DE102021109415A1 - PROCEDURE, COMPUTER PROGRAM PRODUCT, PARKING ASSISTANCE SYSTEM AND VEHICLE - Google Patents

Abstract

A method for operating a parking assistance system (110) for a vehicle (100) is proposed. The parking assistance system (110) can be operated in an exploration mode for exploring an at least partially unexplored area (205). The method comprises the steps: a) starting (S1) the exploration mode depending on a user input, b) receiving (S2) at least one sensor signal indicative of the area (200) of the vehicle (100), c) autonomous driving (S3) of the vehicle (100) as a function of the at least one received sensor signal,d) determining (S4) a digital environment map (MAP0 - MAP2) of the explored area as a function of the at least one received sensor signal and/or at least one other signal received during autonomous driving and for the sensor signal indicative of the surroundings (200), unde) storing (S5) the determined digital surroundings map (MAPO-MAP2).

Description

The present invention relates to a method, a computer program product, a parking assistance system and a vehicle with a parking assistance system.

Parking assistance systems are known which have a summoning function, in which the vehicle drives autonomously from the parking assistance system from a starting point to a destination. The starting point is in particular a parking lot where a user has parked the vehicle, and the destination is in particular a current position of the user. You can also say that the vehicle picks up the user.

US 2015/0346727 A1 discloses a method in which an autonomous vehicle automatically searches for a parking space and parks the vehicle there. In one embodiment, the vehicle is set up to pick up a user at a predetermined position. US 2016/0327949 A1 , U.S. 2017/0344010 A1 and U.S. 2018/0130161 A1 disclose other conventional devices and methods.

Against this background, an object of the present invention is to improve the operation of a parking assistance system.

1. a) Starten des Erkundungsmodus in Abhängigkeit einer Nutzereingabe,
2. b) Empfangen zumindest eines für die Umgebung des Fahrzeugs indikativen Sensorsignals,
3. c) autonomes Fahren des Fahrzeugs in Abhängigkeit des zumindest einen empfangenen Sensorsignals,
4. d) Ermitteln einer digitalen Umgebungskarte des erkundeten Gebiets in Abhängigkeit des zumindest einen empfangenen Sensorsignals und/oder von zumindest einem weiteren, während des autonomen Fahrens empfangenen und für die Umgebung indikativen Sensorsignal, und
5. e) Speichern der ermittelten digitalen Umgebungskarte.

According to a first aspect, a method for operating a parking assistance system for a vehicle is proposed. The parking assistance system can be operated in an exploration mode for exploring an at least partially unexplored area. The procedure includes the steps:

1. a) Starting the exploration mode depending on a user input,
2. b) receiving at least one sensor signal indicative of the area surrounding the vehicle,
3. c) autonomous driving of the vehicle depending on the at least one received sensor signal,
4. d) determining a digital environment map of the explored area as a function of the at least one received sensor signal and/or at least one additional sensor signal which is indicative of the environment and received during autonomous driving, and
5. e) storing the determined digital map of the surroundings.

The advantage of this method is that the vehicle can independently explore its surroundings in order to then orientate itself in the area. The vehicle is therefore not dependent on external sources, such as externally provided road maps, which are often not up-to-date and/or which do not contain obstacles that are limited in time, such as roadworks. In addition, the exploration mode can also be carried out on private land that is not covered by road maps, for example. By executing the exploration mode and determining the digital environment map of the explored area, the parking assistance system is in particular enabled to determine a route between two points in the area and to drive along the determined route. This can advantageously be used for summoning the vehicle to pick up the user of the vehicle.

The exploration mode can in particular be referred to as an autonomous exploration mode. In the exploration mode, the vehicle is in particular controlled autonomously by the parking assistance system. A trajectory is not specified in the exploration mode. The vehicle can drive forward and/or backward in the exploration mode. The vehicle can make left turns and right turns in the explore mode. In particular, the vehicle can take any of the possible branches or paths at an intersection, a junction or a fork in the road in order to continue exploring along the respective path.

Step a) includes in particular detecting the user input by means of a user interface coupled to the parking assistance system. The user interface can include an operating element of the vehicle, but can also be integrated in another device, in particular a mobile device of the user, such as a mobile phone. Accordingly, the user input can be received wirelessly, for example via Bluetooth®, via WLAN, via radio, via a mobile network, via infrared and the like. The user input can include various specifications regarding the exploration mode, which will be discussed in more detail below.

The term “sensor signal indicative of the environment” is understood here to mean any sensor signal that establishes a relationship between the vehicle and its environment. The sensor signal can be received by a sensor that is assigned to or integrated in the vehicle and/or can be received by a sensor that is external to the vehicle.

Examples of the sensor signal include an ultrasonic sensor signal, an optical sensor signal such as an image from a camera, from a radar and/or from a lidar, a position sensor sensor signal, such as a GPS signal, and the like.

In step b), a sensor signal is received in particular, on the basis of which the parking assistance system can navigate the vehicle, for example an ultrasonic sensor signal, on the basis of which obstacles in the vicinity of the vehicle can be determined.

The vehicle can also be referred to as an autonomous vehicle or an automated vehicle. The degree of automation of the vehicle has, for example, an automation level according to the SAE classification system. The SAE classification system was published in 2014 by SAE International, an automotive standards organization, as J3016, "Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems". It is based on six different levels of automation and takes into account the level of system intervention and driver attention required. The SAE levels of automation range from level 0, which corresponds to a fully manual system, through driver assistance systems in levels 1 and 2 to semi-autonomous (levels 3 and 4) and fully autonomous (level 5) systems, where a driver is no longer required . An autonomous vehicle (also known as a driverless car, self-driving car, and robotic car) is a vehicle capable of sensing its surroundings and navigating without human input, and conforms to SAE automation level 5. In the context of the proposed method the vehicle acts especially at level 5.

While the vehicle is moving autonomously, at least one additional sensor signal indicative of the environment is received. A digital environment map is determined on the basis of the received sensor signals. The digital map of the surroundings is in particular a digital representation of the surroundings of the vehicle. The digital environment map can have different levels of abstraction, which can also depend on the available sensor signals. At a high level of abstraction, the digital environment map includes, for example, a division into an area that can be driven on and an area that cannot be driven on. At a slightly lower level of abstraction, the digital environment map can also include an indication for traffic signs, an indication for obstacles that can be driven over, such as curbs, an indication for lanes, cycle paths and/or sidewalks and the like. At an even lower level of abstraction, the digital environment map can also include a classification of objects in the environment of the vehicle, such as specifying whether a detected object is another road user, such as another vehicle, or a structural obstacle, such as a fence or a building or the like.

Additional sensor signals are preferably received continuously during autonomous driving. In addition to sensor signals indicative of the surroundings, these can also include sensor signals indicative of a driving state of the vehicle, in particular odometry sensor data, such as a wheel speed sensor signal and/or a wheel angle sensor signal. On the basis of the odometry sensor data, the digital environment map can, for example, be determined true to scale. Alternatively or additionally, position sensor data can be received continuously.

The determined digital environment map is saved and is then available for further use.

• Starten des Herbeirufen-Modus in Abhängigkeit der Nutzereingabe,
• Laden der gespeicherten digitalen Umgebungskarte,
• Empfangen zumindest eines für die Umgebung des Fahrzeugs indikativen Sensorsignals,
• Ermitteln einer Trajektorie für das Fahrzeug, die eine aktuelle Position des Fahrzeugs mit einer Zielposition verbindet, in Abhängigkeit der digitalen Umgebungskarte und dem zumindest einen empfangenen Sensorsignal, und
• autonomes Fahren des Fahrzeugs entlang der ermittelten Trajektorie.

According to one embodiment of the method, the parking assistance system can be operated in a summon mode. Summon mode includes the steps:

• start summon mode depending on user input,
• loading the stored digital map of the area,
• Receiving at least one sensor signal indicative of the surroundings of the vehicle,
• Determining a trajectory for the vehicle, which connects a current position of the vehicle with a target position, as a function of the digital map of the surroundings and the at least one received sensor signal, and
• autonomous driving of the vehicle along the determined trajectory.

Summon mode can also be referred to as Summon. In summon mode, the vehicle arrives at a target position specified by the user using the digital map of the area previously determined in exploration mode. It should be noted that the target position does not necessarily have to be the current position of the user. The target position can also be a parking space that the vehicle is supposed to drive to autonomously and where it is supposed to park. In this respect, the summon mode also includes an autonomous parking mode.

The vehicle is navigated on the basis of the digital environment map and the at least one received sensor signal indicative of the environment. Preferably will continuously receive sensor signals during autonomous driving, on the basis of which a collision with obstacles in the area can be avoided, for example.

In advantageous embodiments, summon mode can be coupled with explore mode. For example, the vehicle is located in an at least partially unexplored area, which means that there is no or only an incomplete digital environment map of the area. The user nevertheless starts the summon mode of the parking assistance system. In this case, the parking assistance system cannot determine a trajectory to the target position, since the digital map of the surroundings is not sufficiently complete. In this case, the parking assistance system starts the exploration mode, for example, and the user is informed of this, for example, by means of a corresponding message. The reconnaissance mode is preferably carried out in such a way that the parking assistance system carries out a reconnaissance trip with the vehicle, but this is aimed at getting to the target position as directly as possible. For this purpose, the parking assistance system selects the path that leads in the direction of the target position at possible path junctions. The direction can be determined using a compass or using a vector in a coordinate system that contains the starting position and the target position. One can also say that the trajectory for the Summon mode is determined in such a way that it runs in unexplored areas along a direct connection (as the crow flies) of the two points to be connected. At the same time as the vehicle is approaching the target position in this way, the parking assistance system determines the digital map of the surroundings and saves it.

According to a further embodiment of the method, further sensor signals indicative of the environment are received during the autonomous driving along the determined trajectory, with the digital environment map being updated as a function of the further received sensor signals.

One can also say that the digital environment map is refined on the basis of the additional sensor signals. In this embodiment, for example, new obstacles and/or objects that were not present during exploration of the area and/or removed obstacles and/or objects that were present during exploration and are now no longer present can be detected and included in the digital environment map are taken into account. In addition, for example, lane boundaries can be localized more precisely by performing statistics on the existing sensor signals.

The more frequently the vehicle drives autonomously in the area, the more precisely the digital environment map can be determined. Furthermore, the digital environment map is kept up to date, which is particularly advantageous in changing environments.

According to a further embodiment of the method, the user input for starting the summon mode comprises the target position for the vehicle.

The target position is in particular a pickup position where the user would like to be picked up, or is the position of a parking space that is reserved for the user, for example. The target position can be specified in particular in the form of coordinates in a coordinate system that is independent of the vehicle, for example as coordinates in a world coordinate system.

According to a further embodiment of the method, the user input for starting the exploration mode includes a maximum exploration time, a maximum exploration radius, a maximum exploration distance and/or a predetermined area to be explored.

The maximum exploration time is, for example, a maximum length of time that the parking assistance system should spend exploring the area. The maximum reconnaissance radius is, for example, a maximum distance from the current position of the vehicle that the vehicle should be at during reconnaissance. The maximum reconnaissance distance is, for example, a maximum distance that the vehicle should cover during the reconnaissance. The predetermined area to be explored can include, for example, an area drawn on a digital map. In particular, the area comprises an area delimited by a closed line. The line or the area can be specified, for example, in the form of coordinates in a coordinate system.

According to a further embodiment of the method, the received sensor signal indicative of the environment includes a localization signal, an ultrasonic sensor signal and/or an optical sensor signal.

The term localization signal is understood to mean, in particular, a sensor signal that enables localization of the vehicle in a vehicle-independent coordinate system, such as a GPS signal or the like.

According to a further embodiment of the method, an assessment of a digital map of the surroundings is determined for a specific area, the assessment including the completeness, accuracy, complexity, variability and/or topicality of the digital map of the surroundings.

Completeness is understood, for example, as the proportion of the explored area to the total area of the area. Accuracy is understood to mean, for example, how high a measurement error is for individual features or for all features present in the digital map of the surroundings. The accuracy depends, for example, on the available sensors and the number of reconnaissance trips in a specific area. The complexity is understood, for example, as a measure of how many roads or paths the area includes and how these are intertwined. For example, complexity can be specified as the number of cross-connections or crossings relative to the total navigable route or the total area of the explored area. The variability is understood, for example, as a measure of how much the traffic situation changes over time due to moving obstacles. The variability can be specified, for example, as the number of moving obstacles relative to the number of fixed obstacles and/or the total navigable distance or total area of the explored area. Up-to-dateness is understood to mean, in particular, a measure of how up-to-date the digital map of the environment is. This can be specified, for example, in the form of the time of the last reconnaissance trip or the update of the digital map of the surroundings.

Each of the ratings mentioned can be ascertainable for a sub-area of the digital map of the surroundings, so that, for example, different sub-areas can have different up-to-dateness.

For example, it can be derived from the evaluations that an additional reconnaissance trip for a specific area or sub-area would be helpful in order to better explore the area.

According to a further embodiment of the method, depending on the assessment of the digital map of the environment, a confidence for a determined trajectory that connects a current position and a target position on the digital map of the environment and / or a period of time that the vehicle will probably need to reach the target position , determined.

The confidence indicates, for example, a probability that the vehicle will reach the target position along the determined trajectory. Here, the confidence is correlated with the various assessment standards as follows. Confidence is positively correlated with completeness, accuracy, and timeliness, that is, confidence increases as completeness, accuracy, and timeliness increase. Confidence is negatively correlated with complexity and variability, that is, confidence decreases as complexity and variability increase.

Based on the confidence, several possible trajectories can be compared, for example, and the best possible trajectory can thus be determined. The best possible trajectory is, for example, the one that minimizes the time it takes to reach the target position and at the same time has a very high level of confidence.

• Durchführen einer Objektklassifikation für Objekte in der Umgebung des Fahrzeugs in Abhängigkeit der empfangenen Sensorsignale, wobei zumindest zwischen beweglichen Objekten und feststehenden Objekten unterschieden wird, und wobei die einem jeweiligen Objekt zugeordnete Klasse in der digitalen Umgebungskarte mit dem Objekt gespeichert wird.

According to a further embodiment of the method, step d) additionally comprises:

• Carrying out an object classification for objects in the area surrounding the vehicle as a function of the received sensor signals, a distinction being made at least between moving objects and stationary objects, and the class assigned to a respective object being stored with the object in the digital map of the area.

The object classification can preferably be carried out by a trained neural network. This is preferably a GAN (generative adversarial network).

This embodiment has the advantage that it can be seen from the digital environment map whether there is a probability that an object cannot be found again at a specific position. This can be advantageous if, for example, a delivery truck has blocked an entrance during the reconnaissance trip and the entrance is therefore stored as blocked in the digital map of the surroundings. If it is determined that the obstacle is a moving object (the delivery truck), then, for example, a trajectory that uses the driveway can still be planned.

• Ermitteln einer bestimmungsgemäßen Funktion einer Fläche in der Umgebung des Fahrzeugs in Abhängigkeit der empfangenen Sensorsignale, wobei die ermittelte bestimmungsgemäße Funktion in der digitalen Umgebungskarte mit der Fläche gespeichert wird.

According to a further embodiment of the method, step d) additionally comprises:

• Determining an intended function of an area in the vicinity of the vehicle as a function of the received sensor signals, the determined intended function being stored in the digital environment map with the area.

The term "intended function of an area" includes, for example, the information that it is a roadway, a parking lot, a footpath, an entrance, an exit, a bus stop, a pick-up point and the like. For example, an area is a sum of several areas or a single area.

According to a further embodiment of the method, the trajectory is determined as a function of the class assigned to the object and/or as a function of the intended function of the surface.

An example of this has already been explained above using the delivery van. In a further example, it is avoided, for example, that the trajectory runs over a parking space and/or a footpath, even if this is marked as free.

• Übertragen der empfangenen Sensorsignale und/oder der ermittelten digitalen Umgebungskarte an eine zu dem Fahrzeug externe Einheit, und/oder
• Empfangen einer digitalen Umgebungskarte von der zu dem Fahrzeug externen Einheit.

According to a further embodiment of the method, this additionally comprises:

• Transmission of the received sensor signals and/or the ascertained digital environment map to a unit external to the vehicle, and/or
• Receiving a digital environment map from the unit external to the vehicle.

In this embodiment, the digital map of the surroundings can be determined at least partially by the external unit and/or can be provided by it. The external unit is, for example, a server with which the parking assistance system establishes a communication connection. The communication connection is established, for example, by means of WLAN or a cellular network.

One advantage of this embodiment is that, for example, a number of parking assistance systems can have access to the external unit, so that each parking assistance system does not have to determine its own digital map of the surroundings. Furthermore, the digital environment map for a respective area can be kept up-to-date better if several users participate in it with their respective vehicles and parking assistance systems.

According to the second aspect, a computer program product is proposed which comprises instructions which, when the program is executed by a computer, cause the latter to execute the method described above.

A computer program product, such as a computer program means, can be made available or supplied by a server in a network, for example, as a storage medium such as a memory card, USB stick, CD-ROM, DVD, or in the form of a downloadable file. This can be done, for example, in a wireless communication network by transferring a corresponding file with the computer program product or the computer program means.

• eine Benutzerschnittstelle zum Empfangen einer Nutzereingabe und zum Starten des Erkundungsmodus in Abhängigkeit der Nutzereingabe,
• eine Empfangseinheit zum Empfangen von für die Umgebung des Fahrzeugs indikativen Sensorsignalen,
• eine Steuereinheit zum Veranlassen eines autonomen Fahrens des Fahrzeugs in Abhängigkeit des zumindest einen empfangenen Sensorsignals,
• eine Ermittlungseinheit zum Ermitteln einer digitalen Umgebungskarte des erkundeten Gebiets in Abhängigkeit der für die Umgebung indikativen Sensorsignale, und
• eine Speichereinheit zum Speichern der ermittelten digitalen Umgebungskarte.

According to a third aspect, a parking assistance system for a vehicle is proposed. The parking assistance system can be operated in an exploration mode for exploring an at least partially unexplored area. The parking assistance system includes:

• a user interface for receiving a user input and for starting the exploration mode depending on the user input,
• a receiving unit for receiving sensor signals indicative of the surroundings of the vehicle,
• a control unit for initiating autonomous driving of the vehicle as a function of the at least one received sensor signal,
• a determination unit for determining a digital environment map of the explored area as a function of the sensor signals indicative of the environment, and
• a storage unit for storing the determined digital map of the surroundings.

The embodiments and features described for the proposed method apply accordingly to the proposed parking assistance system. The proposed parking assistance system is preferably operated according to the method according to the first aspect.

The parking assistance system is set up in particular for semi-autonomous or fully autonomous driving of the vehicle. Partially autonomous driving is understood to mean, for example, that the parking assistance system controls a steering device and/or an automatic drive level. Fully autonomous driving means, for example, that the parking assistance system also controls a drive device and a braking device.

The respective unit of the parking assistance system can be implemented in terms of hardware and/or software. In the case of a hardware implementation, the respective unit can be embodied, for example, as a computer or as a microprocessor. In the case of a software technical implementation, the respective unit can be used as a computer program product, as a function, be embodied as a routine, as an algorithm, as part of a program code or as an executable object. Furthermore, each of the units mentioned here can also be designed as part of a higher-level control system of the vehicle, such as a central electronic control device and/or an engine control unit (ECU: Engine Control Unit).

According to a fourth aspect, a vehicle is proposed with at least one surroundings sensor for detecting and outputting a sensor signal indicative of the surroundings of the vehicle and with a parking assistance system according to the third aspect.

The vehicle is, for example, a passenger car or a truck. The vehicle preferably includes a number of sensor units that are set up to detect the driving state of the vehicle and to detect an environment of the vehicle. Examples of such sensor units of the vehicle are image recording devices, such as a camera, a radar (“radio detection and ranging”) or a lidar (“light detection and ranging”), ultrasonic sensors, location sensors, wheel angle sensors and/or wheel speed sensors.

Further possible implementations of the invention also include combinations of features or embodiments described above or below with regard to the exemplary embodiments that are not explicitly mentioned. The person skilled in the art will also add individual aspects as improvements or additions to the respective basic form of the invention.

• 1 zeigt eine schematische Ansicht eines Fahrzeugs aus einer Vogelperspektive;
• 2 zeigt eine schematische Ansicht eines Gebiets aus einer Vogelperspektive;
• 3A-3C zeigen jeweils eine schematische Ansicht einer ermittelten digitalen Umgebungskarte des Gebiets der 2;
• 4 zeigt ein Beispiel einer geplanten Trajektorie in dem Gebiet;
• 5 zeigt ein schematisches Blockschaltbild eines Ausführungsbeispiels eines Parkassistenzsystems; und
• 6 zeigt ein schematisches Blockschaltbild eines Ausführungsbeispiels eines Verfahrens zum Betreiben eines Parkassistenzsystems.

Further advantageous refinements and aspects of the invention are the subject matter of the dependent claims and of the exemplary embodiments of the invention described below. The invention is explained in more detail below on the basis of preferred embodiments with reference to the enclosed figures.

• 1 Fig. 12 shows a schematic view of a vehicle from a bird's eye view;
• 2 shows a schematic view of an area from a bird's eye view;
• 3A-3C each show a schematic view of a determined digital map of the area of the area 2 ;
• 4 shows an example of a planned trajectory in the area;
• 5 shows a schematic block diagram of an embodiment of a parking assistance system; and
• 6 shows a schematic block diagram of an embodiment of a method for operating a parking assistance system.

Elements that are the same or have the same function have been provided with the same reference symbols in the figures, unless otherwise stated.

1 FIG. 12 shows a schematic view of a vehicle 100 from a bird's eye view. The vehicle 100 is, for example, a car that is arranged in an environment 200 . Car 100 has a parking assistance system 110, which is embodied as a control unit, for example. In addition, a plurality of environment sensor devices 120, 130 are arranged on car 100, these being optical sensors 120 and ultrasonic sensors 130, for example. The optical sensors 120 include, for example, visual cameras, a radar and/or a lidar. The optical sensors 120 can each capture an image of a respective area from the environment 200 of the car 100 and output it as an optical sensor signal. The ultrasonic sensors 130 are set up to detect a distance to objects arranged in the environment 200 and to output a corresponding sensor signal. Using the sensor signals detected by the sensors 120, 130, the parking assistance system 110 is able to drive the car 100 semi-autonomously or fully autonomously. Except the ones in the 1 illustrated optical sensors 120 and ultrasonic sensors 130 can be provided that the vehicle 100 has various other sensor devices 120, 130. Examples of this are a wheel speed sensor, a wheel angle sensor, a microphone, an acceleration sensor, an antenna with a coupled receiver for receiving electromagnetically transmittable data signals, and the like.

The parking assistance system 110 is, for example, as shown in FIG 5 explained trained and set up, the basis of 6 carry out the procedures explained. The parking assistance system 110 can in particular based on the 2 - 4 have explained functionality.

2 FIG. 12 shows a schematic view of an area 205 from a bird's eye view. The area 205 shows an example of a parking lot with several parking spaces, which can be a private company parking lot or a public parking lot, for example. The parking lot has a roadway 207, which is delimited by a roadway boundary 208, for example a marking or a curb, from the parking spaces provided and/or from obstacles 210 and the like. It should be noted that the lane boundary 208 could also be simply the end of a paved area can be given. In this example, the parking spaces are arranged on the other side of lane 207. It can be said that the lane 207 forms an area that can be driven on, which is delimited by the lane boundary 208 . Correspondingly, areas lying outside of this area can be referred to as non-trafficable areas.

The area 205 includes structural obstacles 210, a building 211, barrier posts 212 and traffic signs 214, 216, 218. The traffic signs are, for example, a traffic sign 214 “one-way street” and a traffic sign 216 “no entry”. The traffic sign 218 is designed as a lane marking and indicates that it is a stop and/or a delivery and loading zone where no vehicles 220 should be parked. In addition, there is a larger number of vehicles 220 in the area 205, which are parked on respective parking spaces. For the sake of clarity, the vehicles 220 are not individually identified with a reference number. Another vehicle 221 is parked on area 218 .

The vehicle 100, for example, like the vehicle 1 is trained, is also parked in a parking lot. It is subsequently based on the 3A - 3C explains how the vehicle 100 autonomously explores the area 205 in an exploration mode and thereby determines a digital environment map MAP0-MAP2, which is then used in a summon mode (see 4 ) is available.

the 3A-3C each show a schematic view of a determined digital map of the surroundings MAP0-MAP2 of the area 205 of FIG 2 , these being shown at different points in time during a reconnaissance trip.

the 3A shows the digital environment map MAP0 at a time when the exploration mode was just started. For example, user 105 (see 4 ) by means of a corresponding application on a mobile device, a corresponding control command to parking assistance system 110 (see 1 or 5 ) of the vehicle 100 to start the exploration mode. The control command can also be referred to as a user input and includes, for example, different specifications for carrying out the exploration mode. Such specifications are, for example, a maximum exploration time, a maximum exploration radius, a maximum exploration route and/or a predetermined area to be explored. In embodiments, the user input may also include a location of the vehicle 100 . In the exploration mode, the vehicle 100 acts autonomously, being controlled in particular by a control unit 112 (see FIG 5 ) of the parking assistance system 110 is controlled.

Parking assistance system 110 activates, for example, a sensor system 120, 130 on vehicle 100 (see FIG 1 ) and receives at least one sensor signal corresponding to the environment 200 (see 1 ) of the vehicle 100 is indicative. The sensor signal includes, for example, information on features 208 and/or objects 220 in the immediate vicinity of vehicle 100, from which an initial driving direction can be derived. The sensor signal preferably also includes position information that relates to a coordinate system that is independent of the vehicle, such as a GPS signal. The parking assistance system 110 begins to determine the digital environment map MAP0 as a function of the at least one received sensor signal, with only the one received sensor signal being used for this at this point in time, as well as possibly available position information. Therefore, at this point in time, the digital environment map MAP0 only includes the direct environment of the vehicle 100.

The parking assistance system 110 now controls the vehicle 100 autonomously, initially parking out of the parking position and then, as in FIG 3B shown travels along the trajectory TR0. During this journey, parking assistance system 110 receives at least one additional sensor signal that is indicative of surroundings 200 of vehicle 100 . In particular, this can be a sensor signal that was detected and output by the same sensor 120, 130 as the first sensor signal received. Parking assistance system 110 preferably receives current sensor signals continuously, in particular periodically. The digital environment map MAP1 is continuously updated on the basis of the further received sensor signals, so that it is gradually completed when the vehicle 100 advances autonomously into unexplored areas. If the vehicle 100 drives in areas that have already been explored, then the digital surroundings map MAP1 for the corresponding area can also be updated, that is to say that new obstacles 210 and/or objects are added to the digital surroundings map MAP1 or objects and/or that no longer exist Obstacles 210 are removed from the digital map of the surroundings.

In embodiments, it can also be provided that the parking assistance system receives a sensor signal from a sensor unit arranged externally to the vehicle, such as a traffic camera or the like, and also takes this into account when determining the digital map of the surroundings.

In embodiments, object classification of detected objects or obstacles 208-220 may be performed. Here, the detected objects or obstacles 208 - 220 are classified in particular as mobile or stationary, which can facilitate subsequent orientation based on the stored digital map of the environment MAP0 - MAP2, and can lead to better results when planning a trajectory based on the stored digital map of the environment MAP0 - MAP2 can contribute. More specific classifications are also possible, for example as a vehicle, structural obstacle, traffic sign, bollard, curb and the like. A “Vehicles” class can also be subdivided into subclasses, for example cars, trucks, delivery vans, emergency vehicles and the like. The object classification is carried out in particular on the basis of external features that can be captured using a camera.

In further embodiments, free areas can also be classified. A distinction is made here, for example, between "road", "parking space", "loading and unloading zone", "footpath", "cycle path" and the like. Other features, such as a direction of travel or the like, can also be taken into account here.

the 3C shows the digital environment map MAP2 after the exploration of the area 205 has been completed, with the autonomously driven trajectory TR0 being shown in the digital environment map MAP2. The digital environment map MAP2 is stored so that it can be loaded and used accordingly at a later point in time when the vehicle 100 is again in the area 205 . In this example, the digital environment map MAP2 is complete. It should be noted that the exploration mode is not necessarily executed in such a way that the respectively determined digital map of the surroundings MAP0-MAP2 is complete.

4 shows an example of a planned trajectory TR1 in the area 205. For the area 205, as shown in FIG 3A - 3C described, a digital area map MAP2 determined. For example, the user 105 of the vehicle 100 starts the summon mode of the parking assistance system 110 (see FIG 1 or 5 ) by using the application on his mobile device to send a corresponding control command to parking assistance system 110 of vehicle 100. The control command can also be referred to as a user input and includes in particular a target position ZP to which vehicle 100 is to move.

The parking assistance system 110 loads the stored digital map of the surrounding area MAP2, with the applicable digital surrounding map MAP2 being selected, for example on the basis of the current position AP (this can also be referred to as the initial position or start position) of the vehicle 100 and the target position ZP, provided that several different digital surrounding maps MAP0 - MAP2, which relate to different areas 205, for example, are stored. The starting position AP and the target position ZP are entered, for example, in the digital environment map MAP2 and a trajectory TR1 is then determined, which connects the starting position AP with the target position ZP. The trajectory TR1 is determined in particular in such a way that it only runs over drivable areas in the digital map of the surroundings MAP2 and traffic rules, such as the travel direction requirement for one-way streets, are observed.

In this example, the target position ZP is at the point where the vehicle 221 was parked during the reconnaissance trip. On the basis of lane marking 218, parking assistance system 110 can derive, for example, that vehicle 221 was only parked temporarily at this position for loading or unloading, which is why, when planning trajectory TR1, it assumes that target position ZP is free. If this is not the case, the trajectory TR1 can be dynamically replanned as soon as a received sensor signal indicates that the target position ZP is occupied by another vehicle 221.

During the autonomous drive along the planned trajectory TR1, the parking assistance system 110 orients itself in particular on the basis of the digital environment map MAP2 and on the basis of currently received sensor signals. The currently received sensor signals can also be used to update the digital map of the surroundings MAP2, which means that it can be improved.

It should be noted that the target position ZP does not necessarily have to be at the user 105 . It is also possible for the user 105 to set a free parking space as the target position ZP, for example, upon arrival in the area 205, so that the parking assistance system 110 drives the vehicle 100 autonomously using the stored digital area map MAP0 - MAP2 to the parking space and the vehicle 100 parked there.

5 shows a schematic block diagram of an embodiment of a parking assistance system 110 for a vehicle 100, for example the vehicle 100 of FIG 1 . The parking assistance system 110 is in an exploration mode for exploring an at least partially unexplored area 205 (see 2 ) operable. The parking assistance system 110 includes a user cer interface 111 for receiving a user input and for starting the exploration mode depending on the user input, a receiving unit 112 for receiving for the environment 200 (see 1 ) of vehicle 100 indicative sensor signals, a control unit 113 for initiating autonomous driving of vehicle 100 as a function of the at least one received sensor signal, a determination unit 114 for determining a digital map of the surroundings MAP0-MAP2 (see 3A - 3C ) of the explored area 205 as a function of the sensor signals indicative of the environment 200, and a memory unit 115 for storing the ascertained digital environment map MAP0-MAP2.

6 shows a schematic block diagram of an embodiment of a method for operating a parking assistance system 110, for example the parking assistance system 110 of FIG 1 or the 5 , for a vehicle 100 (see 1 ), wherein the parking assistance system 110 is in an exploration mode for exploring an at least partially unexplored area 205 (see 2 ) is operable. In a first step S1, the exploration mode is started depending on a user input. In a second step S2, at least one sensor signal indicative of the surroundings of the vehicle is received. In a third step S3, the vehicle is driven autonomously depending on the at least one received sensor signal. In a fourth step S4, a digital environment map MAP0-MAP2 (see 3A - 3C ) of the explored area 205 as a function of the at least one received sensor signal and at least one additional sensor signal that is indicative of the environment and that is received during autonomous driving. In a fifth step S5, the determined digital environment map MAP0-MAP2 is stored.

Although the present invention has been described using exemplary embodiments, it can be modified in many ways.

Reference List

100

vehicle

105

user

110

parking assistance system

111

user interface

112

receiving unit

113

control unit

114

investigation unit

115

storage unit

120

environmental sensor

130

environmental sensor

200

vicinity

205

Area

207

roadway

208

lane boundary

210

obstacle

211

building

212

obstacle

214

traffic sign

216

traffic sign

218

lane marking

220

vehicles

221

vehicle

AP

initial position

MAP0

environment map

MAP1

environment map

MAP2

environment map

S1

process step

S2

process step

S3

process step

S4

process step

S5

process step

TR0

driven trajectory

TR1

planned trajectory

ZP

target position

QUOTES INCLUDED IN DESCRIPTION

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

Patent Literature Cited

• US 2015/0346727 A1 [0003]
• US 2016/0327949 A1 [0003]
• US 2017/0344010 A1 [0003]
• US 2018/0130161 A1 [0003]

Claims (15)

Method for operating a parking assistance system (110) for a vehicle (100), wherein the parking assistance system (110) can be operated in an exploration mode for exploring an at least partially unexplored area (205), the method having the steps: a) Starting (S1) the exploration mode depending on a user input, b) receiving (S2) at least one sensor signal indicative of the surroundings (200) of the vehicle (100), c) autonomous driving (S3) of the vehicle (100) depending on the at least one received sensor signal, d) determining (S4) a digital environment map (MAPO - MAP2) of the explored area as a function of the at least one received sensor signal and/or at least one additional sensor signal received during autonomous driving and indicative of the environment (200), and e) storage (S5) of the determined digital map of the surroundings (MAP0-MAP2). procedure after claim 1 , characterized in that the parking assistance system (110) can be operated in a summoning mode, with the steps: starting the summoning mode as a function of a user input, loading the stored digital map of the area (MAPO - MAP2), receiving at least one for the area ( 200) of the vehicle (100) indicative sensor signal, determining a trajectory (TR1) for the vehicle (100), which connects a current position (AP) of the vehicle (100) with a target position (ZP), depending on the digital map of the surroundings (MAPO - MAP2) and the at least one received sensor signal, and autonomous driving of the vehicle (100) along the determined trajectory (TR1). procedure after claim 2 , characterized in that further, for the environment (200) indicative sensor signals are received during the autonomous driving along the determined trajectory (TR1), and that the digital environment map (MAPO - MAP2) is updated depending on the other received sensor signals. procedure after claim 2 or 3 , characterized in that the user input for starting the Summon mode comprises the target position (ZP) for the vehicle (100). Method according to one of the preceding claims, characterized in that the user input for starting the exploration mode comprises a maximum exploration time, a maximum exploration radius, a maximum exploration distance and/or a predetermined area to be explored. Method according to one of the preceding claims, characterized in that the received sensor signal which is sensitive to the surroundings (200) comprises a localization signal, an ultrasonic sensor signal and/or an optical sensor signal. Method according to one of the preceding claims, characterized in that an evaluation of the determined digital map of the surrounding area (MAPO - MAP2) is determined for a specific area (205), the evaluation being complete, precise, complex, variable and/or up-to-date of the digital environment map (MAPO - MAP2). procedure after claim 7 , characterized in that depending on the assessment of the digital map of the environment (MAP0 - MAP2) a confidence for a determined trajectory (TR1) that connects a current position (AP) and a target position (ZP) on the digital map of the environment (MAP0 - MAP2). , And/or a period of time that the vehicle (100) will probably need to reach the target position (ZP) is determined. Method according to one of the preceding claims, characterized in that step d) comprises: carrying out an object classification for objects (208 - 221) in the surroundings (200) of the vehicle as a function of the received sensor signals, with at least between moving objects (220, 221 ) and stationary objects (208 - 218), and wherein the class assigned to a respective object is stored with the object in the digital environment map (MAPO - MAP2). Method according to one of the preceding claims, characterized in that step d) comprises: determining an intended function of an area (207) or a sum of several areas in the vicinity (200) of the vehicle (100) as a function of the received sensor signals, the determined intended function is stored in the digital environment map (MAPO - MAP2) with the area (207). procedure after claim 9 or 10 , characterized in that the trajectory (TR1) is determined as a function of the class assigned to the object (208-221) and/or as a function of the intended function of the surface (207). Method according to one of the preceding claims, characterized by : transmitting the received sensor signals and / or the determined digital map (MAPO - MAP2) to the vehicle (100) external unit, and / or receiving a digital map (MAP0 - MAP2) from the unit external to the vehicle (100). Computer program product, comprising instructions which, when the program is executed by a computer, cause the latter to carry out the method according to one of Claims 1 - 12 to execute. Parking assistance system (110) for a vehicle (100), wherein the parking assistance system (110) can be operated in an exploration mode for exploring an at least partially unexplored area (205), with: a user interface (111) for receiving a user input and for starting the exploration mode depending on the user input, a receiving unit (112) for receiving sensor signals indicative of the surroundings (200) of the vehicle (100), a control unit (113) for initiating autonomous driving of the vehicle (100) as a function of the at least one received sensor signal, a determination unit (114) for determining a digital environment map (MAPO - MAP2) of the explored area as a function of the received sensor signals indicative of the environment (200), and a storage unit (115) for storing the determined digital map of the surroundings (MAPO - MAP2). Vehicle (100) with at least one surroundings sensor (120, 130) for detecting and outputting a sensor signal indicative of the surroundings (200) of the vehicle (100), and with a parking assistance system (110). Claim 14 .

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