Method for predicting availability of vehicle marker-based location and method for controlling a vehicle - Patents.com

Abstract

The present invention relates to a method (100) for predicting availability of landmark-based localization of a vehicle (401), the method (100) comprising: receiving (101) map data (412) of a landmark map (411) of a road traffic network; determining (103) a landmark (413) for at least one roadway (403) to be traveled by the vehicle (401) based on landmark information of the landmark map (411); calculating (105) an availability value of the landmark (413) of the at least one roadway (403) to be traveled by the vehicle (401) with respect to an availability criterion; and outputting (107) availability information comprising an availability value for the landmark (413) of the roadway (403) to be traveled.

Description

[Technical field]

[0001] The present invention relates to a method for predicting availability of a vehicle's landmark-based location.Furthermore, the present invention relates to a method for route planning for an autonomously controllable vehicle.Furthermore, the present invention relates to a method for controlling a vehicle. [Background technology]

[0002] Autonomous and highly automated driving is considered to be a trend of the future. For the orientation of an autonomously controllable vehicle, the mapping of the vehicle's surrounding area is of great importance. The localization of the vehicle is achieved in particular by matching corresponding indicia of the indicia map with objects located in the surrounding area of ​​the vehicle, which are detected through the surrounding area sensor. If such a type of localization is not possible because the corresponding objects are not detected through the surrounding area sensor during the journey, autonomous control cannot be performed. For the autonomous control of the vehicle, it is therefore crucial to select a route in which a sufficient number of objects are expected to be reliably detected for matching with corresponding indicia of the indicia map. Summary of the Invention [Problem to be solved by the invention]

[0003] It is therefore an object of the present invention to provide an improved method for predicting the availability of landmark-based location of a vehicle, an improved method for route planning for an autonomously controllable vehicle, and an improved method for controlling a vehicle. [Means for solving the problem]

[0004] This problem is solved by a method for predicting the availability of a landmark-based localization of a vehicle, a method for route planning for an autonomously controllable vehicle and a method for controlling a vehicle, respectively, according to the independent claims. Preferred embodiments are the subject of the dependent claims.

[0005] According to one aspect of the present invention, a method for vehicle index-based location availability prediction is provided, comprising: Receiving map data of a landmark map of a road traffic network, the landmark map including landmark information of a plurality of roadways drivable by a vehicle, the landmarks being configured to be detected by a vehicle traveling on the roadways through sensor data of a surrounding area sensor of the vehicle and used to locate the vehicle; determining a landmark based on landmark information of a landmark map for at least one roadway to be traveled by the vehicle; calculating an availability value of at least one roadway landmark to be traveled by the vehicle with respect to an availability criterion, the availability value representing a quantitative measure of the usefulness of the landmark for vehicle localization when the roadway is traveled by the vehicle; outputting availability information including an availability value for the indicator of the roadway to be traveled; Includes.

[0006] This allows realization of the technical advantage that an improved method for predicting the availability of a landmark-based localization of a vehicle can be provided. The method according to the invention serves in particular for route planning for a vehicle, for example for an autonomously controllable vehicle. For a route to be traveled by the vehicle, indices of a landmark map are determined for each roadway of the route and an availability value is calculated for each landmark. The availability value then represents a quantitative measure of the usefulness of the landmark for localization of the vehicle when the roadway of the selected route is traveled. The landmark of the landmark map is then useful for localization of the vehicle if the respective landmark can be detected by the vehicle via the surrounding area sensor when the vehicle travels on each roadway of the selected route. The landmark of the landmark map then corresponds to a corresponding object in the surrounding area. The object may be arranged along each roadway to be traveled by the vehicle. The object may be arranged, for example, on the roadway edge of the roadway to be traveled. However, depending on the position of the vehicle on the roadway, the type of surrounding area sensor or the conditions of the surrounding area, such as weather conditions or traffic volume, not all objects can be identified through the surrounding area sensor of the vehicle at any time or each time the vehicle passes over the roadway and therefore can be used for the vehicle's localization. After the availability values ​​have been calculated for a number of indicators of the various roadways, corresponding availability information for the indicators of the roadway to be traveled is output. Using the output availability information, a corresponding route selection can be made based on the availability of indicators or objects located along the individual roadways of the selected route. For example, when planning a route, based on the availability information, the driver can be provided with a route with the highest availability of indicators in addition to the route with the shortest travel time. The availability here represents a value, for example a percentage or a probability value, that indicates how many objects can be identified or with what probability the detection of an object is expected.

[0007] According to one embodiment, the availability criteria includes a detectability of the indicator by the surrounding area sensor of the vehicle based on a sensor type and / or a directional characteristic of the surrounding area sensor of the vehicle, and calculating the availability value includes: Determining a sensor type and / or directional characteristics of at least one surrounding area sensor of the vehicle; determining the detectability of indicia of a roadway to be traveled by the vehicle for a sensor type and / or a directional characteristic of at least one surrounding area sensor; Includes.

[0008] This allows for the technical advantage that an accurate calculation of the availability of the indicators stored in the indicator map for the localization of the vehicle can be achieved. For this purpose, the availability criterion taken into account for the calculation of the availability value is defined as the detectability of the indicator by the surrounding area sensors of the vehicle to be driven along the roadway based on the sensor type and / or the directional characteristic of the surrounding area sensors of the vehicle. The sensor type of the surrounding area sensors can include the configuration of the surrounding area sensors as a camera sensor, a radar sensor, a lidar sensor. The directional characteristic is understood in the present invention as the corresponding directional sensitivity of the respective surrounding area sensor. In this way, based on the sensor type and the directional characteristic, the detectability of the indicators arranged along the roadway to be driven by the vehicle can be calculated for each surrounding area sensor of the vehicle. In this way, the detectability of the indicators by the respective surrounding area sensors can depend on the one hand on the relative position of the indicator to the vehicle, since the respective indicator is reflected in full, in part or not at all by the directional characteristic of the respective surrounding area sensor. The detectability of the indicia may also be given by the respective properties of the indicia, which, depending on their reflectivity, may be well or poorly or not at all detectable by various types of surrounding area sensors, e.g., an object that can be detected without problems by a radar sensor may be barely detectable by a camera sensor, for example, at night or in poor lighting, and therefore not useful for locating the vehicle.

[0009] According to one embodiment, the availability criterion comprises the detectability of the indicator by the surrounding area sensors of the vehicle, taking into account the traffic volume of the roadway to be traveled, and calculating the availability value comprises: Determining a traffic volume on a roadway to be traveled by a vehicle; determining the detectability of a roadway marking to be driven by the vehicle, whereby the occlusion of the roadway marking by traffic on the roadway is calculated; Includes.

[0010] This allows the technical advantage to be realised that a further improvement in the calculation of the availability information of the individual indicators of the indicator map can be realised. For this purpose, the detectability of the indicators by the surrounding area sensor of the vehicle is calculated, taking into account the traffic volume of the roadway to be travelled by the vehicle as an availability criterion. Since the individual indicators are usually arranged along the roadway to be travelled by the vehicle, the detectability of the indicators by the surrounding area sensor of the vehicle can be significantly impaired by other road traffic vehicles arranged in the surrounding area of ​​the vehicle in addition to the properties of the respective surrounding area sensor. If the traffic volume is high and a correspondingly large number of other vehicles are arranged in the surrounding area of ​​the vehicle, each of which prevents the detection of the indicators arranged at the edge of the roadway by the surrounding area sensor of the vehicle, this leads to a correspondingly low availability of the indicators of the respective roadway, since the indicators are not or cannot be detected by the surrounding area sensor due to the blocking other vehicles.

[0011] According to one embodiment, determining the traffic volume includes determining an average number of vehicles and / or an average speed per unit time on the roadway to be traveled by the vehicle, and determining the detectability includes: Calculating the average roadway indicator coverage based on the average number and / or speed of vehicles per unit time; Includes.

[0012] This allows the technical advantage to be realized that an accurate prediction of the traffic volume can be made for each roadway to be traveled by the vehicle, which in turn contributes to an improved determination of availability information for each roadway. Since the method according to the invention is primarily intended for route planning, in order to determine the availability of the indicators of the roadway to be traveled by the respective vehicle in the future, the traffic volume that is likely to occur on the respective roadway at the time when the roadway is traveled by the vehicle must be predicted. By calculating the average traffic volume in this way and, on the basis of this, calculating the average occlusion of the indicators by the vehicles of the traffic volume, an accurate and probabilistic prediction of the traffic volume that will occur can be realized for any time point located in the future. The average traffic volume can be calculated on the basis of the average number or average speed of the vehicles on the respective roadway.

[0013] According to one embodiment, calculating the availability value includes determining at least one characteristic of the indicator, the at least one characteristic including type of indicator, number of indicators, number of indicators of a particular type or category, spread and / or size of the indicator, reflective ability of the indicator; recognizability of the indicator, and determining the detectability is performed with respect to the at least one particular characteristic of the indicator, and a detectability corrected characteristic is calculated.

[0014] This allows for the technical advantage of achieving a more accurate calculation of the availability value or availability information. The detectability of the multiple indicators of the respective roadway can be further quantified through various indicator features, such as, for example, the type of indicator, the number of indicators or the spatial extent of the indicators. The features can then be extracted from the detected indicators, in particular by the implementation of a corresponding trained artificial intelligence. According to the invention, the features are in particular statistics that describe the set of indicators in their entirety.

[0015] According to one embodiment, calculating the availability value includes comparing at least one feature of the indicia of the map display with a corresponding detectability corrected feature.

[0016] This allows for the technical advantage of a more accurate calculation of the availability value. For this purpose, a comparison is made between the characteristics of the indicators of the indicator map and the characteristics of the corresponding indicators with corrected detectability. For this purpose, for example, the number of indicators in the indicator map can be compared or related to a correspondingly reduced number of indicators that is expected for a certain traffic volume. Due to the corresponding traffic volume and other vehicles that are respectively arranged in the surrounding area of ​​the vehicle, not all indicators on the roadway can be detected by the vehicle. In this way, a quantitative value for the availability of each indicator of the indicator map can be calculated from the comparison of the indicators of the indicator map with the calculated number of indicators that can be detected by the surrounding area sensor of the vehicle for the respective traffic volume.

[0017] According to one embodiment, a detectability determination is made for at least one known position of the vehicle on the roadway, or for different known positions of the vehicle on different travel lanes of the roadway.

[0018] This allows the technical advantage to be realised that the position-dependent detectability of the markings of the roadway to be travelled in each case can be determined. By taking the position into account, a further accuracy of the determination of the availability of the markings of the marking map can be realised. By taking into account the different travel lanes of the roadway to be travelled, an additional accuracy of the availability determination is further provided.

[0019] According to one embodiment, determining the detectability is performed by a corresponding trained artificial intelligence, which is trained on surrounding area sensor data of at least one surrounding area sensor of the vehicle, the surrounding area sensor data being recorded under a plurality of different traffic volumes during a plurality of trips of the vehicle along at least one roadway.

[0020] This may provide the technical advantage of allowing accurate, rapid and reliable determination of detectability.

[0021] According to one embodiment, the indicia are distinctive objects located on the edges of the roadway and include buildings, traffic signs, and roadway markings.

[0022] This allows for the technical advantage of allowing a comprehensive consideration of various indicators. In particular, the characteristic objects are given by any object detectable by radar, lidar, ultrasound and video suitable for localization, and may include directional arrows, lane markings, especially broken lines, trees and other vegetation, bridges, scattered structures such as poles and posts; elements for dividing roadways: paving stones, guard rails and bollards. This list should not be understood as exhaustive.

[0023] In addition, it is possible to detect and use indicators that cannot be named semantically but can be extracted from the raw data of the surrounding area sensor by a corresponding trained artificial intelligence. The artificial intelligence usually recognizes or detects key points in the surrounding area sensor data and assigns them a vector that represents the type of this point. Such key points that are unknown to the operator of the artificial intelligence and cannot be named semantically, but are nevertheless reliably detected by the corresponding artificial intelligence, can also be used as characteristic objects in the sense of the present invention.

[0024] According to another aspect, a method for route planning for an autonomously controllable vehicle is provided, comprising: - performing a method for vehicle index-based location availability prediction according to one of the above embodiments for a number of possible routes for the vehicle between a pre-determined start point and a pre-determined end point; determining a route for the vehicle that has the highest predicted availability of the vehicle's index-based location based on the performed availability prediction; Includes.

[0025] This can provide the technical advantage of improved route planning for autonomously controllable vehicles, providing not only the fastest route but also a route that anticipates the highest availability of indicators required for position determination and therefore the highest probability of fully autonomous control of the vehicle.

[0026] According to another aspect, there is provided a method of controlling a vehicle, the method comprising: implementing a method for route planning for an autonomously controllable vehicle; Driving the vehicle based on the selected route; Includes.

[0027] This allows for the technical advantage of improved control of autonomously controllable vehicles, which relies on improved route planning and improved availability predictions, having the technical advantages listed above.

[0028] According to one embodiment, driving the vehicle includes executing an operating plan, the operating plan including a driving maneuver of the vehicle that enables optimal utilization of the indicators of the indicator map.

[0029] This allows for the technical advantage of improved control of the vehicle to be realized. In particular, the vehicle can execute a driving maneuver that optimizes availability based on the result of the availability determination. For example, the driving maneuver can be intended to change the driving lane of the roadway to be traveled when a discrepancy is determined regarding the availability of the indicator for various driving lanes of the driving lane.

[0030] According to another aspect, there is provided a computing unit configured to perform a method for vehicle landmark-based localization availability prediction and / or a method for route planning for an autonomously controllable vehicle and / or a method for controlling a vehicle according to one of the above embodiments.

[0031] According to another aspect, a computer program product is provided, comprising commands which, when executed by a data processing unit, cause the implementation of a method for vehicle landmark-based localization availability prediction and / or a method for route planning for an autonomously controllable vehicle and / or a method for controlling a vehicle according to one of the above embodiments.

[0032] Embodiments of the invention will now be described with reference to the following drawings, in which: [Brief description of the drawings]

[0033] [Figure 1] FIG. 1 is a schematic diagram showing a system for controlling a vehicle. [Diagram 2] 1 is a flowchart of a method for vehicle index-based location availability prediction, according to one embodiment. [Diagram 3] 1 is a flowchart of a method for route planning for an autonomously controllable vehicle, according to one embodiment. [Figure 4] 4 is a flowchart of a method for controlling a vehicle, according to one embodiment. [Diagram 5] FIG. 1 is a schematic diagram illustrating a computer program product for implementing a method for vehicle index-based location availability prediction and / or a method for route planning for an autonomously controllable vehicle and / or a method for controlling a vehicle. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0034] FIG. 1 shows a schematic diagram of a system 400 for controlling a vehicle 401 .

[0035] Image A of Fig. 1 shows a vehicle 401 traveling on a roadway 403. Along the roadway 403, various indicia 413 are arranged. The indicia 413 are configured as various objects, e.g. buildings, plants, traffic signs, etc., which allow orientation of the vehicle 401. Furthermore, image A shows an indicia map 411. In the indicia map 411, the illustrated roadway 403 with the correspondingly arranged indicia 413 is displayed. Furthermore, image A shows a computation unit 415 on which an artificial intelligence 419 is installed.

[0036] Here, the computation unit 415 is configured to implement the inventive method for predicting the availability of index-based localization of the vehicle 401 .

[0037] Furthermore, the vehicle 401 comprises at least one surrounding area sensor 405, which allows surrounding area recognition of the surrounding area of ​​the vehicle 401. Furthermore, the vehicle 401 comprises a computing unit 417. The computing unit 417 may for example be configured for an autonomous or semi-automated control of the vehicle.

[0038] The computing unit 415 may be configured, for example, as an external server unit or as an external cloud server.

[0039] To implement the method of the invention for predicting the availability of an index-based localization of the vehicle 401, the calculation unit 415 first receives the index map 411 in the form of corresponding map data 412. Furthermore, the calculation unit 415 is provided with sensor information data 407 of the surrounding area sensors 405 of the vehicle 401. The sensor information data 407 may for example include information on the sensor type of the surrounding area sensors or on the directional characteristics of the respective surrounding area sensors 405 of the vehicle 401. Furthermore, the calculation unit 415 may be provided with traffic volume 409 data relating to the roadway 403. The traffic volume 409 data may be current data of the traffic volume at a given time point on one particular roadway or on a number of different roadways. Alternatively, the data may cover a past time point. Alternatively, the data may represent an average traffic volume. The data 409 may for example be transmitted for other vehicles that have traveled on the respective roadway at a given time point. Alternatively, the data 409 may be archived data. Furthermore, the data 409 may include the number and / or speed of vehicles.

[0040] To calculate the availability prediction for landmark-based positioning of the vehicle 401, the calculation unit 415 calculates an availability value for the roadway 403 to be traveled by the vehicle 401 based on the map data 412 of the landmark map 411 for the landmarks 413 located along the roadway 403, taking into account the availability criteria.

[0041] According to one embodiment, the availability criterion for each individual landmark 413 may take into account the detectability of the landmark 413 by the surrounding area sensors 405 of the respective vehicle 401 . For this purpose, information in the sensor information data 407 regarding the sensor type and / or directional characteristic 410 of the individual surrounding area sensors 405 can be taken into account. In this way, based on the indicia information of the indicia map 411, for each indicia 413 of the indicia map 411 arranged along the roadway 403 to be traveled by the vehicle 401, a corresponding detectability of the respective indicia 413 by the surrounding area sensor 405 can be calculated depending on the respective sensor type or directional characteristic 410 of the respective surrounding area sensor 405 of the vehicle 401. The detectability then represents a quantifiable amount by which the respective indicia 413 can be detected by the surrounding area sensor 405 of the vehicle 401. Such detectability can depend, for example, on the nature of the respective indicia 413 and / or on the nature of the surrounding area sensor. For example, the indicia 413 may have a favorable reflectivity for a lidar or radar sensor, but may be difficult to perceive for a camera sensor, for example due to low ambient light.

[0042] Alternatively or additionally, the detectability of the indicator 413 can be calculated taking into account the expected traffic volume on the respective roadway 403. Based on the corresponding data 409 of the current or average traffic volume expected on the respective roadway 403, the traffic volume can be calculated for the time when the vehicle 401 travels on the corresponding roadway 403. For the calculation, for example, the average speed or the average number of vehicles expected on the roadway 403 at a future time can be used for the calculation of the average occlusion. The average occlusion then represents the occlusion of the indicator 413 arranged at the edge of the roadway 403 by other vehicles that are arranged on average when traveling on the roadway 403 based on the traffic volume in the surrounding area of ​​the vehicle 401.

[0043] In image B, such a calculation of the detectability of individual indicators 413 is graphically shown for a surrounding area sensor 405 of a vehicle 401 travelling on a roadway 403. The vehicle 401 is arranged in the illustrated drawing in the left driving lane 404 of the roadway 403. Furthermore, three other vehicles of the expected traffic volume 409 are shown in the right driving lane 404 of the roadway 403. Furthermore, image B shows three directional characteristics 410 of three different surrounding area sensors 405 of the vehicle 401. Here, one directional characteristic 410 is directed towards the area ahead of the vehicle 401, whereas the other two directional characteristics 410 are directed towards the area behind the vehicle 401. In the illustrated drawing, the indicator 413 arranged on the right roadway edge of the roadway 403 is occluded by the other vehicles of the traffic volume 409 with respect to the surrounding area sensor 405 of the vehicle 401. This is illustrated in image B by an average occlusion 414. The average occlusion 414 can be expressed, for example, as a percentage. Of the six landmarks 413 arranged on the left roadway edge of the roadway 403, only five landmarks 413 are within the area of ​​the directional characteristic 410 in the illustrated drawing. The landmarks 413 that are not occluded by the directional characteristic 410 cannot be detected by the vehicle 401 at the illustrated position P. According to the invention, the availability of the landmarks 413 in the landmark map 411 can be calculated position-by-position for various positions P of the vehicle 401 on the roadway 403. That is, in the image B, for the position P of the vehicle 401, only five of the six landmarks 413 at the left roadway edge 403 can be detected by the surrounding area sensor 405 of the vehicle 401.

[0044] According to an embodiment, for the calculation of the availability values ​​of the various indicators 413, the characteristics of the indicators 413 can be determined. The characteristics can include for example the type of indicator 413, the number of indicators 413 in the area of ​​the roadway 403 to be traveled, the spatial extent or size of the indicators 413, or the reflectivity of the indicators 413. To determine the detectability, these characteristics of the indicators 413 can be taken into account by the calculation of the corresponding detectability corrected characteristics. In the example of the number of indicators 413 as characteristics, the detectability corrected number of indicators 413 can be calculated as the number of indicators 413 detectable by the surrounding area sensor 405 for the respective sensor type or directional characteristic 410 of the surrounding area sensor 405 or for the calculated and predicted traffic volume 409.

[0045] In this way, the availability value calculated in this way for each individual landmark 413 for the selected roadway 403 can be expressed, for example, as a percentage of the number of landmarks 413 of the roadway 403. That is, the corresponding availability information can indicate that for the respective roadway 403, a certain percentage of the landmarks 413 of the landmark map 411 are available for locating the vehicle 401.

[0046] In this way, for appropriate route planning of the vehicle 401, in addition to the calculated route with the shortest travel duration, the route with the highest availability of the calculated route indicator 413 can also be provided to the vehicle 401 or the driver based on the calculated availability information of the various roadways 403 of the respective route.

[0047] The corresponding route data 421 may be provided in each vehicle 401 by a calculation unit 415 configured as an external server unit.

[0048] The external server unit 415 is thus configured to calculate, for the vehicle 401 and the corresponding route or roadway 403 to be driven, the availability of landmarks 413 or objects located on the respective roadway and to determine the corresponding route with the maximum availability of landmarks 413. Such information can be provided to the vehicle 401 in communication with the external server unit 415.

[0049] Thus, for the calculation of the route, according to the invention, a data connection can be established between the calculation unit 415 configured as an external server unit and the vehicle 401, for example in the form of a wireless data connection. Sensor information data 407 of the surrounding area sensors 405 of the vehicle 401 can then be transmitted to the calculation unit 415. In addition to data 409 relating to the average traffic volume, the calculation unit 415 or the external server unit can calculate a corresponding route with maximum availability by means of the inventive method for availability prediction and method for route planning and provide this to the vehicle 401 via wireless communication.

[0050] FIG. 2 illustrates a flow chart of a method 100 for predicting availability of index-based location of a vehicle 401 according to one embodiment.

[0051] According to the present invention, in a first method step 101, map data 412 of a landmark map 411 of a road traffic network is received, the landmark map 411 including landmark information of a plurality of landmarks 413 of a plurality of roadways 403 drivable by a vehicle 401, the landmarks 413 being configured to be detected by the vehicle 401 traveling on the roadways 403 through sensor data 406 of the surrounding area sensor 405 of the vehicle 401 and to be used for locating the vehicle 401.

[0052] In a next method step 103 , on the basis of the landmark information of the landmark map 411 , a landmark 413 is determined for at least one roadway 403 which is to be traveled by the vehicle 401 .

[0053] In a next method step 105, an availability value of the indicator 413 of at least one roadway 403 to be traveled by the vehicle 401 is calculated with respect to the availability criterion, the availability value representing a quantitative measure of the usefulness of the indicator 413 for locating the vehicle 401 when the roadway 403 is traveled by the vehicle 401.

[0054] For this purpose, in the illustrated embodiment, in a next method step 109 the sensor type and / or the directional characteristic 410 of the surrounding area sensor 405 of the vehicle 401 is determined.

[0055] Furthermore, in another method step 113, traffic volume is determined.

[0056] For this purpose, in method step 115 the average number of vehicles on the roadway 403 and / or the average speed to be traveled by the vehicle is determined.

[0057] In a next method step 117, the average vehicular obstruction 414 of the traffic volume indicator 413 is calculated based on the average number of vehicles or the average speed.

[0058] Additionally, characteristics of the indices 413 are determined in method step 119. The characteristics may include, for example, the number, characteristics, or spatial extent of the indices.

[0059] In method step 111, the detectability of the individual indicators by the surrounding area sensors 405 of the vehicle 401 is calculated based on the sensor type or directional characteristics and / or based on the calculated traffic volume or average occlusion.

[0060] In a next method step, at least one feature of the index 413 is compared with the detectability corrected features calculated in method step 119. The comparison can provide availability values ​​in the form of quantitative numerical values ​​for the various features, which may be expressed, for example, as percentages.

[0061] In a next method step 107 , availability information based on the availability values ​​calculated in method step 105 is output for an index 413 of an index map 411 for the roadway 403 to be traveled by the vehicle 401 .

[0062] FIG. 3 illustrates a flow chart of a method 200 for route planning for an autonomously controllable vehicle 401 according to one embodiment.

[0063] According to the present invention, first in method step 201, the method 100 for predicting the availability of index-based location of a vehicle 401 is performed for a number of possible routes of the vehicle 401 between a predetermined start point and a predetermined end point.

[0064] In a next method step 203, based on the performed availability prediction, a route 421 for the vehicle 401 with the highest predicted availability for index-based location of the vehicle 401 is determined.

[0065] Driving the vehicle 401 may, in one embodiment, include executing a maneuver plan. In particular, a driving maneuver that improves the availability of indicators in an indicator map for a roadway to be traveled by the vehicle 401 may be planned and executed by the vehicle 401. For example, such a driving maneuver may include a change to a particular travel lane of the roadway to be traveled, for which a higher availability of indicators is expected. Alternatively, the driving may include another driving maneuver that may improve the availability of indicators, such as a planned reduction in speed or activation of the vehicle headlights, through which objects located along the travel lane to be traveled are better visible by the vehicle's surrounding area sensors.

[0066] FIG. 4 illustrates a flow chart of a method 300 for controlling a vehicle 401 according to one embodiment.

[0067] According to the invention, first in method step 301 the method 200 for route planning for an autonomously controllable vehicle is performed.

[0068] In a next method step 303, the vehicle 401 is controlled on the basis of the selected route.

[0069] FIG. 5 shows a schematic diagram of a computer program product 500 including commands for implementing the method 100 for predicting availability of index-based location of a vehicle 401 and / or the method for route planning for an autonomously controllable vehicle 401 and / or the method for controlling a vehicle 401 when the program is executed by a computing unit.

[0070] The computer program product 500 is stored in the illustrated embodiment on a storage medium 501, which may be any storage medium known in the art.

Claims

1. A method (100) for predicting availability of index-based location of a vehicle (401), comprising: Receiving (101) map data (412) of a landmark map (411) of a road traffic network, the landmark map (411) including landmark information of a plurality of landmarks (413) of a plurality of roadways (403) drivable by a vehicle (401), the landmarks (413) being configured to be detected by a vehicle (401) traveling on the roadways (403) through sensor data (406) of a surrounding area sensor (405) of the vehicle (401) and used to locate the vehicle; determining (103) a landmark (413) for at least one roadway (403) to be traveled by said vehicle (401) based on said landmark information of said landmark map (411); - calculating (105) an availability value of said indicator (413) of at least one roadway (403) to be traveled by said vehicle (401) with respect to an availability criterion, said availability value representing a quantitative indication of the usefulness of said indicator (413) for locating said vehicle (401) when said roadway (403) is traveled by said vehicle (401); outputting (107) availability information including said availability value for said indicator (413) of said roadway (403) to be traveled; A method comprising:

2. The availability criteria include a detectability of the indicator (413) by the surrounding area sensor (405) of the vehicle (401) based on a sensor type and / or a directional characteristic (410) of the surrounding area sensor (405) of the vehicle (401), and calculating (105) the availability value comprises: Determining (109) a sensor type and / or directional characteristics (410) of at least one surrounding area sensor (405) of said vehicle (401); - determining (111) the detectability of the indicia (413) of the roadway (403) to be traveled by the vehicle (401) for the sensor type and / or the directional characteristic (410) of the at least one surrounding area sensor (405); The method of claim 1 , comprising:

3. The availability criterion comprises a detectability of the indicator by the surrounding area sensor of the vehicle, taking into account the traffic volume on the roadway to be traveled, and calculating (105) the availability value comprises: determining (113) a volume of traffic on the roadway to be traveled by the vehicle; determining (111) the detectability of the indicia of the roadway to be traveled by the vehicle by calculating the occlusion of the indicia of the roadway by the traffic volume of the roadway; The method (100) of claim 1 or 2, comprising:

4. Determining (113) the traffic volume (409) comprises: determining (115) an average number of vehicles per unit time and / or an average speed on the roadway to be traveled by the vehicle, wherein determining (111) the detectability includes: Calculating (117) an average occlusion (414) of said roadway features (413) based on said average number and / or speed of vehicles per unit time; The method (100) of claim 3, comprising:

5. Calculating (105) the availability value comprises: The method (100) according to any one of claims 2 to 4, comprising determining (119) at least one characteristic of the indicia (413), the at least one characteristic comprising: type of the indicia, number of the indicia, number of the indicia of a particular type or category; visibility of the indicia, spread and / or size of the indicia, reflective ability of the indicia (413), and determining (111) the detectability is performed with respect to the at least one particular characteristic of the indicia, and a detectability corrected characteristic is calculated.

6. Calculating (105) the availability value comprises:

6. The method of claim 5, comprising comparing (121) the at least one feature of the indicia (413) of the indicia map (411) with a corresponding detectability corrected feature.

7. 7. The method (100) of any one of claims 2 to 6, wherein determining (111) the detectability is performed for at least one known position (P) of the vehicle (401) on the roadway (403) or for various known positions of the vehicle (401) on various travel lanes (404) of the roadway (403).

8. 8. The method (100) according to any one of claims 2 to 7, wherein determining (111) the detectability is performed by a corresponding trained artificial intelligence (419), the artificial intelligence (419) being trained on surrounding area sensor data (406) of the surrounding area sensor (403) of at least one vehicle (401), the surrounding area sensor data (406) being recorded under a plurality of different traffic volumes (409) during a plurality of trips of the vehicle (401) along the at least one roadway (403).

9. The method (100) of any one of claims 1 to 8, wherein the indicia (413) are distinctive objects located on the edge of the roadway (403) and include buildings, traffic signs, roadway markings.

10. A method (200) for route planning for an autonomously controllable vehicle (401), comprising: Executing (201) the method (100) for predicting the availability of a marker-based localization of a vehicle (401) according to any one of claims 1 to 9 for a number of possible routes of the vehicle (401) between a pre-determined start point and a pre-determined end point; determining (203) a route (421) for the vehicle (401) that has the highest predicted availability for index-based location of the vehicle (401) based on the performed availability prediction; The method (200).

11. A method (300) for controlling a vehicle, comprising: Implementing (301) the method (200) of route planning for an autonomously controllable vehicle according to claim 10; Driving (303) the vehicle (401) based on the selected route; The method (300).

12. 12. The method (300) of claim 11, wherein driving the vehicle comprises executing an operational plan, the operational plan comprising driving maneuvers of the vehicle that enable best utilization of the indicators of the indicator map.

13. A computing unit (415, 417) configured to implement the method (100) for predicting availability of an index-based location of a vehicle as claimed in any one of claims 1 to 9, and / or the method (200) for route planning for an autonomously controllable vehicle as claimed in claim 10, and / or the method (300) for controlling a vehicle as claimed in claim 11 or 12.

14. A computer program product (500) comprising commands which, when executed by a data processing unit, cause the method (100) for vehicle index-based localization availability prediction according to any one of claims 1 to 9, and / or the method (200) for route planning for an autonomously controllable vehicle according to claim 10, and / or the method (300) for controlling a vehicle according to claim 11 or 12 to be performed.

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