Method and assistance system for informing a driver when cornering a vehicle on a road curve

Abstract

The present invention relates to a method for informing a driver when cornering a vehicle (300) on a road curve (302), wherein a warning is provided to the driver via a human-machine interface of the vehicle (300) if a determined warning level (400) for cornering is greater than a predefined threshold, the warning level (400) being continuously updated from at least a starting point of a warning region in the road curve (302) to a target point (304) in the road curve (302).

Description

[0001] Description

[0002] title

[0003] Method and assistance system for informing a driver when a vehicle is cornering through a road curve

[0004] Field of invention

[0005] The invention relates to a method for informing a driver when a vehicle is driving through a curve in the road, a corresponding assistance system and a corresponding computer program product.

[0006] State of the art

[0007] A vehicle may have an assistance system that warns the driver if they approach an upcoming curve at an inappropriate speed.

[0008] DE 10 2014 225 625 A1 describes a method for assisting a driver of a single-track motor vehicle to safely navigate a curve.

[0009] Disclosure of the invention

[0010] Against this background, the approach presented here comprises a method for informing a driver when a vehicle is cornering through a road curve, a corresponding assistance system, and a corresponding computer program product according to the independent claims. Advantageous further developments and improvements of the approach presented here result from the description and are described in the dependent claims.

[0011] Advantages of the invention: In the approach presented here, a driver is warned if they are still traveling too fast shortly before a critical point in a curve. For this purpose, the vehicle's speed is continuously evaluated in relation to a target speed at the point and the distance to that point, and a warning level is determined. The driver then receives a warning if the warning level is higher than a preset value.

[0012] The preset value can be selected by the driver, for example. This allows the driver to determine at which warning level they want to be warned.

[0013] The approach presented here allows the driver to be informed or warned if he enters a curve at too high a speed.

[0014] A method is proposed for informing a driver when a vehicle is cornering through a road curve, wherein a warning is individually provided to the driver via a human-machine interface of the vehicle when a determined warning level for cornering is greater than a predefined threshold, wherein the warning level is continuously updated at least from the beginning of a warning area of ​​the road curve to a target point of the road curve.

[0015] Ideas for embodiments of the present invention can be considered to be based, among other things, on the thoughts and findings described below.

[0016] A warning via a human-machine interface can be issued visually, haptically, and / or audibly. For example, a warning light can illuminate in a driver's field of vision, a control element can vibrate, and / or a sound can be played through a speaker.

[0017] A warning level can classify a vehicle's speed relative to a distance from a target point on a road curve, where the vehicle is expected to reach a predetermined speed. The target point could be, for example, the apex of the curve. The warning level can be continuously determined using the vehicle's position relative to the target point and its current speed. When the determined warning level exceeds a certain threshold, the warning is issued.

[0018] If the warning level falls below the threshold, the warning can be ended. If the warning level remains above the threshold, the warning can remain in effect.

[0019] The predetermined target speed can be extracted from real-world driving dynamics data. In particular, numerous driving dynamics data points from the same road curve can be evaluated, and a target speed can be extracted using statistical methods.

[0020] A warning zone and the target point can also be determined from the actual driving dynamics data. Alternatively, the warning zone can be taken from a map. The warning zone can begin far enough before the road curve to give the driver sufficient time to react to the warning.

[0021] The warning level and / or warning range can be determined and / or provided individually for each driver currently using the vehicle, i.e., based on driver characteristics and / or observations of the driver's driving behavior. This data can, for example, be gradually learned by a system.

[0022] Furthermore, information reflecting the currently determined warning level can be provided via the vehicle's human-machine interface if the driver has activated an information mode. In information mode, the warning level can also be communicated below the threshold. The information can be provided with a lower intensity than the warning itself. The information can be displayed visually, for example, via a variable display on the vehicle. The information can be provided via the same human-machine interface or via a different human-machine interface on the vehicle. Information about the selected mode can also be provided. For example, the information can be provided as long as the vehicle is within the predefined warning zone of the road curve.

[0023] A further warning level for a subsequent curve can be determined if a warning zone of the subsequent curve overlaps the warning zone of the current curve. The warning can be provided if at least one of the warning levels is higher than the threshold. Two or more curves may follow each other in quick succession. If the curves become tighter from one to the next, the speed appropriate for the current curve may be too high for the next one. By providing a warning before the next higher warning level, the driver can prepare for the next curve while still in the current one.

[0024] The warning level can also be updated after the target point has been reached. A warning can be issued after the target point if the determined warning level is higher than the threshold. This allows the driver to continue being warned if they are still speeding even after passing the target point.

[0025] The warning after reaching the target point can be issued at a reduced intensity if the warning level drops. The warning can also be terminated if the warning level falls below the threshold.

[0026] The warning after reaching the destination point can be provided with increased intensity as the warning level rises. As the warning level increases, an actual hazard may arise. Increasing the intensity can draw the driver's attention and allow them to take corrective action.

[0027] The warning will stop being displayed if the warning area is left. The warning is only displayed when driving around a curve in the road.

[0028] The threshold can be defined depending on the selected driving mode of the vehicle. For example, the vehicle can have at least two driving modes. The driver can freely choose the modes. In a first mode, the threshold can be lower than in a second mode. This allows for earlier warnings in the first mode than in the second.

[0029] The threshold can be defined based on weather conditions. Under certain weather conditions, road friction may be reduced. In such cases, a lower speed is required in curves. With reduced road friction, the threshold can be set lower to warn the driver before the vehicle reaches its limits.

[0030] In a method for determining a warning level when a vehicle is cornering through a road curve, the target deceleration of the vehicle required to reach a predefined target speed at a predefined target point of the road curve can be compared with at least one threshold value to determine the warning level.

[0031] A target speed for a specific point on a road curve can be extracted from real-world driving dynamics data. In particular, numerous driving dynamics data points from the same road curve can be analyzed, and a target speed can be extracted using statistical methods. The target point can be, for example, the apex of the road curve. The target point can also be identified using the driving dynamics data. In this way, a truly relevant target point for the road curve can be found.

[0032] When a vehicle approaches or travels through a curve in the road, a theoretically necessary target deceleration can be determined. This deceleration would be required to reach a known target speed at the target point. The target deceleration can be calculated using the target speed, the vehicle's current speed, and its current distance from the target point. The current distance can be determined using the vehicle's navigation system. The distance can be continuously measured. The calculated target deceleration can be compared to a predefined threshold. If the target deceleration exceeds the threshold, a warning level can be determined.

[0033] The warning level can be used to inform the driver that they should brake to reach the target speed. The specific target deceleration can be compared to several threshold values. Different threshold values ​​determine different warning levels.

[0034] The target deceleration can be determined within a warning zone of the road curve. A warning zone can also be derived from actual driving dynamics data. The warning zone can coincide with a curve section that includes the road curve. However, the warning zone can also be larger than the curve section and begin before the road curve. A defined warning zone limits the determination of the warning level. Outside the warning zone, the determination can be omitted. By potentially starting the warning before the road curve, the driver's attention can be drawn to the curve.

[0035] The target deceleration can be determined using the vehicle's current acceleration or deceleration. The target deceleration can be smaller if the vehicle is already decelerating or decelerating. Conversely, the target deceleration can be greater if the vehicle is accelerating before the curve.

[0036] The target deceleration can be determined using a reaction time. A reaction time can be an average value. The reaction time can represent the average time it takes for a person to react to a warning. The reaction time increases the target deceleration because the vehicle is not yet braking during the reaction time, and afterward, increased braking is required to reach the target speed at the destination.

[0037] An individual reaction time for a vehicle's driver can be determined from previously observed driver reaction times. Driver reaction times can be recorded, for example, after prior warnings. These reaction times can vary from driver to driver. Through statistical analysis of these reaction times, an individual reaction time can be determined for each driver.

[0038] The threshold can be determined using previously observed deceleration during cornering. This allows the threshold to be adjusted to the driver's past braking behavior. A driver who has braked gently but early in the past is likely to be overwhelmed by a high threshold, as the high threshold results in a late warning. Conversely, a driver who has braked late but sharply in the past is likely to be confused by a low threshold, as the low threshold results in an early warning. By observing braking behavior, the threshold can be adjusted to the driver's habits.

[0039] Previously observed decelerations and the current deceleration before or during the current cornering maneuver can be displayed in a histogram. A maximum and a minimum threshold can be derived from the histogram. A histogram enables a statistical analysis of braking behavior. Individual braking maneuvers before or during different cornering maneuvers can be correlated with similar, previous braking maneuvers in similar cornering maneuvers by displaying them in the histogram. This allows for the identification of clusters of similar braking maneuvers under similar conditions and the derivation of different thresholds for future cornering maneuvers under varying conditions.

[0040] No warning level can be determined if the target deceleration is less than a minimum threshold. If the target deceleration is less than the minimum threshold, a warning may be unnecessary, thus avoiding driver confusion.

[0041] In a method for determining at least one target parameter for a curve driving through a road curve, trajectories of recorded and georeferenced vehicle dynamics data can be evaluated to identify a curve area of ​​the road curve, whereby the target parameter for at least one point of the curve area is extracted from the vehicle dynamics data recorded for that point.

[0042] When a vehicle travels around a curve, a centrifugal force acts on it. This centrifugal force is transferred from the vehicle's wheels to the road. The centrifugal force acts perpendicular to the wheel. The maximum force that can be transmitted at the wheel is physically limited. This force is the resultant force of the centrifugal force and a longitudinal force at the wheel. The longitudinal force arises from braking and accelerating the vehicle. The relationship between centrifugal force, braking or acceleration force, and resultant force is graphically represented by the Kamm circle.

[0043] Even without an acting longitudinal force, the maximum transmissible force limits the vehicle's possible cornering speed. A maximum centrifugal force is reached at the apex of the curve trajectory actually driven by the vehicle. At the apex, the curve trajectory has its smallest radius. The curve trajectory can deviate from the road's path. In particular, the curve trajectory can have a larger radius at the apex than the road's path. At the latest by the apex, the speed must be reduced to at least the maximum possible cornering speed.

[0044] The approach presented here identifies and analyzes curves in data recorded by many different vehicles and drivers along a route. For each detected curve, at least one target parameter is determined from the data. This target parameter is typically a target speed at a vertex of the curve. However, the target parameter can also be a different value for another point on the curve. It is also possible to extract the profile of the target parameter across the curve.

[0045] The target parameter is not the highest value recorded at that point, but rather is determined using a majority of the data recorded for that point. In particular, outliers are ignored to compensate for measurement errors or rare causes such as traffic jams or slow-moving vehicles. Driven curve radii can be extracted from the vehicle dynamics data and filtered to obtain a representative curve radius for the road curve. In other words, the driven curve trajectories can be used. Alternatively, the curve radius can be extracted from a map. The driven curve radii can be averaged to obtain the representative curve radius, removing outliers in the process. The representative curve radius allows for an assessment of how the curve is driven in practice.For example, the width of a roadway can be used to a greater extent to drive a curve radius than the center of the roadway has.

[0046] The target parameter can be determined using the representative curve radius. For example, the target parameter can be extracted at the vertex of the representative curve radius.

[0047] Extrema of the curves can be identified. A cluster of extrema can be identified as a curve section. This cluster can be identified as a curve section if the extrema are closer together than a threshold value. Extrema with excessively large variances can be discarded. The extrema of different drivers differ slightly from one another. However, in an actual curve, all drivers will follow at least similar trajectories.

[0048] The positions of the extrema can be averaged, and an averaged position can be determined as the apex of the road curve. The target parameter, at least for the apex, can be extracted from the vehicle dynamics data. The apex derived from the vehicle dynamics data may differ from the apex of the road surface. By evaluating the vehicle dynamics data, the target parameter can be extracted at the apex actually driven, which is relevant to the driver.

[0049] At least speed profiles can be used as vehicle dynamics data. The vehicle speed can be analyzed as a profile. Alternatively or additionally, lean angle profiles can be used as vehicle dynamics data. For single-track vehicles, such as motorcycles, a lean angle profile can provide precise information about important points in a curve. Motorcycles, in particular, corner differently than multi-track vehicles. The lean angle can reduce lateral forces acting on the rider.

[0050] At least one target velocity at that point can be extracted as a target parameter.

[0051] Speeds recorded at a given point can be filtered to obtain the target speed. For example, predefined percentiles of speeds can be used to remove outliers. Alternatively or additionally, the speeds can be averaged.

[0052] The method is preferably computer-implemented and can be implemented, for example, in software or hardware, or in a hybrid form of software and hardware, for example, in an assistance system.

[0053] Furthermore, the approach presented here creates an assistance system, whereby the assistance system is trained to carry out, control or implement the steps of a variant of the procedure presented here in appropriate facilities.

[0054] The assistance system can be an electrical device with at least one processing unit for processing signals or data, at least one storage unit for storing signals or data, and at least one interface and / or a communication interface for reading or outputting data embedded in a communication protocol. The processing unit can be, for example, a signal processor, a so-called system ASIC, or a microcontroller for processing sensor signals and outputting data signals depending on the sensor signals. The storage unit can be, for example, flash memory, an EPROM, or a magnetic storage device. The interface can be configured as a sensor interface for reading sensor signals from a sensor and / or as an actuator interface for outputting data signals and / or control signals to an actuator.The communication interface can be configured to read or output data wirelessly and / or via a wired connection. The interfaces can also be software modules, such as those found on a microcontroller alongside other software modules.

[0055] Also advantageous is a computer program product or computer program with program code that can be stored on a machine-readable carrier or storage medium such as a semiconductor memory, a hard disk memory or an optical memory and is used to carry out, implement and / or control the steps of the method according to one of the embodiments described above, in particular if the program product or program is executed on a computer or device.

[0056] It should be noted that some of the possible features and advantages of the invention are described herein with reference to different embodiments. A person skilled in the art will recognize that the features of the control unit and the method can be suitably combined, adapted, or exchanged to arrive at further embodiments of the invention.

[0057] Brief description of the drawings

[0058] Embodiments of the invention are described below with reference to the accompanying drawings, whereby neither the drawings nor the description are to be interpreted as limiting the invention.

[0059] Fig. 1 shows a representation of the identification of curve regions in velocity profiles using a method according to an implementation example;

[0060] Fig. 2 shows a representation of a distinction between a curved area and an area without a curve using a method according to an exemplary embodiment;

[0061] Fig. 3 shows a representation of a vehicle before a curve; Fig. 4 shows a flowchart for determining a warning level before a curve;

[0062] Fig. 5 shows examples of determining different warning levels before curve sections;

[0063] Fig. 6 shows a representation of a target speed profile and an actual speed profile in a curve section; and

[0064] Fig. 7 shows a representation of a target velocity profile and of possible velocity profiles after a vertex of a curve section.

[0065] The figures are schematic only and not to scale. Identical reference symbols denote identical or equivalent features.

[0066] Embodiments of the invention

[0067] Fig. 1 shows a representation of the identification of curve sections 100 in speed profiles 102 using a method according to an exemplary embodiment. The speed profiles 102 represent recorded georeferenced vehicle dynamics data 104 from journeys with different vehicles and different drivers on the same route 106. The speed profiles 102 are shown in a diagram where the distance 106 is plotted on its abscissa and the speed 108 on its ordinate. The vehicle dynamics data 104 can alternatively or additionally include other recorded measured values, such as acceleration, lean angle, or steering angle.

[0068] Route 106 contains several dynamically relevant cornering sections (100) and sections without such cornering in between. A selection of these cornering sections (100) is highlighted by markings.

[0069] Within the curve ranges 100, the driving dynamics data 104 of all vehicles and all drivers are similar. Within the curve ranges 100, the driving dynamics data 104 show low variation. Between these ranges, the driving dynamics data 104 of the different vehicles and different drivers show high variation.

[0070] In particular, the speed profiles 102 in the curve sections 100 exhibit local minima. The locations or positions of the minima are closely clustered along the track 106. The minima are grouped around the actual apexes 110 of the curve sections 100. The minima show low dispersion in the curve section 100. Before the apex 110, the drivers decelerated to varying degrees from different initial speeds. After the apex 110, the drivers accelerated out of the curve to varying degrees.

[0071] At least one point per curve section 100, a target parameter is extracted from the vehicle dynamics data 104.

[0072] Here, at the vertices 110, the speeds driven by the various drivers and different vehicles are extracted from the speed profiles 102, and a target speed for the respective vertex 110 is determined from these speeds as the target parameter. Outliers at both high and low ends are ignored by filtering the speeds using statistical methods. For example, only a speed interval is used in which 90 percent of the driven speeds lie. The remaining 10 percent are ignored. This also allows vehicle dynamics data 104 with faulty georeferencing to be ignored.

[0073] Within this speed range, different target speeds can then be defined for different driving styles. For example, an upper target speed at the upper limit of the speed range can be selected for a highly dynamic driving style, while a lower target speed near the lower limit of the speed range can be selected for a less dynamic, relaxed driving style.

[0074] Fig. 2 shows a representation of a differentiation between a curve region 100 and a region without a curve using a method according to an exemplary embodiment. Here, for example, two consecutive regions are shown. For both regions, a density of the minima of the velocity profiles from Fig. 1 is shown in a diagram, which has the distance 106 plotted on its abscissa and the density on its ordinate. The density corresponds to the inverse of the standard deviation. In curve region 100, the density is higher than a threshold value 200. Therefore, this region is recognized as curve region 100. In the other region, the density is also elevated, but lower than the threshold value and therefore does not represent a relevant curve region.

[0075] Fig. 3 shows a representation of a vehicle 300 approaching a curve 100. The vehicle 300 is a motorcycle. The vehicle 300 is traveling on a road towards a curve 302. The curve 302 is defined by the curve 100. At a point approximately in the middle of the curve 100, the apex 110 is marked as the target point 304. A target speed 306 is stored for the target point 304 in a database of the vehicle or in a remote database.

[0076] In addition to the representation of curve section 100, a representation of a target speed profile 308 through curve section 100 is shown. The target speed profile 308 is shown in a diagram where the distance 106 is plotted on its abscissa and the speed 108 on its ordinate. The target speed profile 308 has a minimum at the target point 304. The minimum corresponds to the target speed 306.

[0077] Fig. 4 shows a flowchart for determining a warning level 400 for a vehicle before a curve. The warning level 400 is determined using a target speed 306 at the apex of the curve, the vehicle's current speed 108, and its distance 404 from the apex. The warning level 400 is determined based on the required target deceleration 406 to reach the target speed 306 at the apex. The target deceleration 406 is compared to a threshold value 408, and the appropriate warning level 400 is determined. In one embodiment, the target deceleration 406 is compared to a single threshold value 408, and the warning level 400 is issued if the target deceleration 406 is greater than the threshold value 408. If the target deceleration 406 is less than the threshold value 408, no warning level 400 is issued.

[0078] In one embodiment, the target delay 406 is compared with several different threshold values ​​408. If the target delay 406 is greater than the lowest threshold value 408 but less than the next higher threshold value 408, a lowest warning level 400 is issued. If the target delay 406 is greater than the next higher threshold value 408, a next higher warning level 400 is issued.

[0079] In one embodiment, the target deceleration 406 is further determined taking into account a reaction time 410. This results in a greater target deceleration 406, since the vehicle continues without deceleration during the reaction time 410, and the driver can only react to a warning issued at the beginning of the reaction time 410 after this time has elapsed. By considering the reaction time 410, less distance to the target point is available for the required speed reduction, which is why the target deceleration 406 is determined to be higher.

[0080] In one embodiment, the vehicle's current acceleration 412 is taken into account when determining the warning level 400. If the vehicle is already decelerating or braking during the determination of the warning level 400, the negative acceleration 412 is subtracted from the target deceleration 406, and the warning level 400 is determined using the reduced value. However, if the vehicle continues to accelerate with a positive acceleration 412, this acceleration 412 is added to the target deceleration.

[0081] Fig. 5 shows two examples for determining different warning levels 400 before curves. For each example, a time-dependent speed profile 102 of a vehicle 300 before a target point 304 of the curve is shown in a diagram, with time plotted on its abscissa and speed 108 on its ordinate. To determine the respective warning level 400, a speed difference 502 between the speed 108 and a target speed 306, as well as a time interval 504 until reaching the target point 304, are evaluated. From the speed difference 502 and the time interval 504, a target deceleration 406 of the vehicle 300 is directly derived. The target deceleration 406 is represented by the slope of a line connecting an instantaneous coordinate of the vehicle 300 in the diagram and a coordinate of the target point 304.The steeper the connecting line, the greater the target delay 406 to reach the target speed 306 in a time period of 504. The greater the target delay 406, the higher the warning level 400 is determined.

[0082] In the first diagram, the vehicle accelerates 300 towards the target point 304, but is still far from the target point 304. This results in a target deceleration 406, which is greater than a first threshold value 408, and a first warning level 400 is determined.

[0083] In the second diagram, vehicle 300 accelerates to a constant speed of 108 and approaches target point 304. However, the travel time 504 to target point 304 is short, and the speed difference 502 is high. This results in a target deceleration 406, which is greater than both the first threshold 408 and a second threshold. A second warning level 400 is therefore triggered.

[0084] Fig. 6 shows a representation of a target speed profile 308 and an actual speed profile 102 in a curve section 100. The profiles are plotted in a diagram where time is plotted on its abscissa and speed 108 on its ordinate. Here, the speed profile 102 remains below the target speed profile 308. At the beginning of the curve section 100, the speed 108 does approach the target speed profile 308, but the vehicle decelerates more strongly than the target deceleration and passes the target point 304 at a lower speed 108 than the target speed 306. After the target point 304, however, the vehicle accelerates out of the curve more strongly than the target acceleration, causing the speed profile 102 and the target speed profile 308 to converge again.Since the speed 108 will exceed the target speed profile 308, the driver of the vehicle is warned. Fig. 7 shows a representation of a target speed profile 308 and possible speed profiles 102 after a target point 304 of a curve section 100. The target speed profile 308 and the speed profiles 102 are plotted in a diagram, as in Fig. 6, which has time on its abscissa and speed 108 on its ordinate.

[0085] An initial speed profile 102 shows a lower speed 108 at target point 304 than the target speed profile 308. After target point 304, the speed 108 decreases. Therefore, the speed difference between the target speed and the speed 108 is positive, and the acceleration difference between the target acceleration and the vehicle's acceleration is also positive. The initial speed profile 102 is non-critical, and no warning is issued.

[0086] A second speed profile 102 also shows a lower speed at target point 304 than the target speed profile 308. After target point 304, the speed 108 increases, as shown in Fig. 6. The speed difference between the target speed and the speed 108 is therefore positive. However, the acceleration difference between the target acceleration and the vehicle's acceleration is negative. A warning level is determined here, and the driver is warned if the warning level exceeds a predefined threshold.

[0087] A third speed profile, 102, shows a higher speed of 108 at target point 304 than the target speed profile 308. After target point 304, the speed increases to 108. The speed difference between the target speed and the speed of 108 is therefore negative, and the acceleration difference between the target acceleration and the vehicle's acceleration is also negative. This triggers the highest warning level.

[0088] A fourth speed profile 102 shows a higher speed of 108 at target point 304 than the target speed profile 308. After target point 304, the speed decreases to 108. The speed difference between the target speed and the speed of 108 is negative. However, the acceleration difference between the target acceleration and the vehicle's acceleration is positive. In this case, either the highest warning level is issued, or a warning level is determined, and the driver is warned if the warning level exceeds a predefined threshold.

[0089] Possible embodiments of the invention are summarized below or presented using slightly different wording.

[0090] A curve and speed identification system for curve speed warning devices for motorized two-wheelers is presented.

[0091] Here, target speeds and warning points for curve speed warning systems of motorized two-wheelers are determined by computer algorithms from map data and / or vehicle dynamics data.

[0092] The target speeds and warning points for curve speed warning systems for motorized two-wheelers are determined with sufficient reliability by computer algorithms using map data and / or vehicle dynamics data, enabling reliable warnings to be issued to the rider at relevant points in the curve. These serve as the fundamental database for curve speed warning systems. If curve radii are determined using vehicle dynamics, they reflect the radii actually driven (influenced by line choice), whereas the geometric road radii in map data typically correspond to the radius of the center line.

[0093] First, areas are determined that are to be considered as a curve.

[0094] From a sufficiently large number of recordings of driving dynamics data from real journeys on identical stretches of road, containing the speed v and the lean angle a, the radius can be determined using the relationship

[0095] -determined. Possibilities for determining a curve region from this are, in the first step, a) to calculate the mean radius or another statistical percentile of all recorded journeys, or b) to find local minima of the radius of each individual journey and to determine a density distribution of local radius minima.

[0096] A hysteresis analysis is then performed for both variants. When considering the density of local minima, a lower and upper threshold can be exceeded. If the lower threshold is again undershot, a curve is formed between the sections where the lower threshold is reached.

[0097] The evaluation using statistically determined radii (mean radius or other percentiles) is the reverse of this. The intersection with a higher radius threshold marks the curve region, provided that a lower threshold is crossed in between.

[0098] Alternatively, the curvature of the road can be considered (=1 / radius).

[0099] Data sources can include, for example, proprietary maps with road curve radii or freely usable maps from which curve radii are determined using geometric methods based on the road course.

[0100] The determination of curve ranges is based on hysteresis considerations, as described above.

[0101] When curve radii are determined by driving dynamics, they reflect the radii actually driven (influenced by line choice), while the geometric road radii in map material usually correspond to the radius of the center line.

[0102] On identified curve regions, the speed profiles and, if applicable, the vehicle dynamics radii of real-world driving data are analyzed and statistically evaluated. For a warning function, higher speed percentiles are suitable, e.g., the 95th percentile. The point with the statistically lowest speed and / or the point with the smallest static radius are suitable reference points for a curve region that a speed warning system can use as a warning point.

[0103] As an extension, the warning system can also use several warning reference points of a curve area, up to a quasi-continuous specification of a target speed through the entire curve area.

[0104] If the measurement data set is labelled with further attributes, e.g. motorcycle type, weather, day / night, a corresponding sub-data set can be used in the statistical assignment of the speed percentiles to make adjustments to the individual motorcycle and the external conditions.

[0105] A method for calculating a warning level to inform a driver about excessive speed for the upcoming curve is presented.

[0106] A curve warning system can warn of impending dangers at upcoming curves based on the vehicle's speed.

[0107] A specific method is described for calculating a suitable warning level for curve warning systems. This requires that a target speed suitable for the driver for an upcoming curve be determined in a separate procedure.

[0108] This method uses the calculation of the necessary deceleration to reach the target speed at a specific point for the upcoming curve. The warning level is based on this calculated deceleration. The driver's reaction time is also taken into account. Typical decelerations are driver-specific and can be derived from historical driving data. This allows for the programming of a driver-specific warning level.

[0109] Traditionally, only speed is used. The calculation of a typical driver deceleration, as presented here, provides an intuitively understandable warning level. While speed directly affects centrifugal force and thus determines the lateral component of the Kamm circle, which in turn describes the driving dynamics and driver comfort range, considering acceleration adds the missing longitudinal component. This ensures that both dimensions are taken into account.

[0110] In the first sub-function, the distance ds of the vehicle to the point p on the curve ahead, where the target speed vtar is to be reached, is determined. This target speed is assumed to be given and can be determined using various methods. Taking into account the current vehicle speed uego, this distance can be converted into a time dtego until this point is reached.

[0111] In the next sub-function, the driver's reaction time, dtdelay, is taken into account. In the simplest approach, this is assumed to be constant. In an alternative implementation, the reaction time is learned from warnings issued by the system and the driver's response to them.

[0112] Knowing the time required to reach a suitable speed, a target deceleration can be calculated, which the driver should then set.

[0113] > v tar ~ v ego ütar ~ dt

[0114] An optional additional function allows the vehicle's current acceleration value (uego) to be taken into account. This ensures that the warning immediately disappears as soon as the driver reacts to it and the vehicle is already decelerating.

[0115] The warning delay `awarn` is calculated as follows: `-warn ^tar ego`

[0116] Warning levels can be derived from this warning delay. In the simplest case, for example, via a lookup table.

[0117] In another embodiment, these levels are learned from typical driver decelerations on an individual system. Machine learning methods, for example, can be used for this purpose. Alternatively, a histogram of achieved decelerations can be iteratively updated continuously during the journey (e.g., with 10 bins from -1 to -10 m). A2 / s) will be.

[0118] A delay value at is entered into the histogram if and only if a curve follows within the epoch t ... t + tmax, i.e., if an existing point pCurve is crossed. The example lookup table can then be scaled so that the warning delays are within the specified range [-1 ... -6 / s]. A 2] scaled to the maximum and minimum decelerations actually achieved by the driver (e.g. 90th and 10th percentiles).

[0119] Figure 5 shows the vehicle's position a certain time interval (dt) before the curve. The target cross indicates the target speed. The value dv and the calculated target deceleration result in a non-critical warning level. In the second illustration, the vehicle is closer to the target point in time. The calculated deceleration value indicates a higher criticality and thus a higher warning level.

[0120] The approach presented here can also be used for a collision warning system.

[0121] Methods for warning motorcyclists approaching a curve at excessive speed and for assisting with speed selection while cornering are presented. A warning function for a single-track vehicle is described, which helps the rider navigate curves safely. In a curve warning system for motorized two-wheelers, depending on the selected Emergency or Guidance mode, the rider is appropriately warned of impending excessive cornering speed when approaching a curve, or a continuous display is provided to facilitate safe cornering.

[0122] The way motorcyclists navigate curves differs significantly, partly due to their ability to vary their line more within the lane than car drivers. A rider on a scenic drive will likely proceed at a leisurely pace and consider steering the motorcycle a secondary task. For a sporty rider, however, handling the motorcycle is the primary task, which they strive to optimize.

[0123] This necessitates different approaches to the curve warning function. While the sporty rider only wants a warning if they are traveling too fast for the upcoming curve, the touring rider wants the function to provide a sense of security. This means the curve warning function should continuously indicate, both when approaching and during the curve, whether they are traveling at an appropriate speed or whether they need to adjust their speed to the curve's shape. Here, we present two versions of a warning and display concept for safe speed selection when cornering, in Emergency or Guidance mode, which can be set by the rider.

[0124] Curves can be determined using a method for curve identification and for determining associated speeds over the curve path based on aggregated driving data.

[0125] Based on the current vehicle speed and a target speed at a destination point, a target deceleration can be calculated. Based on this target deceleration and the current deceleration, a warning level can be determined.

[0126] The warning level can be displayed, for example, via LED strips. The warning concept for emergency mode works as follows: When approaching a curve, a warning level is continuously calculated. In its simplest form, the target point for calculating the warning level is the point in the preceding identified curve where the minimum target speed (vmin), preferably determined from the driving data, occurs. With closely spaced curves, the driver may need to adjust their speed to the second curve while already traversing the first. Therefore, in a further configuration, the warning level is calculated not only for the target point of the next curve but also for the one after that. The maximum of these warning levels is then displayed.

[0127] Only when the warning level exceeds a sufficiently high threshold will the driver receive a clear warning via the HMI, such as an LED strip, e.g., only red LEDs, possibly coupled with a shift light. The warning level is continuously calculated while approaching the destination. If the driver reduces their speed while approaching the destination, causing the warning level to fall below the threshold, the warning disappears. If the warning level is still above the threshold upon reaching the destination, meaning the vehicle speed is above the target speed, the warning remains active until acceleration is detected or the curve is exited. In these cases, too, the warning disappears. A warning is only displayed via the HMI if the conditions described above are met; otherwise, in emergency mode, only the active function is indicated.To implement the Emergency mode, higher quantiles of the speed data can be used to calculate the target speeds than for the Guidance mode.

[0128] In Guidance mode, a warning level is calculated when approaching a curve and continuously throughout the curve until its end. From a certain distance to the curve and throughout the entire curve negotiation, the driver receives a warning via the HMI. Even at a non-critical warning level, the driver receives a warning (unlike in Emergency mode), for example, in the form of two green LEDs on either side. This indicates "curve ahead" to the driver even before the curve is reached. Furthermore, more granular warning levels can be applied in Guidance mode, allowing a warning cascade from non-critical to very critical to be displayed via the HMI, depending on the severity of the situation. After passing the target point, the driver continues to receive a warning via the HMI, depending on their speed, until the end of the curve.To determine the warning level after passing the target point, the speed difference Av = vtarget-vego between the target and ego speeds, as well as their time derivative Av, must be calculated. Depending on these values, four cases must be distinguished when determining the warning level.

[0129] Cases 1 and 3 are self-explanatory. In case 2, the ego speed is below the target speed but is approaching it with a risk of exceeding it. A warning level is determined based on the value of / 2, which depends on the distance Av is from the target speed and the speed at which Av is approaching it. This example shows a calculation rule for f2. In the simplest case, the warning level can then be determined using a lookup table depending on the value of fi.

[0130] In case 4, the ego speed is higher than the target speed. The simplest implementation here outputs the highest possible warning level. However, if it can be seen, based on the distance Av from the target speed and the speed at which Av is approaching it, that the target speed will soon be undercut, a gradual de-escalation of the warning levels can also be implemented using the value of the function fa{Av, Av). Finally, it should be noted that terms such as "exhibiting," "comprising," etc., do not exclude other elements or steps, and terms such as "a" or "an" do not exclude a plurality. Reference symbols in the claims are not to be considered limitations.

Claims

Claims 1. Method for informing a driver when a vehicle (300) is cornering through a road curve (302), wherein a warning is individually provided to the driver via a human-machine interface of the vehicle (300) when a determined warning level (400) for the cornering is greater than a predefined threshold, wherein the warning level (400) is continuously updated at least from the beginning of a warning area of ​​the road curve (302) to a target point (304) of the road curve (302).

2. Method according to claim 1, wherein furthermore information representing the currently determined warning level (400) is provided via the human-machine interface of the vehicle (300) when the driver has activated an information mode.

3. A method according to one of the preceding claims, wherein a further warning level (400) for a subsequent curve through a subsequent road curve (302) is determined when a warning area of ​​the subsequent road curve (302) overlaps the warning area of ​​the current road curve (302), wherein the warning is provided when at least one of the warning levels (400) is greater than the threshold.

4. Method according to one of the preceding claims, wherein the warning level (400) is also updated after the target point (304), wherein the warning is provided after the target point (304) if the determined warning level (400) is greater than the threshold.

5. Method according to claim 4, wherein the warning to the target point (304) is provided with a reduced intensity when the warning level (400) falls.

6. Method according to one of claims 4 to 5, wherein the warning to the target point (304) is provided with increased intensity when the warning level (400) increases.

7. Method according to one of the preceding claims, wherein the provision of the warning is terminated when the warning area is left.

8. Method according to one of the preceding claims, wherein the threshold is defined depending on a selected driving mode of the vehicle (300).

9. Method according to one of the preceding claims, wherein the threshold is defined as dependent on the weather.

10. Assistance system, wherein the assistance system is configured to execute, implement and / or control the method according to one of the preceding claims in appropriate facilities.

11. Computer program product configured to instruct a processor, when the computer program product is executed, to execute, implement and / or control the method according to any one of claims 1 to 9.

12. Machine-readable storage medium on which the computer program product according to claim 11 is stored.

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