Calibration system

Abstract

Method for calibrating a measuring device (6) to be calibrated, which serves to determine a load on an infrastructure arrangement (4), wherein the measuring device (6) acquires measurement data and is calibrated by means of a calibration device (7) using at least one calibration weight, comprising the determination of at least one reference data set, wherein the reference data set includes a vehicle weight of a vehicle (1) which is determined by a reference scale (5), wherein the calibration device (7) automatically compares the reference data set, the measurement data and position data attributable to the vehicle (1) and calibrates the measuring device (6) using the vehicle weight as the calibration weight, characterized in that the position data, the reference data set and / or the measurement data are filtered for data reduction at the latest before the calibration of the measuring device (6).and that the recorded measurement data are provided with time and location information by the calibration device (7), wherein the calibration device (7) generates the location information from a connection information, and wherein the transmission of the measurement data to the calibration device (7) takes place in real time.

Description

[0001] The present invention relates to a method for calibrating a measuring device to be calibrated, which serves to determine a load on an infrastructure arrangement, wherein the measuring device acquires measurement data and is calibrated by means of a calibration device using at least one calibration weight, comprising the determination of at least one reference data set, wherein the reference data set comprises a vehicle weight of a vehicle which is determined by a reference scale.

[0002] The invention further relates to a system for calibrating a measuring device, which serves to determine an infrastructure arrangement by means of measurement data acquired by the measuring device, by means of a calibration unit on the basis of at least one calibration weight, wherein the system has a reference scale for determining at least one reference data set, wherein the reference data set has a vehicle weight of a vehicle.

[0003] JP 2018-179 838 A describes a vehicle measurement system capable of reducing measurement errors without the need for a dedicated test vehicle. A vehicle drives over a first load sensor installed in a test track, which determines the weight of the stationary vehicle's axles. This axle weight, along with vehicle information, is transmitted to a management server, allowing the vehicle's total weight to be calculated. When the vehicle passes over a second load sensor, it is identified, and the management server generates a correction value based on the measurement data from the first load sensor. This correction value then corrects each measured axle load from the second load sensor. The load signals from the corresponding load sensors can be averaged in this process.

[0004] WO 2015 / 052 662 A1 describes a vehicle overload management system comprising multiple control stations along a road. Each control station has an assigned unique identifier and includes at least one vehicle weighing mechanism, at least one electronic identification mechanism for identifying a passing vehicle, and a communication module for communicating with other control stations along the corridor. Each control station is configured to receive, via the communication module, weight measurement data and vehicle identifiers acquired by one or more other control stations along the road traffic corridor and to link the received information with the unique identifiers of the control stations from which it was acquired.The control station can then use at least some of the associated information to determine whether a vehicle passing through the control station should be weighed using the vehicle weighing mechanism.

[0005] In his 2019 master's thesis, "Weigh-in-Motion Auto-Calibration Using Automatic Vehicle Identification" (D3), Zhang Durlandal, FZ, describes sensors installed in main lanes of highways that determine vehicle weight, wheelbase, vehicle class, speed, vehicle length, and traffic volume. Recordings from trucks at multiple sensor locations are correlated, taking into account minimum and maximum travel times between individual sensors. This correlation is achieved using an assignment filter.

[0006] US 6,980,093 B2 describes a sensor array. A primary set of sensors is located along a highway approaching a weigh-in / checkpoint, and a secondary set of sensors is located along a ramp used by vehicles exiting the highway into the weigh-in / checkpoint. The secondary sensors use vehicle identification based on transponders and / or alternative means (such as license plate readers) suitable for lower speeds and for vehicles without transponders. The sensors are connected to a processing system that accesses a database containing data on vehicles using the highway. When the primary sensors detect certain parameters, the vehicles are instructed to exit the highway and proceed onto the weigh-in / checkpoint's approach ramp.The secondary sensors along the ramp enable the identification of vehicles with and without transponders, as well as more accurate detection, partly due to the lower speed of the vehicle when passing the sensors.

[0007] US 9,851,241 B2 describes a method for calibrating a WIM (Weigh-in-Motion) sensor embedded in a road surface. In this method, a WIM sensor measures the dynamic wheel force on the road surface while a calibration vehicle is driving by. This wheel force data is transmitted to an evaluation unit. As the calibration vehicle passes by, WIM signal data is simultaneously measured at the WIM sensor and transmitted to the evaluation unit. In the evaluation unit, the wheel force data is synchronized with the WIM signal data. A calibration function is determined by comparing the dynamic wheel force data with the WIM signal data.

[0008] US 2009 / 0151421A1 describes a weigh-in-motion (WIM) system for weighing moving vehicles, where the system is capable of automatically determining and periodically applying calibration factors for WIM scale readings. The automatic calibration can include transferring both WIM and static weight readings for the same vehicle to a database, mapping the weight readings, recording a series of such weight readings, and analyzing the differences between the WIM and static weight readings to calculate the WIM scale calibration factors. The calibration factors can be based on vehicle characteristics such as vehicle weight, vehicle class, and / or vehicle speed at the WIM scale.

[0009] The measuring devices described above, which are embedded in roads or installed in bridges, for example, serve to determine the loads on the respective roads, bridges, or other infrastructure. For this purpose, the measuring devices are calibrated at regular intervals. During calibration, traffic is slowed down at the measuring device being calibrated. Often, closures of the respective infrastructure are necessary for calibration. This leads to traffic jams and other disruptions for road users. During calibration, the measuring device is calibrated using calibration weights, either statically with stationary loads or dynamically with moving loads, in order to subsequently determine the traffic load on the infrastructure elements accurately.

[0010] During the calibration of the measuring equipment, traffic will be disrupted for a certain period of time. This leads to high costs, traffic jams, and other disruptions that must be prevented.

[0011] Therefore, the object of the present invention is to calibrate the measuring device without affecting traffic.

[0012] This problem is solved by the features of claim 1.

[0013] For this purpose, the calibration device automatically compares the reference data set, the measurement data and the position data that can be assigned to the vehicle and calibrates the measuring device using the vehicle weight as the calibration weight.

[0014] The determination of the vehicle weight used in the reference data set by the reference scale is preferably carried out independently of the calibration objective. For example, the determination of the vehicle weight by the reference scale may primarily be for reasons of traffic control, load verification, and / or toll collection.

[0015] Furthermore, the determined vehicle weight or even the complete reference data set can be provided by a third party. For example, public authorities, such as the Federal Republic of Germany or the German federal states, operate reference scales that are calibrated at regular intervals, and the reference data sets determined by these scales are made available.

[0016] Preferably, the vehicle weight is determined by a weight measurement.

[0017] According to another aspect, at least one reference scale is preferably calibrated.

[0018] The measuring device for the infrastructure arrangement can, in particular, be located directly on the infrastructure arrangement itself and / or, viewed along a flow direction of traffic, be located directly in front of or behind the infrastructure arrangement.

[0019] The calibration device can use the position data to match a range of the measurement signal that is affected by the vehicle driving over the infrastructure arrangement and / or the associated measuring device with the reference data set for the same vehicle.

[0020] The reference scale determines the vehicle's weight and transmits it to the calibration device. Using the transmitted reference data and the vehicle's position data, the calibration device can assign the determined vehicle weight, which is then used to calibrate the measuring device, to the correct vehicle.

[0021] Looking at even more detail, the calibration device uses the vehicle's position data to determine, if necessary, whether and when this vehicle is driving or has driven over the infrastructure and / or the associated measuring device. In this way, the calibration device assigns the corresponding portion of the measurement signal to the (correct) vehicle.

[0022] Ultimately, the calibration device automatically links the vehicle weight determined by the reference scale with the portion of the measurement signal affected by the same vehicle driving over the infrastructure. Based on this automatic mapping, the calibration device can compare the portion of the measurement signal, in particular at least one measurement signal peak caused by the vehicle driving over the infrastructure and / or the associated measuring device, with the corresponding vehicle weight.

[0023] This allows the measuring device to be calibrated without causing any disruption to road users, as the calibration takes place in flowing traffic. Furthermore, the calibration is performed automatically, meaning it can be carried out with little or no personnel.

[0024] Another advantage of this method is that the measuring device can be (re)calibrated repeatedly without disrupting traffic. For example, the device can be calibrated at regular intervals, such as daily, weekly, or monthly, using previously calibrated vehicles that serve as calibration weights. This allows for adjustments to environmental factors, such as weather and temperature conditions, which can affect the measuring device and consequently its data. As a result, good accuracy of the measuring device can be maintained over extended periods, regardless of weather conditions.

[0025] Preferably, the vehicle's position data is determined over time, for example by a position tracking system, and transmitted to the calibration device. This allows the system to determine when the vehicle was at a particular location or to trace its route. Consequently, it is also possible to determine when the measuring device to be calibrated or the reference scale was crossed. This facilitates the evaluation of the recorded data and enables easy calibration.

[0026] Preferably, the position data is determined continuously over time. This allows for more precise tracking of the vehicle's movements. Additionally, the position data can also be transmitted continuously.

[0027] Preferably, an identification feature of the vehicle is automatically read by a (first) identification device at the reference scale and / or the identification feature is automatically read by a (second) identification device at the measuring device.

[0028] The position data may include information regarding the reading of the identification feature at the reference scale and / or regarding the reading of the infrastructure arrangement.

[0029] In this case, the identification devices are part of the position tracking system.

[0030] According to one aspect, the position of the respective identification device is known, and in order for the vehicle's identification feature to be read by the respective identification device, the vehicle must be in the immediate vicinity of the respective identification device. Thus, the reading of the vehicle's identification feature by the respective identification device allows the conclusion that the vehicle is or was at the respective identification device at the time of the readout. Accordingly, the position of the corresponding vehicle at that time relative to the associated reference scale or infrastructure arrangement can be inferred. Information regarding the readout of the (at least one) identification feature can therefore constitute position data or be a component of position data.

[0031] The (at least one) identifying feature can include an official vehicle identifier, such as a license plate. The respective identification device can include an optical detection instrument, for example, a camera.

[0032] Alternatively or additionally, the (at least one) identification feature can include an individual transponder signal of the vehicle. The respective identification device can accordingly include a transponder reading device.

[0033] Preferably, the vehicle's position data is determined using a satellite-based positioning system, such as GPS, the Galileo system, the GLONASS system, and / or the BeiDou system. GPS (Global Positioning System) describes a satellite-based method for position detection. This method is widely used and found in a large number of vehicles. As a result, the system is easy to implement or is already present. Consequently, the system can be used cost-effectively.

[0034] Preferably, vehicle position data is determined via an on-board unit for a toll system. A toll, broadly speaking, is a road usage fee calculated based on a rate per kilometer driven, depending on the system. To monitor and verify the distance traveled, the toll system records vehicles at random or repeatedly, allowing the toll fee to be calculated based on the collected data and the vehicle's known position. Furthermore, the toll data can be used to reconstruct the route traveled, making this a cost-effective way to track the vehicle's journey and thus its position.

[0035] Preferably, the reference data set is provided with time and / or location information regarding the determination of the vehicle weight. Particularly preferably, the reference data set is provided with time and location information regarding the determination of the vehicle weight, especially when multiple reference scales and / or multiple vehicles are used for the process. This allows for retrospective reconstruction, by comparing the position data of the vehicles with the reference data sets, of which of the at least one reference scale was loaded by which vehicle at what time. Therefore, retrospective calibration can also be performed.

[0036] Preferably, the recorded measurement data are annotated with time and location information and made available to the calibration device. This allows for real-time and retrospective analysis of when and with what weight each measuring device was loaded. Furthermore, time and location information within the measurement data set or data sets facilitates easy assignment.

[0037] The measurement data, including time and location information, can be stored in the calibration device and / or an external storage device connected to the calibration device. The measurement device itself can also add time and / or location information to the measurement data. Alternatively, the calibration device can add time and / or location information to the measurement data, particularly if the data is transmitted to the calibration device in real time or near real time. The calibration device can, for example, infer the location of the measurement device from the connection information used to transmit the measurement data. This connection information could include, for example, IP addresses, telephone numbers, email addresses, signatures, or similar data.This also applies to the at least one reference data set and the corresponding reference scale.

[0038] Preferably, the calibration device assigns the vehicle weight to the vehicle based on the vehicle's position data and at least one reference data set. To do this, the vehicle's position data is used to determine when or if the vehicle passed over the reference scale and whether the reference scale created a corresponding reference data set. The reference data set can then be determined and assigned to a vehicle based on the time information of the vehicle's position data at the respective reference scale. Similarly, in a further development of the method, the vehicle weights of several vehicles are determined by the at least one reference scale and assigned to the respective vehicle based on its position data, so that each of these vehicles can subsequently be used as a calibration weight for calibrating the measuring device(s) to be calibrated.

[0039] The position data, the reference data set, and / or the measurement data are filtered before the measuring device is calibrated. Consequently, the calibration device only needs to process a portion of the data, resulting in good data processing speed. This also enables rapid calibration of the measuring device being calibrated.

[0040] In a particularly preferred embodiment, the measuring device subjects the measurement data to filtering for data reduction before transmission. For example, the transmission of the measurement data can be limited to those areas in which the measurement data indicates that the measuring device has been traversed by a vehicle exceeding a minimum weight and / or that the infrastructure is subjected to stress caused by such a vehicle. Preferably, only those areas of the measurement data are transmitted in which at least one value of the measurement signal exceeds a corresponding threshold. The transmitted area can include information from the measurement signal before and / or after the threshold has actually been exceeded. The remaining areas of the measurement signal are optionally not transmitted.

[0041] Preferably, the calibration device and / or the measuring device adjusts measurement data based on the calibration. This allows the adjusted measurement data from the measuring device to accurately determine the weight and / or load on the infrastructure structure imposed by a specific vehicle. In particular, the adjusted measurement data for vehicles whose weight is not determined by one of the at least one reference scale also allows for the determination of the respective vehicle weight and / or the load on the infrastructure structure imposed by that vehicle. This is also possible for measurement data acquired before calibration, enabling subsequent correction (adjustment) of the measurement data.

[0042] Preferably, the calibration device automatically calibrates the measuring device using reference data, position data, and measurement data for several different vehicles. Calibration using multiple, different vehicles ensures good accuracy of the measuring device. Furthermore, this allows for a comparison of the reference data sets, enabling the identification of failed measurements by the reference scale. This results in a high level of reliability and accuracy for the procedure.

[0043] Preferably, load data regarding the stress on the infrastructure is determined in the calibration unit using automated algorithms and / or machine learning methods. This load data reflects the stress on the infrastructure caused by vehicles traversing, and in particular driving over, it. In other words, the load data from the (possibly correctly calibrated) measuring device allows conclusions to be drawn about the weight and / or stress on the infrastructure caused by a particular vehicle traversing it. Furthermore, the load data enables earlier detection of potential overloads on the infrastructure, allowing for appropriate countermeasures to be taken.

[0044] Furthermore, the above-mentioned problem is solved by a system with the features of claim 12.

[0045] The system features a position detection arrangement for the automatic acquisition of position data of the vehicle.

[0046] The system also includes a calibration unit which is set up to automatically use the vehicle weight contained in the reference data set as the calibration weight for the calibration of the measuring device and, as a necessary condition, to automatically determine from the position data if the reference data set and measurement data are to be assigned to the same vehicle.

[0047] This means that, in principle, any vehicle that both crosses the reference scale (where its weight is determined) and then traverses the infrastructure and / or its associated infrastructure can be used to calibrate the measuring device. The system checks, based on the position detection system and thus the position data, whether the vehicle crossed the reference scale and then, or before, crossed the measuring device to be calibrated. This allows for a data comparison between the vehicle weight in the corresponding reference data set and the measurement data—more precisely, at least a portion of the measurement data corresponding to the same vehicle crossing the infrastructure and / or its associated measuring device.The vehicle weight from the reference data set can be used to verify whether the measurement data accurately reflects the vehicle weight determined by the reference scale and / or the load on the infrastructure expected from this vehicle weight. This verification is performed by the calibration unit, which uses the position data, at least one reference data set (or sets), and the measurement data.

[0048] This arrangement allows the vehicle weight to be determined while traffic is flowing, and the measuring device can be calibrated within the context of moving traffic. Consequently, all traffic disruptions are avoided, so that no traffic jams or similar issues arise during the calibration of the measuring device.

[0049] All features and advantages described in relation to the process apply accordingly to the system and vice versa.

[0050] In particular, the system can provide each reference data record with location information and / or time information regarding the determination of the vehicle weight. Alternatively or additionally, the measurement data can include location information regarding the respective measuring device and / or time information. For example, the measuring device can be configured to provide time-dependent measurement signals.

[0051] In general, the measurement data from the measuring device can be compared with the position data and the reference data sets for several vehicles.

[0052] The system can include multiple reference scales. Alternatively or additionally, the system can include multiple measuring devices.

[0053] According to one aspect, the following information, for example, may suffice as position data: The information that the vehicle is located at a specific reference scale at a certain first time, and the information that the vehicle has passed a specific infrastructure arrangement and / or the associated measuring device at a second time.

[0054] For example, the position detection arrangement can have a (first) identification device in the reference scale and a (second) identification device in the measuring device.

[0055] The first identification device is designed to detect when the vehicle is at the associated reference scale and to record position data. • on the one hand, the location of the associated reference scale, an identifier for the associated reference scale and / or an identification of the vehicle (for example, an official vehicle registration number) and • on the other hand, a (first) point in time when the vehicle is located at the associated reference scale, to be provided for transmission to the calibration facility.

[0056] Similarly, the second identification device is designed to recognize when the vehicle enters the infrastructure arrangement and / or associated measuring device and to record position data. • on the one hand, the location of the infrastructure arrangement or the associated measuring device, an identifier for the associated measuring device and / or the identification of the vehicle and • on the other hand, a (second) point in time when the vehicle is located at the associated infrastructure arrangement and / or associated measuring device, to be provided for transmission to the calibration facility.

[0057] If the system comprises several reference scales, a (first) identification device is particularly preferably provided on each of the reference scales. If the system comprises several measuring devices, a (second) identification device is particularly preferably provided on each of the measuring devices.

[0058] For example, a successfully calibrated measuring device can be used as a reference balance to calibrate other measuring devices. In this case, the identification device of the successfully calibrated measuring device can be considered the primary identification device. "Successfully calibrated" in this context can mean that no adjustment is necessary for the calibrated measuring device or that a correct adjustment is applied to this measuring device.

[0059] Particularly preferred are the identification devices for the automatic reading of (at least) one identification feature of the vehicle.

[0060] When the vehicle is at the reference scale and / or using the reference scale, the associated identification device automatically reads the vehicle's (at least one) identification feature. When the vehicle passes over the infrastructure arrangement or the associated measuring device, the associated identification device automatically reads the vehicle's (at least one) identification feature.

[0061] The identification devices may, for example, each include a time determination unit and a license plate recognition unit.

[0062] According to another aspect, the position detection arrangement preferably includes, either alternatively or additionally, a receiver for a satellite-based positioning system, such as a GPS receiver, a Galileo receiver, a GLONASS receiver, and / or a BeiDou receiver. In particular, the receiver can be mounted on the vehicle. The time-dependent position data determined by the receiver allows for the determination of whether and when the vehicle was (or has been) at the reference scale, as well as whether and when the vehicle was (or has been) at the measuring device. The GPS receiver enables the use of the Global Positioning System (GPS) for position detection and recording. This GPS system is already widely used, making implementation straightforward. Furthermore, the use of the GPS system is cost-effective.

[0063] According to another aspect, the position detection device is preferably configured to continuously determine the time-dependent position data for the vehicle. In particular, the position detection device can be configured to continuously determine this data, at least during the use of the vehicle (during driving operation).

[0064] Preferably, the position detection system includes an on-board unit (OBU) of the respective vehicle. This could, for example, be an on-board unit for an automated toll system, which can record the distance traveled on toll roads so that a toll can be calculated for the recorded route. Such toll systems are in use for trucks in many European Union countries, such as Germany, making this a simple method for detecting and collecting position data. Furthermore, in Germany, an on-board unit is mandatory for certain vehicles above a specific year of manufacture and weight, so the position data is already collected automatically and only needs to be transmitted to the calibration device. Consequently, no additional components or elements are required to collect the vehicle's position data.

[0065] The system incorporates a data filter for data reduction. The data consists of position data, measurement data, and / or the reference data set. For example, the reference scale may have a data filter to filter the reference data set, the measuring device may have a data filter to filter the measurement data, and / or the position sensing arrangement may have a data filter to filter the position data. Alternatively, the data filter may be located within the calibration unit. One objective of data reduction is to achieve efficient data transmission, ensuring that only the data actually used is transmitted. Irrelevant data is discarded. Furthermore, data reduction enables the calibration unit to operate quickly, resulting in faster calibration of the measuring device.

[0066] Preferably, the calibration unit includes an assignment unit for assigning the reference data set, the measurement data, and / or the position data. In particular, the assignment unit can be configured to automatically assign the reference data set for the vehicle and measurement data for the same vehicle to each other based on the position data (at least for the respective vehicle). If the same vehicle passes over several infrastructure arrangements or associated measuring devices, the assignment unit assigns (ranges of) measurement data from several measuring devices to the same reference data set accordingly. Using the assignment unit, the calibration device checks whether, and if so, for which period, the vehicle's position data matches the reference data set and / or the measurement data, so that a possible match between the vehicle's position data and a corresponding reference data set or measurement data can be inferred.

[0067] Once the mapping unit has mapped the corresponding data (position data, measurement data and reference data sets) to each other, the calibration device can calibrate the measuring device to be calibrated using the mapped data.

[0068] In particular, the allocation unit can be set up to • a correspondence of a (first) position of the specific vehicle at the first time point with a location of the reference scale and • a match of the first time point with time information of a reference data set containing a vehicle weight determined by the same reference scale, to recognize and conclude that the vehicle weight contained in this reference data set is or was the vehicle weight of this specific vehicle at the first time.

[0069] Alternatively or additionally, the allocation unit can be set up in particular to: • a correspondence between a (second) position of the specific vehicle at the second time point and a location of the measuring device and • a correlation of the second time point with time information for a specific area of ​​the measurement signal from the same measuring device, which is influenced by driving over this measuring device and / or the associated infrastructure arrangement, to recognize and conclude that this specific area of ​​the measurement signal is influenced by driving over this measuring device and / or the associated infrastructure arrangement with the specific vehicle.

[0070] Furthermore, the calibration unit can be specifically configured to calibrate and, if necessary, adjust this measuring device by comparing this specific range of the measurement signal with the vehicle weight of the specific vehicle at the first time point. Generally, the second time point can be earlier or later than the first.

[0071] In a further development of the invention, the calibration device includes plausibility criteria for assessing whether the reference data set is suitable for calibrating the measuring device based on the vehicle weight contained in this reference data set.

[0072] For example, the plausibility criteria may include one, several, or all of the following criteria: • A distance between the reference scale where the specific vehicle is located at the first time and the measuring device where the respective vehicle is located is less than a maximum distance. • A time difference between the first time point and the second time point is smaller than a maximum time difference; the maximum time difference can depend on the distance. • The position data for the specific vehicle indicate that the specific vehicle does not make a continuous stop between the first time and the second time that is longer than a maximum stop time; a longer stop may, for example, indicate a loading or unloading operation, so that the vehicle weight at the first time does not correspond to the vehicle weight at the second time.

[0073] Preferably, the measuring device to be calibrated, the reference scale, and / or the position detection device are (at least temporarily) in data communication with the calibration unit. This allows for easy data exchange. Furthermore, the data connection can be established via a third party, so that, for example, data such as measurement data or position data, and datasets such as reference datasets, can be introduced into the system externally. For instance, the reference dataset can be provided by the operator of the reference scale, while a toll operator can provide the vehicle's position data.

[0074] Preferably, the respective data connection enables automated and / or electrical, preferably digital, data transfer of the reference data set, measurement data, and position data. This automated and / or electrical data transfer eliminates the need for further manual input, allowing the system to operate automatically.

[0075] Preferably, the measuring device to be calibrated and / or the reference scale are arranged on and / or integrated into an infrastructure structure. Traffic infrastructure structures include, for example, roads, bridges, overpasses or underpasses, level crossings, or the like. Depending on the type of infrastructure structure, the measuring device can be integrated into it, as is the case with bridges. In the case of bridges, the measuring device may, for example, include strain gauges attached to load-bearing components of the bridge. Alternatively or additionally, the measuring device may include force sensors and / or pressure sensors, also called scales, which are installed in the bridge's bearings. In the case of roads as infrastructure structures, the measuring device may, for example, be designed as a scale. For this purpose, a section of the road is removed and the measuring device, in the form of the scale, is installed.Consequently, the measuring device can be adapted, positioned, or integrated according to the infrastructure layout. Similarly, the reference scale can be equipped as a force sensor, pressure sensor, and / or strain sensor. A combination of different sensors (strain sensors, force sensors, pressure sensors, or the like) can be used in a reference scale and / or measuring device. This enables a wide range of applications for the measuring device, the reference scale, and the calibration unit.

[0076] Preferably, the measuring device for acquiring environmental data includes at least one environmental sensor, for example, at least one temperature sensor and / or at least one wind sensor. The environmental data is transmitted to the calibration device. Based on the environmental data, the temperature behavior and / or structural behavior of the infrastructure can be determined and / or modeled. Environmental conditions such as temperature and wind can influence the behavior of the infrastructure, the impact of vehicle weight on the measurement data, and / or the stress on the infrastructure caused by the vehicle. For example, a crosswind causes a vehicle to have different lane loads, leading to inaccuracies in the measurement data. A strong crosswind from the left side (as viewed from the vehicle's direction of travel) can reduce the load on the left side of the roadway and increase the load on the right side.By incorporating environmental data, for example, temperature behavior and / or structural behavior can be taken into account during the calibration of the measuring device, leading to even more precise calibration. In particular, the measuring device can be tested for exceptionally high measurement accuracy, even under varying environmental conditions.

[0077] Furthermore, environmental data can be used, for example, as correction data when adjusting the measurement data. In other words, the system is ideally suited for automatically adjusting the measuring device based on the environmental data. Naturally, the system can also allow for precise adjustment of measurement data retrospectively, taking the recorded environmental data into account.

[0078] Preferably, the system includes a device for performing machine learning procedures. The calibration device is particularly preferably configured for performing machine learning procedures, for example, for comparing position data, measurement data, and reference datasets, for calibration, and / or for adjustment. Alternatively or additionally, the measuring device can be configured for performing machine learning procedures, in particular for processing and / or filtering the measurement data. The machine learning procedure enables a computer-based evaluation of the recorded loads. Furthermore, data recorded by the machine learning procedure, such as loads or weights, can be graphically processed. Consequently, a precise evaluation of the data can take place. Results of the measurements from the measuring device can, for example, be visualized after calibration or, if required, disseminated.

[0079] The procedure and system described above allows for a simple calibration method and close-meshed use of measuring devices, thus enabling comprehensive monitoring and network monitoring of infrastructure arrangements.

[0080] Preferably, the vehicle's identity is pseudonymized. This allows data and information associated with the vehicle to be processed only under a pseudonym, resulting in good data security and benefiting data privacy.

[0081] The invention is described below with reference to a preferred embodiment in conjunction with the drawing. This shows: Fig. 1 a schematic representation of the system for calibrating a measuring device; Fig. 2 A schematic representation of the system for calibrating a measuring device with multiple identification devices.

[0082] Fig. Figure 1 shows a vehicle 1 with a position detection device 2. The vehicle 1 is located on a road 3 that crosses several traffic infrastructure devices 4. A reference scale 5 is located in one infrastructure device 4, and a measuring device 6 to be calibrated is located in each of the other traffic infrastructure devices 4 that the vehicle traverses. The reference scale 5 is preferably calibrated. This makes the reference scale particularly suitable as the primary reference scale 5.

[0083] The reference scale 5, the measuring devices 6 to be calibrated, and the position detection arrangement 2 are in data communication with the calibration unit 7. The calibration unit 7, in turn, is in data communication with an output unit 8. Data connections are shown as dashed lines.

[0084] The position detection arrangement 2 can, for example, be integrated into, consist of, or comprise an on-board unit (OBU) of the vehicle 1. In particular, it can be an OBU for an automated tolling system for road traffic. The position detection arrangement 2 continuously records the positions of the vehicle 1. In this embodiment, the position detection arrangement 2 itself assigns a corresponding time information to each position of the vehicle 1. The recorded positions of the vehicle 1, together with the corresponding time information, are transmitted as position data to the calibration device 7.

[0085] The transmission of the recorded position data to the calibration device 7 preferably takes place at least in sections via mobile network. In particular, the position acquisition device 2 or OBU can send the position data via mobile network.

[0086] The measuring devices 6 include temperature and wind sensors (not shown) which record environmental data regarding wind and / or temperature at the respective infrastructure assembly 4. This environmental data can be used, for example, to determine and / or model the temperature behavior of the infrastructure assembly 4. Furthermore, the wind load on the infrastructure assembly 4 itself and / or vehicles 1 on the infrastructure assembly 4 can be taken into account based on the environmental data. For example, vehicles 1 exhibit different track loads in crosswinds. This can influence the measurement data. Such influences can be taken into account during the calibration and adjustment of the measuring device 6 using this environmental data.

[0087] In general, the transmission of position data from the position acquisition device 2 to the calibration unit 7 can be indirect. For example, the position acquisition device 2 can first transmit the position data to another data processing device, such as a server system of a toll system operator. This other data processing device can then forward the position data, or more generally, at least a portion of the position data, to the calibration device 7. For example, the toll system operator's server system may only forward the position data to the calibration device if certain conditions are met. These conditions may include, in particular, that the operator of the corresponding vehicle 1 has consented to the disclosure and evaluation of the vehicle 1's position data.

[0088] In particular, if the position sensing arrangement 2 sends the position data to the calibration device 7 or the other data processing arrangement in real time or near real time, the immediate recipient of the position data (i.e., the calibration device 7 or the other data processing arrangement) can instead annotate the position data with the associated time information, for example, the time of receipt.

[0089] The position detection arrangement 2 includes a GPS receiver, which can also be used for navigation of vehicle 1.

[0090] Reference scale 5 continuously determines the weights of vehicles 1 as they cross and pass over it. For each vehicle 1, a reference data record is generated containing the vehicle's weight and a timestamp of the measurement. In general, the weights of all passenger cars and trucks can be determined and stored. However, since the passenger car reference data records are preferably not used for calibration, they are not transmitted. Therefore, the reference data records are reduced. This reduction is achieved using a filter (not shown) that removes unnecessary reference data records. Threshold values, such as a minimum weight for vehicles 1, can be used for this purpose.Consequently, only reference data records for vehicles 1 that exceed the threshold are transmitted, or reference data records that exhibit a range around the threshold exceedance are transmitted. For example, a range from just before to just after the threshold exceedance is transmitted, so that, for instance, further circumstances and characteristics of vehicle 1 can be inferred from the slope or load curve of the reference data record. The reference data records are time-stamped, i.e., time information such as date and time, and transmitted to the calibration device 7, specifying the location of the reference scale 5.

[0091] When a vehicle 1 passes over the reference scale 5, the reference scale 5 records the vehicle's weight and timestamps it. Simultaneously, the position detection arrangement 2 records the path of vehicle 1, allowing the calibration device 7 to assign the reference data set determined by the reference scale 5 to the corresponding vehicle 1 in real time or retrospectively. A reference data set is now linked to vehicle 1.

[0092] If vehicle 1 now drives over one of the measuring devices 6 to be calibrated, the calibration device 7 detects this based on the position data. Consequently, the calibration device 7 assigns a portion of the measurement data generated by this measuring device 6 while being driven over by vehicle 1 to that specific vehicle 1. Based on this, the measuring device 6 to be calibrated can be calibrated using the previously determined vehicle weight of the same vehicle 1. The calibration device 7 uses the reference data set, the position data of vehicle 1, and the measurement data for calibration.

[0093] Using the vehicle weight from the reference data set, the calibration device 7 checks whether this range of measurement data from this measuring device 6 correctly reflects the vehicle weight determined by the reference scale 5 and / or the load on the infrastructure expected from this vehicle weight. If this is not the case, the calibration device 7 adjusts the measuring device 6, preferably based on the detected difference(s), so that the measurement data from this measuring device 6 now reflect the correct vehicle weights and / or the correct loads on the infrastructure. In this sense, the measurement data from the measuring device 6 and / or the calibration device 7 can be corrected.

[0094] The vehicle weight therefore corresponds to the calibration weight. This takes place during normal traffic flow, so a closure of infrastructure 4 is not necessary. This avoids disruptions to other road users. Since the amount of data recorded by both the reference scale 5 and the measuring device 6 to be calibrated can be relatively large, data reduction can be performed for the measurement data and / or the data from the reference scale 5. Relevant peaks or values ​​corresponding to the passage of relevant vehicles are identified. For example, an area containing the peak is selected, and the other values ​​or areas are filtered out. The area containing the peak is then transmitted to the calibration unit 7.

[0095] All generated data or parts thereof, such as vehicle weights or reference data sets, can be automatically evaluated, for example, using algorithms and / or machine learning methods. These methods can process the loads determined by the reference scale 5 and / or the measuring devices 6 and transmit them to the output unit 8. Furthermore, in certain load cases, for example, in the event of overload, appropriate warnings, such as an alarm, can be issued so that appropriate measures can be taken.

[0096] All generated data, or parts thereof, can either be stored and / or temporarily stored centrally, for example in a cloud, on a server, or on a central computer or similar system. Alternatively, this data can be transmitted directly to the measuring device 6 and / or the calibration unit 7 to be calibrated.

[0097] For example, previously recorded measurement data can be adjusted or corrected retrospectively based on calibration settings used to calibrate the measuring device 6, so that previously recorded measurement data can also be used retrospectively. This allows for a retrospective view, so that this data is not lost, but rather can be used retrospectively.

[0098] Once a measuring device 6 to be calibrated has been calibrated, it can be used as a secondary reference balance 5. The procedure for calibrating another measuring device 6 to be calibrated remains the same as described previously.

[0099] In Fig. 2 denotes the same reference symbols as in Fig. 1. The same elements as in Fig. 1 and a repetition of the associated explanations is not necessary.

[0100] The in Fig. The embodiment of the system shown in 2 differs from the one shown in Fig. The embodiment shown in 1 differs essentially in which position data are collected and in what way they are collected.

[0101] In Fig. 2. The vehicle 1 has a unique, individual identification feature 2", for example, a license plate. Identification devices 2' are arranged on the reference scale 5 and the measuring devices 6 to be calibrated, which automatically read the identification feature 2" of the vehicle 1. Whenever the vehicle 1 passes directly by one of the identification devices 2', the respective identification device 2' reads the identification feature 2" of that vehicle 1. In this example, the identification feature 2" in the form of the license plate is optically detected by the corresponding identification device 2'.

[0102] The information obtained by reading the data for the identification of vehicle 1 is provided with a location of the reading identification device 2' and / or an identifier of the reading identification device 2'. It is also time-stamped.

[0103] The data set compiled in this way is then transmitted to the calibration device 7. For this purpose, the identification devices 2' communicate with the calibration device 7, in particular for data exchange. In this embodiment, the data sets compiled in this way, which originate from the different identification devices 2', constitute the position data.

[0104] The calibration device 7 communicates with the identification devices 2', for example, via mobile network and / or another remote data transmission system. Transmission can also occur indirectly via one or more intermediate data processing systems, for example, via the cloud and / or the server.

[0105] Vehicle 1 is identified by its identification feature 2". The information obtained through reading this feature can be, for example, a photograph of the license plate, a processed photograph of the license plate, or a designation or identification of the corresponding vehicle obtained from an evaluation of the license plate. The evaluation of the photograph can be performed by the identification device 2' or by the calibration device 7. It is also possible for the evaluation to be performed partly by the identification device 2' and partly by the calibration device 7.

[0106] The calibration device 7 automatically compares the position data and automatically recognizes, based on the position data, when a reference data set and a range of measurement data belong to the same vehicle 1. Accordingly, the measuring devices 6 are automatically calibrated by the calibration device 7 as described above and, if necessary, also automatically adjusted. Reference symbol list 1 vehicle 2 Position detection arrangement 2' Identification device 2'' Identification feature 3rd Street 4. Transport infrastructure order 5 Reference scale 6 Measuring device 7 Calibration unit 8 output units

Claims

[1] Method for calibrating a measuring device (6) to be calibrated, which serves to determine a load on an infrastructure arrangement (4), wherein the measuring device (6) acquires measurement data and is calibrated by means of a calibration device (7) using at least one calibration weight, comprising the determination of at least one reference data set, wherein the reference data set includes a vehicle weight of a vehicle (1) which is determined by a reference scale (5), wherein the calibration device (7) automatically compares the reference data set, the measurement data and position data attributable to the vehicle (1) and calibrates the measuring device (6) using the vehicle weight as the calibration weight, characterized by, that the position data, the reference data set and / or the measurement data are filtered for data reduction at the latest before the calibration of the measuring device (6), and that the recorded measurement data are provided with time and location information by the calibration device (7), wherein the calibration device (7) generates the location information from a connection information, and wherein the transmission of the measurement data to the calibration device (7) takes place in real time. [2] Method according to claim 1, characterized by , that the position data of the vehicle (1) are determined, preferably continuously, as a function of time by a position detection arrangement (2, 2') and are transmitted to the calibration device (7). [3] Method according to claim 1 or 2, characterized byautomatic reading of an identification feature (2") of the vehicle (1) by a first identification device (2') at the reference scale (5) and automatic reading of the identification feature (2") by a second identification device (2') at the measuring device (6), wherein the position data includes information regarding the reading of the identification feature (2") at the reference scale (5) as well as regarding the reading at the infrastructure arrangement (4). [4] Method according to any one of claims 1 to 3, characterized by , that the position data of the vehicle (1) are determined using a satellite-based positioning system. [5] Method according to any one of claims 1 to 4, characterized by , that the position data of the vehicle (1) are determined via an on-board unit of the vehicle (1) for a toll system. [6] Method according to any one of claims 1 to 5, characterized by, that the reference data set is provided with time and location information regarding the determination of the vehicle weight. [7] Method according to any one of claims 1 to 6, characterized by , that the calibration device (7) assigns the vehicle weight to the vehicle (1) based on the position data of the vehicle (1) and the reference data set. [8] Method according to any one of claims 1 to 7, characterized by , that the calibration device (7) and / or the measuring device (6) adjusts measurement data based on the calibration. [9] Method according to any one of claims 1 to 8, characterized by , that the calibration device (7) automatically calibrates the measuring device (6) using the reference data set, position data and measurement data for several different vehicles (1). [10] Method according to any one of claims 1 to 9, characterized by , that a calibrated and, if necessary, adjusted measuring device (6) is used as a reference balance. [11] Method according to any one of claims 1 to 10, characterized by , that load data relating to the load on the infrastructure arrangement (4) are determined by automated algorithms and / or machine learning methods in the calibration facility (7). [12] System for calibrating a measuring device (6) which is set up to provide measurement data for determining loads on an infrastructure arrangement (4), wherein the system includes a reference scale (5) and is set up to determine at least one reference data set, wherein the reference data set includes a vehicle weight of a vehicle (1) determined by means of the reference scale (5), wherein the system comprises a position detection arrangement (2, 2') for the automatic acquisition of time-dependent position data of the vehicle (1), and that the system has a calibration device (7) which is configured to automatically use the vehicle weight contained in the reference data set as the calibration weight for the calibration of the measuring device (6) and, as a necessary condition for this, to automatically determine from the position data if the reference data set and measurement data are to be assigned to the same vehicle (1), characterized by , that the system has at least one data filter for data reduction, and that the calibration device (7) is configured to provide the recorded measurement data with time and location information, wherein the calibration device (7) is configured to generate the location information from a connection information, and wherein the measuring device (6) and the calibration device (7) are configured to transmit the measurement data to the calibration device (7) in real time. [13] System according to claim 12, characterized by, that the position detection arrangement (2) includes a receiver for a satellite-based positioning system. [14] System according to claim 12 or 13, characterized by , that the position detection arrangement (2) includes an on-board unit of the vehicle (1) for a toll system. [15] System according to any one of claims 12 to 14, characterized by , that the position detection arrangement at the reference scale (5) has a first identification device (2') and at the measuring device (6) has a second identification device (2'), wherein the identification devices (2') are configured to automatically read an identification feature (2") of the vehicle (1). [16] System according to any one of claims 12 to 15, characterized by, that the calibration device (7) has an assignment unit which is configured to automatically assign the reference data set for the vehicle (1) and measurement data for the same vehicle (1) to each other on the basis of the position data. [17] System according to any one of claims 12 to 16, characterized by , that the measuring device (6) to be calibrated, the reference balance (5) and / or the position detection device (2, 2') are in data communication with the calibration device (7). [18] System according to any one of claims 12 to 17, characterized by that the measuring device (6) to be calibrated and / or the reference scale (5) are arranged on a traffic infrastructure arrangement (4) and / or are integrated into a traffic infrastructure arrangement (4). [19] System according to any one of claims 12 to 17, characterized by that the system has a facility for performing machine learning procedures.

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