EP3983757A1 - Verfahren zum optimieren eines umfeldmodells - Google Patents
Verfahren zum optimieren eines umfeldmodellsInfo
- Publication number
- EP3983757A1 EP3983757A1 EP20725143.0A EP20725143A EP3983757A1 EP 3983757 A1 EP3983757 A1 EP 3983757A1 EP 20725143 A EP20725143 A EP 20725143A EP 3983757 A1 EP3983757 A1 EP 3983757A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- environment
- sensor set
- measurement data
- environment model
- models
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
- G01C21/32—Structuring or formatting of map data
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
- G01S13/862—Combination of radar systems with sonar systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/87—Combinations of radar systems, e.g. primary radar and secondary radar
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/87—Combinations of systems using electromagnetic waves other than radio waves
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
Definitions
- the invention relates to a method for optimizing an environment model using at least one control device.
- the invention also relates to a control device, a computer program and a machine-readable storage medium.
- Different sensors are used in vehicles that can be operated automatically to identify and classify static and dynamic objects.
- camera sensors radar sensors
- Ultrasonic sensors and inertial sensors are used. These sensors enable the immediate local environment to be modeled
- Vehicles which is often combined with map data. This enables long-term driving maneuvers of the vehicles to be implemented.
- a method for optimizing an environment model by at least one control device is provided.
- the control device can be, for example, a control device external to the vehicle, which is designed as a server unit or as a cloud system.
- the control device can be a control device arranged inside the vehicle.
- measurement data are received from a first sensor set and at least one second sensor set.
- first sensor set Preferably the first sensor set and at least one second sensor set.
- the sensor set has a first scanning area and the second sensor set has a second scanning area, it being possible for the first scanning area and the second scanning area to overlap in areas in an overlapping area.
- the scanning areas of the respective sensor sets can also be used without an overlap or the
- Overlap area can be used for performing the method.
- An environment model is created for each sensor set based on the measurement data received from the respective sensor set.
- an environment model can be created using measurement data from several sensor sets.
- the at least two environment models are then merged to form an optimized environment model.
- a control device is provided, the control device being set up to carry out the method.
- the control device can be, for example, a control device internal to the vehicle or a control device external to the vehicle.
- the vehicle-external control device can be, for example, a control device internal to the vehicle or a control device external to the vehicle.
- the vehicle-external control device can be, for example, a control device internal to the vehicle or a control device external to the vehicle.
- Control unit can receive and evaluate measurement data from vehicles in order to verify and optimize the environment models.
- a control device configured internally in the vehicle can, for example, be connected to a vehicle control system for executing automated driving functions or can be designed as part of the automated vehicle control system. This allows the control unit to access measurement data from the sensors used in the vehicle and the environment models created.
- the control device can have a communication unit for establishing data-conducting communication connections to other vehicles or to control devices of other vehicles.
- a computer program which comprises instructions that are used when executing the
- Computer program by a computer or a control device cause the latter to carry out the method according to the invention.
- a machine-readable storage medium is provided on which the computer program according to the invention is stored.
- the vehicle-internal control unit is, for example, in one
- a sensor set can consist of one or more sensors.
- the sensors can be designed differently or in the same way.
- the sensors can be part of an environment sensor system of a vehicle.
- the sensor set can be LIDAR sensors, radar sensors, and
- the sensor set can also represent a part, a group of the environment sensor system or the entire environment sensor system.
- further sensors such as acceleration sensors or odometers, can also be implemented in the sensor set.
- Redundancy of measurement data can be created, which enables a review and optimization of the respective environment models. For example, if discrepancies are found between the environment models in Overlap area, a check can be initiated or an averaging of the measurement data can be carried out in order to achieve optimization.
- the at least two environment models created can be combined to form an optimized environment model which can map a larger area or a larger scanning area.
- the optimized environment model can map a larger area or a larger scanning area.
- the environment model can already have a
- Performance of the sensor set are provided.
- the method can be carried out by several sensor sets operated in parallel.
- the respective sensor sets can preferably be spatially spaced from one another.
- the sensor sets can have a different alignment of the scanning areas and monitor an identical scene or the overlapping area of the respective scanning areas at least in areas.
- Measurement data determined on such a redundant basis can be used to create an optimized environment model, which can represent a sensor environment more realistically.
- a larger area can be mapped by the resulting environment model by using the measurement data from several sensor sets.
- the area shown can optionally also be used without the
- Overlap area be carried out.
- the information or the results of the environment model calculation can preferably be stored and used at a later point in time.
- the use of this information can be initiated, for example, when a vehicle moves in a direction or an area of one of the scanning areas of the sensor sets. This can take place, for example, when changing lanes, turning and the like.
- the method can be used both on and off test tracks
- the at least two sensor sets are arranged in one vehicle or in different vehicles.
- the at least two sensor sets can have a different position and a different orientation, so that the respective
- the environment model of a first sensor set which is based on measurement data from the first scanning area
- the environment model of a second sensor set which is based on measurement data from the second scanning area.
- environment models can be strung together as long as desired, with at least two environment models being able to overlap in areas.
- the optimized environment model can be created, which is achieved through the spatial separation of the vehicles or sensor sets and / or through a different perspective of the Sensor sets and / or more special
- Sensor characteristics shows a higher accuracy than the environment models of the individual sensor sets or vehicles.
- This measure enables the errors in the individual environment models to be determined and optimized.
- This principle can also be applied in series if several vehicles or sensor sets work with compatible and transferable input data, so that a single vehicle has more input data available to perceive its surroundings.
- a vehicle can have several sensor sets in order to detect possible systematic errors in individual sensor sets.
- the uncertainty or flawedness of the environment model can be reduced.
- merging the at least two environment models results in an inaccuracy of the received Measurement data reduced in the overlap area. Based on a comparison of the resulting environment models in the overlap area, the
- Environment models are verified. If, for example, there is a deviation in the results, a review or recalculation of the environment models can be initiated. Alternatively or in addition, a mean value can be formed from the environment models or an offset can be taken into account to compensate for deviations in order to create an optimized environment model.
- an expanded scanning area is mapped by the optimized environment model, which area corresponds to the first scanning area and the second scanning area.
- the respective environment model which area corresponds to the first scanning area and the second scanning area.
- the sensor sets can preferably
- Vehicles can be arranged, each vehicle having a control device that can be connected to the respective sensor sets.
- the control units can communicate with each other across all vehicles and, for example, exchange measurement data and environment models. It can be a
- Synchronization of measurement data and information between the vehicles can be realized, which results in an increase in the possible range of the respective sensor sets and the precision of the environment models.
- Environment models are exchanged between at least two control units via a communication link.
- the respective sensor sets are preferably connected to control units.
- a control device can also be part of a sensor set.
- Several control units can exchange data and information, such as measurement data, environment models and calculation results, with one another via wireless communication links.
- the communication link can for example be based on a GSM, UMTS, LTE, 4G, 5G, WLAN, radio and similar transmission standard.
- the at least two environment models are compared, verified and / or merged into one optimized environment model executed by at least one vehicle-external or vehicle-internal control unit.
- the information from the different sensor sets or vehicles can thus be exchanged or synchronized continuously or at defined time intervals during a journey.
- the measurement data and environment models from the different sensor sets can be transmitted to a control unit external to the vehicle, which subsequently checks and verifies the respective environment models and measurement data. In this way, an optimized environment model can be created outside the vehicle as a reference model for other vehicles and sensor sets.
- the environment model of the first sensor set and / or the environment model of the second sensor set is completed, corrected and / or expanded by merging the at least two environment models.
- errors in the individual environment models can be determined and corrected, compensated or optimized.
- parameters of the environment models can be adapted or the measurement data on which the creation of the respective environment models is based corrected.
- the measurement data and / or the environment models of the different sensor sets can preferably have the same time base.
- the common time base can be set, for example, by GPS signals or a common clock generator.
- Fig. 1 is a schematic plan view of an arrangement for
- FIG. 2 shows a schematic diagram to illustrate the method according to an embodiment.
- FIG. 1 shows a schematic top view of an arrangement 1 to illustrate a method 2 according to the invention.
- the arrangement 1 has a first vehicle 4 and a second vehicle 6. Both vehicles 4, 6 can be designed as vehicles that can be operated automatically and that create an environment model for planning and executing actions.
- Arrangement 1 have any number of vehicles.
- the first vehicle 4 has a first control device 8.
- the first control device 8 is connected to a first sensor set 10.
- the first sensor set 10 can for example have a LIDAR sensor and one or more radar sensors.
- the control device 8 can in particular measure data from the first
- the first control device 8 is connected to a machine-readable storage medium 12 which is used to store data and on which, for example, an executable by the first control device 8
- Computer program can be stored in order to carry out method 2.
- the second vehicle 6 has a second control device 14, which is connected to a second sensor set 16 in a data-conducting manner. As a result, the second control device 14 can receive measurement data from the second sensor set 16.
- the second sensor set 16 is arranged on the rear of the second vehicle 6. There is also a second
- machine-readable storage medium 18 is provided, which can be read by the second control unit 14.
- the second machine-readable storage medium 18 can be configured analogously to the first machine-readable storage medium 12.
- Sensor set 16 can have, for example, LIDAR sensors and camera sensors.
- the two control units 8, 14 can use a wireless
- Communication link 20 data and information with one another
- control units 8, 14 can communicate via the wireless communication link 20 with a control unit 22 external to the vehicle and also exchange data and information.
- the first sensor set 10 is set up to scan a first scanning area 24.
- a second scanning area 26 is scanned by the second sensor set 16.
- the first scanning area 24 and the second scanning area 26 have an overlap area 28 in which they overlap.
- the measurement data of the sensor sets 10, 16 are thus redundantly available in the overlap area 28.
- the scanning areas 24, 26 are partially covered or shaded by neighboring vehicles 30.
- the scanning areas 24, 26 and the impact of the vehicles 30 are illustrated schematically.
- FIG. 2 shows a schematic diagram to illustrate method 2 according to an exemplary embodiment.
- Method 2 is used to optimize an environment model using at least one control device 8, 14, 22.
- measurement data 31 are received from a first sensor set 10 and measurement data 32, 33 from at least one second sensor set 16.
- the measurement data are transmitted via a
- Communication link 20 is exchanged between control units 8, 14, 22.
- the communication connection 20 can for example be a WLAN, GSM, LTE or a similar wireless connection.
- the measurement data preferably have a common time base or are determined in a synchronized manner.
- the sensor sets 10, 16 each have a scanning area 24, 26 which overlap in an overlapping area 28.
- an environment model 34, 35, 36 is created for each sensor set 10, 16 based on the received measurement data 31, 32, 33 of the respective sensor set 10, 16. This can be done by the vehicle
- Control devices 8, 14 take place.
- the at least two environment models 34, 35, 36 are compared and verified with one another, for example, using the overlap area 28.
- an overlap area between the first two environment models 34, 35 and an overlap area between each further Pair of environment models 35, 36 are used for comparison and verification.
- a comparison, verification and / or merging of the at least two environment models 34, 35, 36 results in an optimized environment model
- This step can be carried out by the control units 8, 14 on the vehicle or by the control unit 22 external to the vehicle.
- the at least two environment models 34, 35, 36 can thus be optimized into one
- the arrows illustrate a possible feedback of the optimized environment model 37 in order to improve the respective environment models 34, 35, 36 of the sensor sets 10, 16.
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Electromagnetism (AREA)
- Automation & Control Theory (AREA)
- Traffic Control Systems (AREA)
- Image Generation (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102019208498.2A DE102019208498A1 (de) | 2019-06-12 | 2019-06-12 | Verfahren zum Optimieren eines Umfeldmodells |
| PCT/EP2020/062704 WO2020249328A1 (de) | 2019-06-12 | 2020-05-07 | Verfahren zum optimieren eines umfeldmodells |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP3983757A1 true EP3983757A1 (de) | 2022-04-20 |
Family
ID=70680495
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP20725143.0A Ceased EP3983757A1 (de) | 2019-06-12 | 2020-05-07 | Verfahren zum optimieren eines umfeldmodells |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US12585017B2 (de) |
| EP (1) | EP3983757A1 (de) |
| JP (1) | JP2022536166A (de) |
| CN (1) | CN114270141A (de) |
| DE (1) | DE102019208498A1 (de) |
| WO (1) | WO2020249328A1 (de) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102020123808A1 (de) | 2020-09-11 | 2022-03-17 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren und System zum Erfassen von Umgebungsdaten zur Absicherung einer Umfelderkennung |
| DE102023134749A1 (de) * | 2023-12-12 | 2025-06-12 | Dr. Ing. H.C. F. Porsche Aktiengesellschaft | Verfahren zum Betrieb eines Kraftfahrzeugs, Kraftfahrzeug |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2018055695A (ja) * | 2017-10-26 | 2018-04-05 | エスゼット ディージェイアイ テクノロジー カンパニー リミテッドSz Dji Technology Co.,Ltd | ある環境内で無人航空機を制御する方法、ある環境のマップを生成する方法、システム、プログラムおよび通信端末 |
Family Cites Families (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100253595A1 (en) * | 2009-04-02 | 2010-10-07 | Gm Global Technology Operations, Inc. | Virtual controls and displays by laser projection |
| CN109884618B (zh) * | 2014-02-20 | 2023-05-26 | 御眼视觉技术有限公司 | 车辆的导航系统、包括导航系统的车辆和导航车辆的方法 |
| FR3020616B1 (fr) * | 2014-04-30 | 2017-10-27 | Renault Sas | Dispositif de signalisation d'objets a un module de navigation de vehicule equipe de ce dispositif |
| CN111380545B (zh) * | 2015-02-10 | 2024-11-12 | 御眼视觉技术有限公司 | 用于自主车辆导航的方法、服务器、自主车辆以及介质 |
| DE102015213694A1 (de) * | 2015-07-21 | 2017-01-26 | Robert Bosch Gmbh | Sensorsystem zum Erkennen überstehender oder freiliegender Objekte in der Umgebung eines Fahrzeugs |
| DE102016205139B4 (de) * | 2015-09-29 | 2022-10-27 | Volkswagen Aktiengesellschaft | Vorrichtung und Verfahren zur Charakterisierung von Objekten |
| DE102016003308B3 (de) * | 2016-03-17 | 2017-09-21 | Audi Ag | Verfahren zum Betrieb eines Fahrerassistenzsystems eines Kraftfahrzeugs und Kraftfahrzeug |
| DE102016212688A1 (de) * | 2016-07-12 | 2018-01-18 | Zf Friedrichshafen Ag | Verfahren und Vorrichtung zur Ermittlung des Umfelds eines Fahrzeugs |
| US10248124B2 (en) * | 2016-07-21 | 2019-04-02 | Mobileye Vision Technologies, Inc. | Localizing vehicle navigation using lane measurements |
| US11067996B2 (en) * | 2016-09-08 | 2021-07-20 | Siemens Industry Software Inc. | Event-driven region of interest management |
| DE102016220075A1 (de) * | 2016-10-14 | 2018-04-19 | Audi Ag | Kraftfahrzeug und Verfahren zur 360°-Umfelderfassung |
| DE102017203838B4 (de) * | 2017-03-08 | 2022-03-17 | Audi Ag | Verfahren und System zur Umfelderfassung |
| US10930152B2 (en) * | 2017-06-20 | 2021-02-23 | Hitachi, Ltd. | Travel control system |
| US10334331B2 (en) * | 2017-08-25 | 2019-06-25 | Honda Motor Co., Ltd. | System and method for synchronized vehicle sensor data acquisition processing using vehicular communication |
| DE102018007658A1 (de) * | 2018-09-27 | 2019-03-07 | Daimler Ag | Verfahren zum Bereitstellen von erweiterten Umfeldmodellen für zumindest teilweise autonome Fahrzeuge, Steuergerät zum Ausführen eines solchen Verfahrens, sowie Fahrzeug mit einem solchen Steuergerät |
-
2019
- 2019-06-12 DE DE102019208498.2A patent/DE102019208498A1/de active Pending
-
2020
- 2020-05-07 CN CN202080056966.0A patent/CN114270141A/zh active Pending
- 2020-05-07 US US17/618,280 patent/US12585017B2/en active Active
- 2020-05-07 WO PCT/EP2020/062704 patent/WO2020249328A1/de not_active Ceased
- 2020-05-07 EP EP20725143.0A patent/EP3983757A1/de not_active Ceased
- 2020-05-07 JP JP2021573399A patent/JP2022536166A/ja active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2018055695A (ja) * | 2017-10-26 | 2018-04-05 | エスゼット ディージェイアイ テクノロジー カンパニー リミテッドSz Dji Technology Co.,Ltd | ある環境内で無人航空機を制御する方法、ある環境のマップを生成する方法、システム、プログラムおよび通信端末 |
Also Published As
| Publication number | Publication date |
|---|---|
| DE102019208498A1 (de) | 2020-12-17 |
| JP2022536166A (ja) | 2022-08-12 |
| CN114270141A (zh) | 2022-04-01 |
| US12585017B2 (en) | 2026-03-24 |
| WO2020249328A1 (de) | 2020-12-17 |
| US20220413148A1 (en) | 2022-12-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| DE102019200612B4 (de) | Vorrichtung und Verfahren zum Kalibrieren eines Multiple-Input-Multiple-Output-Radarsensors | |
| EP1842382B1 (de) | Verfahren, Vorrichtung, Computersoftware und entsprechender Datenträger zum Bestimmen einer Objekteigenschaft eines Objekts mit Hilfe von Bildern, die mit Hilfe einer Kamera erfasst werden | |
| EP4021778B1 (de) | Verfahren und messfahrzeug zur ermittlung einer ist-lage eines gleises | |
| DE102017213217A1 (de) | Testfahrtszenario-Datenbanksystem für realitätsnahe virtuelle Testfahrtszenarien | |
| DE102019108477A1 (de) | Automatische navigation unter verwendung von deep reinforcement learning | |
| DE102018106549A1 (de) | Methoden und systeme zur integrierten fahrzeugsensorkalibrierung und -wartung | |
| DE102017117327A1 (de) | Verfahren und Systeme zur Überprüfung der Integrität von Lenksystemen | |
| DE112014000532T5 (de) | Kurvenmodelliervorrichtung, Kurvenmodellierverfahren und Fahrzeugnavigationsvorrichtung | |
| WO2020229002A1 (de) | Verfahren und vorrichtung zur multi-sensor-datenfusion für automatisierte und autonome fahrzeuge | |
| DE102014207523A1 (de) | Verfahren zum kalibrieren eines radarsensors und radarsystem | |
| DE112015001150T5 (de) | Verfahren, Vorrichtung und System zur Unterstützung von Platooning | |
| WO2020249328A1 (de) | Verfahren zum optimieren eines umfeldmodells | |
| EP0416370B1 (de) | Verfahren und Vorrichtung zum Erkennen und Identifizieren von Fehlern an Sensoren | |
| EP3990863A1 (de) | Angleichen von koordinatensystemen mehrerer karten basierend auf trajektorien | |
| DE102021125136A1 (de) | Vorrichtung und verfahren zum vorhersagen der trajektorie eines umliegenden fahrzeugs | |
| DE102018007960A1 (de) | Verfahren zum Abgleich von Kartenmaterial mit einer erfassten Umgebung eines Fahrzeugs, Steuergerät, eingerichtet zum Ausführen eines solchen Verfahrens, sowie Fahrzeug mit einem solchen Steuergerät | |
| EP4548047A1 (de) | Verfahren zur ermittlung und bereitstellung von fahrspurverläufen | |
| DE102014207694B4 (de) | Verfahren zum Evaluieren der Errechnung von Umfeldmodellen durch Fahrzeuge | |
| EP3926304B1 (de) | Verfahren zum beurteilen einer genauigkeit einer positionsbestimmung einer landmarke, sowie bewertungssystem | |
| EP4165370B1 (de) | Verfahren zum bewerten einer digitalen karte, sowie bewertungssystem | |
| DE112011105210T5 (de) | Ortskurvenkorrekturverfahren, Ortskurvenkorrekturvorrichtung und mobiles Objektgerät | |
| DE102018103474A1 (de) | Ein system und verfahren zur objektabstandserkennung und positionierung | |
| DE102020206356A1 (de) | Verfahren zum Ermitteln einer Ausgangspose eines Fahrzeugs | |
| WO2023099066A1 (de) | Simulation zur validierung einer automatisierenden fahrfunktion für ein fahrzeug | |
| DE102019207215A1 (de) | Verfahren zum Verwenden einer merkmalbasierten Lokalisierungskarte für ein Fahrzeug |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: UNKNOWN |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE |
|
| PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE |
|
| 17P | Request for examination filed |
Effective date: 20220112 |
|
| AK | Designated contracting states |
Kind code of ref document: A1 Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR |
|
| DAV | Request for validation of the european patent (deleted) | ||
| DAX | Request for extension of the european patent (deleted) | ||
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: EXAMINATION IS IN PROGRESS |
|
| 17Q | First examination report despatched |
Effective date: 20230623 |
|
| REG | Reference to a national code |
Ref country code: DE Ref legal event code: R003 |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE APPLICATION HAS BEEN REFUSED |
|
| 18R | Application refused |
Effective date: 20241219 |