A method for generating a most probable path for an advanced driver assistance system of a vehicle, a computer program product, a non-transitory

Abstract

A method for generating a most probable path for an advanced driver assistance system of a vehicle (10), comprising the steps of: (a) checking whether or not there is a junction to a plurality of road

Description

[0001] The present invention relates to the field of automobiles. In particular, the present invention relates to a method for generating a most probable path for an advanced driver assistance system of a vehicle according to the pending claim 1. Furthermore, the present invention relates to a corresponding computer program product, a corresponding non-transitory computer-readable storage medium, as well as to a corresponding electronic computing device. BACKGROUND INFORMATION

[0002] The advanced driver assistance systems (ADAS) may utilize information from a digital map for their function. For example, the speed limit for cruise-control can be recognized by a camera as well as extracted from the digital map. Furthermore, a sharp corner can also be extracted from the digital map.

[0003] A certain ADAS application predicts where the driver might go, which may be called the most probable path (MPP), even in case there is no specific destination navigation device, in sense the most probable path information to the ADAS device in the motor vehicle.

[0004] According to the state of the art a most probable path creator has to create a new most probable path when a driver does not drive along the present most probable path. Meanwhile, a most probable path creator requires some time as well as system resources in order to create the most probable path. Therefore, it is very important for the most probable path creator to create realistic most probable paths at a time as much as possible.

[0005] A loop path is one of the cases that the most probable path creator tries to avoid in the most probable path because a driver rarely drives in loop paths.

[0006] JR 2016 503 533 A provides a method of generating a predictable range for use by a ADAS of a vehicle includes using digital location-dependent data, driver data, and vehicle data to determine a likelihood that a different branch road will be selected at a decision point along a currently traveling road segment, and retrieving a probability that each branch road will be selected. The probability may be based on one or more of the angle of the branch road relative to the entry road, the road class of the branch road, the speed profile of the branch road, the history of the branch road selected by the vehicle at the determined point, and the history of the branch road selected by individual drivers or vehicles at the determined point. SUMMARY OF THE INVENTION

[0007] It is an object of the present invention to provide a method, a corresponding computer program product, a corresponding non-transitory computer-readable storage medium, as well as a corresponding an electronic computing device navigation device, by which an efficient way for estimating a most probable path is provided.

[0008] This object is solved by a method, a corresponding computer program product, a corresponding non-transitory computer-readable storage medium, as well as a corresponding electronic computing device according to the independent claims. Advantageous embodiments are presented in the dependent claims.

[0009] One aspect of the invention to a method for generating a most probable path (MPP) for an advanced driver assistance system of a vehicle by an electronic computing device of the vehicle, wherein the electric computing device comprises a GPS receiver, a database storing a map, and a most probable path creator, (a) It is checked whether or not there is a junction to a plurality of roads ahead in the route of the vehicle by referring to the map based on an information of current position of the vehicle obtained by the GPS receiver, (b) When there are a plurality of roads at the junction, roads that have already been explored as route candidates are excluded, (c) If there are unexplored roads at the junction, a road with the highest weighting as a route candidate by referring a weighting information of the road in the map is selected, and the selected road is added to the route candidates selected so far. (d) If there is no road that has not yet been explored at the junction, returning back to a previous junction is performed; (e) The previous steps (a)-(d) are repeated until a total length of the most probable path exceeds a predetermined length to generate the most probable path by the most probable path creator (MPP creator).

[0010] In particular, the present invention relates to a method and a device of predicting the most probable path to take, even if the destination is not entered. The purpose of this invention is to eliminate loop path and dead ends from the prediction of the path and generates the most probable path in an efficient manner.

[0011] The method is in particular performed inside of the vehicle, but it can also be performed in a server and the vehicle receives the predicted route from the server.

[0012] Map database is stored in the vehicle, but also the online map database can be available, for example map database is stored in a server. The database includes weighting information. The map provider decides the weighting information for each road at the junction.

[0013] Therefore, an efficient way for providing the most probable path by the electronic computing device is provided.

[0014] According to an embodiment the predicted most probable path is transmitted for a route planning of an assistance system of the motor vehicle. The assistance system can be provided as a so-called ADAS (advanced driver assistance system). Therefore, for example an at least in part assisted driving of the motor vehicle may be performed by the assistance system.

[0015] In another embodiment the most probable path is generated without a destination input for the vehicle. In particular, a user / driver of the motor vehicle may drive without inputting a destination to the navigation system. Therefore, the electronic computing device is configured for calculating / estimating the most probable path and may transmit this to the ADAS system for an advanced assisting of the driver.

[0016] In another embodiment the most probable path is generated such, that a loop of the motor vehicle on the route is prevented. In particular, it is provided, that the route is provided such that no loop has to be driven by the driver. Therefore, time consuming loops are prevented.

[0017] According to another embodiment roads are excluded, if the road is blocked to go ahead for the motor vehicle. For example, if the road provides a dead end or a construction site the road is excluded. Therefore, blocked routes can be excluded from the most probable path.

[0018] In another embodiment a length of excluded road candidates are subtracted from the total length of the most probable path. This has the advantage, that the most probable path can be predicted in an efficient manner, without using length which are excluded from the route.

[0019] According to another embodiment the most probable path is estimated depending on a current position of the vehicle. In particular, the current position may be captured by a global positioning system (GPS). Therefore, a precise estimating of the most probable path is provided.

[0020] In particular, the method is a computer-implemented method. Therefore, another aspect of the invention relates to a computer program product comprising program code means for performing a method.

[0021] A still further aspect of the invention relates to a non-transitory computer-readable storage medium comprising at least the computer program product according to the preceding aspect.

[0022] Furthermore, the present invention relates to an electronic computing device for predicting a route of a vehicle by referring to a map stored in a database, wherein the electronic computing device is configured for performing a method according to the preceding aspect. In particular, the method is performed by the electronic computing device.

[0023] The electronic computing device is configured for predicting a route of the vehicle by referring to a map and for generating a most probable path where the destination of the vehicle is not inputted. The electronic computing device therefore comprises a database storing the map wherein the map includes weighting information of the road. Furthermore, a GPS receiver is provided for obtaining information on position of the vehicle. The electronic computing device further comprises a path creator, in particular a most probable path creator, for performing the following steps until the total length of the most probable path exceeds a predetermined length: Obtaining information on the current position of the vehicle from the GPS receiver and checking whether or not there is a junction to a plurality of roads (links) ahead in the route of the vehicle based on the information on a current position by referring to the map stored in the database; when there are a plurality of roads at a junction, excluding roads that have already been explored as route candidates from selection; if there are unexplored roads at the junction, selecting a road with a highest weighting as a route candidate by referring a weighting information of road in the map database, and adding the selected road of the route candidates selected so far to create the most probable path; and if there is no road that has not yet been explored at the junction, returning back to a previous junction.

[0024] A still further aspect of the invention relates to a vehicle comprising at least the electronic computing device. The vehicle may be configured as a motor vehicle.

[0025] A computing unit / electronic computing device may in particular be understood as a data processing device, which comprises processing circuitry. The computing unit can therefore in particular process data to perform computing operations. This may also include operations to perform indexed accesses to a data structure, for example a look-up table, LUT.

[0026] In particular, the computing unit may include one or more computers, one or more microcontrollers, and / or one or more integrated circuits, for example, one or more application-specific integrated circuits, ASIC, one or more field-programmable gate arrays, FPGA, and / or one or more systems on a chip, SoC. The computing unit may also include one or more processors, for example one or more microprocessors, one or more central processing units, CPU, one or more graphics processing units, GPU, and / or one or more signal processors, in particular one or more digital signal processors, DSP. The computing unit may also include a physical or a virtual cluster of computers or other of said units.

[0027] In various embodiments, the computing unit includes one or more hardware and / or software interfaces and / or one or more memory units.

[0028] A memory unit may be implemented as a volatile data memory, for example a dynamic random access memory, DRAM, or a static random access memory, SRAM, or as a non-volatile data memory, for example a read-only memory, ROM, a programmable read-only memory, PROM, an erasable programmable read-only memory, EPROM, an electrically erasable programmable read-only memory, EEPROM, a flash memory or flash EEPROM, a ferroelectric random access memory, FRAM, a magnetoresistive random access memory, MRAM, or a phase-change random access memory, PCRAM.

[0029] Further advantages, features, and details of the invention derive from the following description of preferred embodiments as well as from the drawings. The features and feature combinations previously mentioned in the description as well as the features and feature combinations mentioned in the following description of the figures and / or shown in the figures alone can be employed not only in the respectively indicated combination but also in any other combination or taken alone without leaving the scope of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The novel features and characteristic of the disclosure are set forth in the appended claims. The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and together with the description, serve to explain the disclosed principles. The same numbers are used throughout the figures to reference like features and components. Some embodiments of system and / or methods in accordance with embodiments of the present subject matter are now described below, by way of example only, and with reference to the accompanying figures.

[0031] The drawings show in:

[0032] Fig. 1 a schematic block diagram according to an embodiment of a motor vehicle;

[0033] Fig. 2 a schematic flow chart according to an embodiment of the method;

[0034] Fig. 3 -7 show schematic flow process of creating most probable path according to an embodiment of the method

[0035] In the figures the same elements or elements having the same function are indicated by the same reference signs. DETAILED DESCRIPTION

[0036] In the present document, the word "exemplary" is used herein to mean "serving as an example, instance, or illustration". Any embodiment or implementation of the present subject matter described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

[0037] While the disclosure is susceptible to various modifications and alternative forms, specific embodiments thereof have been shown by way of example in the drawing and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

[0038] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion so that a setup, device or method that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or device or method. In other words, one or more elements in a system or apparatus preceded by “comprises” or “comprise” does not or do not, without more constraints, preclude the existence of other elements or additional elements in the system or method.

[0039] In the following detailed description of the embodiment of the disclosure, reference is made to the accompanying drawing that forms part hereof, and in which is shown by way of illustration a specific embodiment in which the disclosure may be practiced. This embodiment is described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

[0040] Fig.1 shows a schematic block diagram according to an embodiment of a vehicle 10, in particular of a motor vehicle. The motor vehicle 10 comprises at least a head unit 12 comprising at least one electronic computing device 58. According to the shown embodiment the electronic computing device 58 may comprise at least a processor 14 and a memory 16. Furthermore, the electronic computing device 58 may comprise a GPS receiver 18. The GPS receiver 18 is connected to a navigation application 20. Furthermore, the electronic computing device 58 may comprise a navigation application 20 and ADAS application 60. The navigation application 20 may comprise a software 22 as well as a database 24 comprising navigation maps 26 as well as resources 28. Furthermore, the GPS receiver 18 may be connected to an ADAS application 60, wherein the ADAS application 60 may comprise a MPP creator 30 (most probable path) and other logics 32. Furthermore, the ADAS application 60 may comprise a database 34 comprising at least high-definition maps 36 and resources 38. In this description, the resources means general software resource files. For example icons, photos, sounds, texts and so on.

[0041] Furthermore, the electronic computing device 58 may comprise a communication interface 40, wherein the communication interface 40 is connected to a further communication interface 42 of a server 44, for example for providing online maps. The server 44 may comprise a database 46 comprising at least navigation maps 48, high-definition maps 50 and resources 52.

[0042] Furthermore it is shown, that the ADAS application 60 is configured for communicating with assistance system devices 54 and 56.

[0043] Fig. 2 shows a schematic flow chart according to an embodiment of a method for predicting a route and generating a most probable path of the vehicle 10 by referring to a high-definition maps 36 stored in the database 34 by the electronic computing device 58 of the head unit 12 of the vehicle 10. The electronic computing device 58 can also refer the high-definition maps 50 in the database 46 in the server by wireless communication through the communication interfaces 40, 42. A road is represented as a “link” in a high-definition map. In a first step S1 the method starts. In a second step S2 it is checked, if the number of connected links to explore ahead is equal 1. If yes, a third step S3 is performed, wherein the highest weighting in a stack is pushed from the remaining candidate links. If not, a fourth step S4 is performed, wherein all explored links from the candidates to go ahead are excluded. Coming from the fourth step S4 a fifth step S5 is performed, wherein it is checked, if the number of remaining candidate links is higher or equal 1. If yes, the third step S3 is performed. If not, a sixth step S6 is performed, wherein a top link from the stack is popped. After that a seventh step S7 is performed, where a length of the popped link from the sum length of the most probable path is subtracted. From the seventh step S7 the second step S2 is performed again.

[0044] Coming from the third step S3 an eight step S8 is performed, wherein the length of the pushed link is added to sum the length of the most probable path. After the eighth step S8 a nineth step S9 is performed, wherein it is checked if the sum of the length of the most probable path is higher than the maximum length defined for the most probable path. If not, the second step S2 is performed. If yes, a tenth step S10 is performed, wherein the method ends.

[0045] Therefore, Fig. 2 shows the method for predicting a route of the vehicle 10 by referring to the high-definition map 36 stored in the database 34 by the Most Probable Path (MPP) creator 30. Obtaining information on the current position of the vehicle 10 is performed and it is checked whether or not there is a junction to a plurality of roads ahead in the route of the vehicle 10 based on the information on current position by referring to the high-definition maps 36 by the electronic computing device 58. When there are a plurality of roads at the junction, roads that have already been explored as route candidates are excluded from the selection by the electronic computing device 58. If there are unexplored roads at the junction, selecting a road with the highest weighting as a route candidate by referring a weighting information of the road in the high-definition map 36 in the database 34 is performed, and adding the selected road to the route candidates selected so far to create a most probable path by the electronic computing device 58 is performed. If there is no road that has not yet been explored the junction, returning back to a previous junction by the electronic computing device 58 is performed. The previous steps are repeated until a total length of the most probable path exceeds a predetermined length by the electronic computing device 58.

[0046] In particular, the proposed invention is in the area of the ADAS application 60 and describes a method for the most probable path creator 30. Which is kind of ADAS application 60 to avoid loop path in the most probable path using map attributes.

[0047] The solution therefore is a road is represented as a “link” L1 — L11 (Fig. 3 - Fig. 7) in the digital map and the most probable path is created by following the road with the highest probability when reaching intersection.

[0048] The link list of the most probable path is stored in a most probable path link stack 62. This links in the stack can be pushed / popped by the most probable path creator 30 and this operation continues until the sum of the most probable path length reaches the maximum most probable path length defined.

[0049] The most probable path creator 30 collects links L1 - L11 in the stack following the below rules in order to avoid loop path. If there is only one connected link ahead then the link is pushed in the stack. If there are more than one connected links then the highest weight of link in the stack is pushed, and the length of the pushed link is added into the sum length of the most probable path. If the link is blocked to go ahead for instance due to road dead end, construction, country boarder, end of map, then the link is popped from the stack until the top link has unexplored connected link. The length of the popped links are subtracted from the sum of the length of the most probable path. The popped links are excluded from the most probable path candidate links, so no considering it as a part of the most probable path link from next time is performed. The process steps are continued as long as the sum length of the most probable path is less than the maximum most probable path links defined in the system. The links list remaining in stack is the most probable path links which avoids loop path.

[0050] As shown in the Fig. 3 to Fig. 7, the most probable path creator works in reference to the information of the weight of connected links at each junction. In Fig. 3 a scenario with different junctions J1 -J3 is shown. Furthermore different Links L1 -L11 are shown. L2 has the weight 55 / 100 and L2 has the weight 45 / 100 at the junction J1. L4 has the weight 60 / 100 and L5 has the weight 40 / 100 at the junction J2. L7 has the weight 70 / 100 and L9 has the weight 30 / 100 at the junction J3. For example a combined link L1, L2, L4 and L6 may end in a dead end 64. Also the combined links L1, L2, L5, L7, L8 and the combined link L1, L2, L5 and L9 may end in a dead end 64. Just the link combination L1, L3, L10 and L11 may not end in a dead end 64. Furthermore in Fig. 3 the path link stack 62 is empty. Fig. 3 therefore, shows a beginning of the provided method.

[0051] In Fig. 4 a first probable path is computed. In particular the links L1, L2, L4 and L6 are computed. Because after the link L6 is a dead end 64, the algorithm goes back to the junction J2 and excludes the link L4 and L6.

[0052] After the example shown in Fig. 4 the algorithm proceeds with the example shown in Fig. 5. A new link combination L1, L2, L5, L7 and L8 is executed. As shown, this may also lead to a dead end 64. Therefore, L7 and L8 is excluded. In Fig. 6, the next link combination is computed. In particular, the combination L1, L2, L5 and L9 is tested. This may also end in a dead end 64. Therefore, all links despite L1 are excluded in the path link stack 62. Fig. 7, then shows the next step. As all links L2, L4, L5, L6, L7, L8, and L9 are excluded the next link combination L1, L3, L10 and L11 is tested. This may not end in a dead end 64. Therefore, this is computed as the most probable path. Reference signs 10 Vehicle 12 Head unit 14 Processor 16 Memory 18 GPS receiver 20 Navigation application 22 Software 24 Database 26 Navigation maps 28 Resources 30 Most probable path creator 32 Other logics 34 Database 36 High-definition maps 38 Resources 40 Communication interface 42 Further communication interface 44 Server 46 Database 48 Navigation maps 50 High-definition maps 52 Resources 54 ADAS device 56 ADAS device 58 Electronic computing device 60 ADAS application 62 Path link stack 64 Dead end S1 -S10 Steps of the method L1 - L11 Links

Claims

1. A method for generating a most probable path for an advanced driver assistance system of a vehicle (10) by an electronic computing device (58) of the vehicle (10), wherein the electric computing device (58) comprises a GPS receiver (18), a database (34) storing a map (36), and a most probable path creator (30), comprising the steps of:(a) checking whether or not there is a junction to a plurality of roads ahead in the route of the vehicle (10) by referring to the map (36) based on an information of current position of the vehicle (10) obtained by the GPS receiver (18);(b) when there are a plurality of roads at the junction, excluding roads that have already been explored as route candidates;(c) if there are unexplored roads at the junction, selecting a road with the highest weighting as a route candidate by referring a weighting information of the road in the map (36), and adding the selected road to the route candidates selected so far;(d) if there is no road that has not yet been explored at the junction, returning back to a previous junction; and(e) repeating the previous steps (a)-(d) until a total length of the most probable path exceeds a predetermined length to generate the most probable path by the most probable path creator (30).

2. The method according to claim 1, characterized in thatthe generated most probable path is transmitted for a route planning for an assistance system (54, 56) of the vehicle (10).

3. The method according to claim 1 or 2, characterized in thatthe most probable path is generated without a destination input for the vehicle (10).

4. The method according to any one of claims 1 to 3, characterized in thatthe most probable path in generated such, that a loop of the vehicle (10) on the route is prevented.

5. The method according to any one of claims 1 to 4, characterized in thatroads are excluded, if the road is blocked to go ahead for the vehicle (10).

6. A computer program product comprising program code means for performing a method according to any one of claims 1 to 5.

7. A non-transitory computer-readable storage medium comprising at least the computer program product according to claim 6.

8. An electronic computing device (58) for generating a most probable path for an advanced driver assistance system of a vehicle (10), comprising:- a GPS receiver (18) for obtaining an information of a current position of the vehicle (10);- a database (34) storing a map (36) which includes weighting information of roads in the map;- a most probable path creator (30) for generating the most probable path, wherein the electric computing device (58) is configured for performing a method according to any one of claims 1 to 5.

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