EP4364107A1 - Verfahren und vorrichtung zum unterstützen einer umfelderkennung für ein automatisiert fahrendes fahrzeug - Google Patents
Verfahren und vorrichtung zum unterstützen einer umfelderkennung für ein automatisiert fahrendes fahrzeugInfo
- Publication number
- EP4364107A1 EP4364107A1 EP22735133.5A EP22735133A EP4364107A1 EP 4364107 A1 EP4364107 A1 EP 4364107A1 EP 22735133 A EP22735133 A EP 22735133A EP 4364107 A1 EP4364107 A1 EP 4364107A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- vehicle
- determined
- relevant
- environment
- areas
- 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.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
Definitions
- the invention relates to a method and a device for supporting an environment detection for an automated vehicle.
- An environment detection or environment perception (sensors and processing) of automated driving functions has the task of detecting or recognizing surrounding road users, such as vehicles, cyclists or pedestrians. Capturing the road users relevant to a driving task is a prerequisite for safe action by the automated vehicle. In urban traffic in particular, however, there are a large number of different road users, not all of whom are always relevant to the future behavior of the vehicle. For example, not recognizing a vehicle driving ahead is far more critical than not recognizing a cyclist crossing the road at a safe distance behind the vehicle. An environment detection should therefore be targeted.
- a method for focus-based marking of sensor data is known from US 2019/0374151 A1.
- Data from a vehicle's sensors is collected along with data tracking a driver's gaze. The route traveled by the vehicle can also be recorded.
- the driver's gaze is evaluated in relation to the sensor data to determine which feature the driver was focused on.
- a focus record is created for the feature. Focus records for many drivers can be aggregated to determine a frequency of observing the feature.
- a machine learning model can be trained using the focus datasets to identify an area of interest for a given scenario to more quickly identify relevant hazards.
- the security system may be configured to receive vehicle position data indicative of a position of a vehicle, a first lane segment in a lane coordinate system based on the determine vehicle position data, wherein the first lane segment is a lane segment in which the vehicle is located, determine a relevant set of lane segments based on a safe area from the first lane segment, determine or receive obstacle position data indicative of a second lane segment in the lane coordinate system , wherein the second lane segment is a lane segment in which an obstacle is located, and to classify the obstacle either as an irrelevant obstacle if the second lane segment is not included in the relevant set of lane segments, or as a relevant obstacle if the second lane segment is included is included in the corresponding set of lane segments.
- the invention is based on the object of creating a method and a device for supporting environment detection for an automated vehicle, with which environment detection, in particular with regard to targeted environment detection, can be improved.
- a method for supporting environment detection for an automated vehicle is provided, with a maneuver category of a maneuver currently being carried out of the vehicle being determined, with at least one of the specific maneuver category being assigned in a stored assignment based on the specific maneuver category being determined an associated relevant surrounding area in the surrounding area of the vehicle is determined for the determined at least one basic area, taking into account current parameters of the vehicle and/or the surrounding area, with the relevant surrounding areas determined for the at least one basic area being provided for the surrounding area detection, so that the surrounding area detection can be carried out taking into account the relevant areas of the environment determined in each case.
- a device for supporting an environment detection for an automated vehicle comprising a data processing device with at least one computing device and at least one memory, wherein the data processing device is set up to a maneuver category of a currently performed maneuver of the vehicle, starting from the specific maneuver category to determine at least one of the specific maneuver category assigned in a stored assignment base area, to the determined at least one base area, taking into account current parameters of the vehicle and / or the environment in each case an associated relevant environment area in To determine the vehicle's surroundings and to provide the relevant surroundings areas for the surroundings detection that are determined for the at least one base area, so that the surroundings detection can be carried out taking into account the relevant surroundings regions that have been determined in each case.
- a basic idea here is to subdivide a behavior of the vehicle into maneuvers of different maneuver categories.
- a maneuver category is in particular a semantic subdivision of a behavior, in particular in sections, of the automated vehicle.
- a maneuver category can be one of the following, for example: following a lane, changing lanes, approaching an intersection, crossing an intersection, turning left, turning right, approaching a pedestrian crossing or crossing a pedestrian crossing, etc.
- each maneuver is assigned base regions that define regions relevant to this maneuver relative to the vehicle or in relation to the environment.
- the base areas are defined in particular in a general manner. This means in particular that the base areas do not (yet) have a specific relationship (e.g. exact dimensions, positions, etc.) to a current environment of the vehicle, but are defined relative to the vehicle or only in relation to a maneuver in general (e.g. base area includes pedestrian crossing). .
- the base areas can be specified manually for the various maneuver categories and stored in the allocation.
- provision can also be made for automatically defining the base areas, for example with the aid of machine learning methods and/or artificial intelligence.
- At least one base area assigned to the specific maneuver category in the stored assignment is determined on the basis of the specific maneuver category.
- a single or multiple base area(s) can be assigned to a maneuver category in the assignment.
- an associated relevant area in the area surrounding the vehicle is determined for the determined at least one basic area, taking into account current parameters of the vehicle and/or the area.
- the generally defined basic areas are transferred, in particular, to specific, relevant environmental areas that are specific to the current environment.
- Current parameters of the vehicle are in particular a position, a speed and/or an acceleration, etc.
- Current parameters of the environment are, in particular, lane courses and lanes, which can be determined, for example, based on a road map, as well as a position and/or a configuration of pedestrian crossings, etc.
- Another current parameter of the environment can be a permissible maximum speed on lanes in the environment, which can also be retrieved from a map or determined from recorded sensor data (eg by evaluating traffic signs in the environment).
- Parameters of the vehicle and the environment can also include braking and/or acceleration values and/or reaction times for the vehicle and/or other vehicles. In particular, such braking and/or acceleration values and/or reaction times can include typical values or statistical average values.
- the relevant surrounding areas can be determined on the basis of parameterizable equations that are specified in each case for the individual basic areas. To determine, an equation is then parameterized with the current parameters and the concrete, relevant environmental area is determined via this. Provision is made in particular for the worst case of a given traffic situation to be taken into account (“worst-case scenario”), so that there is a safety tolerance in particular.
- the relevant surrounding areas determined for the at least one base area are provided for the surrounding area recognition, so that the surrounding area recognition can be carried out taking into account the respectively determined surrounding areas.
- the specific relevant environmental area(s) can be taken into account in the environmental recognition for the allocation of computing power when processing environmental data, so that the focus when processing and/or evaluating the environmental data is on the specific relevant environmental area(s). (e) can be laid.
- limited computing and/or memory resources can be used in a targeted manner.
- An advantage of the method and the device is that the determination of the relevant areas around the area enables a targeted recognition of the area around.
- the relevant environmental areas are already generally predefined in the assignment and linked to the maneuver categories, so that only the specific configurations based on the current situation (vehicle and environment) have to be made. This procedure simplifies the effort and allows computing power and memory requirements to be saved or kept low even when determining the relevant surrounding areas.
- Portions of the device may be embodied individually or collectively as a combination of hardware and software, such as program code executing on a microcontroller or microprocessor. However, it can also be provided that parts are designed individually or combined as an application-specific integrated circuit (ASIC) and/or field-programmable gate array (FPGA).
- ASIC application-specific integrated circuit
- FPGA field-programmable gate array
- the data processing device comprises in particular at least one of the aforesaid computing devices and at least one memory.
- One specific embodiment provides for the environment detection to be configured in such a way that the environment detection is limited to the relevant areas of the environment. This allows existing resources (sensors, computing power, memory, etc.) of the vehicle are used in a targeted manner (and possibly completely) for the environment detection in the relevant environment areas.
- One specific embodiment provides for the measures to be carried out while the vehicle is in operation.
- the relevant environmental areas are determined during automated driving of the vehicle.
- the measures for determining the relevant environmental areas are carried out online.
- the measures are carried out based on stored surroundings data and/or vehicle data, with the specific relevant surroundings areas being stored at corresponding positions in a surroundings map, with the surroundings map being provided for the surroundings recognition.
- the method can also be used to prepare and/or plan an environment detection that is subsequently carried out. In particular, this can reduce the amount of computing power and/or storage required for the environment detection, since the relevant areas of the environment can be retrieved from the map provided when the vehicle is driving in an automated manner.
- a respective switching state of light signal systems arranged in the surrounding area is taken into account.
- the relevant environmental areas can be further restricted, as a result of which the need for computing power and/or memory can be further reduced.
- relevant surrounding areas or sub-areas of relevant surrounding areas which correspond to areas in which traffic flows have been brought to a standstill by a corresponding switching state of a traffic signal system (e.g. traffic signal system is on "red"), are not intended for the environment detection or that a relevant environmental area is correspondingly reduced by the partial areas that are affected by a corresponding switching state of the traffic signal system.
- traffic flows that are blocked by a switching state of a traffic signal system are not taken into account in the environment recognition or are taken into account with less effort.
- a computing-resource-dependent reaction time of the vehicle is taken into account when determining at least one of the respectively associated relevant environmental areas.
- a relevant area around the area can be enlarged if a reaction time increases, so that in particular vehicles traveling further away, which could potentially collide with the vehicle due to the longer reaction time, can be taken into account in the area detection.
- the reaction time of the vehicle is usually in the range of a few hundred milliseconds, this being dependent on a total of available or usable computing power in the vehicle and/or a total of available or usable memory space.
- an acceleration profile of the vehicle which is established on the basis of the specific maneuver category, is taken into account when determining at least one of the respectively associated relevant environmental areas.
- the acceleration profile can include both acceleration, deceleration (deceleration), and constant velocity (zero acceleration).
- the respectively associated relevant surrounding area is determined taking into account the guideline for the construction of city streets (RASt).
- RASt city streets
- information from the guideline regarding visibility in crossing areas can be taken into account.
- a relevant surrounding area can be reduced in size as a result, since a range of vision is limited in any case. This makes it possible to save computing power and/or storage space.
- 1 shows a schematic representation of an embodiment of the device for supporting an environment detection for an automated vehicle
- FIG. 2 shows a schematic representation to clarify an assignment of maneuver categories to base areas
- FIGS. 3 to 8 show schematic representations to clarify the determination of the relevant surrounding area from the base area
- FIG. 9 shows a schematic representation of an exemplary acceleration profile of a vehicle
- FIGS. 10 and 11 show schematic representations to clarify the determination of the relevant surrounding area from the base area
- Fig. 12 is a schematic representation to clarify relevant
- FIG. 13 shows a schematic flow chart of an embodiment of the method for supporting an environment detection for an automated vehicle.
- the device 1 shows a schematic representation of an embodiment of the device 1 for supporting an environment detection 53 for an automated vehicle 50 .
- the device 1 is arranged in the vehicle 50, for example, and serves in particular to prepare for the environment recognition 53.
- the device 1 comprises a data processing device 2 with a computing device 3 and a memory 4.
- the data processing device 2 is set up to determine a maneuver category 20 of a maneuver currently being carried out by the vehicle 50 .
- the data processing device 2 receives, for example, status data of the vehicle 50, such as sensor data 10, which is recorded by means of a sensor system 51 of the vehicle 50, and navigation data 11 (e.g. a planned route, maximum speeds, history of the Lanes, etc.), which are provided by a navigation device 52 of the vehicle 50, supplied.
- the sensor data 10 and the navigation data 11 can include both vehicle data and environment data.
- the data processing device 2 evaluates the status data and, using methods known per se, uses this to determine the maneuver category 20 of the maneuver currently being carried out.
- Data processing device 2 at least one base area 21 assigned to the specific maneuver category 20 in a stored assignment 15.
- the assignment 15 can, for example, comprise a tabular assignment in which base areas 21 assigned to each maneuver category 20 are stored.
- Data processing device 2 determines an associated relevant surrounding area 22 in the area surrounding vehicle 50 for the determined at least one base area 21, taking into account current parameters of vehicle 50 and/or the surrounding area Determines environmental data of the environment, in particular based on the sensor data 10 and the navigation data 11.
- the relevant surrounding areas 22 determined for the at least one base area 21 are provided by the data processing device 2 for the surrounding area recognition 53 so that the surrounding area recognition 53 can be carried out taking into account the respectively determined surrounding area 22 .
- the relevant environmental areas 22 are provided in the form of a data packet, for example.
- the environment detection 53 is configured in such a way that the environment detection 53 is limited to the relevant areas 22 of the environment.
- the measures are carried out based on stored surroundings data 12 and/or vehicle data 13, with the specific relevant surroundings areas 22 being stored at corresponding positions in a surroundings map 30, with the surroundings map 30 being provided for the surroundings recognition 53.
- the device 1 can in particular be arranged outside the vehicle 50 .
- the device 1 can be designed as a central server, with the environment map 30 being transmitted to the vehicle 50 after the measures have been carried out and the relevant environmental areas 22 stored therein can be retrieved from the environmental map 30 in the environmental recognition 53 .
- the switching state e.g. "red”, "green” etc.
- the switching state can be determined, for example, based on the sensor data 10 recorded.
- the switching state can also be queried and/or received via a car-to-infrastructure interface and/or a car-to-car interface.
- Relevant environmental areas 22, which include traffic flows and/or roadway sections blocked, for example, by the switching state of a traffic signal system, can then be reduced in size or discarded.
- an acceleration profile 16 of the vehicle 50 which is established on the basis of the specific maneuver category 20, is taken into account when determining at least one of the respectively associated relevant environmental areas 22.
- the respectively associated relevant surrounding area 22 is determined taking into account a guideline 17 for the construction of city streets (RASt).
- visual ranges 18 can be taken into account.
- FIG. 2 shows a schematic illustration to clarify an assignment 15 of maneuver categories 20-x to base regions 21-x.
- assignment 15 has the form of a table in which the individual maneuver categories 20-x are linked to the individual base areas 21-x.
- the maneuver categories 20-x and the basic regions 21-x can, for example, have been determined and/or defined manually or automatically on the basis of empirical data.
- the base regions 21-x assigned to this maneuver category 20-x are determined using the assignment 15. If the specific maneuver category 20-x is 20-6, for example, then the associated basic areas 21-1 and 21-4 and, if there is a pedestrian crossing at the intersection ahead, also the basic area 21-6 are determined.
- the base areas 21-x correspond here in particular to the following areas:
- a base area 21-6 comprising vulnerable road users at pedestrian crossings.
- the determination of the relevant surrounding areas 22-x starting from the base areas 21-x is explained below by way of example in FIGS. 3 to 11.
- the determination is based on parameterizable equations by inserting the respective parameters (of the vehicle and/or the environment) into the equations accordingly.
- FIGS. 3a and 3b Schematic representations are shown in FIGS. 3a and 3b to clarify the determination of the relevant surrounding area 22-1 from the base area 21-1.
- the determination is made with the aid of an equation using a lane width S t known from a map of the surroundings and an additional tolerance distance S tol .
- the first summand relates to a distance covered due to a maximum possible acceleration a acell,max during the reaction time t reaction
- the second summand relates to a distance covered due to a constant speed v 0 in the reaction time t reaction
- the third summand relates to a braking distance with maximum braking (Deceleration) with a brake,max for the reaction time t reaction .
- the relevant area then results, as shown in FIG. 3b, from a sum of a vehicle length and S B +S t and the two adjacent lanes with the lane width Si and a width S t of the lane of the vehicle.
- the relevant surrounding area 22-7 can be calculated from a corresponding basic area 21-7, for example using the above equation for S B with the tolerance S tol additionally taking into account a lateral offset S lat can be calculated as follows, in particular to take into account a swerving onto a laterally adjacent area on an opposite lane:
- the first summands here relate to a distance through maximum lateral acceleration a ego,lat accel.max or d obj,lat accel,max for a reaction time t reaction,ego of the vehicle 50 (“ego”) or a reaction time t reaction, obj of an oncoming vehicle (“obj").
- the second summands relate to a lateral acceleration when braking with a ego,lat brake,max or with a obj,lat brake,max for the reaction times t reaction,ego or t reaction,obj .
- a relevant surrounding area 22 - 7 results from this, as shown in FIG .
- FIG. 5 shows a schematic representation to clarify the determination of the relevant surrounding area 22 - 2 from the base area 21 - 2 , which includes approaching vehicles in a lane into which a change is to be made.
- the following equation can also be used to determine the rear partial area with a distance S w : where ⁇ limit denotes a current speed limit.
- the relevant surrounding area 22-2 can then be determined from the variables shown in FIG. 5 and a lane width S t of the adjacent lane.
- FIG. 6 shows a schematic illustration to clarify the determination of the relevant surrounding area 22 - 3 from the base area 21 - 3 , which includes approaching vehicles in a lane that is adjacent to a lane into which a change is to be made.
- the determination is carried out as for the base area 21-2 shown in FIG. 5 or the relevant surrounding area 22-2 determined therefrom.
- FIG. 7 shows a schematic illustration to clarify the determination of the relevant surrounding area 22 - 8 from the base area 21 - 8 , which includes vehicles that are driving in a lane that merges with a lane in which vehicle 50 is driving. It is assumed here that the vehicle 50 does not have the right of way (“pay attention to the right of way”).
- t ego ,intersection is the time it takes to reach the lane at the intersection into which the vehicle is to turn and t is a target speed of vehicle 50 in the lane into which the vehicle is turning.
- t ego is the time it takes to reach the lane at the intersection into which the vehicle is to turn
- t is a target speed of vehicle 50 in the lane into which the vehicle is turning.
- S acc ego is the distance covered by the vehicle 50 while it is approaching the target speed t accelerated.
- S acc ,obj is the distance that other vehicles potentially present complete while the vehicle 50 accelerates to the target speed t .
- FIG. 8 shows a schematic representation to clarify the determination of the relevant surrounding area 22 - 8 from the base area 21 - 8 , which includes vehicles that are driving in a lane that merges with a lane in which vehicle 50 is driving. It is assumed here that the vehicle has the right of way.
- an acceleration profile 40 of the vehicle 50 which is established on the basis of the specific maneuver category, is taken into account when determining at least one of the respectively associated relevant surrounding areas 22-x.
- Such an acceleration profile 16 is shown as an example in FIG. 9 for the situation shown in FIGS.
- a progression of a speed v of the vehicle over time t is shown.
- the vehicle is accelerated in a first region 16-1.
- a subsequent area 16-2 from a time t limit the final speed ⁇ limit is reached and the speed remains constant.
- the vehicle drives in the direction of the intersection at speed ⁇ limit (cf. FIGS. 7 and 8).
- t ego ls refers in particular to the time it takes the vehicle to reach the end of the intersection or the position where the two lanes merge.
- the first summand relates in particular to a route that another vehicle travels in the time t ego,IS , where t ego,IS is in particular the time that vehicle 50 needs to reach the lane. is the maximum permissible speed (speed limit).
- the second and third addends relate to a braking distance of a potential other road user in the lane into which the vehicle is turning. ⁇ obj designates a reaction time of the other road user.
- FIG. 10 shows a schematic representation to clarify the determination of the relevant surrounding area 22 - 5 from the base area 21 - 5 , which includes vehicles in crossing lanes. Without considering an acceleration profile 16 (Fig. 9), the relevant environmental area 22-5 can be determined using the following equation:
- Sc (t ego ,exit - t 0 ) ⁇ ⁇ limit + s tol with t ego ,exit as the time at which the vehicle 50 has crossed the intersection and t 0 a current time.
- s tol is in particular an additional safety distance selected as an example, but which can also be omitted.
- the relevant environmental area 22-5 can be determined using the following equation:
- S sm is in particular an additional safety distance selected as an example (e.g.
- the relevant surrounding area 22-6 can be determined based on a length l cw and a width (not shown) of the pedestrian crossing and a respective circular area around the two ends of the pedestrian crossing.
- the circular areas at the ends can still be clipped around areas that are not walkable and/or that belong to driveable areas outside of the pedestrian crossing.
- FIG. 12 shows a schematic representation to clarify relevant environmental areas 22 - x in a real environment in which vehicle 50 is moving and in which other road users 60 are present. Schematic courses of traffic lanes 70 are also shown (only a few are provided with their own reference numbers as examples), which are stored in particular on a map and are retrieved from this map depending on the position for the current surroundings.
- FIG. 13 shows a schematic flowchart of an embodiment of the method for supporting an environment detection for an automated vehicle.
- the environment data include, for example, map data from an environment map with reference to a current position of the vehicle, such as lane positions, lane widths, crossing lanes, etc.
- the vehicle data include, for example, a current position, a speed and an acceleration of the vehicle.
- Vehicle data can also include a planned driving route, which can be provided, for example, by a navigation device of the automated vehicle.
- a maneuver category of a maneuver currently being carried out by the vehicle is determined on the basis of the received environment data and the received vehicle data.
- the maneuver category can be determined using methods known per se, for example using artificial intelligence.
- At least one base area assigned to the specific maneuver category in a stored assignment is determined. In this way, several base areas can also be determined for a maneuver category.
- an associated relevant surrounding area in the surrounding area of the vehicle is determined for the determined at least one base area, taking into account current parameters of the vehicle and/or the surrounding area. This is done in particular by parameterizing equations using parameters that are provided via the received environment data and/or vehicle data. In particular, the equations define dimensions or extents of the relevant environmental areas in the specific environment, taking into account the specific situation (speed, acceleration, reaction time, etc.).
- the relevant environmental areas determined for the at least one basic area are provided for the environmental recognition, so that the environmental recognition can be carried out taking into account the environmental areas determined in each case.
- the environment detection is configured in such a way that the environment detection is limited to the relevant areas of the environment.
- measures 100-104 are carried out based on stored environment data and/or vehicle data, with the specific relevant environment areas being stored at corresponding positions in an environment map, with the environment map being provided for environment detection. Measure 105 can then be carried out using the environment map.
- a respective switching state of light signal systems arranged in the surrounding area is taken into account.
- the current switching status can be determined, for example, from recorded sensor data and/or queried from a traffic infrastructure.
- a computing resource-dependent reaction time of the vehicle is taken into account when determining at least one of the respectively associated relevant environmental areas.
- an acceleration profile of the vehicle which is determined based on the specific maneuver category, is taken into account when determining at least one of the respectively associated relevant environmental areas.
- measure 103 the respectively associated relevant surrounding area is determined taking into account the guideline for the construction of city streets (RASt).
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Abstract
Description
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Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102021206983.5A DE102021206983A1 (de) | 2021-07-02 | 2021-07-02 | Verfahren und Vorrichtung zum Unterstützen einer Umfelderkennung für ein automatisiert fahrendes Fahrzeug |
| PCT/EP2022/066490 WO2023274746A1 (de) | 2021-07-02 | 2022-06-16 | Verfahren und vorrichtung zum unterstützen einer umfelderkennung für ein automatisiert fahrendes fahrzeug |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| EP4364107A1 true EP4364107A1 (de) | 2024-05-08 |
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ID=82319636
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP22735133.5A Pending EP4364107A1 (de) | 2021-07-02 | 2022-06-16 | Verfahren und vorrichtung zum unterstützen einer umfelderkennung für ein automatisiert fahrendes fahrzeug |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US20250329126A1 (de) |
| EP (1) | EP4364107A1 (de) |
| CN (1) | CN117751394A (de) |
| DE (1) | DE102021206983A1 (de) |
| WO (1) | WO2023274746A1 (de) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024208617A1 (de) | 2023-04-06 | 2024-10-10 | Volkswagen Aktiengesellschaft | Verfahren und vorrichtung zur unterstützung der umfelderkennung eines fahrzeugs |
| DE102023124167A1 (de) * | 2023-09-07 | 2025-03-13 | Bayerische Motoren Werke Aktiengesellschaft | Steuervorrichtung und verfahren zum steuern eines betriebs eines kraftfahrzeugs |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10351883A1 (de) | 2003-10-30 | 2005-06-02 | Valeo Schalter Und Sensoren Gmbh | Verfahren zum Anpassen des Detektionsbereiches einer Umfelderkennungsvorrichtung eines Kraftfahrzeugs |
| DE102012108543A1 (de) | 2012-09-13 | 2014-03-13 | Continental Teves Ag & Co. Ohg | Verfahren und Vorrichtung zum Anpassen der Umfelderfassung oder einer Assistenzfunktion auf Basis von Informationen einer digitalen Karte oder einer Verkehrsinformationen im Fahrzeug |
| US10267908B2 (en) * | 2015-10-21 | 2019-04-23 | Waymo Llc | Methods and systems for clearing sensor occlusions |
| WO2018053175A1 (en) * | 2016-09-14 | 2018-03-22 | Nauto Global Limited | Systems and methods for near-crash determination |
| DE102017200897B4 (de) | 2017-01-20 | 2022-01-27 | Audi Ag | Verfahren zum Betrieb eines Kraftfahrzeugs |
| US10849543B2 (en) | 2018-06-08 | 2020-12-01 | Ford Global Technologies, Llc | Focus-based tagging of sensor data |
| DE102018212266A1 (de) | 2018-07-24 | 2020-01-30 | Robert Bosch Gmbh | Anpassung eines auswertbaren Abtastbereichs von Sensoren und angepasste Auswertung von Sensordaten |
| DE102019129263A1 (de) | 2019-10-30 | 2021-05-06 | Wabco Europe Bvba | Verfahren zur Überwachung einer momentanen Fahrzeugumgebung eines Fahrzeuges sowie Überwachungssystem |
| US11529951B2 (en) | 2019-12-24 | 2022-12-20 | Intel Corporation | Safety system, automated driving system, and methods thereof |
-
2021
- 2021-07-02 DE DE102021206983.5A patent/DE102021206983A1/de active Pending
-
2022
- 2022-06-16 WO PCT/EP2022/066490 patent/WO2023274746A1/de not_active Ceased
- 2022-06-16 CN CN202280046719.1A patent/CN117751394A/zh active Pending
- 2022-06-16 EP EP22735133.5A patent/EP4364107A1/de active Pending
- 2022-06-16 US US18/570,877 patent/US20250329126A1/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| WO2023274746A1 (de) | 2023-01-05 |
| US20250329126A1 (en) | 2025-10-23 |
| CN117751394A (zh) | 2024-03-22 |
| DE102021206983A1 (de) | 2023-01-05 |
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