DE102018209982A1 - Method for providing data for a vehicle - Google Patents

Abstract

The invention relates to a method for providing data for a vehicle (52), in which possible paths are determined on the basis of a current position (42) of the vehicle (52), a probability is assigned to the determined paths and then at least one path in Dependence of the assigned probabilities is selected and at least one path data is generated for this.

Description

The invention relates to a method for providing data, in particular card-based data, for a vehicle and an arrangement for performing the method.

State of the art

Many motor vehicles are already equipped with a navigation system. This usually accesses a position sensor and a digitized map of a road network in order to calculate a route from the current position to a predetermined destination. The calculated route is then communicated to the driver of the motor vehicle in a suitable manner in order to guide him along this route to the destination.

In addition, motor vehicles are usually equipped with a large number of sensors, the detected signals of which are fed to one or more vehicle assistance systems, which in turn support and relieve the driver in guiding and controlling the vehicle. These systems can be divided into safety and comfort systems. Driver assistance systems can actively intervene in the vehicle control system, in order to avoid accidents entirely in critical situations, or at least to keep the consequences of the accident as low as possible for those affected.

However, the sensors of the driver assistance systems only detect an event that has already occurred. In order to be able to predict possible future events, a so-called electronic horizon can be formed from the position of the motor vehicle and the map information available for the navigation system. The electronic horizon contains information taken from the digitized map about the streets in the vicinity of the motor vehicle. Information about possible future influences from the vehicle environment can thus be made available to the individual driver assistance systems.

The electronic horizon, which predicts the route of the motor vehicle in the near future, serves as the basis for various assistance or information functions in the motor vehicle. The electronic horizon is typically based on a heuristic, i. H. an algorithm, which is characterized by a low computing effort and short running time, generated on the basis of map information of the road network in the vicinity of the current position of the motor vehicle.

The publication EP 1 775 552 A2 describes a method for providing an electronic horizon for driver assistance systems, in which the current position of the motor vehicle is determined and map information from a digitized map of a road network is used to generate data for the electronic horizon based on the map information in the vicinity of the current position of the motor vehicle, which are forwarded to the driver assistance systems. In order to provide a flexible electronic horizon, it is provided that the data is generated divided into several data units with different amounts of information. The electronic horizon is introduced as a procedure to supply control units with relevant map-based data on the route ahead of their own vehicle.

The publication DE 10 2009 028 070 A1 describes a method for providing an electronic horizon for a driver assistance system of a motor vehicle, in which the current position of the motor vehicle is determined and the electronic horizon is generated using a heuristic on the basis of map information of the road network in the vicinity of the current position of the motor vehicle. A probability assessment of the heuristic is carried out and an accuracy of the heuristic is determined. The electronic horizon is thus generated with the aid of a heuristic on the basis of map information from the road network in the vicinity of the current position of the motor vehicle.

The publication DE 10 2011 083 375 A1 describes a method for the provision of traffic telematics information about the route of a vehicle which is moved in a road system with several roads, the roads being connected between road connection points, and the method comprising at least the steps of determining and assigning a probability to a respective road connection point which the vehicle approaches the road connection point, and the transmission of the road connection points that are more likely to be traveled. The method presented serves for the efficient coding of possible upcoming routes or path segments in the road network.

With the electronic horizon, control devices in the vehicle are now supplied with map-based data, such as speed limits for a function for automated longitudinal control. For this purpose, the electronic horizon is calculated in the navigation component by using the map located in the navigation map.

• - Reduzierte Hardware-Anforderungen an das Fahrzeug bzw. fahrzeugseitige Systeme. Der elektronische Horizont und darauf basierende Informations- und Assistenzsysteme können in Fahrzeugen verfügbar gemacht werden, in denen keine Navigationskomponente vorgesehen ist. Damit sinken auch die Hardware-Anforderungen an das Fahrzeug bzw. fahrzeugseitige Systeme, was eine Reduzierung von CPU- und Speicherkosten mit sich bringt.
• - Verwendung stets aktueller Kartendaten auf dem Backend. Da der elektronische Horizont direkt auf dem Backend berechnet wird und dem Backend stets die aktuellen Kartendaten vorliegen, werden Fahrzeugfunktionen stets mit aktuellen kartenbasierten Daten versorgt. Es entfällt damit auch der Aufwand, eine Karte im Fahrzeug durch Updates zu aktualisieren.
• - Gesteigerte Dateneffizienz. Möchte man in einer Alternativlösung eine stets aktuelle Karte im Fahrzeug mitführen, so ist es hierzu üblicherweise erforderlich, ganze Kacheln z. B. eine NDS-Karte (NDS: Navigation Data Standard) beispielsweise über Mobilfunk zu aktualisieren. In einer Kachel befinden sich in der Regel jedoch wesentlich mehr Daten, als zur Befahrung einer Strecke in der Kachel bzw. in dem durch die Kachel abgedeckten Gebiet erforderlich sind. Unter einer Kachel ist ein rechteckiges Flächenelement zu verstehen, das durch Unterteilung der Karte entsteht. Es werden bei diesem Ansatz also wesentlich mehr Daten heruntergeladen als erforderlich. Der elektronische Horizont, der von einem Backend bereitgestellt wird, liefert dagegen konzeptionell vorzugsweise lediglich die Daten, die für die vorausliegende Strecke zweckmäßig benötigt oder unbedingt erforderlich sind.

In the future, it should be possible to supply vehicle functions with an electronic horizon, which is provided by a backend system. A backend system represents a server Infrastructure that, for example, via wireless communication, e.g. B. cellular, is connected. In this context, one also speaks of a cloud-based electronic horizon. The advantages are:

• - Reduced hardware requirements for the vehicle or vehicle systems. The electronic horizon and information and assistance systems based on it can be made available in vehicles in which no navigation component is provided. This also reduces the hardware requirements for the vehicle or vehicle systems, which means a reduction in CPU and memory costs.
• - Use of current map data on the backend. Since the electronic horizon is calculated directly on the backend and the current map data is always available to the backend, vehicle functions are always supplied with current map-based data. There is also no need to update a map in the vehicle with updates.
• - Increased data efficiency. If, in an alternative solution, you would like to carry a map that is always up-to-date in the vehicle, it is usually necessary for this to complete tiles. B. to update an NDS card (NDS: Navigation Data Standard) for example via mobile radio. However, there is usually much more data in a tile than is required to travel a route in the tile or in the area covered by the tile. A tile is a rectangular surface element that is created by dividing the map. This approach means that significantly more data is downloaded than is necessary. The electronic horizon that is provided by a backend, on the other hand, conceptually delivers only the data that is expediently required or absolutely necessary for the route ahead.

• - Robustheit gegenüber Mobilfunkabbrüchen,
• - geringe erforderliche Kommunikationsbandbreite.

The following requirements for the so-called cloud-based electronic horizon are also to be mentioned:

• - robustness against mobile phone abortions,
• - low communication bandwidth required.

Disclosure of the invention

Against this background, a method according to claim 1, an arrangement according to claim 10, a computer program with the features of claim 11 and a machine-readable storage medium according to claim 12 are presented. Embodiments result from the dependent claims and from the description.

With the method presented, it is possible to supply a vehicle with data, in particular card-based data, which are provided, for example, by an external unit. The method presented enables in particular an efficient transmission of an electronic horizon from a backend system.

For this purpose, it is provided that possible paths are determined taking into account the current position of the vehicle. A probability is assigned to each of the determined paths. The travel profile and thus the behavior of the driver in the past can also be taken into account. Then at least one path is selected depending on the assigned probabilities. Data, for example map-based data, such as an electronic horizon, are generated for this at least one path.

If the data is provided outside the vehicle, it can then be transmitted to the vehicle or to a system operated by the vehicle.

The data can generally be provided in the vehicle. Alternatively, it can be provided that the data are provided by a unit external to the vehicle and then transmitted to the vehicle or to a system operated on the vehicle side.

A technical solution is presented here that enables an efficient transmission of data, in particular map-based data, such as an electronic horizon and / or map data, from a back-end system to a vehicle. In this context, an algorithm is presented that selects or selects a filtering of relevant route sections, whereby the individual travel profile of the vehicle user can be taken into account.

In particular, a new method for the efficient selection and coding of card-based data to be transmitted is presented in order to meet the aforementioned requirements of the cloud-based electronic horizon.

The arrangement presented serves to carry out the method and typically comprises components for carrying out the calculations of the probabilities and for carrying out the selection of the paths as a function of the probabilities. These components have access to data storage in which, for example, trip profiles, map data and electronic horizons are stored. These data memories can also represent components of the arrangement individually, in any combination or together. However, this is not absolutely necessary since the arrangement should only be set up to access the data memories.

Further advantages and refinements of the invention result from the description and the accompanying drawings.

It goes without saying that the features mentioned above and those yet to be explained below can be used not only in the combination specified in each case, but also in other combinations or on their own without departing from the scope of the present invention.

list of figures

• 1 shows components of the arrangement for performing an implementation of the method described.
• 2 shows an embodiment of the method in a flow chart.

Embodiments of the invention

The invention is shown schematically in the drawings using embodiments and is described in detail below with reference to the drawings.

1 shows a schematic representation of units of an arrangement, the total with the reference number 10 is designated. This comprises units in a back-end system 50 which a unit in a vehicle 52 assigned.

The illustration shows a first component, LearningDrivingPatterns 12 , which is used to learn driving patterns or driving profiles of different drivers. This first component 12 thus records driver driving patterns over a certain period of time and can also continuously adapt them. Furthermore, a first data store is LearnedDrivingPatterns 14 , in which the driving patterns or driving profiles are created, and a second data memory MapData 16 , in which a map of the road network is stored.

Furthermore, a second component MPP prognosis (= Most Probable Path Prediction) 20 to calculate possible paths, a third component MPP-Selection (= Most Probable Path Selection) 22 to select paths and a fourth component eHorEncoding 24 intended for coding an electronic horizon. This becomes a third data memory eHorData 30 in the vehicle 52 provided. In the second component 20 go a minimum length L _{eH, min} . 40 of the electronic horizon and a vehicle position Veh-Pos 42 on. In the third component 22 goes a probability value X% 44 on.

• Ist die erforderliche Vorausschau, d. h. die vorausliegende Strecke entlang des elektronischen Horizonts ab aktueller Fahrzeugposition Veh-Pos 42, des elektronischen Horizonts zur Ermöglichung einer Fahrzeugfunktion D_Vor,erf und soll ein Mobilfunkausfall über die Strecke D_offline abgefangen werden, so ist der elektronische Horizont mit einer Mindestlänge von $${\text{L}}_{\text{eH}\text{,min}}={\text{D}}_{\text{Vor}\text{,erf}}+{\text{D}}_{\text{offline}}$$
  
  vom Backend an das Fahrzeug oder fahrzeugseitige System zu übermitteln. Der vorgeladene elektronische Horizont wird im Fahrzeug in dem dritten Datenspeicher eHorData 30 gespeichert.

In the event of a cellular failure, the following can be reacted to:

• Is the required foresight, ie the route ahead along the electronic horizon from the current vehicle position Veh-Pos 42 , the electronic horizon to enable a vehicle function D _{Before, req} and is said to be a cellular failure over the route D _offline be intercepted, so is the electronic horizon with a minimum length of $${\text{L}}_{\text{eH}\text{, min}}={\text{D}}_{\text{In front}\text{, erf}}+{\text{D}}_{\text{offline}}$$
  
  to be transmitted from the backend to the vehicle or vehicle-side system. The preloaded electronic horizon is stored in the vehicle in the third data memory eHorData 30.

The data that are transmitted to the vehicle are thus generated in such a way that this information relates to the route D _Offiine contain.

berechnet werden.If there is a cell phone availability card and if it is used to forecast the entry into a cell phone hole, this cell phone hole can be used over the route D _MFoff which are already _preloading the electronic horizon by appropriate adaptive parameterization of the value of D _offline = D _MFoff and thus indirectly $${\text{L}}_{\text{eH}\text{, min}}={\text{D}}_{\text{In front}\text{, erf}}+{\text{D}}_{\text{offline}}$$

be calculated.

• Die Auswahl der zu übermittelnden vorausliegenden Pfadsegmente des elektronischen Horizonts erfolgt angepasst an das individuelle Fahrtprofil des Fahrzeugnutzers. Damit werden Pfadsegmente bevorzugt, die häufig vom Fahrer befahren werden. Die Nutzungswahrscheinlichkeit genutzter Pfade wird dazu durch die erste Komponente LearningDrivingPatterns 12 erlernt und in dem ersten Datenspeicher LearnedDrivingPatterns 14 gespeichert.

Solutions for reducing the required communication bandwidth of the cloud-based electronic horizon can also be provided:

• The selection of the preceding path segments of the electronic horizon to be transmitted is adapted to the individual travel profile of the vehicle user. Path segments that are frequently traveled by the driver are thus preferred. The likelihood of use of the paths used is determined by the first component, LearningDrivingPatterns 12 learned and in the first data store LearnedDrivingPatterns 14 saved.

• In einem ersten Schritt 100 erfolgt die Berechnung ausgehend von der gegenwärtigen Fahrzeugposition (Veh-Pos 42 in 1) sämtlicher möglicher Pfade, vorzugsweise unter Ausschluss von Ringschlüssen, mit einer Pfadlänge von jeweils L_Pfad = L_eH,min. In der Regel erfolgt die Pfad-Berechnung auf Basis einer Karte des Straßennetzes, z. B. im NDS-Format (NDS: Navigation Data Standards), die im zweiten Datenspeicher MapData (Bezugsziffer 16 in 1) abgelegt ist.

2 shows a possible execution of the presented method in a flow chart. The illustration shows that trip profiles are user-related or e.g. B. can be abstracted for a user group. Based on this learned Trip profiles are calculated by the second component MPPPrognosis (reference number 20 in 1 ) the possible paths ahead in the road network, according to the following scheme:

• In a first step 100 the calculation is based on the current vehicle position (Veh-Pos 42 in 1 ) all possible paths, preferably excluding ring closures, with a path length of L _path = L _{eH, min} . As a rule, the path is calculated based on a map of the road network, e.g. B. in NDS format (NDS: Navigation Data Standards), the MapData (reference number 16 in 1 ) is filed.

In a second step 102 The probability of use is assigned to each path on the basis of the user's learned travel profile in the first data store LearnedDrivingPatterns (reference number 14 in 1 ). In the event that no travel profiles have been learned for a path, z. B. a conventional heuristic can be used. This provides, for example, that the electronic horizon is generated on the basis of map information from the road network in the vicinity of the current position of the motor vehicle. A heuristic probability assessment can be carried out and a heuristic probability of occurrence can be determined. The electronic horizon is thus generated with the aid of a heuristic on the basis of map information from the road network in the vicinity of the current position of the motor vehicle.

Note that the sum of the probabilities of all paths is 100%.

In a third step 104 the paths are sorted according to their probability of use, typically the most probable path in the first place.

In a fourth step 106 the cumulative probability is formed by adding the usage probabilities of the paths over the paths in order of their probability.

In a fifth step 108 the selection or selection of the first N_x paths takes place, which after the cumulative probability formation leads to a cumulative probability of X%, e.g. B. 90%. This selects the most likely paths of the user, so that the driver will move within the selected paths by selecting a few paths with the probability of X%. A kind of threshold is thus introduced, which can be exceeded by the accumulated probabilities.

In a sixth step 110 will be in step five for that 108 selected paths N_x the electronic horizon is coded, typically using the component eHorEncoding (reference number 24 in 1 ) and transmitted to the vehicle. With a probability of 1-X%, the electronic horizon will not supply the vehicle with map-based data for the route traveled by the user. In this case, remedial action can be taken, for example, by reloading the electronic horizon for the route that is not yet supported when entering the corresponding route area or by setting a tolerable, sufficiently high value X%.

For redundancy-free coding of path segments, where a path segment describes an edge between two neighboring nodes; A path is made up of a combination of path segments, the electronic horizon and their relationship to one another are transmitted in the form of a list, e.g. B. in the form of a neighborhood list, a so-called adjacency list. A determination and assignment of a probability to a respective road connection point with which the vehicle approaches the road connection point and a transmission of the road connection points which are driven with increased probability can be provided. This enables the complete reconstruction of the tree structure of the path segments of the electronic horizon.

QUOTES INCLUDE IN THE DESCRIPTION

This list of documents listed by the applicant has been generated automatically and is only included for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent literature cited

• EP 1775552 A2 [0006]
• DE 102009028070 A1 [0007]
• DE 102011083375 A1 [0008]

Claims (12)

Method for providing data for a vehicle (52), in which possible paths are determined on the basis of a current position (42) of the vehicle (52), a probability is assigned to the determined paths and then at least one path depending on the assigned probabilities is selected and at least one path data is generated for this. Procedure according to Claim 1 , in which the data are provided by a unit external to the vehicle. Procedure according to Claim 2 , in which the data is provided to the vehicle (52) via mobile radio and in which, in the event of a mobile radio failure for a route D _offline, the data which are transmitted to the vehicle (52) are generated in such a way that this information relates to the route D Included _offline . Procedure according to Claim 3 , in which the entry into route D is forecast _offline using a mobile radio _availability card. Procedure according to one of the Claims 1 to 4 , in which map-based data are generated that represent an electronic horizon for the at least one selected path. Procedure according to one of the Claims 1 to 5 , in which the determined paths are sorted according to the assigned probabilities and a number of paths with the highest probabilities is selected from these. Procedure according to Claim 6 , in which the paths are selected so that the sum of their associated probabilities exceeds a threshold. Procedure according to one of the Claims 1 to 7 , in which data is reloaded. Procedure according to one of the Claims 1 to 8th , which takes into account the driver's travel profile. Arrangement for providing data for a vehicle (52) which is used to carry out a method according to one of the Claims 1 to 9 is set up. Computer program with program code means, which is set up to implement a method according to one of the Claims 1 to 9 to be executed when the computer program on a computing unit, in particular a computing unit in an arrangement (10) according to Claim 10 , is performed. Machine-readable storage medium with a computer program stored on it Claim 11 ,

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