Method for predicting a driving route

Abstract

The present invention relates to a method for predicting a driving route (21-24) of a motor vehicle, in which a starting position (30) of the motor vehicle is determined. It is checked whether a starting position (30) of an earlier driving route (21-24) stored in a memory of the motor vehicle is located within a pre-given circle (40) around the starting position (30). A predicted driving route is selected from the stored driving routes.

Description

Technical field

[0001] The invention relates to a method for predicting a driving route of a motor vehicle. The invention further relates to a computer program for carrying out each step of the method and a machine-readable storage medium storing the computer program. Finally, the invention relates to an electronic control device configured to carry out the method. Background art

[0002] In order to comply with emission regulations, a diesel particulate filter is required in the exhaust line of a motor vehicle with a diesel engine. The particulate filter must be cleaned of its soot deposits at certain time intervals so that its flow resistance does not reduce the engine power. For this purpose, the soot layer is burned off, where carbon dioxide and water vapor are formed from the soot. The choice of the time point for initiating particulate filter regeneration is oriented, for example, towards the driving route section of the motor vehicle and the pressure difference caused via the particulate filter. At the same time, it must also be ensured that suitable framework conditions prevail during the entire regeneration period. The regeneration of the particulate filter is an exothermic process. When the motor vehicle transitions to coasting operation or idling, there is, for example, a risk that the exhaust mass flow rate decreases in the case of a highly loaded particulate filter and that the temperature in the particulate filter increases when the oxygen partial pressure is simultaneously increased, and this temperature increase can cause damage to the particulate filter.

[0003] JP 2003314250 A proposes to select the time point for initiating the regeneration of a particulate filter based on section information of a predicted driving route of a motor vehicle. Here, the prediction of the driving route is based on user input into the navigation system of the motor vehicle. Summary of the invention

[0004] In a method for predicting a driving route of a motor vehicle, first the starting position of the motor vehicle is determined. This can take place in particular with the aid of data from the global positioning system (GPS) detected by the navigation system of the motor vehicle. Subsequently, it is checked whether the starting position of an earlier driving route stored in the memory of the motor vehicle lies within a predefinable circle around the actual starting position. Then the predicted driving route is selected from the stored driving routes.

[0005] The method has the following advantages: The driving route can also be predicted independently of the user input of the motor vehicle driver. Exactly in the case of frequently traveled driving sections, since the driver finds the road even without the assistance of a navigation system, the driver often abandons entering the driving destination into the navigation system of the motor vehicle. The method utilizes the fact that drivers usually pass through specific driving sections again and again, such as the drive from their place of residence to their place of work, so that this information can be used for prediction. Here, a table of frequently traveled driving routes can be stored in the memory and used for prediction. It is assumed that a driver starting the motor vehicle from a known starting position or from near that starting position uses one of the driving routes usually starting from that starting position.

[0006] If the starting position is, for example, the driver's place of residence, then multiple stored driving routes will often start from that place of residence. To enable selection, preferably, the stored driving routes here have the time of their start of travel and / or the working day. Then, during selection, the current time and / or the current working day are compared with the time and / or the working day of the stored driving routes. Since the drive to the place of work is usually only started on working days and only around always similar times, and other drives, for example, to often keep social appointments, are usually also started on specific days and at specific times, it is possible in this way to select the most likely driving route of the motor vehicle from a set of potential driving routes.

[0007] To check whether the driving of the motor vehicle actually takes place on the predicted driving route, two embodiments of the method are preferred. In both embodiments, the stored driving routes are divided into segments:

[0008] In the first embodiment, if the motor vehicle reaches the end of a segment, the azimuth angle between the start of the segment of the stored driving route and the end of the segment of the stored driving route is determined and compared with the azimuth angle between the start of the segment of the stored driving route and the end of the segment of the actually traveled driving route. If the two azimuth angles are to differ by more than a pre-given difference, it is recognized that the motor vehicle deviates from the predicted driving route and the prediction is reset. In different embodiments of the method, various absolute reference systems, such as astronomical north, can be used for the azimuth here. In particular, the azimuth angle θ is calculated according to Equation 1:

[0009] (Equation 1)

[0010] Here, represents the difference between the longitudes at the start and at the end of the segment, represents the latitude at the start of the segment and Represents the latitude at the end of a section. The longitude and latitude can be determined here with the aid of GPS.

[0011] In a second preferred embodiment, if the motor vehicle reaches the end of a section, for the plurality of sections traveled, in particular for all sections traveled, the differences between the azimuth angles between the start and the end of the respective section of the stored travel route and between the azimuth angles between the start of the respective section of the stored travel route and the end of the respective section of the actually traveled travel route are compared separately. If the sum of the values of the differences exceeds a pre-given threshold, it is recognized that the motor vehicle has deviated from the predicted travel route and the prediction is reset. Here, the threshold is preferably pre-given according to the number of the summed values. In order to avoid false recognition of deviation from the predicted travel route, it is particularly preferred here that the larger the number of the summed values, the higher the threshold is selected. The first preferred embodiment only considers the deviation of the desired azimuth angle in the last section traveled, while in the second embodiment, multiple sections are considered. Compared with the action according to the first embodiment, this makes the evaluation of whether the motor vehicle is still on the predicted route more reliable on the one hand and more computationally intensive on the other hand.

[0012] The sections are preferably defined by points stored at the same linear intervals from each other. In an alternative preferred configuration, in order to better make full use of the storage space, the sections can have variable lengths. Here, it is appropriate to act such that the first section is selected to be shorter and the subsequent sections are selected to be longer. Thus, the route can be recognized faster at the start of the travel. The variable division is carried out according to the section index or according to the linear interval from the starting position. Here, each point defines the end of one section and the start of the next section. This enables the storage of a large number of travel routes with a large number of sections without having to generate a large amount of data for this purpose. By the way that the section length is not defined by the length of the actually traveled road section but instead by the linear interval, it is not necessary to intermediate store the exact route profile when detecting a new travel route. More precisely, it is sufficient to know the starting point of the current section and the current stopping location of the motor vehicle, and the starting point of the current section is simultaneously the end point of the previous section. Then, it can be determined by continuously recalculating the linear interval d according to formula 2: when the end of the section is reached and a new point must be stored. Formula 2 is the Haversine formula:

[0013] (Formula 2)

[0014] Here, R represents the radius of the earth. The variable c can be extracted from formula 3, and the variable a can be extracted from formula 4:

[0015] (Formula 3)

[0016] (Formula 4)

[0017] As in Formula 1, represents the difference in longitude, represents the latitude at the start of the segment, represents the latitude at the current position, and represents the difference in dimension.

[0018] To limit the amount of data accumulated, it is preferable to limit the number of segments stored for each driving route. If the motor vehicle travels a longer driving route than a pre-given maximum number of segments, in different embodiments of the method it may be provided that either the driving route is not stored or only the number of segments corresponding to the pre-given maximum number is stored, and it is supplemented only by the specific destination coordinates of the driving route. In yet another alternative embodiment, it may also be provided that the storage requirements for the driving route are limited by dynamically determining the number of segments for each driving route and only limiting the total storage requirements.

[0019] In addition to the length of the stored driving route, the high number of the driving routes may also result in an excessive amount of data being formed. Therefore, it is furthermore preferable to store the frequency of passing through the stored driving route for each stored driving route. Each time a stored driving route that has already been detected in the memory is passed through, the counter assigned to that driving route is incremented by one. If the number of stored driving routes exceeds a pre-given maximum number, then the driving route with the lowest frequency is deleted, because it is least likely that the driving route will be traveled again in the future in this case.

[0020] It is furthermore preferable to take the frequency into account when selecting the predicted driving route. If a plurality of earlier stored driving routes of the motor vehicle start from the starting position, it is especially assumed that the driving will most likely take place on the driving route that has been passed through most frequently in the past.

[0021] In particular, the predicted driving route can be used to select the time point for starting the regeneration of the exhaust particulate filter. Here, the length of the segment can preferably be selected according to the regeneration duration of the particulate filter installed in the motor vehicle.

[0022] A computer program is set up to perform each step of the method, especially when the computer program is running on a computing device or an electronic control device. This makes it possible to implement different embodiments of the method on an electronic control device without having to make structural changes to it. For this purpose, the computer program is stored on a machine-readable storage medium. By installing (Aufspielen) the computer program onto a conventional electronic control device, an electronic control device is obtained that is set up to predict the driving route of a motor vehicle by means of this method. Description of the Drawings

[0023] Embodiments of the present invention are shown in the drawings and are explained in more detail in the following description.

[0024] Figure 1 A motor vehicle is schematically shown, the driving route of which can be predicted by means of an embodiment of the method according to the present invention.

[0025] Figure 2 Shows the selection of the most likely driving route of a motor vehicle from a set of stored driving routes in an embodiment of the present invention.

[0026] Figure 3 Shows how in an embodiment of the present invention the starting position and the end position of a section of a driving route can be defined by means of its longitude and latitude on the earth.

[0027] Figure 4 Shows in a flowchart how in an embodiment of the present invention the driving route of a motor vehicle can be stored.

[0028] Figure 5 Shows in a flowchart how in an embodiment of the present invention the driving route of a motor vehicle can be predicted. Detailed Description of the Invention

[0029] Figure 1 A motor vehicle 10 is shown, which is driven by an internal combustion engine 11 in the form of a diesel engine. An exhaust particulate filter 13 is arranged in the exhaust gas line 12 of the internal combustion engine 11. An electronic control device 14 that controls the internal combustion engine 11 receives GPS data from a navigation device 15, which data indicates the position of the motor vehicle 10. In addition, section information is displayed to the driver 16 of the motor vehicle 10 by means of the navigation device 15.

[0030] In the electronic control device 14, information about the driving routes that the motor vehicle 10 has passed in the past is stored. Here, for each driving route, its starting position, its ending position, and other intermediate positions are stored at intervals of one kilometer straight line (Luftlinie) currently. The sections between two stored positions of a driving route respectively form segments of the driving route.

[0031] It shows in Figure 2 how the starting position 30 of the motor vehicle is identified by means of its GPS data after the motor vehicle 10 starts. Four driving routes 21 to 24 are stored in the electronic control device 14, and the starting positions of these driving routes are located in a circle 40 with a current radius of 500 m around the actual starting position 30 of the motor vehicle 10. Here, each of these driving routes 21 to 24 is assigned the working day and time when its respective driving starts. In an embodiment of the method according to the invention, now a selection is made from the four potential driving routes by comparing the current time and the current working day with the starting times and starting working days of the stored driving routes 21 to 24. The driving route 23 whose time and working day best match the current time and the current working day is assumed to be the most likely driving route of the motor vehicle, and it is predicted that the motor vehicle 10 will move forward on this driving route 23. Once the motor vehicle 10 has advanced a current straight-line interval d of 1 km, it is checked whether the motor vehicle is located on the predicted driving route 23. The possible positions that may be reached within this distance are shown in Figure 2 as a dashed circle around the starting position 30. Now the azimuth angle (Peilungswinkel) between the starting position 30 of the motor vehicle 10 and the current position is determined by means of formula 1, and this azimuth angle is compared with the azimuth angle between the starting position 30 and the stored first point 31. If these azimuth angles are consistent within a pre-given tolerance range, it is recognized that the motor vehicle 10 is still located on the predicted driving route 23. This check is repeated at the end of the next segment, where the point 31 where the new segment starts is used as the starting point for calculating the two azimuth angles. Starting from this point 31, the azimuth angles are calculated with respect to the new actual position of the motor vehicle 10 on the one hand and with respect to the end point 32 of this segment on the other hand, and a new comparison is made. This action is continued with the end points 33, 34, and 35 of the subsequent segments. Thus, for example, it can also be verified by the azimuth (Peilung) between points 33 and 34 that the motor vehicle 10 actually remains on the predicted route 23 and does not, for example, turn onto the driving route 24, which shares the section alignment with the predicted driving route 23 in the area from the starting position 30 to point 33.

[0032] The respective vehicle position is determined by means of GPS data. In Figure 3Exemplarily shown is how to define the latitude of the starting position 30 for a section segment between the starting position 30 and the point 31 indicating the end of the segment. and longitude as well as the latitude of the end point 31 of this segment and longitude for use in Formulas 1 and 4. The Earth radius R is used in Formula 2 to calculate the straight-line interval d.

[0033] In another embodiment of this method, the segments do not have a constant length of 1 km straight-line interval. Instead, the segments have variable lengths, where the first segment is selected to be shorter and the subsequent segments are selected to be longer. The variable division is either based on the segment index, such that the first five segments each have a length of 500 m straight-line interval, and all subsequent segments each have a length of 1 km straight-line interval.

[0034] If the motor vehicle 10 is traveling on a driving route that has not been stored in the electronic control unit 14, then in one embodiment of the method according to the invention, the driving route is stored according to Figure 4 the flowchart in. Since it is not clear at the start of the driving cycle whether it is a new route or a known route, the part of the method shown there is started as a standard in each driving cycle. To characterize this new driving route, all parameters related to the method of the starting point 30 of the route are detected. Here, it is the longitude and latitude of the starting position 30 as well as the time tt:tt when the driving started and the weekday W. These data are transmitted to the data collection step 60. Subsequently, it is calculated 52 by means of Formula 2: how large is the straight-line interval d that has passed since leaving the starting position 30. If the check 53 yields that this straight-line interval d is still less than the current threshold d of one kilometer s , then the calculation 52 is continuously continued. Once the straight-line interval d reaches the threshold d s , it is recognized that the end of the segment of the new driving route has been reached. The longitude and latitude of this end position are detected. In addition, the azimuth angle between the start and the end of the segment is calculated by means of Formula 1. When the end of the first segment is reached, this means determining the longitude and latitude of the first end point 31, and calculating the azimuth angle This data is also submitted to the data collection step 60. Subsequently, the continuous calculation of the straight-line interval d continues in step 52, where further calculations use the coordinates of the points defined in step 54 as the initial positions. For other segments, this is continued with a straight-line interval d of one kilometer until the end of the driving route is reached or until the number of segments reaches a pre-given maximum number, which is currently 30.

[0035] First, the position data and azimuth data collected in the data collection step 60 are examined 61: whether there is already another driving route in the memory 70 storing the driving routes traveled by the motor vehicle 10 so far, and the end position of this other driving route is within a circle with a current radius of 500 m around the end position of the currently determined driving route. If this is the case, the end position of the currently traveled driving route is corrected 62 so that it corresponds to the already known stored end position. Subsequently, another examination 63 is carried out: whether the storage of the new driving route exceeds the maximum number of storable driving routes, which is currently 20 for example. If this is the case, a deletion command 64 is sent to the memory 70, and by this deletion command, the driving route least traveled by the motor vehicle 10 is deleted among all the stored driving routes. Subsequently, the collected data of the new driving route is stored 65 in the memory 70, and this part of the method is ended 66. If it turns out to be a known driving route afterwards, steps 50 to 66 can be omitted and not stored in the memory 70.

[0036] In an embodiment of the method according to the invention, after the motor vehicle 10 starts 80, an attempt is made to predict the driving route of the motor vehicle 10 by means of the process shown in Figure 5 In the data detection step 81, the position data of the starting position 30 provided by the navigation system 15 is detected, i.e., the longitude of the starting position and its latitude In addition, the current time tt:tt and the current working day W are extracted from a clock (not shown) of the motor vehicle 10. This data is transmitted to the memory 70. In the memory, it is checked whether at least one driving route is stored, the starting position 30 of which lies within a circle 40 with a current radius of 500 m around the current starting position 30. If there are multiple suitable driving routes, the most likely driving route is selected based on the consistency of the time tt:tt and the working day W and the frequency of the respective routes. Then this most likely driving route is handed back 82 to the method. If the check 83 reveals that no suitable driving route can be handed back from the memory 70, the prediction is not possible and this part of the method ends. Otherwise, this driving route is detected 84 as the predicted driving route. This driving route is displayed to the driver 16 via the navigation system 15. In addition, in the memory 70, a counter is incremented for this driving route, which counter records the frequency of use of the stored driving routes. Subsequently, a continuous check 85 is carried out: whether the straight-line distance d covered by the motor vehicle 10 and calculable with the aid of formula 2 is so long that this reaches the end of a section of the predicted driving route. If this is to be the case, the position data of the end position of this section, i.e. the longitude and the latitude are requested in order to calculate on the one hand the azimuth between the starting position and the end position of the stored section and on the other hand the azimuth between the starting position of this section and the current vehicle position using formula 1. If the check 87 reveals that the difference between the two azimuths θ lies within a pre-given tolerance range, the monitoring of the driving route is continued for the next section using the check 85. Otherwise, it is recognized 88 that the motor vehicle 10 has deviated from the predicted driving route. This information is transmitted to the driver 16 via the navigation device 15. In addition, in the memory 70, the counter for this driving route is decremented again. Subsequently, this part of the method ends 89.

[0037] In a further embodiment of the method according to the invention, in step 86, the values of the deviations of the azimuths θ of all previously passed sections of the driving route are added to the value of the deviation for the current section. In the check 87, then this sum is compared with a threshold value which depends on the number of sections passed. As long as this threshold value is not exceeded, the method is continued for the next section using the check step 85. Otherwise, it is recognized 88 that the motor vehicle 10 has deviated from the predicted driving route.

[0038] As long as the motor vehicle 10 is located on the predicted driving route, the route information contained therein is used for planning the optimal start of regeneration of the exhaust particulate filter 10. To this end, the soot accumulation during driving, the average temperature in the exhaust system, and the time point optimal for particulate filter regeneration for the respective driving routes 21-24 have been determined and stored when storing the driving routes 21-24.

[0039] In one embodiment of the method according to the invention, the following possibility is furthermore provided: the driver 16 can delete the content of the memory 70 by means of an input in the navigation device 15. Thereby, data protection is ensured when the motor vehicle 10 is to be sold, for example.

Claims

1. A method for predicting a driving route (21 - 24) of a motor vehicle (10), wherein an initial position (30) of the motor vehicle (10) is determined (81), it is checked (83) whether the initial position (30) of an earlier driving route (21 - 24) of the motor vehicle (10) stored in a memory (70) lies within a predeterminable circle (40) around the initial position (30), and a predicted driving route is selected (84) from the stored driving routes. The stored driving route (21-24) is divided into segments, and if the motor vehicle (10) reaches the end of a segment, the azimuth angle ( ) between the start and the end of the segment of the stored driving route (21-24) is compared with the azimuth angle ( ) between the start of the segment of the stored driving route (21-24) and the end of the segment of the actually traveled driving route (21-24) (87). If the difference between the two azimuth angles (θ) is greater than a pre-given difference, it is recognized that the motor vehicle deviates from the predicted driving route and the prediction is reset (88), or The stored driving route (21 - 24) is divided into segments, and if the motor vehicle (10) reaches the end of a segment, then for a plurality of segments passed through, the azimuth angle between the start of the respective segment of the stored driving route (21 - 24) and the end of the respective segment of the stored driving route (21 - 24) is respectively compared with the azimuth angle between the start of the respective segment of the stored driving route (21 - 24) and the end of the respective segment of the actually traveled driving route (21 - 24) ( ), and if the sum of the values of the differences exceeds a pre-given threshold, it is recognized that the motor vehicle deviates from the predicted driving route and the prediction is reset (88). ).

2. The method according to claim 1, wherein Each stored driving route (21 - 24) has a time (tt:tt) and / or a weekday (W) at which it starts, and during selection (84), the current time (tt:tt) and / or the current weekday (W) are compared with the time (tt:tt) and / or the weekday (W) of the stored driving routes (21 - 24).

3. The method according to claim 1, wherein The threshold is predetermined according to the number of the summed values.

4. The method according to any one of claims 1 to 3, characterized in that The segments are defined by points (31 - 36) stored at the same linear interval (d) from one another.

5. The method according to claim 4, characterized in that, The linear interval (d) is calculated by means of the Haversine formula.

6. The method according to any one of claims 1 to 3, characterized in that The number of segments stored for each driving route (21 - 24) is limited.

7. The method according to any one of claims 1 to 3, characterized in that, For each stored driving route (21 - 24), the frequency of passage along the stored driving route is stored, and when the predeterminable maximum number of stored driving routes is exceeded, the driving route with the lowest frequency is deleted (64).

8. The method according to claim 7, wherein The frequency is taken into account during selection (84) of the predicted driving route.

9. The method according to any one of claims 1 to 3, characterized in that, The predicted driving route is used in order to select a time point for starting the regeneration of an exhaust particulate filter (13).

10. A computer program product, which is set up to carry out each step of the method according to any one of claims 1 to 9.

11. A machine-readable storage medium, on which the computer program product according to claim 10 is stored.

12. An electronic control device (14), which is set up to predict a driving route of a motor vehicle (10) by means of the method according to any one of claims 1 to 9.

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