows the detected road user to be reliably identified, for example, by comparing the detected positions within the road user with the positions of transmission sources (emitters) of electromagnetic waves that are installed and known as road users at different positions in different vehicle types or models.

[0013] The method can comprise a step of outputting an electromagnetic signal to the road user, carried out before the reading step. In this case, in the output step, a different electromagnetic signal with different (frequency) spectra can be output at different times. Furthermore, the influence of interference sources on the analysis can be avoided by taking measurements at two different times. This can be advantageous, for example, if a source is directed at the road user at one time and this source is switched off at a second time. A differential measurement can be advantageous here. Under certain circumstances, the electromagnetic detector can be switched on automatically.

[0014] By actively generating suitable electromagnetic waves by an emitter of the traffic monitoring device, interference can be induced, resulting in noise suppression if a high level of noise from different emitters is present in the surrounding area. The principle is similar to the noise-canceling method established in audio technology. In this case, electromagnetic signals are detected by the detector from the surrounding area, and suitable electromagnetic waves are emulated by a processing unit in an emitter of the traffic monitoring device or transmitted into the surrounding area of ​​the traffic monitoring device.

[0015] According to one embodiment of the approach presented here, a step of distinguishing a currently used road user drive type and / or drive mode of the road user based on the presence and / or distribution of electromagnetic wave components at different positions in the image can also be provided. This allows for rapid and unambiguous identification of individual road users. In the step of determining the road user signal, a make of the vehicle as a road user, a model of the vehicle as a road user, vehicle owner information, and additionally or alternatively a color of the vehicle as a road user can be represented as road user data. Advantageously, precise identification of the road user detected by the traffic monitoring device can be achieved.

[0016] The method may include a step of providing the road user signal to an interface to an external storage device in order to compare the determined road user data of the detected road user with road user data of a reference road user. The determined road user data of the detected road user can be stored in the external storage device.

[0017] For unknown road users, a new data set is saved. This involves an automatic, self-learning addition to a database in the storage device to learn new road user types and new electromagnetic spectra. This means that the spectrum is saved, an image of it, e.g., in the form of a photo or live video, is attached to the data set, and optionally, an AI-controlled recognition is performed. Manual comparison can be performed by an operator / human in the back office.

[0018] In so-called environmental zones, driving with an internal combustion engine may be prohibited – even if it involves burning e-fuels. Hybrid vehicles as road users have at least one electric motor in addition to the internal combustion engine. By detecting the electromagnetic radiation / emissions emanating from the vehicle as a road user, conclusions can be drawn about the actual driving mode. It is important to distinguish whether a purely electric mode has been selected or whether the electric motor emits only low emissions. The latter would indicate mixed operation, which should be penalized because it would place excessive strain on the environment. Electromagnetic emissions in the engine area or electromagnetic emissions that typically indicate the activity of a spark plug or injection pump would indicate that the internal combustion engine is engaged.This type of driving behavior, in particular, should be penalized for environmental reasons. Another application of the detection of electromagnetic fields in vehicles as road users involves making braking systems visible, especially regenerative braking systems, which generate electric fields in the corresponding components during braking. In addition to the brake lights, this can determine whether, when, for how long, and with what energy.

[0019] The step of evaluating and additionally or alternatively determining can be carried out using an artificial intelligence algorithm.

[0020] One of the steps of the method can be performed in a unit that can be located separately from another unit in which another step of the method can be performed. In this way, road user identification can be performed at at least two measurement locations.

[0021] This method can be implemented, for example, in software or hardware or in a mixed form of software and hardware, for example in a control unit.

[0022] The approach presented here further provides a device configured to perform, control, or implement the steps of a variant of a method presented here in corresponding devices. This embodiment of the invention in the form of a device also allows the problem underlying the invention to be solved quickly and efficiently.

[0023] For this purpose, the device can have at least one computing unit for processing signals or data, at least one memory unit for storing signals or data, at least one interface to a sensor or an actuator for reading sensor signals from the sensor or for outputting data or control signals to the actuator, and / or at least one communication interface for reading or outputting data embedded in a communication protocol. The computing unit can be, for example, a signal processor, a microcontroller, or the like, wherein the memory unit can be a flash memory, an EEPROM, or a magnetic storage unit.The communication interface can be designed to read in or output data wirelessly and / or via a wired connection, wherein a communication interface that can read in or output wired data can read this data, for example, electrically or optically from a corresponding data transmission line or output it to a corresponding data transmission line.

[0024] In this case, a device can be understood as an electrical device that processes sensor signals and outputs control and / or data signals depending on them. The device can have an interface, which can be implemented in hardware and / or software. In a hardware implementation, the interfaces can, for example, be part of a so-called system ASIC, which contains a wide variety of functions of the device. However, it is also possible for the interfaces to be separate integrated circuits or to consist at least partially of discrete components. In a software implementation, the interfaces can be software modules that are present, for example, on a microcontroller alongside other software modules.

[0025] A traffic monitoring device for detecting a road user in an environment of the traffic monitoring device comprises an embodiment of a device mentioned herein. The traffic monitoring device further comprises a sensor device and an electromagnetic detector. In this way, the road user can be easily detected, and the road user data can be reliably and quickly recorded and evaluated.

[0026] The electromagnetic detector can be integrated into the video camera and, for example, also overlay the image of the road user with the data from the electromagnetic detector.

[0027] The sensor device can comprise a laser sensor, a lidar sensor, a radar sensor, and, additionally or alternatively, an ultrasonic sensor. This advantageously allows a road user to be reliably detected. The sensors can be manufactured cost-effectively and installed in the traffic monitoring device in a space-saving manner.

[0028] The traffic monitoring device can have a lighting device. The lighting device can be arranged on the traffic monitoring device or adjacent to the traffic monitoring device. The lighting device can be switched on, for example, in poor lighting conditions, such as in the dark, to create an image of the road user. At least one electromagnetic signal can be projected onto the road user, so that electromagnetic wave components can subsequently be detected on the image using a sensor device and / or electromagnetic detector.

[0029] Also advantageous is a computer program product or computer program with program code that can be stored on a machine-readable carrier or storage medium such as a semiconductor memory, a hard disk memory, or an optical memory. If the program product or program is executed on a computer or a control device, the program product or program can be used to carry out, implement, and / or control the steps of the method according to one of the embodiments described above.

[0030] Examples of the approach presented here are shown in the drawings and explained in more detail in the following description. It shows:

[0031] Fig. 1 shows an illustration of an embodiment of a traffic monitoring device;

[0032] Fig. 2 is a flowchart of an embodiment of a method for operating a traffic monitoring device; and

[0033] Fig. 3 is a block diagram of an embodiment of a device for operating a traffic monitoring device.

[0034] In the following description of advantageous embodiments of the present invention, the same or similar reference numerals are used for the elements shown in the various figures and having a similar effect, whereby a repeated description of these elements is omitted. If an embodiment includes an "and / or" connection between a first feature and a second feature, this should be understood to mean that the embodiment, according to one embodiment, has both the first feature and the second feature, and according to another embodiment, either only the first feature or only the second feature.

[0035] A road user is understood to mean, in particular, a vehicle such as a car or truck, motorcycle or bicycle, scooter, etc., but also a wheelchair. A road user does not necessarily have to roll. They can also glide, hover, fly, or walk. For this reason, the term "road user" refers to any moving road user and thus includes, in particular, pedestrians. The latter can also carry electromagnetic emitters (e.g., cell phones, radio-controlled watches, VR glasses, etc.), and they too are at least surrounded by clothing of various brands and models in a wide variety of colors, which have a high identification and recognition value. This is particularly important in the context of civil security. In the course of digitalization, data must be linked equally to every object.Thus, road user data is equivalent to road user data, pedestrian data, or personal data. For ease of reading, the terms "road user" and "road user data" will continue to be used, as most road users travel with a vehicle.

[0036] For further simplification, the masculine form has been used frequently. Of course, all genders are included.

[0037] Fig. 1 shows an illustration of an embodiment of a traffic monitoring device 110 for detecting a road user 100. The traffic monitoring device 110 is designed to monitor traffic or traffic events in an environment of the traffic monitoring device 110.

[0038] The traffic monitoring device 110 has a mast 115 and is arranged adjacent to a roadway 105, with the road user 100 being arranged here as a vehicle on the roadway 105. The traffic monitoring device 110 has a sensor device 130 and an electromagnetic detector 120 for detecting the road user 100.

[0039] The sensor device 130 is designed, for example, as a camera and detects the road user 100 when it is located within a detection range of the sensor device 130. More precisely, the sensor device 130 creates an image of the road user 100. The electromagnetic detector 120 is designed, for example, to detect electromagnetic emissions from the road user 100. Motors 180 (for example, wheel hub motors or motors for comfort functions in general), sensors 160, and also the radio devices (WLAN, V2X, mobile communications) 170 of the road user 100 generate, for example, emissions that are detected by the sensor device 130 and / or the electromagnetic detector 120 as electromagnetic wave components from the superimposed image of the road user 100.The electromagnetic wave components are arranged, for example, at different positions in the image, whereby a number and / or arrangement of the motors 180 and / or sensors 160 of the road user 100 can be determined. The motors 180 and the sensors 160 have, for example, a road user-specific arrangement and / or number on the road user 100. The radio devices 170 of the road user 100 are also road user-specific. An evaluation of the arrangement and / or number of the electromagnetic wave components in or from the image can thus lead to a precise identification of the road user 100 – by superimposing the sensors / detectors, the model, make, color, and characteristics of the electromagnetic emitters, for example, of the vehicle as road user 100, can be determined.

[0040] In addition, it is possible to determine the intensity of the electromagnetic wave components in the image in order to detect, for example, the use of unauthorized, modified, and / or counterfeit motors 180 and / or sensors 160 for the road user 100. Using the approach presented here, a clear identification of the radio devices 170 of the road user 100 is also possible. By overlaying the image with the data from the electromagnetic sensor / detector, an (illegal) modification of properties, such as paintwork, radio tuning, etc., of the road user 100 can be detected using the traffic monitoring device 110. Identification of the road user 100 is also possible in poor lighting conditions, for example, in the dark.For this purpose, the traffic monitoring device 110 has a lighting device 190, which is arranged on the traffic monitoring device 110 merely as an example and is designed to illuminate the road user 100.

[0041] In other words, Fig. 1 shows a traffic monitoring device 110, which can also be referred to as a traffic monitoring system, at the side of the roadway of a road 105 at point A, with a mast 115 or tripod and with a sensor device 130, which can also be referred to as an image sensor or video camera, and an electromagnetic detector 120. The electromagnetic detector 120 receives emitted or reflected electromagnetic waves 150 from the road user 100. The most important emission sources or reflectors are listed: 180 engine(s), 160 sensor, 170 radio devices. These emission sources or reflectors are detected both by the electromagnetic detector 120 and, if necessary, also by the sensor device 130. The sensor device 130 is additionally equipped with an automatic license plate reader for recognizing and evaluating the license plate 145. The lighting device 190, which can also be referred to as a light source orA laser, which can be referred to as a laser, is directed, for example, at road user 100 and is preferably built into the housing of traffic monitoring device 110 or arranged in the form of a special street lamp. The same applies to sensors such as lidar, radar, etc. for determining speed or red light violations. According to one embodiment, the approach presented here uses artificial intelligence, abbreviated to K1, which compares video data with data from the electromagnetic detector on a computing unit not shown here, for example in the back office. In particular, a superposition of the data leads to a geometric mapping that provides a video image of road user 100 on which the data or spectra of the electromagnetic detector 120 can be seen.In a further step, this data can be compared with data from a database, or a forensic analysis of a suspected road user can be subsequently reproduced and compared with the data generated here. Example: A getaway vehicle used as a road user for an ATM bombing is captured by the traffic monitoring device 110. The drivers are masked and cannot be identified in the vehicle as road user 100. The license plate 145 was stolen from another vehicle. Months later, a vehicle is found as a road user. This vehicle is subsequently measured using the method presented here. A comparison of the data with the data from the day of the getaway leads to a clear match. This allows for further forensic investigations to be carried out in a targeted manner in the vehicle as road user 100.Since these forensic investigations are very expensive and time-consuming, suspicion of a vehicle type as a road user is not sufficient - a unique "fingerprint" using spectrum mapping is better.

[0042] In other words, Fig. 1 shows a combination of a traffic monitoring device 110, which can also be referred to as a traffic monitoring unit, with a built-in electromagnetic detector 120 for analyzing electromagnetic waves. In addition to / alternatively to the frequency detection of the road user electronics, the frequency detection and evaluation of any active and passive emitters can be detected using the electromagnetic detector 120. The focus is on the detection of additional unique features for identifying road users for the area of ​​civil security, but also TLE (Traffic Law Enforcement), particularly in the area of ​​environmental protection in designated environmental zones. With the approach presented here, Make - Model - Colour can be extended to include the properties of the spectrum of any reflected or emitted electromagnetic waves.

[0043] Newer road users are equipped with electric motors and sensors that can be detected using the approach presented here. This results in new methods for visualizing and thus identifying road users. In addition to pure video / image sensor detection of the make, model, and color of a vehicle as road user 100, a secure spectral breakdown of the electromagnetic emitters is performed. In addition, characteristic features of road user lighting and, above all, the electromagnetic radiation of the road user sensors and motors, which is invisible to the human eye, and their interaction are used to uniquely identify road user 100.

[0044] Alternatively, a separate analysis of the electromagnetic frequency spectrum of road users is possible without comparison with image data and / or video data of road user 100 or license plate 145. Identification of road users using video data "make-model-color" is possible, for example, whereby the light sources can only be detected via video.

[0045] In other words, the approach presented here enables a cost-effective extension of a traffic monitoring device 110 using an electromagnetic detector 120, as well as a legally binding assignment and identification of road users. Furthermore, the approach presented here enables an increase in the hit rate for "make-model-color" by expanding the visualization of road user-specific properties of the electromagnetic emitters, such as drive and servo motors, brake units, pumps, low beams, indicators, brake lights, laser sensors, lidar sensors, or their specific electromagnetic spectra and geometric arrangements relative to one another - mapping. The approach presented here is particularly applicable in the field of civil security, for example, when using counterfeit license plates or duplicates.In the case of road users who have been repainted and electrically modified after a vehicle theft, it is possible to identify the differences from the vehicle manufacturer's original equipment, thus providing reasonable initial suspicion that this vehicle has been modified as a road user to conceal a crime. Furthermore, a fully automatic comparison with an alarm message to a computing unit is possible, which can be part of the traffic monitoring device 110 or as a back-office solution. A frequency sweep using a defined lighting and / or electromagnetic emitter device 190 can be projected as an excitation signal onto the radio device 170 or the sensors 160, 180.

[0046] In summary, the traffic monitoring device 110 comprises the sensor device 130 and the electromagnetic detector 120 for the secure identification of road users. Image data from the sensor device 130 is provided to a computing unit for determining the vehicle make, the vehicle model, and / or the license plate 145 and / or the vehicle driver, and optionally the vehicle color. Electromagnetic detector data from the electromagnetic detector 120 is provided to the computing unit for determining the emitted and / or reflected frequencies and / or frequency spectra. The emitted and / or reflected frequencies and / or frequency spectra are compared with vehicle-specific data from a database to assign a vehicle make, vehicle model, and / or vehicle color.The computing unit performs frequency and / or frequency spectrum mapping of the individual reflectors or emitters of the road user and measures their relative positions and / or lists them in a coordinate system. The computing unit compares the image data from the image sensor and the data from the electromagnetic detector, thereby determining further road user characteristics or verifying the road user characteristics from the image data using data from the electromagnetic detector. The computing unit outputs a unique road user, including unique vehicle owner characteristics such as the currently registered license plate and the currently registered vehicle owner.

[0047] Active irradiation by means of the illumination device 190 is carried out, for example, by one or more light sources, for example with different wavelengths, lasers, lamps, and an electromagnetic emitter, etc., and the spectral analysis is performed on the captured image. If necessary, a laser / emitter sweep is recorded, i.e., the laser / emitter is scanned once over the road user 100, and the response is spectrally and, if necessary, also temporally broken down to obtain a type of "signature of the road user." Thus, differences in the road user 100 may potentially enable unambiguous identification. The illumination device 190 can also be used to irradiate the road user 100 with a uniform spectrum to improve lighting conditions in the dark. Furthermore, identification of the road user 100 from more than one measurement location is possible.A comparison of the image data by means of the electromagnetic detector 120 is possible, for example, using artificial intelligence, for example a convolutional neural network (CNN).

[0048] Fig. 2 shows a flowchart of an embodiment of a method 200 for operating a traffic monitoring device. The method 200 is similar to or corresponds to the method described in Fig. 1 and is carried out, for example, using the traffic monitoring device described in Fig. 1.

[0049] The method 200 comprises, merely by way of example, a step 220 of outputting an electromagnetic wave signal to the road user. A different electromagnetic wave signal with different frequency spectra is output at different times. The output step 220 is performed before the reading step 205. In the reading step 205, a sensor signal is read in from the sensor device via an interface. The sensor signal represents an image of a road user detected in an area surrounding the traffic monitoring device. According to one embodiment, in the reading step 205, an image of the area surrounding the detected road user in an optically visible range and / or in an infrared range and data from the electromagnetic detector are read in as an image.

[0050] In a step 207 of overlaying, the image of the road user is overlaid with the data from the electromagnetic detector.

[0051] Furthermore, the method 200 comprises a step 210 of evaluating spectral electromagnetic wave components and / or the spectrum of electromagnetic wave components at different positions of the image in order to obtain an evaluation signal using the sensor signal.

[0052] Furthermore, method 200 includes a step 215 of determining a road user signal using the evaluation signal. The evaluation step 210 and / or the determination step 215 are performed, for example, using an artificial intelligence algorithm.

[0053] According to one embodiment, in step 215 of determining, the evaluation signal at different positions is compared with expected electromagnetic wave components at corresponding positions read from a database in order to obtain the road user data. The road user signal represents road user data of the detected road user. Additionally or alternatively, the road user signal represents, as road user data, a make of the vehicle as a road user, a model of the vehicle as a road user, vehicle owner information, and / or a color of the vehicle as a road user. According to one embodiment, in step 215 of determining, a distance and / or a relative arrangement between at least two positions in the image is determined.According to one embodiment, the method 200 comprises a step 225 of providing the road user signal to an interface to an external storage device in order to compare the determined road user data of the detected road user with road user data of another road user.

[0054] According to one embodiment, one of the steps of the method 200 is performed in a unit that is arranged separately from another unit in which another step of the method 200 is performed.

[0055] Fig. 3 shows a block diagram of an embodiment of a device 300 for operating a traffic monitoring device. Device 300 is designed, for example, to control the method from Fig. 2 or a similar method.

[0056] For this purpose, the device 300 has a unit 305 for reading in a sensor signal 315. The sensor signal 315 is read in by the sensor device 130 via an interface. The sensor signal 315 represents an image of a road user detected in an area surrounding the traffic monitoring device. For example, an image of the area surrounding the detected road user in an optically visible range and / or in an infrared range is read in as the image. The device 300 also includes a unit for overlaying the image of the road user with the data from the electromagnetic detector.

[0057] In addition, the device 300 has a unit 310 for evaluating electromagnetic wave components at different positions of the image to obtain an evaluation signal 320. The evaluation signal 320 is evaluated using the sensor signal 315.

[0058] The device 300 also has a unit 325 for determining a road user signal 335 using the evaluation signal 320. The road user signal 335 represents road user data of the detected road user, for example, a make of the vehicle as a road user, a model of the vehicle as a road user, vehicle owner information, and / or a color of the vehicle as a road user. The evaluation signal 320 is compared, for example, at different positions with expected electromagnetic wave components read from a database at corresponding positions to obtain the road user data.

[0059] According to one embodiment, device 300 comprises a unit 340 for outputting a signal 350. Output unit 340 is controlled, merely by way of example, before read-in unit 305. In output unit 340, a different signal with different electromagnetic wave spectra is output at different times. This can cause interference, which results in noise suppression if a high noise content from different emitters is present in the environment. The principle is similar to the noise-canceling method established in audio technology. In this case, electromagnetic signals are detected by the detector, and suitable electromagnetic waves are emulated in an emitter (not shown) of the traffic monitoring device or emitted into the environment of the traffic monitoring device.

[0060] The device 300 has, merely by way of example, a unit 345 for providing the road user signal 335 to an interface to an external storage device 360 ​​in order to compare the determined road user data of the detected road user with road user data of another road user. This also makes it possible to determine the degree of use of, for example, electric vehicles on a specific route section.

Claims

Patent claims 1. A method (200) for operating a traffic monitoring device (110) for a road user (100), wherein the traffic monitoring device (110) has a sensor device (130) and at least one electromagnetic detector (120), the method (200) comprising the following steps: Reading (205) a sensor signal (315) via an interface from the sensor device (130), wherein the sensor signal (315) represents an image of a road user (100) detected in an area surrounding the traffic monitoring device (110) and data from the electromagnetic detector (120); Overlaying (207) the image of the road user with the data from the electromagnetic detector; Evaluating (210) the spectrum of electromagnetic wave components at different positions of the image to obtain an evaluation signal (320) using the sensor signal (315); and Determining (215) a road user signal (335) using the evaluation signal (320), wherein the road user signal (335) represents road user data of the detected road user (100) and, in step (215) of determining, the evaluation signal (320) is compared at different positions with expected electromagnetic wave components read from a database at corresponding positions in the image in order to obtain the road user data.

2. Method (200) according to claim 1, wherein in the step (205) of reading in as an image an image of the surrounding area of ​​the detected road user (100) is read in in an optically visible range and / or in an infrared range and / or UV range.

3. Method (200) according to one of the preceding claims, wherein in the step (215) of determining, a distance and / or a relative arrangement between at least two positions in the image at which electromagnetic wave components were determined is determined.

4. Method (200) according to one of the preceding claims, comprising a step of distinguishing a currently used road user drive type and / or drive mode based on the presence and / or distribution of electromagnetic wave components at different positions in the image.

5. Method (200) according to one of the preceding claims, wherein in the step (215) of determining the road user signal (335) as road user data, a make of a vehicle as road user (100), a model of a vehicle as road user (100), owner information and / or a color of a vehicle as road user (100) is determined.

6. Method (200) according to one of the preceding claims, comprising a step (225) of providing the road user signal (335) to an interface to an external storage device (360) in order to compare the determined road user data of the detected road user (100) with road user data of a reference road user.

7. The method (200) according to any one of the preceding claims, wherein the step (210) of evaluating and / or the step (215) of determining is carried out using an artificial intelligence algorithm.

8. The method (200) according to any one of the preceding claims, wherein one of the steps of the method (200) is carried out in a unit arranged separately from another unit in which another step of the method (200) is carried out.

9. Device (300) which is designed to carry out and / or control the steps of the method (200) according to one of the preceding claims 1 to 8 in corresponding units.

10. Traffic monitoring device (110) for detecting a road user (100) in an environment of the traffic monitoring device (110), with a device (300) according to claim 9, wherein the sensor device (130) has an image sensor, a laser sensor, a lidar sensor, a radar sensor and / or an ultrasonic sensor.

11. Traffic monitoring device (110) according to claim 10, comprising a lighting device (190), wherein the lighting device (190) is arranged on the traffic monitoring device (110) or adjacent to the traffic monitoring device (110).

12. Computer program product with program code for carrying out the method (200) according to one of the preceding claims 1 to 8, when the computer program product is executed on a device.

13. A machine-readable storage medium on which the computer program according to claim 12 is stored.

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