Driver information system for two-wheelers

Abstract

Driver assistance system for a two-wheeler; wherein the system comprises the following: a data source (5) that provides map data for an electronic map; a position sensor (4) that provides a position of the two-wheeler; a first sensor (3) that provides data representing a current value of a first dynamic parameter that characterizes the state of the two-wheeler; a second sensor (7) that provides data representing a current value of a second dynamic parameter that characterizes the state of the two-wheeler; a processor unit (9) connected to the first sensor (3), the data source (5) and the position sensor (4) and configured to calculate a critical value of the first dynamic parameter for a given curve; and a display device (15) connected to the processor unit (9), wherein the display device (15) displays information to the driver based on the current value and the calculated critical value of the first dynamic parameter; wherein the processor unit (9) is configured to calculate an estimated value of the second dynamic parameter for a given curve based on the first dynamic parameter and at least one static parameter, wherein the processor unit (9) is configured to calibrate the at least one static parameter based on the current value and the estimated value of the second dynamic parameter for a specific curve, and wherein the display device (15) displays information to the driver based on the estimated value and a critical value of the second dynamic parameter.

Description

TECHNICAL AREA

[0001] The present disclosure relates to the field of driver information systems and driver assistance systems, in particular a driver assistance system for two-wheeled vehicles, such as motorcycles. GENERAL STATE OF THE ART

[0002] Various types of driver information systems and so-called "driver assistance systems" (DAS) are known. These systems are designed to support the driver during the driving process. As such, driver assistance or driver information systems can be used to control vehicle functions or to automatically provide information and warnings to the driver. Typical driver assistance systems include, for example, navigation systems, adaptive cruise control, intelligent speed assistance, lane keeping assist, etc.

[0003] In cars, driver assistance systems can warn the driver, for example, if they are about to enter a curve at excessive speed. Such a system uses information about the car's current speed and the radius or curvature of a curve directly ahead to assess the risk of the maneuver. Based on this information (and the known characteristics of the car), the driver assistance system can calculate the expected lateral forces (centrifugal forces) and lateral acceleration while driving through the upcoming curve. Driving through the curve is deemed unsafe if the expected lateral forces exceed the frictional forces between the road and the car's tires, which can be estimated based on the road condition (icy, wet, or dry) and the type of tires fitted to the car.Naturally, a safety factor is taken into account in such an assessment. If the driver assistance system determines that the current speed is unsafe for an upcoming curve, a warning can be automatically issued to the driver. Alternatively or additionally, the car can be automatically braked until a safe speed is reached well in advance of the curve. In this way, accidents can be prevented or at least the risk of accidents can be reduced.

[0004] The situation is more complex for two-wheeled vehicles, such as motorcycles. The maximum safe speed depends not only on the expected lateral and frictional forces when negotiating a particular curve. The fact that two-wheeled vehicles assume a leaning position when cornering must also be taken into account. The maximum lean angle is therefore determined by physical and psychological factors and is defined as the angle of lean that should not be exceeded while negotiating a specific curve.

[0005] Especially for inexperienced motorcyclists, an automatic maximum speed recommendation before entering a curve can be crucial information to avoid leaning into a curve that could be dangerous or uncomfortable. This information can also be useful for experienced motorcyclists when riding at the limits of their capabilities.

[0006] Publication DE 10 2012 201 802 A1 discloses a driver assistance system for a two-wheeler that determines a limit value for the maximum lean angle to be assumed by the two-wheeler when negotiating a curve, for example, taking into account the structural geometry of the two-wheeler or based on an observation of rider-specific riding behavior. From the current speed of the two-wheeler, determined by a speed sensor, and from information about the curve ahead, obtained from a data source, the driver assistance system can estimate the lean angle the two-wheeler will assume in the upcoming curve. A signaling device can warn the rider if the predicted lean angle exceeds a physically critical lean angle or a lean angle subjectively perceived as uncomfortable by the rider.Alternatively, the driver assistance system can actively intervene in the handling of the two-wheeler via a control unit. Publication DE 10 2013 200 435 A1 discloses a method for assisting the rider of a two-wheeler when approaching curves, in which a navigation system is used to determine the topology of a curve located ahead of the two-wheeler in the direction of travel, a suitable trajectory for safely negotiating the curve is determined, the position of the two-wheeler within its own lane is determined, and the rider is informed via information means in which direction to steer the two-wheeler to achieve the determined trajectory. Publication US 2014 / 0189937 A1 relates to a helmet with a multitude of electronic components. Publication DE 10 2010 027768 A1 discloses a method for displaying a curve profile on a display device. SUMMARY

[0007] This document describes a driver assistance system for a two-wheeled vehicle. The driver assistance system is used when driving along a route. According to an example of the invention, the system comprises a data source providing map data from an electronic map, a position sensor providing the position of the two-wheeler, a first sensor providing data representing the current value of a first dynamic parameter characterizing the state of the two-wheeler, and a second sensor providing data representing the current value of a second dynamic parameter characterizing the state of the two-wheeler. The system further comprises a processor unit connected to the first sensor, the data source, and the position sensor, and configured to calculate a critical value of the first dynamic parameter for a specific curve on the route.A display unit is connected to the processor unit to show information to the driver based on the current value and the calculated critical value of the first dynamic parameter. The processor unit is configured to calculate an estimated value of the second dynamic parameter for a given curve based on the first dynamic parameter and at least one static parameter, and to calibrate the at least one static parameter based on the current value and the estimated value of the second dynamic parameter for a specific curve. The display unit then shows information to the driver based on the estimated value and a critical value of the second dynamic parameter.

[0008] Furthermore, a method for operating a driver assistance system for a two-wheeler is described. According to an example of the invention, the method comprises providing map data from an electronic map and providing, using a position sensor, the position of the two-wheeler. Using a first sensor, data is provided that represents a current value of a first dynamic parameter, which characterizes the state of the two-wheeler. Using a second sensor, data is provided that represents a current value of a second dynamic parameter, which characterizes the state of the two-wheeler. The method further comprises calculating a critical value of the first dynamic parameter for a specific curve and displaying information to the rider based on the current value and the calculated critical value of the first dynamic parameter.Furthermore, an estimated value of the second dynamic parameter for a given curve is calculated based on the first dynamic parameter and at least one static parameter, and the at least one static parameter is calibrated based on the current value and the estimated value of the second dynamic parameter for a specific curve. The procedure also includes displaying information to the driver based on the estimated value and a critical value of the second dynamic parameter. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The invention is more easily understood with reference to the following description and the drawings. The components in the illustrations are not necessarily to scale; instead, the focus is on illustrating the principles of the invention. Furthermore, identical reference symbols in the drawings denote corresponding components. The drawings show: Fig. 1 an embodiment of a driver assistance system. Fig. 2 an exemplary helmet which includes a field of view display used by the driver assistance system. Fig. 3. The driver's view through the field of vision display; and Fig. 4 a flowchart illustrating an exemplary procedure for operating a driver assistance system of a two-wheeler. DETAILED DESCRIPTION

[0010] Fig. Figure 1 shows a driver assistance system according to one embodiment, illustrated in a block diagram. The driver assistance system 1 includes a processor 9, which can be any conventional signal processor, a microcontroller, a central processing unit of an integrated computer, etc. Several peripheral units are connected to the processor 9. The speed sensor 3 provides information about the current speed of a motorcycle. For example, the speed sensor 3 could be the motorcycle's speedometer. However, any type of sensor can be used to obtain the speed information, such as a GPS sensor 4, which provides speed information in addition to the data about the absolute position. Furthermore, the data source 5, which provides map data, is connected to the processor 9.Data source 5 provides information about the current route and therefore upcoming curves. Data source 5 can include a map database from a navigation system. Data source 5 can also be connected to a wireless mobile communication interface (e.g., according to the UMTS standard) to receive map data (and therefore information about upcoming curves) via a wireless connection to a mobile communication network. For example, the map data can be accessed via online services such as Google Maps. Furthermore, the data source can be connected to the GPS sensor 4, which provides current position data. This current position data can be used to extract the desired information from the map data. In particular, the current position can be used to identify a specific curve on the current route.

[0011] The rider assistance system also includes the tilt sensor 7, which is connected to the processor 9 and configured to provide measured data representing the motorcycle's current lean angle. As mentioned above, the information provided by the (map) data source 5, along with parameters representing the motorcycle's characteristics (including static and dynamic parameters), can be used to calculate the motorcycle's critical speed, which should not be exceeded to safely navigate the curve. Furthermore, a critical lean angle can be calculated based on this information. Additionally, the information provided by the speed sensor 3 and tilt sensor 7 can be used to assess whether the motorcycle's actual speed and lean angle are below their respective critical values.Current travel speed and inclination are examples of dynamic parameters that characterize the state of the two-wheeler and are continuously measured or can be calculated based on measured data. Other examples of dynamic parameters include shock absorber displacement and road surface conditions (dry, wet, icy, gravelly, etc.). In contrast, static parameters characterize the two-wheeler itself. Static parameters are therefore usually constant for a specific two-wheeler (and do not change significantly during travel); they include weight (excluding the rider), center of gravity (excluding the rider), and so on. The static parameters can be stored in memory 11, which is connected to or contained within processor 9.The aforementioned dynamic parameters can also be stored in memory 11 and updated regularly (either at fixed time intervals or periodically in response to specific events). Furthermore, the difference between the current speed and the critical value (i.e., the speed control margin) and the difference between the current inclination and the critical inclination (i.e., the inclination control margin) can be calculated. Therefore, the inclination while driving through an upcoming curve can be estimated (predicted) based on at least some of the aforementioned dynamic parameters (especially the current speed) and static parameters (especially the weight and the position of the center of gravity). The aforementioned inclination control margin is the difference between the critical inclination and the estimated inclination for a specific curve.These calculations and the aforementioned assessment can be implemented by software running on processor 9. However, parts of the described functionality can also be implemented using dedicated hardware or electronic components.

[0012] Furthermore, sensor data (dynamic parameters) can be used to calculate critical speed and inclination values. For example, an accelerometer can be used to measure lateral acceleration in a curve. The road condition sensor 6 (which may include, for example, a rain sensor, temperature sensor, etc.) can be used to obtain information about the road condition (icy, wet, dry, etc.). In particular, on wet roads, the frictional forces between the tires and the road are lower than on dry roads. Since it is relevant to the grip between the tires and the road, the road condition is also considered a dynamic parameter that characterizes the condition of the motorcycle. Camera 8 and an image processor can be used to obtain further information about the road the motorcycle will travel on. The processor 9 can also be configured to (e.g.,The processor can store measured data (e.g., lateral acceleration, speed, and tilt) for specific curves (or curves with a specific radius) in memory 11 and use such "historical data" to estimate the aforementioned critical speed and tilt values ​​for an upcoming curve. Furthermore, the processor can calculate statistical data (e.g., average and variance) from sensor data actually measured while driving through a curve and can use the statistical information (e.g., average lateral acceleration for a specific radius and speed) to calculate the aforementioned critical values. The processor 9 can also assess the motorcycle's current speed and / or tilt (estimated for an upcoming curve) relative to the calculated critical values ​​and assign a risk level (e.g.,(on a scale of 0 to 10 or “low”, “medium”, “high”, etc.) depending, for example, on how close the current speed is to the calculated critical value and / or on how close the expected gradient (in the upcoming curve) is to the calculated critical value.

[0013] Historical data (from measured and / or calculated dynamic parameters) can be stored for a specific curve. This historical data can be statistically evaluated; for example, an average slope can be calculated for a specific travel speed and curve radius. The historical data (and / or statistical information, such as derived averages) can be used to (re)calibrate static parameters that are typically constant (before and after calibration). To provide an example, it is assumed that, given a set of static parameters, processor 9 overestimates the expected slope for a specific speed and curve radius.The estimated inclination, calculated for a specific speed and curve radius, and the corresponding inclination actually measured while driving through the curve, can then be used to adjust (calibrate) the static parameters so that the estimated and actual inclinations for the next curve are more in agreement. That is, the discrepancy between estimated and actual values ​​is reduced (ideally to zero). Various methods for adjusting or calibrating (at least some) of the static parameters are known and are therefore not described in detail here. For example, Kalman filters can be used for this purpose.

[0014] Furthermore, the input interface 13 can be connected to the processor 9. The input interface can be, for example, a touchscreen, a keyboard, or any other suitable device with which a user can input data into the processor 9. The input interface 13 can generally be used to control the operation of the driver assistance system. For example, the user can input data to influence the aforementioned critical values ​​for speed and inclination. To this end, the user can, for example, set a safety factor (a safety margin) to be taken into account when calculating the critical value. If the user selects a safety margin of 30 percent, for example, the critical values ​​actually used by the system will be reduced by 30 percent compared to the theoretical values ​​obtained through the original calculation.Furthermore, the input interface 13 can be used to control the map data source 5 (e.g. to set a desired route) or to control other functions of the driver assistance system.

[0015] The processor 9 can be connected to an output interface 15, which may be a display, such as a gaze display, that could be integrated into a motorcycle helmet or eyeglasses. Eyeglasses with gaze displays are widely known and have been marketed, for example, as Google Glass. ® and Epson Moverio ®Multimedia glasses are marketed. These eye-tracking displays allow the results of the calculations and assessments performed by Processor 9 to be shown to the motorcycle rider. For example, the risk level assigned by the processor to the current speed can be displayed to the rider via the eye-tracking display by showing a colored symbol. For example, a green symbol could indicate a low risk level, a yellow symbol a medium risk level, and a red symbol a high risk level, indicating that the rider should brake (speed alert). However, a separate symbol can also be displayed to the rider indicating that the current speed is too high to safely navigate the upcoming curve and that braking is necessary.Color coding can also be used, for example, in conjunction with the speed alarm. A yellow symbol could indicate a recommendation to reduce speed slightly, while a red symbol could indicate a recommendation to brake and significantly reduce speed. Of course, color coding is only one option. Additionally or alternatively, the shapes of the symbols or pictograms can be changed to indicate different risk levels or speed alarms. The processor 9 can also be configured to instruct the automatic cruise control system 17 to slow down.

[0016] As mentioned, the field of view indicator 15 can be included in the motorcycle helmet 20. As in Fig. As shown in Figure 2, the helmet 20 includes a visor 21 and a field-of-view projector 22 configured to project the display onto the visor. The setup is essentially the same for field-of-view displays integrated into eyeglasses. Fig. Figure 3 shows the rider's view through the visor 21 of the helmet 20. The rider can see the front section of the motorcycle, as well as the surrounding landscape, the road, and the horizon 40, through the visor. Other visible objects can be generated in the rider's field of vision by the viewfinder (the projector 22 projects the display onto the visor 21). For example, different colored indicator lights 41, 42, and 43 (symbols) can be generated in the rider's field of vision by the viewfinder. In this example, a green symbol 41 indicates a low risk level for the current speed and a particular upcoming curve, a yellow symbol 42 indicates a medium risk level, and a red symbol 43 indicates a high risk level, suggesting to the rider that slowing down is recommended before entering the upcoming curve. Furthermore, the viewfinder shows Fig. 3 As an illustrative example, the virtual bar chart display 44, which is generated in the driver's field of vision by the projector 22, can provide the driver with an indication of the speed control reserve with regard to the critical speed calculated by the processor 9 for a specific upcoming curve.

[0017] As also in Fig. As shown in Figure 3, the virtual horizon line 45 is inclined relative to the actual horizon. The inclination angle of the virtual horizon line 45 corresponds to the expected (calculated by processor 9) lean of the motorcycle as it travels through the corresponding upcoming curve. During optimal cornering, the virtual horizon line and the actual horizon line are congruent or parallel. If a camera (see camera 8 in Figure 3) is used, the virtual horizon line will be aligned with the actual horizon line. Fig. 1) and image processing, additional graphical symbols can be generated in the rider's field of vision to improve guidance. For example, the ideal line 47 for a specific curve can be calculated by the processor 9 and displayed through the viewfinder as if projected onto the road. For this purpose, the camera must regularly capture images of the road ahead and detect the lane markings (e.g., the center line and shoulder or the edge of the road). The camera can be mounted on the helmet 20 or on the motorcycle. If the calculated (estimated) ideal line remains on the road (or on the right-hand lane of the road), the line can be displayed in green, for example. Otherwise, if the calculated ideal line leaves the road due to excessive speed (for the current road conditions), the ideal line would be displayed in a different color (or flashing).This means that the color coding can be used to alert the driver. In the present illustration, the unsafe ideal line 48 is shown as a dashed line, and the sides of the road are indicated by dotted lines.

[0018] The driver assistance system described herein can be integrated into a motorcycle, with processor 9 being the central processing unit of an onboard computer. Data source 5 (see Fig. 1) can be part of an on-board navigation system. The speed sensor 3 can be the same sensor that generates the signal for the motorcycle's speedometer. Alternatively, the present rider assistance program can be implemented in a mobile device, such as a mobile phone or tablet PC, using associated software, which may be provided as an app run by the mobile device. In this case, the processor 9 would be the central processing unit of the mobile device. The mobile device can also have an integrated mobile navigation system that displays the map data (see Fig. 1, data source 5) and provides the motorcycle's position on the map via an integrated GPS sensor 4. The map data can be stored on the mobile device or retrieved via a wireless connection, such as one operating according to the UMTS or LTE standard. Even the tilt sensor 7 can be integrated into the mobile device if the mobile device is equipped with a gyroscope integrated into a semiconductor chip. The current speed can also be determined using the onboard GPS sensor. The input interface 13 can be implemented using the mobile device's touchscreen. Furthermore, the mobile device can communicate with the output interface 15 (the viewfinder display) via a radio connection such as Bluetooth (IEEE 802.15.1) or wireless LAN (IEEE 802.11).Similarly, the mobile device can be connected to the vehicle's onboard computer via a cable or other wireless connection, and components of the driver assistance system can be distributed between the mobile device and the motorcycle. Camera 8 can also be connected to the mobile device or an onboard computer using a wireless connection, for example, according to a standard of the IEEE 802.11 family.

[0019] Fig. 4 is a flowchart illustrating an exemplary procedure for operating a driver assistance system, such as the one in Fig. The system shown in Figure 1 is shown. Accordingly, the method includes providing map data from an electronic map (step 51), e.g., using map data source 5, as in the embodiment shown in Figure 1. Fig. 1 shown. The method further includes providing a position of the two-wheeler (step 52), e.g. using the GPS sensor 4, also in the embodiment shown. Fig. Figure 1 illustrates this. Furthermore (step 53), the procedure involves providing data representing a current value of a first dynamic parameter that characterizes the state of the two-wheeler. The first dynamic parameter can be, for example, the speed or the inclination of the two-wheeler, which can be measured, for example, by the speed sensor 3 or the inclination sensor 7 (see Figure 1). Fig. 1) can be measured. Furthermore, the procedure also includes calculating a critical value of the first dynamic parameter (e.g., a critical speed or critical slope value) for a specific curve (step 54) and displaying it based on the current value and the calculated critical value of the first dynamic parameter (step 55). As mentioned above, the specific curve can be identified based on the map data and the measured position.

[0020] The procedure can be executed and / or controlled at least partially using a processor that executes software instructions, such as the central processing unit 9, which in the example consists of Fig. Figure 1 illustrates this. In one embodiment, the method involves providing, for example, using a second sensor, data representing the current value of a second dynamic parameter that characterizes the state of the two-wheeler. In this case, an estimated value of the second dynamic parameter is calculated for a given curve, and the information displayed to the rider is based on this estimated value and a critical value of the second dynamic parameter. In this example, the first dynamic parameter can be the speed of the two-wheeler, and the second dynamic parameter can be the inclination of the two-wheeler. Accordingly, the first sensor is a speed sensor such as speed sensor 3, and the second sensor is an inclination sensor such as inclination sensor 7, as shown in the embodiment in Figure 1. Fig. Figure 1 shows that the estimated value of the second dynamic parameter (e.g., the estimated inclination value) is calculated based on the first dynamic parameter (e.g., the current speed) and at least one static parameter (e.g., the weight of the two-wheeler including the rider). Several examples of static parameters have already been shown in connection with Fig. 1 described.

[0021] According to one exemplary embodiment, the static parameters can be calibrated based on the current value and the estimated value of the second dynamic parameter for a specific curve (e.g., the weight of the two-wheeler including the rider). This means, for example, that the static parameters used to calculate an estimated incline (predicted incline value) for a particular curve can be adjusted so that the predicted values ​​correspond to the values ​​actually measured for that specific curve. Additionally, the estimated value of the second dynamic parameter (e.g., the estimated / predicted incline) can be calculated based on values ​​of the first and / or second parameter that have been measured or calculated for a multitude of curves. That is, measured and calculated data for a particular curve can be used to make corresponding estimates for another curve (e.g., a different curve).to calculate (has a different radius).

[0022] Additionally or alternatively, the procedure can include calculating an ideal line for riding through a specific curve, based on (at least) the current value of the first parameter (e.g., the motorcycle's cruising speed). If the display used to provide information to the rider is a field-of-view display, the ideal line can be shown as if projected onto the road. Furthermore, the ideal line can be color-coded to indicate whether riding along it is safe or not (see also...). Fig. 3) Additionally or alternatively, the display can be used to show a virtual horizon that is inclined according to the estimated (predicted) or currently measured value of the inclination of the two-wheeler.

[0023] As mentioned above, the procedure can be carried out as described in Fig. Figure 4 additionally includes assigning a risk level to the current speed of the two-wheeler depending on the current and critical values ​​of the first and / or second dynamic parameter. The risk level can be communicated to the rider visually (e.g., using the display device) or audibly.

[0024] Although various embodiments of the invention have been described, it is apparent to those skilled in the art that many other embodiments and implementations are possible within the scope of the invention. Accordingly, the invention is not to be limited, except in consideration of the pending claims and their correspondences. With regard to the various functions performed by the components or structures (arrangements, devices, circuits, systems, etc.) described above, the designations (including a reference to a "means") used to describe such components shall correspond, unless otherwise specified, to each component or structure that performs the specific function of the component described (i.e.,(which is functionally equivalent), even if it is not structurally equivalent to the disclosed structure that performs the function in the exemplary implementations of the invention presented herein. Furthermore, it should be noted that features described with reference to a specific figure can be combined with features of other figures, even where this is not expressly stated.

[0025] In view of the aforementioned series of variations and applications, it is understood that the present invention is not limited by the preceding description or by the accompanying drawings. Instead, the present invention is limited only by the following claims and their legal equivalents.

Claims

[1] Driver assistance system for a two-wheeler; wherein the system comprises: a data source (5) that provides map data for an electronic map; a position sensor (4) that provides a position of the two-wheeler; a first sensor (3) that provides data representing a current value of a first dynamic parameter that characterizes the state of the two-wheeler; a second sensor (7) that provides data representing a current value of a second dynamic parameter that characterizes the state of the two-wheeler; a processor unit (9) connected to the first sensor (3), the data source (5) and the position sensor (4) and configured to calculate a critical value of the first dynamic parameter for a given curve; and a display device (15) connected to the processor unit (9), wherein the display device (15) displays information to the driver based on the current value and the calculated critical value of the first dynamic parameter; wherein the processor unit (9) is configured to calculate an estimated value of the second dynamic parameter for a given curve based on the first dynamic parameter and at least one static parameter, wherein the processor unit (9) is configured to calibrate the at least one static parameter based on the current value and the estimated value of the second dynamic parameter for a specific curve, and wherein the display device (15) displays information to the driver based on the estimated value and a critical value of the second dynamic parameter. [2] Driver assistance system according to claim 1, wherein the second sensor is an inclination sensor (7) and the second dynamic parameter is an inclination of the two-wheeler. [3] Driver assistance system according to claim 1 or 2, wherein the estimated value of the second dynamic parameter is calculated depending on values ​​of the first and / or second parameter which have been measured or calculated for a plurality of curves. [4] Driver assistance system according to one of claims 1 to 3, wherein the first sensor is a speed sensor (3) and the first dynamic parameter is a travel speed of the two-wheeler. [5] Driver assistance system according to one of claims 1 to 4, wherein the critical value of the first dynamic parameter is a parameter that should not be exceeded in order to safely traverse the curve. [6] Driver assistance system according to any one of claims 1 to 5, wherein the display device (15) is a transparent field-of-view display; wherein the processor unit (9) is configured to calculate an ideal line (47, 48) for driving through a specific curve based on at least the current value of the first parameter; and wherein the display device (15) is configured to display the ideal line (47, 48) in such a way that it appears as if projected onto the road. [7] Driver assistance system according to claim 6, wherein the ideal line (47, 48) is color-coded to indicate whether driving along the ideal line (47, 48) is safe. [8] Driver assistance system according to any one of claims 1 to 7, wherein the display device (15) is configured to display a virtual horizon line inclined according to an estimated or actual value of an inclination of the two-wheeler. [9] Driver assistance system according to one of claims 1 to 8, wherein the processor unit (9) is configured to assign a risk level to a current speed of the two-wheeler depending on the current and critical values ​​of the first and / or second dynamic parameter. [10] Driver assistance system according to one of claims 1 to 9, wherein the processor unit (9), the data source (5) and the position sensor (4) are contained in a mobile device. [11] Driver assistance system according to claim 10, wherein the mobile device is connected to an on-board computer of the two-wheeler via a cable or a wireless connection. [12] Method for operating a driver assistance system of a two-wheeler; the method comprising: Providing (51) map data (5) of an electronic map; Providing (52) a position of the two-wheeler using a position sensor (4); Providing (53), using a first sensor (3), data representing a current value of a first dynamic parameter that characterizes the state of the two-wheeler; Providing, using a second sensor (7), data representing a current value of a second dynamic parameter that characterizes the state of the two-wheeler; Calculating (54) a critical value of the first dynamic parameter for a given curve; Calculating an estimated value of the second dynamic parameter for a given curve based on the first dynamic parameter and at least one static parameter; Calibrating at least one static parameter based on the current value and the estimated value of the second dynamic parameter for a specific curve; Display (55) information to the driver based on the current value and the calculated critical value of the first dynamic parameter; and Displaying information to the driver based on the estimated value and a critical value of the second dynamic parameter.

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