WO2009074206A1

WO2009074206A1 - Method for operating a navigation system and navigation system

Info

Publication number: WO2009074206A1
Application number: PCT/EP2008/009664
Authority: WO
Inventors: Volker Oltmann
Original assignee: Daimler Ag
Priority date: 2007-12-12
Filing date: 2008-11-14
Publication date: 2009-06-18
Also published as: DE102008012697A1

Abstract

The invention relates to a method for operating a navigation system (1), particularly a navigation system (1) for a vehicle, wherein current map information (KI) and current vehicle information (FI) are detected and analyzed, on the basis of which a current road position (s_pos) and/or a route ahead (s, card route s_map, drive route s_fzg) is determined, wherein on the basis of a comparison of the current vehicle information (FI) to the current map information (KI) the quality (Q) of the current map information (KI) is determined. According to the invention, at least a degree of the quality (Q) of the current map information (KI) is determined on the basis of a comparison of current map information (KI) and current vehicle information (FI) corresponding thereto, wherein for the determination of the current road position (s_pos) and/or the route ahead (s), the current map information (KI) is considered according to the determined degree of the quality (Q).

Description

Method for operating a navigation system and

Navigation system

The invention relates to a method for operating a navigation system, in particular a navigation system for a vehicle according to the preamble of claim 1. The invention further relates to a navigation system according to the preamble of claim 19.

Navigation systems and methods for determining the position of a vehicle are known and used commercially. In this case, digital maps are used, for example, to enter destinations and to guide the driver of the vehicle to the entered destination by means of a route guidance. The digital maps used have map information as road or route courses, which are formed for example by edges, in particular line elements. If roads and thus their edges meet at an intersection or branch, then these points of the meeting are represented by nodes. The digital maps and the navigation system may include information about the current vehicle environment.

To further improve driver assistance systems (eg for vehicle longitudinal guidance such as cruise control, limiters, ADTR), information from digital maps is important. An adaptive cruise control system (ACC system (ACC = adaptive cruise control) called), for example, with knowledge of the route ahead be further developed in terms of its curves and lines in the function. Through so-called "Map Matching Tolerances" (assignment of vehicle position to a digital map), lack of map updates and

Accuracy differences in the map data can lead to errors while navigating.

US Pat. No. 7,024,307 B2 discloses a card analysis system which determines the quality of current map information of a digital map and, if the quality is inadequate, carries out a map update whose map data are used for navigation. This can still lead to errors in navigation, as well as a map update may have insufficient quality.

The invention is therefore based on the object to provide a method for operating a navigation system, which allows a largely secure navigation. In addition, a suitable navigation system must be specified.

With regard to the method, the object is achieved by the features specified in claim 1. The navigation system concerning the object is achieved by the features specified in claim 21.

Advantageous developments of the invention are the subject of the dependent claims.

In the method for operating a navigation system, in particular a navigation system for a vehicle, current map information and current vehicle information are detected and analyzed, based on which a current route position and / or a preceding route are determined, based on a comparison of the current vehicle information with the current map information a Quality of the current map information is determined. According to the invention determined on the basis of a comparison of current map information and thus corresponding current vehicle information at least a degree of quality of the current map information, to be considered for determining the current route position and / or the preceding route, the current map information according to the determined degree of quality. By a quality-dependent consideration of digital map information during navigation malfunction during navigation or malfunction in the navigation data used driver assistance systems are safely avoided. In particular, the functions and the operation of driver assistance systems are improved without costly updating of the driver assistance system itself.

Under map information in the context of the invention are in particular all a road network, routes, curves, straight lines, intersections, gradients, gradients, elevation, longitudes, latitudes, background, such as waters, built-up areas, railways, bicycle routes, objects such as gas stations, restraints , Parking lots, etc. understood maps that facilitate orientation. Vehicle information within the meaning of the invention is understood in particular to mean the vehicle itself and the vehicle environment representing vehicle data which, for example, by means of sensors, in particular vehicle sensors, such. B. radar sensors, camera sensors, wheel speed sensors, tachometer sensors, rotation ^¬ or yaw rate sensor (gyrometer), acceleration sensor, in particular lateral acceleration sensor, angle sensor, in particular steering wheel angle sensor and / or data receiving units, such as satellite receiver, in particular GPS receiver detected or received.

Conveniently, the current map information, depending on the determined degree of quality without restriction in good quality or limited considered sufficient quality. If the quality of the map information is poor, it will be disregarded. In addition, further gradations of the usability of the map information with appropriate quality differentiation and data differentiation are possible.

In order to be able to determine an exact and qualitatively sufficiently good forecast of the route, the degree of quality of the current map information is continuously determined. Preferably, the scope of consideration of the current map information is continuously adjusted depending on the continuously determined level of quality. Thus, a route forecast that is always adapted to the current map quality is made possible. In addition, the vehicle information (such as vehicle operating / vehicle status data, vehicle environment data) is continuously recorded and taken into account in the route prognosis. In this case, the vehicle information time and / or event-controlled, z. B. with constant timing, at start, in vehicle standstill, recorded and updated.

Conveniently, with unequal sizes of vehicle information to be compared and map information, the vehicle information in question is converted into vehicle information corresponding to the current map information. For example, a steering wheel angle (= vehicle information) is converted into a curve size of the route (= map information) corresponding vehicle size or vehicle information.

In one embodiment of the invention, a navigation or driving route (= vehicle information) and / or a map route (= map information) are or will be determined as the preceding route. The navigation or driving route is a path which is given by the navigation and is measurable while driving. The map route is a path determined by the digital maps as the most likely path (also called MPP for short, with MPP = most probable path). The route ahead - whether the route or the route - covers the routes to be traveled, in particular a road with curves and straights, gradients and gradients. The description of the course of the route preferably takes place on the basis of map information, in particular on the basis of radii and distances to the radii or curvatures and distances to the curvatures or road coordinates or marking points as well as gradient and slope data or altitude data. In this case, the individual streets can be stored as card information in a data memory by these representing edges / boundaries / lines and their intersections or branches or intersections through these representing nodes or areas or can be received by a central unit. Preferably, further map information, such as. B. start of curve, end of curve and / or vertices, are determined and stored.

For correcting and / or continuously monitoring the map data / information and / or the predicted route, a map route and / or route traveled from the start of the journey and / or from a previous route position are determined and taken into account in the subsequent route prognosis, in particular for correcting the map information used.

In detail, the ascertained current and / or previous map information and / or vehicle information, in particular the route, the map route, the beginning of the curve, the end of the curve, the vertices, Curves, such as map curvatures, curvatures and / or distances, such as map distances, travel distances analyzed on the basis of the traveled map and / or route and at least one associated, for example, curvature-related or distance-related correction value determined. In detail, a distance-related correction value is determined on the basis of differences of current, differently determined distances, such as map or driving distances, taking into account the covered map and / or route.

Subsequently, the determined map distance can be corrected on the basis of a determined average deviation of variously determined distances, wherein the bandwidth of the mean deviation of the corrected map distances is determined and checked on the basis of predefinable distance limit values. The quality can then be determined on the basis of the over and / or underrun of the distance limit values.

Analogously to the examination and analysis of the determined distance data, the curvature values currently determined differently, such as card curvature and curvature, and their average deviation can be used to check the quality of the card information / data.

Preferably, the assessment restarts and correction values are cleared and redetermined when leaving or changing a road, a road class, a road type, a region and / or a country on a route, in particular the route. It will be useful for the street, the street class and / or the street type of the preceding Route, in particular the route previously taken certain correction values as starting values.

The navigation system according to the invention comprises at least one data memory, at least one display element and a data receiving device and a processing unit. In this case, the processing unit comprises means for determining a current route position and / or a preceding route based on current map information and current vehicle information, the determination of the current route position and / or the preceding route being performed according to a determined degree of quality of the current map information.

Embodiments of the invention will be explained in more detail with reference to a drawing.

Showing:

1 shows schematically a block diagram of a navigation system,

2 shows schematically a flowchart of the method according to the invention for operating the navigation system.

Corresponding parts and functions are provided in all figures with the same reference numerals.

1 shows a navigation system 1 with at least one processing unit 2, at least one data memory 3 and a number of vehicle sensors 4 to I ₁ such as wheel speed sensor 4, yaw rate sensor 5, lateral acceleration sensor 6, data receiving device 7. Also For example, additional sensors such as radar units such as near and far range radar, satellite receiving units, steering wheel angle sensors, optical pickup units such as cameras for detecting the vehicle environment and / or control units connected to the processing unit 2 may be provided. The vehicle data and / or vehicle environment data acquired by the vehicle sensors 4 to 7 are supplied to the processing unit 2 as vehicle information FI and used by the latter on the basis of digital map information KI stored in the data memory 3 to forecast a route course s and / or a route position pos.

For the display of the ascertained, in particular preceding route s or the current or a forward route position pos, the navigation system 1 comprises at least one display element 8, which is connected to the processing unit 2. In addition, the processing unit 2 can be connected to at least one driver assistance system 9, to which at least one control signal S for influencing a driving function can be supplied on the basis of the determined predicted route course s or the route position pos.

The method for operating the navigation system 1 will be described in more detail below.

The processing unit 2 determines from the data memory 3 and from the map information KI stored there a forward route s_map, which is referred to below as a map route s_map in order to distinguish it from a route s_fzg determined in particular from the navigation and thus from current vehicle information FI. Based on the vehicle information FI determined, in particular measured route s_fzg is referred to below as the route s_fzg.

In this case, the determined map distance s_map and / or the measured travel distance s_fzg can support the driver assistance function of one of the

Driver assistance systems 9, z. B. a Abstandsregeltempomats, a cruise control system can be used.

The ascertained map sections s_map and / or measured routes s_fzg can in particular be stored as preceding map routes s_map or travel routes s_fzg and thus the route histories s representing the past, as previous and thus already covered map routes s_map.

In addition to detecting the map route s_map on the basis of current, in particular received and / or previous, in particular stored map information KI while driving current vehicle information FI detected by the vehicle sensors 4 to 7 and / or a driver assistance system 9 and used as a reference to the map information KI.

From a comparison between current and / or previous map information KI and / or current and / or previous vehicle information FI, a quality Q of the relevant map information KI can be inferred. If there is virtually no deviation, the determined relevant, i. the current or previous map information KI, used for route prognosis and thus used for a driver assistance function without restrictions.

If the comparison yields deviations that are within specified tolerances, the relevant card information KI is used with function restrictions and used in the route prognosis accordingly restricted.

In the case of deviations beyond the specified tolerances, the relevant map information KI is disregarded and the driver assistance function is operated without map support.

The checking of the card quality Q preferably takes place continuously, for example, time and / or event-controlled, in order to obtain a positive change, i. the quality Q of the current map information KI is within predetermined tolerance values to allow the map support automatically again.

The detailed method for the quality-dependent prediction of a route s will be described in more detail with reference to the flowchart of FIG.

On the basis of the digital map information KI, a preceding path progression s is determined. This can be a path which is determined by the navigation and thus the travel, in particular measured (= travel distance s_fzg), or a path which the map system determines as the most probable path (= map distance s_map). The route s contains the track to be driven in terms of its curves and straights. The description of the route can be made by radii r_map, r_fzg and distance values d_map, d_fzg to the radii r_map, r_fzg or curve curvatures c, in particular map curvatures c_map, driving curves c_fzg, and distance values d, in particular map distances d_map, driving distances d_fzg to these or by coordinates of points ( shape points that mark the road or track) or points that mark the road or track by angles and distance values. The map data or information KI of the forecast is continuously corrected by the route d_mapθ already laid back, so that, for example, a curve start KA, which was announced at the time tθ [s] with a distance of dθ [m], after a distance of dl [ m] at time tl [s] has the distance d to the vehicle from dθ - dl [m].

The map information KI in question is also maintained after reaching relevant positions pos, such as intermediate positions which were determined as map position pos_map or driving position pos_fzg, and time-controlled, in particular stored according to a time specification. A deletion takes place only after a prescribable distance in [m] or [km] was covered. This distance is referred to below as the last distance s_loesch whose length can be specified. Thus, the route s for a previous route according to the last traveled route s_loesch is always known.

For comparison and determination of the quality Q of the current and / or previous map information KI, vehicle information FI, in particular driving conditions, vehicle states, vehicle environment states, for example, with constant timing and / or event-controlled, are detected as a reference, for example by time and / or event. This vehicle information FI includes, for example, at the time of recording the current driving situation under the vehicle. The vehicle information FI is converted to the same physical size as the

Map information KI, which were determined from the map data. In other words: the currently detected or determined vehicle information FI are converted into vehicle information FI_korr corresponding to the current map information KI. Analogously, the determined map information KI in with the current Vehicle information FI corresponding map information KI_korr be converted.

In the following, for the sake of simplicity, the curve curvature c and the associated distance d to the vehicle will be used as the physical quantities used for route prediction, for the sake of simplicity. Curve curvature values of c> 0 are for left turns, c <0 for right turns and d> 0 for a position in front of the vehicle and d <0 for a position behind the vehicle.

In addition to storing values of actual curvatures c, such as the map curvature c_map, and / or values of actual distances or distances d, such as map distances d_map, which are corrected, in particular, by the already traveled distance s_mapθ, the distance d taken from the origin becomes the output distance d_mapθ (= d_map on initial acquisition) and the corresponding start position as starting position pos_mapO determined and stored.

The output distance d_mapθ serves to execute a correction between the different distances, such as the determined map distance s_map and / or the measured travel distance s_fzg, which were determined by independent systems, such as vehicle sensors 4 to 7, map memory 3 and / or driver assistance system 9. In this case, the vehicle information FI, which has been changed, for example, due to worn tires, can be used and taken into account in order to correct the determined routes s. For this purpose, for example, characteristic points (eg curve start KA, curve end KE, vertices SE) are selected by the route profiles s_map, s_fzg of the map and the vehicle, and the differences of the distance values d, d_map, d_fzg are taken into account, taking into account the forward-looking announcement as a function of Initial distance d_mapθ and / or the covered map and travel distances s_mapθ, s_fzgθ to a distance-related correction value K_d processed according to:

K_d = s_map / s_fzg [1] with K_d = correction value, s_map = map route, s_fzg = routes.

The measured driving distance s_fzg is determined, for example, based on vehicle data up to the most recently traveled distance s_loesch.

Subsequently, to the characteristic points, the average values of the deviations of the distances d, i. the average deviation d_mittel (denoted by the reference character MD in FIG. 2) of the determined distance values d, i. the map distance d_map and the travel distance d_fzg, and a resulting bandwidth between minimum and maximum mean deviation d_min and d_max of the distances d between the values of the determined map distance d_map and the measured values of the travel distance d_fzg determined. A constant mean deviation d_mittel can z. B. occur due to latencies. In a more complex method, the vehicle speed v can also be included in the calculation.

The knowledge of the mean deviation d_mittel of the distances d is used, for example, to correct the predicted route course s and / or a control signal S from the navigation system 1 for a driver assistance (in the forecast for the function). The determined bandwidth serves to assess the card quality Q, as described below using the example of a limit value analysis.

If the values of the minimum and maximum deviation d_min or d max of the distances d are within specifiable limits Distance limits d_limitl and d_limit2 (d_limitl <d_limit2) and thus a positive rating of the map quality Q before, so the map information KI are taken over without restriction for the distance d or the curvature c, so that assistance functions without restrictions with the current map data / information KI executed become.

When adhering to further predefinable distance limit values d_limit3 and d_limit4 (d_limit3 <d_limit4), which represent an insufficient map quality Q, the map information KI is taken into account in a limited manner, so that the assistance function can only be carried out with restrictions.

If one of the values of the minimum or maximum deviation d_min or d_max of the distances d or both lies outside the predetermined distance limit values d_limit3 and d_limit4, then the map information KI remains unconsidered and the assistance function is executed without map data.

Furthermore, by means of an optimization method, a scaling factor f_c_opt can be determined between the different ascertained values of the curvatures c, in particular of the determined card curvature c_map of the map and the measured curvature of travel c_fzg of the vehicle. The determination is carried out by means of measured vehicle data up to the last traveled distance s_loesch. In this case, the scaling factor f_c_opt can also be used to correct, for example, the predicted route course s and / or a control signal S of the navigation system 1 for driver assistance (in the forecast for the function).

Subsequently, the information on the determined values of the curvatures c are evaluated. For example, the mean value of the deviations c_mittel (in FIG. 2 with the Reference character MD) of the determined curvatures c and a resulting bandwidth of the minimum and maximum deviations c_min and c_max between the determined values of the card curvature c_map and the curvature c_fzg. The calculation is carried out by means of driving data / information FI up to the last traveled distance s_loesch.

The knowledge of the mean deviation c_mittel of the determined curvatures c (i.e., c_map, c_fzg) is used, for example, to correct the predicted route course s and / or a control signal S of the navigation system 1 for driver assistance (in the forecast for the function).

The determined bandwidth also serves to assess the card quality Q.

If the determined values of the minimum and maximum curvatures c_min or c_max lie within predefinable curvature limit values c_limit5 and c_limit6, then the assistance function can be executed without restrictions with the current map information KI, provided that the check of the minimum and maximum distance values d_min and d_max was positive, i. these lie within the predetermined distance limit values d_limitl and d_limit2.

If the determined minimum and maximum curvature values c_min, c_max lie within further prescribable curvature limit values c_limit7 and c_limit8, then the map information KI is taken into account only to a limited extent so that the assistance function can be executed with restrictions.

If the determined values of the minimum and maximum curvature c min or c max are outside the predetermined values Curvature limits c_limit7 and c_limit8, so the current map information KI remain unconsidered, ie the assistance function is performed without map data KI. The curvature limits c_limit5, c_limit6, c_limit7 and c_limit8 can also be dependent on the absolute values of the curvatures c, so that z. B. for small curvatures c larger thresholds apply than for small ones.

In the event that the bandwidth to the distances d_max, d_min and / or the curvatures c_max, c_min permits an assistance function with limited card usage, a scaling of the function can be carried out, for example, as described below:

The vehicle target deceleration at corner entry may be reduced by a deceleration factor f_dec instead of the ideal deceleration value. The vehicle target acceleration at corner exit can be reduced by a speed factor f_acc. In this case, the delay factor f_dec and / or the

Speed factor f_acc be selected in proportion to the map quality.

The times or points at which the delay phase ends may be as follows:

f_dec_d * d_min [2]

be moved, wherein the delay factor f_dec_d is fixed or determined depending on the map quality Q can be determined.

The times or places to which the

Acceleration phase begins, can according to the following condition:

f acc d * d max [3] be moved, the speed factor f_acc_d is fixed or determined depending on the map quality Q can be determined.

Of course, only courses s are used, which were driven according to the forecast by the navigation system 1 also. D. h., That during a path change z. B. by leaving the vehicle from a predicted route s no evaluation can be made. Likewise, it is possible to start the evaluation and correction when changing the road or changing to a road with a different road class from the beginning, or to change to certain values for the road or road class.

The correction of the map information KI, z. B. with respect to the distances d or bends c can also be done slowly by means of a low-pass filter or similar methods (eg., Incremental addition).

A resumption of the function with map support can be done with the same algorithms, but modified limits d_limitl to d_limit4, c_limit5 to c_limit8. In addition, the resumption may depend on the specification of the number of cycles or times or events, so that only after expiry of predetermined times and / or when predetermined events occur one of the assistance functions and / or the route prognosis take into account and use the current map information KI. The tolerance limits for switching off or functional degradation may differ from those for recovery. This also applies to the observation periods or the last traveled distance s_loesch.

In addition to the acquired driving data and driving information FI, interpolations between the recorded and measured driving data can be used. It is also possible that the method is shortened by one or more steps.

The scaling factor f_c_opt can also be determined differently for left and right-hand curves and used for correction.

In addition, gradient and incline information or altitude data which are stored as map information KI can be taken into account in the navigation method according to the invention, so that the carbon dioxide emission can be reduced in particular by appropriate control of a hybrid vehicle.

LIST OF REFERENCE NUMBERS

1 navigation system

2 processing unit

3 data storage

4 wheel speed sensor

5 yaw rate sensor

6 lateral acceleration sensor

7 data receiving device

8 display unit

9 Driver assistance system

c Curvature c_map Map curvature c_fzg Vehicle curvature c_limit5 to c_limit8 Curvature limits d Distances d_map Map distance d_fzg Travel distance d_limitl to d_limit4 Distance limits

FI vehicle information

KA curve beginning

KE curve end

AI card information

K_d distance-related correction factor

K_c curvature-related correction factor pos_map map position pos_fzg driving position

Q quality s distance s_map map distance s_mapθ distance traveled s_fzg distance s_fzgθ distance traveled s_loesch last distance traveled

S control signal

Claims

claims

Method for operating a navigation system (1), in particular a navigation system (1) for a vehicle, in which current map information (KI) and current vehicle information (FI) are detected and analyzed, on the basis of which a current route position (s_pos) and / or preceding route (s, map s_map, route s_fzg) are determined, based on a comparison of the current vehicle information (FI) with the current map information (KI) the quality (Q) of the current map information (KI) is determined, characterized in that a comparison of current map information (KI) and corresponding current vehicle information (FI) at least one degree of quality (Q) of the current map information (KI) is determined, wherein for determining the current route position (s_pos) and / or the preceding route (s ) the current map information (KI) according to the determined degree quality (Q).

2. The method according to claim 1, characterized in that the current map information (KI) unrestricted or be taken into account or disregarded.

3. The method according to claim 1 or 2, characterized in that the degree of quality (Q) of the current map information (KI) is determined continuously.

4. The method according to any one of the preceding claims, characterized in that the extent of consideration of the current map information (KI) is continuously adjusted in dependence on the continuously determined degree of quality (Q).

5. The method according to any one of the preceding claims, characterized in that in unequal sizes of vehicle information to be compared (FI) and map information (KI) the relevant vehicle information (FI) in the current map information (KI) corresponding vehicle information (FI_korr) are converted.

6. The method according to any one of the preceding claims, characterized in that as a preceding route (s) a navigation or route (s_fzg) and / or a map route (s_map) are determined or will.

7. The method according to any one of the preceding claims, characterized in that the respective route (s) includes a route to be traveled with curves and lines, the route based on map information (KI), in particular on the basis of radii (r) and distances (d d_map, d_fzg) to the Radii (r) or curvatures (c, c_map, c_fzg) and distances (d, d_map, d_fzg) to the curvatures (c, c_map, c_fzg) or road coordinates or landmarks will be described.

8. The method according to any one of the preceding claims, characterized in that as further map information (KI) curve start (KA), curve end (KE) and / or vertices (SE) are determined.

9. Method according to one of the preceding claims, characterized in that a map distance (d_mapθ) and / or travel distance (d_fzgθ) traveled by the start of the journey (mapO, fzgO) and / or by a previous route position (pos_map, pos_fzg) are determined or becomes.

10. The method according to any one of the preceding claims, characterized in that the determined current and / or previous map information (KI) and / or vehicle information (FI), in particular driving distance (s_fzg), map distance (s_map), beginning of curve (KA), end of curve ( KE), vertices (SE), curvatures (c), such as map curvatures (c_map), driving curves (c_fzg) and / or distances (d), such as map distances (d_map), driving distances (d_fzg) based on the covered map and / or route (s_mapθ, s_fzgθ), in particular a last traveled distance (s_loesch) are analyzed and at least one associated correction value (K_d, K_c) is determined.

11. The method according to claim 10, characterized in that a bend-related correction value (K_c) based on differences of current, variously determined

Curves (c, c_map, c_fzg) is determined taking into account the covered map and / or route (s_mapθ, s_fzgθ).

12. The method according to claim 11, characterized in that the determined Kartenkrummung (c_map) is corrected on the basis of the determined mean deviation (c_mittel) of the Krümmungswerte (c_map, c_fzg).

13. The method according to claim 12, characterized in that the bandwidth (c_min, c_max) of the mean deviation (c_mittel) of the card buckling (c_map) and / or corrected Kartenkrummungen (c_map_k) is determined and checked by means of predetermined Krümmungsgrenzwerte (c_limit5 to c_limit8) ,

14. The method according to claim 13, characterized in that the quality (Q) based on the over- and / or shortfall of the

Curvature limits (c_limit5 to c_limit8) is determined.

15. The method according to any one of claims 10 to 14, characterized in that a distance-related correction value (K_d) based on differences of current, variously determined distances (d, d_map, d_fzg) taking into account the covered map and / or route (s_mapθ, s_fzgθ) is determined.

16. The method according to claim 15, characterized in that the determined map distance (d_map) is corrected on the basis of the determined mean deviation (d_mittel) of the distance values (d_map, d_fzg).

17. Method according to claim 16, characterized in that the bandwidth (d_min, d_max) of the average deviation (d_mittel) of the map distances (d_map) and / or corrected map distances (d_map_k) is determined and checked on the basis of predefinable distance limit values (d_limitl to d_limit4) ,

18. The method according to claim 17, characterized in that the quality (Q) based on the over- and / or shortfall of the

Distance limits (d_limitl to d_limit4) is determined.

19. Method according to one of the preceding claims, characterized in that the assessment restarts and correction values are deleted and redetermined when a road, a road class, a road type, a region and / or a country on a route (s), especially the

Driving distance (s_fzg), leaving or changing.

20. The method according to any one of the preceding claims, characterized in that for a road, a road class and / or a road type of a route (s), in particular the Travel distance (s_fzg) before certain correction values are adopted as start values.

21. Navigation system (1), in particular navigation system for a vehicle, comprising at least one

Data memory (3), at least one display element (8) and a data receiving device (7) and a processing unit (2), characterized by the implementation of a method according to one of claims 1 to 18.

22. Navigation system according to claim 21, characterized in that the processing unit (2) comprises means for determining a current one

Track position (s_pos) and / or a preceding route (s) based on current map information (KI) and current

Vehicle information (FI) and the determination of the current route position (s_pos) and / or the preceding route (s) a determined degree of quality (Q) of the current map information (KI) is carried out accordingly.